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Social Science Research: Principles, Methods and Practices - (Revised edition)

(43 reviews)

Anol Bhattacherjee, University of South Florida

ISBN 13: 9781475146127

Publisher: University of Southern Queensland

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Kelle DeBoth Foust, Associate Professor, Cleveland State University on 6/22/23

Comprehensiveness rating: 5 see less

The text really seems to do as it claims; provides the basic overview of the research material needed for graduate students without a lot of other “fluff.” It’s written very clearly, easy to understand and many figures and charts that enhance learning. It covers the majority of the topics that I need it to cover for OTH 740/Research I, at about the level of detail that the students should be able to digest. In particular, I like the sections on survey research, experimental research and that it covers quantitative and qualitative analyses.

Content Accuracy rating: 4

As far as I can tell reading through it, the content is accurate and unbiased (will be able to review further once actually implemented in the intended course).

Relevance/Longevity rating: 4

The content is current at least regarding how we continue to teach and use it in our field. Some of the references are a little outdated, although not much has changed in this world in recent years. I also recognize I can pull more recent literature in order to make the examples up to date and relevant for my particular students.

Clarity rating: 5

This book is written very clearly. I feel that the diagrams really help to add and make sense of higher level concepts that students may struggle with. Concepts that are challenging are recognized as such within the text, with appropriate examples that enhance clarity (will be able to review further once actually implemented in the intended course)

Consistency rating: 5

Yes, the text appears to be internally consistent in terms of terminology and framework.

Modularity rating: 5

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader. – Yes. The division of the content makes sense, and how smaller modules are paired (e.g., qualitative and quantitative analysis paired back to back) is logical to facilitate learning.

Organization/Structure/Flow rating: 5

The text and chapters are laid out in an order that makes sense and provides good flow and continuity between the concepts and analytical applications. In particular, I like how research is introduced, moving into research design and then analysis all within the same text. Will make this more manageable for students.

Interface rating: 5

The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader. – Very well put together, no issues with the interface. I would consider this to be very user/student friendly. In particular, the authors made a point to keep it “short and sweet” so students should not be intimidated by the length of the chapters (which is excellent for helping to convince the students to actually read them).

Grammatical Errors rating: 5

The text contains no grammatical errors. – None detected.

Cultural Relevance rating: 5

The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds. – No offensive content noted, the majority of the examples used do not have cultural significance and therefore the amount of diversity is sufficient.

This review was written based on a preliminary review of the text prior to use and implementation within the intended course. I will update the review if it significantly differs once students have used it for their course study.

Reviewed by Ingrid Carter, Professor, Metropolitan State University of Denver on 4/14/23

The textbook includes many of the important elements of a foundational social science research course. A key element of the course I teach which is not included in the text is how to search for literature to inform the research, how to synthesize... read more

Comprehensiveness rating: 4 see less

Content Accuracy rating: 3

The content appears to be mostly accurate and unbiased. There is a large emphasis on positivist approaches, and more post-positivist and innovative research approaches should be added to the content.

The text is relevant to foundational/introductory social science research courses. As mentioned previously, broader and more diverse perspectives of research are missing.

Clarity rating: 4

The content is presented clearly.

Consistency rating: 4

The text is presented with a consistent framework and format. The variety of frameworks included could be greater, with at minimum a presentation of different research paradigms and ideally with discussion or questions to grapple with related to various research paradigms and approaches.

As the author indicates, the textbook consists of 16 chapters which can be used in a 16-week semester. These can be easily assigned for weekly readings.

The textbook is well-organized.

Interface rating: 4

The interface is relatively clear

No grammatical errors were found in my initial review. I have not yet used the textbook for the course I am teaching, and therefore have not reviewed the textbook page by page nor line by line.

Cultural Relevance rating: 3

More diverse and culturally relevant example to a diverse audience could be embedded. I did not encounter offensive material.

Reviewed by Sanaa Riaz, Associate Professor, Metropolitan State University of Denver on 3/27/23

Comprehensiveness rating: 3 see less

While not meant for advanced graduate and doctoral students, this text is an excellent introductory resource for learning about paradigms in research methods and data analysis and prepares the learner to begin writing a successful research project proposal. The text largely privileges the scientific method and labels diverse social science research methods as such. However, the preparatory considerations in beginning social science research have been discussed. The book contains important terms in bold to guide a beginner reader as well as sample syllabi for incorporating it at the graduate level. However, the text could be made more comprehensive with the inclusion of an effective index and/or glossary.

Content Accuracy rating: 5

The text is a quick guide to considerations and terminologies used in social science research. The content is accurate, error-free and unbiased.

The text provides a basic introduction to research methods in the social sciences. Updates in social science inquiry with respect to social media and popular culture platforms and mixed methods research should be easy to incorporate.

The text has been written from the point of view of a non-expert. It is free of technical jargon and is meant to provide the essentials of social science inquiry and research considerations.

Consistency rating: 3

The text is internally consistent in terms of terminology within a chapter section. However, it is strongly recommended that the framework is revisited for chapters discussing qualitative research methods and approaches. Qualitative data analysis has not been explored in depth and the basic framework for Chapter 13 will need to be substantially expanded to provide for a smoother transition from a discussion on grounded theory to content analysis and hermeneutic analysis and to incorporate information on other analyses undertaken in qualitative research.

Chapters and sections in the text can be easily reorganized and assigned as per needs of the instructor and the course without causing disruption to the reader.

Organization/Structure/Flow rating: 3

Chapter sections of the book covering qualitative research are not presented in a logical manner. It is highly recommended that the readers are told about the place of exploratory and other research in social science research inquiry, rather than labeling them as scientific research. Moreover, mixed methods and qualitative visual and social media platform research needs to be discussed. The book overall shies away from delving into approaches and methods in non-empirical research in the social sciences.

The text is easy to navigate. All words, sections and tables are easily searchable.

The book is free of grammatical errors.

The text does not contain any culturally insensitive information as there are hardly any research project examples incorporated.

Incorporating examples and case studies across social science disciplines (after introducing the disciplines in which social science research is employed in the first chapter) would allow readers to see the applicability of one social science research approach, method and data analysis over another based on the research project focus.

Reviewed by Cahit Kaya, ASSISTANT PROFESSOR, University of Texas Rio Grande Valley on 10/17/22

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55. read more

Comprehensiveness rating: 2 see less

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55.

IT SEEMED ACCURATE

Relevance/Longevity rating: 3

IT IS RELEVANT

IT IS CLEAR

IT IS CONSISTENT

Modularity rating: 3

IT NEEDS MORE MODULES

Organization/Structure/Flow rating: 2

IT CAN BE OGRANIZED BETTER

YES BUT EVEN THOUGH IT CAN BE IMPROVED

Grammatical Errors rating: 4

I DID NOT SEE IT

MORE CULTURAL DIVERSE EXAMPLES CAN BE GIVEN

Reviewed by Dawn DeVries, Associate Professor, Grand Valley State University on 12/9/21

The text provides a complete summary of the research process. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science fields. Two areas could be more in-depth, specifically the IRB discussion and the chapter on surveys. Information provided is accurate and succinct as the author intended, providing a comprehensive overview of the research process.

The content is accurate and presented in an objective manner. There was no perception of bias or conflict that would impact accuracy. The chapters offer a variety of examples, inclusive of a variety of social science fields.

Written in 2012, the information remains relevant with few areas that would ever need to change. The research process and research methods stay fairly consistent with little variation; thus, the text would not need regular updating. Updates, if and when needed, would be easy to implement due to the concise and objective writing and the logical organization of the textbook. One area needing updating (or that instructors would need to supplement) is Chapter 9 on Survey Research. The chapter refers to mail surveys, which in 2021, are almost obsolete. Little is presented or discussed on electronic surveys, survey platforms, or the use of social media in recruitment, survey distribution or every survey completion. Furthermore, there is no mention of the ethical issues related to social media research.

Key terminology is bolded with the definition following, making it easy to identify. Definitions are clear and adequate to facilitate understanding of the concepts and terms. The text presents the research process in a logical and understandable way using scaffolding.

The chapter structure, framework, and style are consistent.

Modularity rating: 4

The chapters provide easily divisible readings of 8-10 pages. The chapters are ordered in a logical fashion and flow easily, yet they could be rearranged to fit instructor preferences for order. Chapters are concise, allowing the combination of multiple chapters for a week’s reading if needed. The text is designed for a 16-week semester, but again, because the chapters are not long, several chapters could be read as one assignment. It would be difficult to reduce chapter readings (say, using only 5 pages of the chapter) because of the conciseness of the information and the shortness of the chapters.

The text is logical and has flow. It starts general (with How to Think Like a Researcher) and builds to specific, more detailed content (Inferential Statistics).

There are no observed problems with the interface of the text. Images used are clear and display without difficulty. No hyperlinks are used.

No observed issues or concerns related to grammar or mechanics.

No concerns about inclusivity or offensiveness. The text is clear and concise, offering a variety of short examples specific to various social science professions.

The text reminds me of my Research Methods textbook from my doctoral program. It addresses the differences between scientific research and social science methods in a clear and concise manner. While it is an overview of the information, it is specific and concise enough for students who need to understand the research process but won’t be engaging in research as their full-time profession. Content is brief in a few areas as mentioned, which will allow the instructor to provide supplemental reading or lecture content specific to the university (i.e., IRB) or to the profession. As the author suggests, certain chapters could be skipped depending on the program. For example, chapters 13 – 15 on statistics could easily be omitted if the program has a research statistics course. A nice add is the sample syllabus for a doctoral program.

Reviewed by David Denton, Associate Professor, Seattle Pacific University on 5/3/21

I use this book with graduate students in education taking an initial course in education research. Dr. Bhattacherjee notes the book is organized for semesters with supplemental readings, as shown by the sample syllabus in the appendix. Nevertheless, I have found the book is excellent in meeting objectives for an introductory course in education research, though it is necessary to add education context and examples. Some of the course objectives I have developed from the textbook include i) distinguishing between questionnaire survey method and interview survey method and ii) summarizing criteria for developing effective questionnaire items, among many others. There are some sections that exceed student knowledge without some background in statistics (e.g. description of factor analysis) but omitting these sections as required reading is easy since there are many subheadings used to segment chapters.

Dr. Bhattacherjee has done an excellent job of clearly communicating the content with accuracy. For example, the textbook distinguishes between qualitative and quantitative analysis (rather than qualitative and quantitative research, an appropriate distinction). The textbook makes other distinctions in a way that helps students comprehend concepts (e.g. survey interview and survey questionnaire). At the same time, the textbook does not over-emphasize research methods or design, which might mislead students to think inflexibly about the topic.

Relevance/Longevity rating: 5

One of the advantages of the book, in my view, is that it will not become obsolete anytime soon. It addresses all major topics of interest for instructors needing to develop student background knowledge in social science research methodology. For example, some topics for which the book provides helpful structure include i) Thinking Like a Researcher, ii) The Research Process, iii) Research Design, iv) and Sampling. In addition, an instructor can easily supplement or provide subject-specific examples where needed since the book is thoroughly segmented by chapter and chapter subheadings.

Dr. Bhattacherjee does a fine job of defining terms concisely. I do not recall use of jargon, or if there are complicated terms, the text provides enough elaboration so that students can at least attain a conceptual understanding. In some instances, definitions are so concise that I find it necessary to elaborate with examples. This, however, is a part of instruction and would be done in any case.

The textbook is highly coherent, in my view. Similar to modularity, consistency is a strength. For example, chapters are grouped into four sections: Introduction to Research, Basics of Empirical Research, Data Collection, and Data Analysis. Further, chapters within major sections are sequential, such as chapters on Science and Scientific Research, followed by Thinking Like a Researchers, followed by The Research Process. In addition, content within chapters is consistent, such as Dr. Bhattacherjee’s logical progression of concepts: empiricism, to positivism, to forms of analysis (qualitative and quantitative), etc

Modularity is one of the clear strengths, again in my view. From a structural perspective, neither the chapters nor subsections are very long because Dr. Bhattacherjee writes concisely. Both chapters and subordinate subsections lend themselves to various kinds of divisions. For example, students in need of supplemental instruction on descriptive statistics, such as content about the normal distribution, can be assigned the subsection on Statistics of Sampling in chapter 8, followed by the subsection on Central tendency in chapter 14. Some non-sequential reading is required if students do not have any background in statistics, but this is not difficult to manage using page numbers or subheadings as reference.

Organization/Structure/Flow rating: 4

The textbook is well organized. Nevertheless, there are some sections that I found helpful to have students read out of sequence. For example, there is a short section at the end of chapter 5, Scale Reliability and Validity, which is perhaps best read after students cover correlation and normal distribution, dealt with in chapter 14. Again, I did not find it difficult to assign sections out of sequence using either page numbers or chapter subheadings as reference.

The textbook does not have interface issues. Chapter titles are hyperlinked within PDF copies to simplify navigation. Some may judge a few of the images as low resolution, but if this is a defect it is not one that interferes with communicating concepts, which is the purpose of the images.

There are a few minor grammatical errors in the 2nd edition, 2012. For example, on p. 126, Dr. Bhattacherjee notes “five female students” when the Chi-square table appears to show four. This is minor, but if students are new to reading Chi-square tables they may not detect the error and believe interpreting a Chi-square table is different than interpreting a typical data table.

The textbook presents appropriate information without prejudice or unfairness. As mentioned, instructors will likely need to include examples that are specific to their course objectives and student populations. For example, chapter 11. Case Research provides exemplars that focus on business and marketing domains. This seems entirely appropriate given Dr. Bhattacherjee’s research area. Instructors using the text for other domains, such as education research, will be interested in elaborating on concepts using examples specific to the needs of their students.

I greatly appreciate that Dr. Bhattacherjee has shared his book as an Open Textbook.

Reviewed by Elizabeth Moore, Associate Professor, University of Indianapolis on 4/24/21

In Chapter 5 on Research Design there isn't any discussion on how to improve content and statistical conclusion validity. There isn't a discussion of threats associated with the four types of validity. The chapter also does not present how the research design and threats to validity are interconnected. There is a lack of comprehensiveness in the presentation of qualitative research as qualitative research rigor is not addressed.

The content is accurate, error-free, and unbiased. I would like more examples focused on social sciences. Some of the examples are related to business/industry. There are many social science examples that could be used.

Many of the examples should be updated. With everything that is (has been) happening in the U.S. and world, there are many examples that can come from the social sciences. For example, there are several examples that could represent the concept of technostress, especially with many professionals having to move into online environments. Students would be more likely to read assigned chapters and understand the material presented if the examples were relevant to their profession.

The book is clear and has high readability. There are several accessibility issues in the document. This should be checked and fixed. There are 5 issues in the document, 4 in tables, 5 in alternative text, etc. Accessibility is a big issue right now. All documents have to be accessible to all students.

While there is consistency within the textbook, in some topics there is a lock of consistency in how some of the terms and material relate to what is actually used in social science disciplines. For example, in basic social science textbooks in chapters presenting an introduction to measurement of constructs, descriptive statistics that are unfamiliar and rarely used, such as geometric mean and harmonic mean, should not be introduced. This information is usually difficult for novice researchers to understand without adding more advanced descriptive statistics.

It is confusing as to why research validity is in Chapter 5 - Research Design. There is not a discussion of how different research types are affected by different types and threats of research validity. The title of Chapter 7 is misleading. The word "scale" is associated with scale of measurement. It would be better to use designing measurement tools/instruments in the chapter name since the types of validity and reliability discussed are related to creating and developing measurement tools/instruments. I also think Chapter 6 - Measurement of Construction should not come before Chapter 7 - Scale Reliability and Validity since measurement of constructs and scale reliability and validity are related to qualitative research.

I like the organization. It follows the current syllabus I use so it will require very little modifications.

As mentioned below, bookmarks would improve navigation of the pdf file. Also, having links from the table of contents to chapters would be helpful. Including some of the important subsections of the chapters would also improve navigation of the pdf version of the book. Tables and charts are helpful and supplement the text. Use of images would break-up the text.

None were noted.

Cultural Relevance rating: 4

See comments above about the relevancy of the material. While it is important to make sure a book is culturally sensitive and not offensive, it is also important to not ignore what is known about social injustices which are well-documented. Look at the lack of diversity in many professions and organizations, this is important to address.

It would be helpful if bookmarks were placed in the pdf version. While this is a social science textbook, it would be helpful to have subsection in Chapter 4 that introduces at least a couple of the main health behavior theories. These are commonly used by many researchers in social sciences.

Reviewed by Barbara Molargik-Fitch, Adjunct Professor, Trine University on 3/6/21

This textbook provides a nice overview of several topics related to social science specific research. read more

This textbook provides a nice overview of several topics related to social science specific research.

The textbook seems to be accurate and error free.

The text seems to be accurate, relevant, and useful.

The text is organized well and had a professional and academic tone while also understandable.

Text seemed to be internally consistent.

Text is easily divisible to be assigned as different points within the course.

Text is well organized.

The text is free of significant interface issues that would distract or confuse the reader.

I did not see grammatical errors.

I did not see any cultural issues.

I will be using this textbook for one of my classes. I am looking forward to using it. I think it has a lot to offer students looking to develop their research skills.

Reviewed by Kenneth Gentry, Assistant Professor, Radford University on 6/2/20

This text provides a great overview of core concepts relevant to health-science research. An overview of theory, designs, sampling, data collection, data analysis, and ethics are provided. It may be helpful in future editions to add additional content relating to qualitative research (i.e. additional types of designs, as well as how trustworthiness and rigor are addressed [for example, what specific steps can be taken by researchers to address dependability, credibility, confirmability and transferability]).

Information presented appears accurate and unbiased.

While much of the content is 'durable' (not likely to soon become obsolete), the relevance is dependent upon the focus of the instructor/course. For example, if the emphasis of the course will be on quantitative research, then this text is highly relevant, however, if the emphasis is on an equal balance between the traditions of qualitative and quantitative, then this text is slightly less relevant due to the more limited nature of its content in qualitative (in comparison to content on quantitative). That is not to say that this text does not address content relevant to qualitative research, however, it does so with decidedly less depth and breadth than quantitative.

While a subjective interpretation of clarity is highly dependent upon the reader, I found this text to strike a good balance between a scholarly, academic tone, and commonly-understood, easily-relatable descriptions of key concepts. There were times where I wish that the latter had been more so, however, considering the target audience of this text, I feel that the author struck a good balance. Occasionally, there were concepts that I anticipated would require additional clarification (beyond the reading) for my graduate students.

Overall, I found the text to be generally consistent in its approach to the content. Occasionally, there were instances when the flow made sense at the chapter level, however, content might have been spread between chapters (i.e. theory is discussed in Chapters 1, 2 and 4).

This ties in with my comments on consistency. Since some concepts are discussed in more than one place, it might be difficult to identify a single reading for a specific topic ... one might need to assign several readings from more than one chapter. However, having said that, I anticipate that those instances would be infrequent. On the whole, the text demonstrates a fairly good degree of modularity.

At the chapter level (i.e. main topics), and within each chapter, information appears well organized. It is the appearance of content in multiple places that was occasionally problematic for me as I read (i.e. when reading about reliability and validity, I questioned why the author did not discuss the types of reliability and validity ... I later found that content in a subsequent chapter).

Interface rating: 3

While images were viewable, many appeared 'pixelated'/'grainy' (low resolution). This was more of a cosmetic issue, and did not affect the overall interpretation of the image.

Overall, the content was grammatically strong.

Content was not culturally insensitive or offensive.

My sincere thanks to this author, and to the Open Textbook Library and Scholar Commons for this text. I truly appreciate the investment of resources that were invested. I just completed instructing 2 semester courses on research in a graduate health science degree program ... I plan to adopt this text the next time I am rotated into those courses again!

Reviewed by Wendy Bolyard, Clinical Assistant Professor, University of Colorado Denver on 4/30/20

This text presents all the topics, and more, that I cover in my master's-level research and analytic methods course. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. I would have... read more

The concepts were presented accurately and often with citations.

The great thing about research methods is that the content ages well (does not change over time). The examples were relevant and should not make the text obsolete. Any instructor should be able to provide current, real-world examples to compare and contrast to those in the text. Although the sample syllabus if for a business class, I did not find the text to be relevant only to business students. The authors uses broad social science illustrations that cross disciplines. This text is definitely relevant to public affairs/public administration.

The text is well-written and provides clear yet concise context.

When students are learning a new language - research methods - they may be confused when definitions vary. Causality is explained with slightly different language which may be misunderstood by students.

One chapter includes a summary section. It would have been helpful to include a summary of key takeaways for each chapter, and perhaps include a list of key terms and definitions (since the text does not include a glossary).

The text follows the linear, systematic research process very well.

The font, size, and spacing varied in some sections. The images were a bit blurred.

A few typos, but otherwise well-written and very clear.

Culturally sensitive with relevant and inclusive cases provided.

I will be adopting this text to supplement other readings assigned in my master's-level research and analytic methods course. I appreciate the clear and helpful context it provides on key concepts that students must understand to become effective researchers. The text is comprehensive yet concise and would not overwhelm students.

Reviewed by Valerie Young, Associate Professor, Hanover College on 12/19/19

I really appreciate the broad focus and examples from social science fields. As a fellow social scientist from a high growth area (communication studies), I would appreciate even more breadth! I supplement with many field-specific resources, so this critique is very minor. An appropriate place and reference might be within the first chapter, under the heading Types of Scientific Research, to give a nod to some of the social science fields and the importance of interdisciplinary questions across disciplinary lines.

I did not find any errors in the content of the book. One critique is that the author rarely cites any sources for assertions or materials. I get the impression that the author is relying on "commonly known" ideas regarding research methods and processes, but I have to consistently remind my students to cite all non-original information, and that example is lacking in this text. As an example, regarding evaluating measurement scales for internal consistency, the author references commonly-accepted factor loadings (>.60) but does not reference or provide linked resources for readers to corroborate this or seek additional readings.

The text content is relevant and the author has taken care to provide relatively timeless sample research examples throughout. Some examples include areas of social and political interest (conflict, crime), business and marketing, and social psychology. The contents of the text are not dated and the author does a fantastic job of offering a variety of relevant examples so that readers of all backgrounds can relate to the content.

Incredibly clear and concise. Main ideas are clearly articulated in headings. Bullet point lists are used infrequently, but appropriately. The writing style is professional, academic in tone, yet relate-able. There is little, if any, discipline-specific references that a graduate student from any area of social sciences could not comprehend; however, this book is empirically-grounded and quantitatively focused. For our readers in fields with lower quantitative literacy, some of the terminology in chapters is better suited for students with basic statistical experience, some research methods or theory coursework completed.

This text is consistent and detailed in the use of interdisciplinary, social scientific terminology.

The layout of materials and the concise writing style contribute to an easy-to-visualize text. The page layout and brief chapters make it appropriate to assign supplemental readings along with the chapter topics. Some areas for improvement: use hyperlinks to reference forward and backward within the text so that readers can pop back and forth to related concepts. Include links in the text to reputable online materials or publications. See my comment below in Organization feedback concerning chapter ordering.

One thing that strikes me as amazing and also challenging about this text is the concision and simplicity for which Bhattacherjee integrates complex information. The chapters are very brief- about half of what would be a typical, field-specific textbook, but the content is simultaneously dense and clear. For example, Chapter 7 addresses scale reliability and validity. In just a few short pages, we get an incredible density of information and terminology, from a formula and brief explanation of Chronbach's alpha to exploratory factor analysis as a method to demonstrate convergent and discriminant validity. There is an appropriate number of tables to visually demonstrate complex topics in-text. Overall, the chapters are well-organized and easy to follow with a working knowledge of basic stats. The introductory chapters have been intentionally placed to introduce readers to basic principles. The following chapters could be assigned as readings in any order that fit with the student's needs (but I find the order of these chapters appropriate, as-is): Chapter 9 Survey Research, Chapter 10 Experimental Research, Chapter 11 Case Research, Chapter 12 Interpretive Research, Chapter 13 Qualitative Analysis, Chapter 14 Quantitative Descriptive Statistics, Chapter 15 Quantitative Inferential Statistics. The final chapter, 16, covers Research Ethics, which seems to have been lopped on at the end of the text. It would be a better fit in the first third; perhaps integrated into one of the first several chapters with a nod toward the evolution of social research.

Regarding navigation, the pdf online version does not allow for creative navigation through the document. Graphics and charts are clear and easy to see in the online pdf version. They are a little smaller than I would like on the page, but the text is clear and the tables and graphs are visually appealing. It looks like most of the graphics were created using PowerPoint. One odd thing I noticed is that the paragraph spacing is inconsistent. In one section, the spacing between paragraph lines seems to be set at 1.25, and then, for no apparent reason, the line spacing moves back to single space. This is not visually distracting, just peculiar. Overall, the graphics in the online version are much clearer than in the softcover print version, which prints only in greyscale, with quite a bit of granulated distortion in the figures.

I did not notice any writing errors.

The research topic examples represented a diverse array of research topics, methods, fields, etc. The overview of science, scientific research, and social science was welcomed and unique to this text. Some areas for improvement would be to include historical scientific figures who are not all male, and link critical methodology in a clearer manner with specific critical and cultural examples of this form of research.

Reviewed by Lee Bidgood, Associate Professor, East Tennessee State University on 10/29/19

The text seems comprehensive, covers a wide range of research approaches, and parts of the research process. I will have to supplement with more of the area-specific writing that my students need, but this is easily added in the adapted version... read more

This text seems to follow the path of other texts that outline research design and methods, such as the Creswell book that I have used for several semesters. I do not detect bias in the text, or any significant errors.

I will discuss disciplinary relevance rather than chronological applicability (which other reviewers have already addressed thoroughly). The course for which I seek a textbook is meant to prepare students in a non-discipline-specific regional studies context, and for a range of methodologies and research design possibilities, mostly in the social sciences and humanities. This text is most relevant to the potential research programs of our students in discussions of the precursors to research design in Chapter 2 (“Thinking like a researcher”) and of the using and creating of theory in Chapter 4 (“Theories in Scientific Research”).

The authors’ prose is clear and easily comprehensible. Definitions are clear, and sufficient (jargon is explained). There could be more examples to clarify and assure comprehension of concepts, I plan to add these in my adaptation.

There is not an overt intra-chapter organization scheme that is consistent from chapter to chapter--each chapter differs in the sorts of content, that some sort of generic outline would feel forced, I think. The “feel” of the text, though, is consistent, and effectively conveys the content.

Because it uses footnote citations instead of endnotes / parenthetical citations, each page contains all of the references contained on it, which helps with modularity. The portions of the text that are less relevant to the course I teach (i.e. the more technical and statistical chapters, such as Chapters 6, 7, 8, 14, and 15 are easily omitted; I will be able to adapt portions of this text (i.e. the discussion of sampling in Chapter 8) without needing to provide all of the chapters. Some of the more technical vocabulary will require editing and explanation, but this seems manageable for me as an adapter.

The book is logically organized and the topics make sense in the order presented. I agree with another reviewer that the ethics portion seems like an appendix, rather than an essential and structural part of the book. As I adapt this text, I would address ethics at the beginning (as I do in my current teaching of research methods) and infuse the topic through other sections to address ethics-related concerns at all stages of research design and implementation. The author’s choice to use footnotes for references is not the one that seemed logical to me at first - it seems “elegant” to put all the references in a list at the rear of a book; now, reading through the whole text, however, I see some value to having the entirety of a citation at hand when reading through the main body of the text. Still, I miss the comprehensive list of works cited at the end of the book, which I would add to a text that I create, since an e-text is not limited by the economics of physically-printed books.

The text is workable as presented in the PDF document that I downloaded. Charts and other imagery are usable. There are no extra navigation features (a link to take a reader to the table of contents in a header or footer, etc.). I am left wondering if, in a PDF form, an OER textbook would be more useful with more navigation features, or if they might make the document buggy, cluttered, or otherwise affect use.

I did not detect any issues with grammar, usage, etc. in the text.

There is a lack of specific examples that might lend a sense of wide scope / global appeal to the textbook, and create an inclusive atmosphere for a reader/student. The author has stated that they hope to translate and widely distribute the text - perhaps, as is the case in the syllabus that the author provides, the hope is that in use for a course, additional readings will provide local knowledge and place-, culture-, and discipline-specific details and context.

This is a solid text that will provide a framework for adaptation in another disciplinary / area context.

Reviewed by Kevin Deitle, Adjunct Associate Professor, TRAILS on 10/6/19

I am pleased with the coverage in the text; it includes the history and foundations of research, as well as chapters on ethics and a sample syllabus. The structure and arrangement of the book differs from my own understandings of research and how I present it in class, but all the material covered in my class appears in the text, and it can be ordered to fit my syllabus. This text spends more time with statistics than I include in a research course, but again, that can be omitted or just used for reference. The book does not include either an index or a glossary, which is unfortunate for anyone who wants a paper version. Of course, most students seem to prefer an electronic text, so I assume they use a search function rather than an index.

I have not spotted any glaring errors, other than an occasional grammatical slip or a cumbersome edit. The author includes a few citations, usually following APA style, but employs footnotes instead of a reference section. The content mostly aligns with my own conceptions of research, although it does have a different arrangement from my presentation in class. This does not suggest that the content is wrong, only that I would likely rearrange it to suit my instructional sequence. I sense no bias in the presentation, including the historical or ethical portions, or sections that mention religion. I’m comfortable that I could rely on this book in class without worrying over slanted content or editorialization.

Research is something of a traditional topic, in the sense that changes or evolutions move at a comfortably slow pace. I expect there is very little of this text that is likely to become obsolete any time soon. The flip side is there is little in this book that is necessarily cutting-edge, but that is not the fault of the author at all. And in the unforeseeable situation where a new protocol or a new advance in either statistics or research warrants an update, I think the organization and the modular design will allow that to happen without major upheavals in the structure or arrangement of the text.

As mentioned elsewhere, the writing is comfortably academic without becoming dense or burdensome. I have seen introductions to research that were more casual and probably fit a beginner audience better than this would, but I daresay this is intended as a core text for a graduate-level class, and for that reason, can be expected to sound less approachable and more authoritative. The text employs features for fast visual reference, to include breaks in the text to allow for visual elements, and bolded text where key terms are introduced or defined. While this would probably not be a particularly exciting text for a self-study course, it will sit well with classes that need a reference text that takes the time to explain concepts with some authority.

Structurally the author has a style and sticks to it throughout the text. Visually this book is sparse, and it will require some effort on the part of the professor to make the content digestible in a classroom environment. However, that also suggests that the arrangement and format remain predictable from the first page to the last, without any surprises in presentation or discourse. Research has a tendency to step on its own toes when it comes to terminology, but this text follows those conventions for the most part, making it mostly congruent with other research texts I have seen. I think this book would complement other research texts without causing too many difficulties in terminology or arrangement.

The author suggests in the preface that the work was intended to be rearranged by sections, and I can appreciate how the chapters and structure support that statement. I do see this more as a foundational reference for a graduate-level course than a self-study text though, and it has the feel of a reference work to it. Text appears in large blocks, is illustrated sparsely, and has no callout texts or pull quotes. Key words are bolded but get no more embellishment, which again suggests a reference rather than an instructional work. I’m sure this material could be the groundwork for a more reader-friendly presentation, if someone wanted less of a reference and more of a textbook.

This might be the most appealing point of the text for me. As I mentioned earlier, I like the overall sequence that the author follows, but at the same time I can appreciate how the sections can be detached and still stand alone. The logic follows principles and theory through to fundamentals, then diverges to cover the details that fit more complex or esoteric versions of research. There is enough statistical explanation to avoid vague generalizations, but at points I expect it would overwhelm a beginner. I would prefer ethics was near the start of the text, rather than an epilogue; our course is arranged to require students to complete ethics training before they may pursue later assignments. But this is easily solved.

On the whole the text is satisfactory, the layout from page to page is acceptable, but there’s a minimum of graphic elements or visual components. Some of the statistical formulas or graphs are low-quality, or have suffered compression artifacts. Their appearance in the text is logical though, and the few tables or diagrams that do appear are in color, with arrows or labels to ease interpretation. The table of contents is primitive, and there is no way to navigate specific tables or diagrams except moving page by page in sequence. External sites are hyperlinked, and the table of contents has been designed for electronic use, but there are no cross-reference features. This gives the text the feel of a word processed document converted to a PDF format, intended to be printed. Overall, the core content is strong, as a printed book it is probably acceptable, but as an electronic textbook it lacks some contemporary features.

I have found very few grammatical errors or incomplete sentences, and none of those were so flagrant as to make the text unusable. If this had been submitted as an academic work it would likely earn some criticism for style or grammar (the author seems to follow APA style, but tends to footnote references simultaneously), but this never impedes the delivery. The text is readable at a collegiate level without becoming over-academic, or for that matter, casual.

The text manages to broach sensitive issues in a level and balanced format; in particular the ethics section manages to discuss some well-known failings in past research without becoming overly critical of the researcher or the participants. Arguably, research and its underlying processes are mostly mechanical (or at least standardized), meaning it is possible for individual researchers to violate cultural, ethnic, racial, or other boundaries, but the underlying science is generally unconcerned with those issues. In that sense, the book has very few opportunities to broach hot-button topics except when dealing with historical or ethical examples.

I appreciate this text as a starting point for a more accessible design, or as a background reference for a full course introducing social science research. I see it as a foundation text or an external source for students who seek a concise fallback for lessons, and with content that is compatible with other textbooks. In many ways it needs much more to compete with established textbooks or dedicated electronic learning tools, and in some places I would like more references for the material that is included. On the whole though, I would consider this as the core text for my next introductory research course.

Reviewed by Krystin Krause, Assistant Professor, Emory and Henry College on 4/10/19

This text covers the core elements of a social science research methods course at the undergraduate level. While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. The concise chapters are undergraduate-friendly and will make a solid foundation with the addition of supplemental reading assignments that show examples of the concepts discussed in the textbook. There is no glossary or index, but keyword searching in the pdf copy is simple and effective.

The text seems to be an accurate reflection of social science research methods, particularly when considering causal inference and hypothesis testing. If your course is also covering descriptive inference, you would want to supplement the text with additional material.

Research methods is not a subject that changes quickly, and thus this text will not become obsolete quickly. The only things that may need updating over time are any links that lead to pages that no longer exist. Any other updates will be relatively easy and straightforward to implement.

The text is written in a style that is accessible for undergraduates. It follows the conventions of including relevant key words and phrases in bold and includes easy to follow definitions of terms. I anticipate that undergraduates will also appreciate how concise the text is.

The chapters are consistent in both terminology and framework. It offers a unified organization that also allows for mixing and matching chapters if an instructor wishes to teach the chapters out of order.

The organization of the text lends itself to be adapted to any introductory social science research methods course, regardless of what order the instructor wants to place the topics being discussed. Chapters could be taught out of order and can be subdivided accordingly.

While it is certainly possible to break apart to teach the text in a different order than how the chapters are originally offered, the progression of the text from the introduction to the chapters on qualitative data analysis is both logical and clear.

The text is free of interface issues, and charts and images appear to be clear and correct. The only exception to this are the links found in the sample syllabus at the end of the book. I was only able to get one of the links to work.

No grammatical errors jumped out at me. There are a few here and there, but they are not distracting for the reader.

The text is not culturally insensitive or offensive.

Because the book is concise, I would recommend its use in addition to other supplementary resources such as class lectures, academic articles that demonstrate the methods discussed in the textbook, and projects that allow students to experience the methods first-hand. It would make a good alternative to more elaborate basic research methods textbooks when the instructor wishes to keep costs for the students low.

Reviewed by Mari Sakiyama, Assistant Professor, Western Oregon University on 4/5/19

The textbook covers the major key elements that are essential in research methods for social science. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. With the use of additional reading... read more

I did not notice any errors or unbiased content. The author had provided accurate information with simple/straightforward examples that can be understood by students with various discipline in social science.

Given the nature of the subject, the content is considered to be up-to-date. However, although there will not be too many changed expected in the research strategies and designs, it is important to note that some of the sampling procedure have been facing some changes in recent years (e.g., telephone survey, online sampling frame).

The textbook provided the content in a clear and concise manner. The author, instead of providing a complex list of academic jargon/technical terminologies, but rather clarified and explained these terms in a simple and straightforward fashion.

Overall, the content was consistent throughout the textbook. Starting with a broad/general statement of each chapter topic, the author narrowed it down to smaller element which is easy for the reader to follow and understand. As he provided in CH.6, it might be even more helpful to have summaries for each chapter.

This textbook is certainly divided into smaller segments, but maybe too small (short). However, as mentioned above, this problem can be solved by adapting additional readings.

The textbook is significantly reader-friendly and well-structured. Although some instructors prefer to cover some chapters earlier (or later) in their semester/term than others, this is just a personal preference. There are no issues with the author’s organization of the textbook.

Overall, the use of indentations, bolding, italicization, and bullet points, was consistent. However, many of the images were blurry (e.g., Figure 8.2, Table 14.1) and some fonts were smaller than others (i.e., pg. 34).

I did not notice any grammatical errors. Even I had missed some, they would not be destructions for the reader. (Note: The scale is confusing. What I mean by '5' is the least amount of grammatical errors were found)

The author did not use any concept that was insensitive or offended people and/or subjects from various backgrounds. (Note: The scale is confusing. What I mean by '5' is the least amount of cultural insensitivity or offensiveness were found)

See my comments above.

Reviewed by Candace Bright, Assistant Professor, East Tennessee State University on 11/7/18

There are some key elements that I would expect to be in a social science research methods book that are missing in this book. I think this comprehensiveness may be appropriate for an undergraduate course (with some supplementation), but the text... read more

The information in the book seems accurate. When necessary, it is cited appropriately.

The content is very relevant. Because the book focuses on methods, it does not need too much change over time. It was published in 2012. The main area that might need to be updated in the discussion regarding the Internet and how it impacts our research options. Perhaps more could be added on machine learning, AI, web-scraping, and social media in general. I increasingly see studies conducted either using social media content or recruiting through social media; neither of these are addressed in this book.

I really like the way the book is laid out. In particular, the qualitative and quantitative analysis sections are well organized. They succinctly cover a lot of information is a way that is very consumable. There were some instances, however, where I thought wording lacked clarity or definitions needed further explanation.

I do not see any issues with consistency.

I like the organization of this book and each chapter does a good job of standing alone on important topics within research methods. The sections within the chapters are clearly marked and logically organized.

The organization is clear and logical. It covers important concepts in research methods in the same order in which they are typically taught, with the exception of ethics. In this book, ethics comes last, whereas I would have taught it earlier.

This might be minor, but I noticed some places where the spacing was different and it was a little distracting. Overall, it is well formatted.

I didn't notice any grammatical errors.

Overall, the text book could use more examples and applied examples, but when present, I find them culturally appropriate.

I have mixed feeling on the image on the cover and the limited visuals within the book. I also don't feel like this textbook has enough visuals or figures that could be used to support comprehension of the materials. More examples would also be helpful. Overall, however, the author has presented a lot of information succinctly and I look forward to using this text (in parts) in future methods courses.

Reviewed by Alysia Roehrig, Associate Professor , Florida State University on 11/5/18

This text provides an overview of many important issues for my graduate research methods course in education. There are a few important topics missing, however. In particular, types of correlational designs and mixed-methods designs would be important to include. Likewise, single-subject designs are not mentioned at all. I will have to supplement these areas with other readings. I also think more about specific threats to internal and external validity should be provided, along with information about when and how certain threats are avoided. There is no glossary but being an online text, it is simple enough to search for certain terms.

Content seems to be error-free and unbiased for the most part. However, I have an issues with the language in chapter 2 about about strong and weak hypotheses because it seems to treat the experimental/causal hypotheses preferentially. The author also states that hypotheses should have IVs and DVs...but what about non-experimental hypotheses?? I think students could be misled by this and I think this requires a lot of unpacking. Thus, I do sense somewhat of a prejudicial treatment of quantitative and experimental research methods. I plan to add information to pages 13 and 15 about how qualitative methods do not involve testing hypotheses though the results might be an inductively derived hypothesis or nascent theory.

The content covered is pretty standard and basic and so not likely to be out-dated soon.

The writing is straightforward and easy to follow.

The use of terms and framework seems to be consistent throughout the book.

The chapter and subject headers all seem to be clear. They will make it easy to select sections for assignment or reordering if revising for use.

The order of topics makes sense and is aligned with the process of conducting research.

The hotlinks in the table of content are nice, but additional navigational aids would be helpful. For example, a back to the Table of Contents (TOC) button would be nice, as well we a list of all subsections (hotlinked) added to a long version of the TOC.

I have not noticed any egregious problems.

There are not many examples, which means there is little opportunity to offend.

Reviewed by Eddie T. C. Lam, Associate Professor/Editor-in-Chief, Cleveland State University on 9/12/18

The book provides ample information for a research course, but it may not meet the needs of every instructor. For this reason, the book should include a few more chapters so that course instructors can have more options for a semester-long research course. For instance, at least one chapter should be on nonparametric statistics and their applications on research studies, while another chapter should be on research paper writing (e.g., what should be included in the Introduction, Methods, Results, Discussion, and so on). For the Appendix, it is nice to provide a sample syllabus for the instructors, but the students may want a sample research paper in proper journal or thesis/dissertation format.

Most of the information presented in this book is accurate. The author has mentioned in Chapter 5 (p. 37) that “construct validity” will be described in the next chapter, but I don’t see any construct validity in Chapter 6 or Chapter 7. In addition, the author may want to emphasize what “alpha is set to 0.05” means. Does it mean the p-value has to be less than 0.05 (p. 125) or p ≤ 0.05 (p. 130) to reject the null hypothesis?

In terms of content, the book has fairly good amount of information. However, it is also obvious that many terms appeared in the last few decades are missing from the book. For example, Survey Monkey and social media can be included in Chapter 9 (Survey Research) and structure equation modeling can be introduced in Chapter 15.

The information is presented in layman’s terms without any jargon. New terms are bolded with clear definition, and sometimes they are illustrated with examples.

The terminology and framework are consistent throughout the text.

The chapters are logically presented and they are grouped under different sections. As mentioned before, the text should add a few more chapters for the course instructors to select from.

In my opinion, “Chapter 16 Research Ethics” should not be standalone (under the “Epilogue”) and it could be part of the “Introduction to Research” (i.e., the first few chapters).

The text does not have any significant interface issues, though the font size of the figures can be larger (e.g., they should not smaller than the font size of the text).

Overall, the text contains very few grammatical errors. However, in a number of occasions, a comma is added for no reason, such as “. . . we must understand that sometimes, these constructs are not real . . .” (p. 44). It is also unnecessary to always add a comma before the word “because.”

The content of the text is not culturally insensitive, and the author does not present any offensive statements or comments anywhere in the text.

It’s time to have a second edition.

Reviewed by Amy Thompson, Associate Professor, University of South Florida on 6/19/18

This text is a nice overview of some of the key points in social science research. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It should be noted that there is more of a focus on... read more

Overall, the text seems accurate. There are some cases when the author gives advice that I don't agree with (i.e. advises against even-numbered Likert scale items, p. 48; encourages people not to do "trendy" research, such as that on new technology, p. 24). Even so, most of the information seems to be accurate.

The book is relevant. It gives a good overview of the theories and methods, which change little over time. I would suggest a few updates, however. Currently, there is controversy on the over-reliance of the p-value, and it would be useful to include some of this discussion on p. 125. Also, on p. 73, the author talks about "mail-in" and "telephone" surveys as a research method, and even goes on to say on p. 74 that most survey research is done by self-administered mail-in surveys with a pre-paid return envelop. This information needs to be updated, as currently, much of the survey research is done via online platforms.

The book is quite clear and provides succinct definitions.

The book seems consistent throughout.

The chapters are short and very readable. There would be no problem dividing the chapters up for a class, or using a portion of the book.

The topics are presented in a logical manner.

The text in some of the tables is blurry, especially when enlarging the PDF. Perhaps the print copy is clearer. The text outside of the tables is clear.

I didn't have any trouble reading or understanding the text.

This book is not offensive.

Overall, this is a good book to have as a reference or an additional text for a class. For my field, it wouldn't be sufficient to use as a stand-alone text. Although its intended audience is graduate students, it's a bit too basic for Ph.D. students, in my opinion. It would be a good text for an intro to research class at the UG or MA level, as a supplemental text. I would recommend it to Ph.D. students to use as a reference because of the key terms included. It's great that a resource like this is available for free to students and faculty in a wide variety of disciplines.

Reviewed by Huili Hao, Assistant Professor, University of North Carolina Wilmington on 5/21/18

This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in social science will find these topics useful in developing their research method skills. However, the book falls short on the depth of the essential concepts. It would also benefit from offering more practical examples for some of the theories or terminology. A glossary is not found within the text, although the table of content lists the topics covered in each of the modules.

Overall, this textbooks seems to be accurate.

The relevancy and longevity of this book are great. It focuses on fundamental research methods as well as incorporates current research approaches. Given the nature of research method that does not change drastically, content is up-to-date and won’t make the text obsolete within a short period of time. The topics are written in the way that necessary updates will be relatively easy and straightforward to implement.

The text is written in a logical and concise fashion. The text is easy to follow. I did not find any jargon or technical terminology used without explanation.

The text consistently matches the topics outlined in the table of content.

The text is clearly organized into five modules: introduction to research, basics of empirical research, data collection, data analysis, and research ethics. It also includes a course syllabus, which is nice and useful. Each of the modules / chapters can also be used as subunits of a research method course without putting the reader at a disadvantage.

The table of content is clear and the chapters are organized in a logic order.

I downloaded the PDF version of the textbook and find it easy to read offline. The formatting, navigation and images/charts seems clear and appropriate.

I had no trouble reading or understanding the textbook.

Overall, this is a good textbook that covers a broad range of topics important in research method. As this textbook is designed as a succinct overview of research design and process, more practical topics are not included in much detail such as how to conduct different statistical analyses using SPSS or SAS, or how to interpret statistical analysis results. It would require additional materials / textbooks for graduate level research method courses.

Reviewed by Jenna Wintemberg, Assistant Teaching Professor, University of Missouri on 5/21/18

I use almost the entire text in an undergraduate Health Science research methods course. I do supplement the text with additional readings on: -selecting a research topic -developing a research question -how to read scholarly articles -how to search the literature -mixed methods research -community-based participatory research -disseminating research findings -evidence-based practice

I have found this text to be accurate, error-free and unbiased.

The content is written in a way that will allow for longevity of use. I compliment this text with current peer-reviewed journal articles which are relevant to my students' career paths and can be updated more regularly.

I have found the book to be clearly written and appropriate for upper-level Health Science undergraduate students. Technical terminology is sufficiently defined.

The text uses a consistent framework throughout.

The text is easily divisible into smaller reading sections. I assign the chapters in an alternative order and students have not had problems with this.

I assign the chapters in an alternative order for my undergraduate students. For example, I have students read chapter 1 following by chapter 16 (research ethics).

There are no interface issues.

The text is free of grammatical errors

The text is not culturally offensive.

Because of the basic nature of the materials presented and clear writing, my upper level undergraduate students have done well with this text. The brevity of the chapters and bolded key terms particularly appeal to the students. I do have to supplement the text with journal articles and other materials. However, I am pleased with this straight-forward text and will continue to use it as the main text in my course moving forward.

Reviewed by Amy Thompson , Associate Professor, University of South Florida on 3/27/18

Reviewed by Debra Mowery, Assistant Professor, University of South Florida on 3/27/18

The text covers all of the areas of basic research information that I cover when I teach research and research methods in the social sciences. The table of contents is straight forward, and the chapters are arranged in a fluid, logical order. The nice thing with this text is that you could rearrange as you see fit for your course without an issue. There is also a sample syllabus in the appendix which could be useful when setting up a course. I feel this text is great for students who may not necessarily be interested in research as a job prospect (their interests may be more clinical in nature) but need the basics of research in a clear, easy to understand, and straight forward format.

I felt the content of this text is accurate, unbiased, and free of any glaring errors..

This text appears to be up-to-date including issues such as web-based or internet surveys and questionnaires. I did see that the copyright for this text was 2012 so not sure if revisions or updates to the original have happened or not. It seems that there should be a way to document if this is the latest version of the text. This may be useful information for users of this text.

This textbook is written in a concise and easy to read and understand manner - it is very user-friendly. This is a plus for students - it means they may actually read the text! Jargon and acronyms were appropriately defined with an explanation of how the terms originated and came to be utilized in research. This is appealing to me as an instructor so there is background information for the students.

The consistency of this text is uniform throughout. One appealing issue I liked was the use of social science examples when explaining topics like theories or paradigms. In some research texts examples are utilized but they may not necessarily be in the discipline that you are teaching.

I do like that this text is divided into 16 chapters which is perfect for a 15/16 week semester. The chapters are not so overwhelming that other supporting readings cannot be assigned to students as well to assist with explanation of the weekly topic. The text serves as a great base for building weekly assignments/readings for students.

The majority of the text is presented in a logical format. One issue I had with the order of the chapters in the text was including Ethics at the end in the Epilogue as if it was an after thought. Ethics, ethical behavior, and rigor are a must in research and should be addressed early on in the research process. Having said this, I feel the chapter on Ethics should be moved up further in the chapter line-up (possibly to chapter 2 or 3).

I did not experience any navigation problems. There was however, distortion with many of the images especially the graphics that were utilized throughout the text. A review of the images/graphics and an update to them would be useful. If this e-text has not been updated since 2012 this may be the issue for the distorted figures.

There are a few grammar/spelling/word choice errors. The errors do not effect the content of the text but when reading it makes you pause and think - what is trying to be said here? It might be useful to the author to have the text proofread or copy edited to resolve these issues.

In reviewing this text I did not see any examples that might be deemed offensive or insensitive to other cultures, orientations, ethnicities, etc,

Reviewed by Kendall Bustad, Clinical Assistant Professor, University of Maryland, College Park on 2/1/18

This book covers all the important topics in social science research and is approachable regardless of discipline and course level (high school, undergraduate, graduate, and even post-graduate). It provides an introduction to philosophy as well as components of research. You'll find yourself returning to the basics, and it gives strong foundations. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections)

The text does not seem to be biased in any way.

The content of the book is up-to-date. The text included relevant descriptions of current software commonly used in research.

If you want to have a compressed body of knowledge of social science research, you may read this one. Beneficial.

The text consistently matches the book outline. Terms were used consistently throughout the text.

Each chapter can stand along as a separate lecture. The headings, subheadings, an bold items are great additions that highlight important topics or definitions.

Most of the text flows in a logical, clear fashion. However, it may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis.

No issues noted.

There are a few grammatical errors.

There does not seem to be any culturally insensitive or offensive text.

Reviewed by Jason Giersch, Assistant Professor, UNC Charlotte on 2/1/18

The biggest challenge faced when writing a book about research methods is the decision about what NOT to include. Instructors and disciplines within the social sciences vary widely in terms of their expectations of students in an introductory methods course, and thus their needs from a textbook also vary. This textbook does an excellent job setting the stage for what we mean by "research" in the social sciences. Students will develop a solid foundation in the goals and rationales behind the methods social scientists employ. Students will also develop a comprehensive vocabulary in social science research methods. However, the book falls short in the development of students' research skills. Learning about methods is important, but not much is gained from that knowledge unless the student also learns how to execute at least some techniques. Furthermore, there is little guidance for the student regarding how to properly write a research paper, something that many instructors will find disappointing. This book is probably comprehensive enough for a 3-credit methods course with test-based assessments in a program where few students pursue graduate work. But if teaching students to actually conduct and write up research is important to the course, there are much better books out there (although at significant cost).

Content is accurate and unbiased.

The relevance and longevity are strong. This book describes some of the most current methods but still focuses on the foundations of research that will be appropriate for the foreseeable future. Updates could be easily made every five years or so to keep up with methodology.

The writing is very easy to follow with helpful examples. Prose is direct and to the point, giving only the essential information so as to allow the learner to develop a grasp of fundamentals. The section on theory, for example, is refreshingly clear for learners. Graphics aid in understanding the material in many parts.

This textbook uses consistent terminology and framework.

The textbook is appropriately structured for a standard 15 week course and even recommends a syllabus. Adapting it to other formats, like a 5 or 10 week summer course, might be tricky. There are ample headings and sub-headings, however, that allow the text to be divided into smaller chunks, which is nice to see given how many students feel overwhelmed by this topic.

Organization and flow is excellent. From an education and instructional standpoint, I wouldn't change the organization.

The simplicity of design is a strength -- students should have no difficulty opening and viewing the text on a wide variety of devices. On the downside, there are no bells and whistles that many some students have come to expect from online textbooks.

The casual writing style makes it very accessible, but one consequence is the very occasional grammar problem. It's a trade-off, I think, that is worth making.

Research methods are pretty "culturally-neutral", so there's nothing in it I would see as insensitive or offensive. That being said, the text recommends SPSS and SAS as software to use while neglecting free options (like R) or more ubiquitous programs (like Excel). For a textbook intended to keep costs at zero, these are glaring omissions.

I could certainly see this book being used as an accessible and low-stress introduction to the world of research methods in the social sciences. The main improvements I would like to see would be (1) sidebars throughout that guide students through the paper-writing process and (2) activities using datasets for students to actually perform some of their own quantitative analyses. Perhaps a companion volume could address these needs.

Reviewed by Nathan Favero, Assistant Professor, American University on 2/1/18

This text provides a fairly comprehensive coverage of topics. It is broad, hitting most of the major topics I need to cover in an intro PhD seminar for social science research methods (I'm teaching public administration/policy, political science, and criminology students). That said, there is not a ton of depth in this textbook. I don't view that as a negative; I prefer having a textbook that gives a basic outline of essential concepts and then fleshing this out with supplemental readings, but some might prefer a textbook that goes into more depth.

Overall, this textbook is accurate but not perfect. Sometimes I wish it was a bit more precise, particularly in coverage of quantitative topics. But I use another textbook to more fully cover quantitative topics anyway for my course.

I would say this textbook reads as modern and relevant, although perhaps it could do more to address emerging methodological concerns in social science disciplines (p-hacking, replication, pre-registration of research designs, etc.).

The textbooks is very accessible and easy to read for someone new to the disciplines of social science.

The book appears to be consistent.

I've assigned students to read the chapters in a different order than they are presented in the text had have not encountered any problems. Chapters are coherently organized into distinct topics.

The organization of the book is logical.

Overall, this book is easy to read and use. Graphs are not always high-resolution, but they are readable.

I have not noticed many grammatical errors.

I have not noticed any clear biases or insensitive handling of material in the book.

I'm delighted to have found this book. It's a great starting point for teaching my students to think about the basics of social science research and provides a nice skeleton on which I can layer more in-depth material for my course.

Reviewed by Holly Gould, Associate Professor, Lynchburg College on 8/15/17

The author states that the text is not designed to go in-depth into the subject matter but rather give a basic understanding of the material. I believe the author covers the necessary topics with enough depth to give the reader a basic... read more

I found no errors in content and no observable bias in any of the chapters.

This text will continue to be relevant because of the nature of the subject matter. Updates may be needed to reflect more current research or trends, but no major changes should be necessary.

The text is written clearly and succinctly. The text is understandable for those who are new to the subject matter.

I found no inconsistencies in the text.

The text is divided into logical chapters, and subheadings seem to be appropriate. Chapters can be read fairly easily in isolation without putting the reader at a disadvantage.

The topics are presented in a logical fashion. Some of the chapters have summaries or conclusions, while other chapters seem to end abruptly. It would be helpful to the reader to have a summary statement at the end of each chapter.

I downloaded and read the text in a PDF reader and had no trouble with formatting, navigation, or images/charts.

The text contains some grammatical errors but the errors are minor and do not distract the reader.

This text is well written and I would recommend it to an individual looking for a bare bones book on basic research methods. It contains information essential to understanding quantitative and qualitative research. The charts and images provided enhance the understanding of the text. At times, the author digs a little deeper into background and formulas for certain statistical ideas, which may be unnecessary to someone looking to understand the basics (e.g. the formula for Cronbach's alpha). Some chapters seem to end abruptly while other chapters have excellent summaries or conclusions. There is one recommendation that goes against the prevailing wisdom on survey design. On page 77, the author indicates that a survey should begin with non-threatening questions such as demographic information. Many experts have written that these types of questions, when asked at the beginning of a questionnaire or survey, can affect the respondents' answers to subsequent questions and should be saved for the end. Aside from these minor issues, this text is a great resource and I recommend it.

Reviewed by Virginia Chu, Assistant Professor, Virginia Commonwealth University on 4/11/17

The text offers an introductory overview to scientific research for PhD and graduate students in social sciences. It covers a broad range of topics, research theories, research process, research design, data collection methods, qualitative and quantitative research, statistical analysis, and research ethics. This book touches on many important topics related to the scientific research process that is typically found in several different text. As the author stated in the preface, this is an introductory book that is minimalist by design, it does not contain in-depth discussions or many examples. This is both a plus and a minus, as it makes the book more compact and allow it to be used by many different disciplines, but may be harder for students to relate. The comprehensive nature of the book allows the reader to be exposed to all the necessary topics, or provides a structure for a course instructor, who then supplements with additional materials to create the depth that is specifically tailored for their discipline. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections), as a new doctoral student will certainly need more details than what is provided in the text to begin their first research endeavor. For example, in the quantitative analysis section, only a handful of basic analysis were discussed in detail (univariate analysis, hypothesis testing, t-test, regression). I would like to see a more practical discussion of ANOVA, as it is a very commonly used statistical analysis tool. These topics may also be more discipline specific, where instructors of research classes can supplement with additional materials. The discussion on research ethics is certainly a nice addition to the book where many other research methods texts lack. An index/glossary is not included with the text, but the table of content clearly outlines the topics discussed for each module.

The book is overall accurate and unbiased. The book covered different social science research methods fairly. I did notice a discrepancy in Figure 5.1, where “single case study” is plotted on the graph as high in external validity, but the rest of the text frequently brought up case studies (especially single case studies) having the difficulty with generalizability which should have low external validity.

The content of the book is up-to-date. The text included relevant descriptions of current softwares commonly used in research. It will also stand against the test of time as research methods do not change drastically. The content can also be updated to reflect new technological updates. One needed update noticed is on page 120, where the authors cautioned that only smaller datasets can be stored in Excel and larger datasets needs a more elaborate database system. While the statement is still relevant, the numbers the author cited appear to be old and Excel has since been updated to handle larger datasets (1,000,000 observations and 16,000 items) than what the author had listed.

The content is written in a very clear and concise manner. It is easy to read and to follow the author’s arguments. I did not notice any jargon or technical term that was used without explanation.

The book has a modular organization, with each chapter designed to be used for a different lecture. Each chapter is a self contained unit that can be used as its own reading. Each chapter also has subsections that are clearly marked with subheadings. Important terms are also highlighted by bolding, making it easy for the reader to identify the important concepts.

The chapters of the book flows logically from one to the next. The current layout of the text groups all the data collection methods together and all the data analysis methods together. It may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis. This could be easily done based on the course instructor preference.

No interface issues noted.

The text is generally free of grammatical and spelling errors, with the exception of 2 minor typos noticed on page 139 (“Rik”, “riska”).

The text and examples provided are not culturally insensitive or offensive.

The text is easy to read and covers a broad and comprehensive range of topics important for research. I particularly enjoyed the discussion on research ethics which is often missing in many research methods texts. I would recommend discussing that topic earlier, together with research design, as many of these ethical issues and IRB requirements come up during research design phase. As the text is a meant to be a concise overview of the research process, the more practical topics are not covered in as much detail and would require supplementary material.

Reviewed by Brock Rozich, Instructor, University of Texas at Arlington on 4/11/17

The textbook covers the majority of what would be expected for a research methods course. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. The glossary for the text is clear and a sample syllabus is provided by the author for individuals wishing to use this text for their course. The text was lacking an index, which would prove helpful for students.

The text is accurate and up-to-date with research methods in the social sciences. A variety of data collection methods and concepts are discussed in an easy to understand manor.

The content is up-to-date with research methods in the social sciences. The text should be able to prove useful for a research methods or as supplementary material for a statistics course for the foreseeable future. While I looked through this text with a focus on using it for a psychology course, I feel that this text would be useful across other fields as well.

The book was clear and built upon concepts in a thorough manner. Technical terms were well defined, though as mentioned previously, an index would be helpful for this text for students to look up key terms if they became lost. The text would be useful for an upper-level undergraduate or introductory graduate level course.

The text is consistent throughout. There were no notable deficiencies in any of the content provided in each chapter.

The course is broken down into logical subsections and chapters. Introductory topics relating to research methods are provided early and are built upon in subsequent chapters. A sample syllabus and course outline are provided for instructors who wish to utilize the text for their class.

The book is constructed in a well-organized fashion, without any issues of chapter structure.

The PDF version of the text worked wonderfully on a laptop, with no issues of navigation or distortion of images. This text was not, however, viewed on a tablet or e-reader, which many students use for classes. Based solely on use of a PDF file on a laptop, the interface was flawless, however, if you are considering using this for a class, I would test it out on an e-reader/tablet first to make sure there are no issues with format/text size, etc.

The book did not appear to have any noticeable grammar or syntactical errors.

There were no notable instances of cultural insensitivity throughout the text. Examples were broad and not specific to an individual race or culture.

This is a wonderful open source option for a main text for a research methods course or as a supplementary option for a statistics course that also focuses on data collection.

Reviewed by Divya Varier, Assistant Professor, Virginia Commonwealth University on 2/8/17

The textbook adequately covers most fundamental concepts related to research methods in the social sciences. Areas that would need attention: a chapter introducing mixed methods research, and a deeper discussion on Research Ethics. More social science based examples on specific research designs, experimental research would be great. The research process could include steps involved in academic research with information on the publishing and peer review process.

Content is accurate for the most part. I would have liked a more nuanced discussion of reliability and validity concepts- introducing the concept of validity as conceptualized by Messick/Kane is needed. In social science, especially education (the field I work in), masters/ doctoral students need to be introduced to the complex nature of establishing reliability and validity. While the content covered is detailed, a more critical introduction of the concepts as being situated in the obtained scores as opposed to the instrument itself would have made the chapter stronger.

Content is for the most part up to date (see above comments for specific areas: reliability, validity, mixed methods); some examples may become outdated very soon (example of political movements in middle eastern countries for example).

The writing is excellent in terms of clarity. I appreciate the use of straight forward language to explain the multitude of concepts!

The text is consistent in its overall approach to research methods as well as consistent in its use of terminology.

Bold font for key terms is appreciated. More insets/boxes within chapters would be a great addition visually. Addition of research studies and discussion questions would be great.

The chapters are well-organized. Only suggestion would be to introduce research ethics early on in the book.

No issues whatsoever in this regard.

No issues with grammar

The text is best suited for universities in western countries although I did not identify any insensitivity that would hinder teaching and learning of research methods using this textbook elsewhere.

Specific chapters in this book will be useful for me, from an instructor's perspective. For example, Chapter 2 - 'thinking like a researcher' is wonderfully written. The chapter on Interpretive Research and Qual. Data Analysis are thorough and clear in presentation of concepts- I definitely would use these chapters in my Research Methods class.

Reviewed by Rachel Lucas-Thompson, Assistant Professor, Colorado State University on 12/5/16

As acknowledged by the author in the preface, this is intended as a survey book that doesn't cover all topics in great detail. The upside is that this is a flexible text that can be used in many disciplines; the down side is that the text is short on examples, which reduces readability. I also prefer a textbook that provides a more detailed discussion of the following issues, but could supplement the textbook with these discussion in class: a) confounding variables, b) writing a research report, and the parts of a research report, c) evaluating the internal and external validity of a study, d) how we handle Likert and Likert-type scales (with better reflection of the rich controversy about this issue), e) historical background that has informed our current ethical guidelines, and f) more detail about manipulated vs. observed independent variables. Also, the 'research process' section doesn't include a step for going through IRB review and approval, so overlooks an important step in social science research. I think more detail is provided about paradigms and theories than is necessary, but those chapters and sections could be left out of course reading assignments quite easily.

In general, I think this textbook would be best suited to a course where the textbook is seen as an overview to supplement course discussions rather than a detailed coverage of research methods principles.

As far as I can tell, the book is accurate. There are some terms that the author uses that are not widely used in my field (developmental psychology, human development & family studies) but the descriptions are clear enough that I think students will be able to understand what is meant (however, it would be great to acknowledge and discuss some of these variations in terminology so the burden isn't entirely on the students who are still learning these concepts).

Research methods and statistics content are unlikely to change rapidly, although with the increasing use of ecological momentary assessments, daily diaries, and internet sampling techniques, it might be useful down the road to include more detail about those techniques.

The book is easy to read and follow, although the lack of examples to clarify concepts sometimes reduces the clarity of ideas (but is in keeping with the philosophy of the book).

I haven't spotted any problems with internal consistency.

It would be very easy to divide this into smaller reading sections and assign at different time points.

In general the organization makes sense; the only exception is having research ethics as an epilogue, when ethical issues need to be considered before a study is completed.

My two suggestions for increasing are a) hyperlinking the table of contents so that it was easier to find exactly what you want in the textbook, and b) providing a more detailed table of contents (with subheadings) so it's easier to determine where in chapters you should reference.

I haven't found any grammatical errors.

The text is neither culturally insensitive nor offensive.

I think this book is very well-suited for intro graduate level courses in research methods, as long as instructors are comfortable with this as an overview supplement rather than a detailed stand alone resource for students.

Reviewed by Robin Bartlett, Professor, University of North Carolina at Greensboro on 12/5/16

Generally the major topics are covered. The table of contents (chapter listing) makes it easy to find content. Occasionally I found what I thought was a topic covered only minimally in a chapter - but then found additional information in a later chapter (e.g., treats to internal validity). Overall I'd say in comparison to most other texts with which I am familiar that most all topics are covered, to some degree, but some topics are covered less than I would expect in a doctoral level textbook.

I found no errors in fact in the textbook. I found it to be written in an accurate and unbiased manner.

Primarily due to the topic covered (research methods), I do not believe the text will become obsolete in a short period of time. I think updates could be easily added, and if the author decided to cover some topics more thoroughly, that could be accomplished relatively easily, too.

The book is written in an easy to read style. It is easy to understand. Technical terminology is explained appropriately. The author puts many words in bold type and then defines or describes the word. Students will like this approach.

I had no issues as I reviewed the book in terms of consistency of terms used. The text is internally consistent.

The chapters of the book are separated by natural divisions. It would be easy to use this book in a course on research methods, in fact, there is a syllabus included at the end of the book that could be used by a faculty member when course creating.

The textbook topics are presented in a logical fashion. The ordering isn't necessarily the same order I have seen in other texts, but the order is reasonable.

I had no major interface problems as I reviewed the book. Some of the diagrams in the book are a little out of focus, but, they are still readable.

I found no grammatical errors in the sections of the book that I read.

I found no cultural insensitivity in the text. I noticed the examples cited were from articles written by authors from different countries.

The book is easy to read and fairly comprehensive in terms of topics covered. Some topics are covered in less detail than in some other books I've had the chance to read / review. I am most accustomed to finding discussion of theories in separate texts and presentation of statistics that might be used to analyze quantitative data in separate texts. There are even a couple of chapters on qualitative methods in this book. So, the book covers a wide variety of topics and introduces them in a clear way. Topics are not covered in as comprehensive way as in many texts.

Reviewed by Kelly Pereira, Assistant Professor, The University of North Carolina at Greensboro on 12/5/16

This text offers a comprehensive overview of social science research methods appropriate for advanced undergraduate and graduate students. The text covers the basic concepts in theory, research design and analysis that one would expect of a text geared toward the social sciences in general. The text could be easily adapted and/or supplemented to fit any discipline-specific needs. While the text covers a broad array of topics, it is a bit superficial and lacks depth in some areas. More examples and case studies, for example, could improve the text's thoroughness. The text also lacks an index, glossary and discussion questions, all of which would have been quite useful for a text of this nature. I do like that it includes a chapter on research ethics and an appendix with a sample syllabus, however.

Based on my review, the text's content is accurate, error-free and unbiased. I liked that it presented both qualitative and quantitative research methods fairly, as this divide is often a source of bias.

The text contains up-to-date approaches to research methods and presents classic theoretical debates. The methods presented should not become obsolete in the near future. Any new trends in research methodology could be easily updated in future versions of this text. I feel the text will be relevant and useful for multiple years.

The text is generally well written. It presents the information in a clear and concise way. I find it provides sufficient contextualization and examples for graduate students with some background already in research methods. Undergraduates will likely require supplemental materials and additional case studies to grasp some of the concepts covered. The illustrations do help guide understanding of concepts presented.

The terminology and research methods frameworks presented in the text are consistent. The use of bolded terms and illustrations throughout the text provide additional consistency.

The division of the text into the following sections: theoretical foundations, concepts in research design, data collection and data analysis, make it easy for instructors to structure a course and assign readings based on these main foundational areas. This format also enables instructors to easily supplement with other materials.

Overall, this is a well-organized text. Bolded words/phrases throughout the text provide some structure to guide reading. The text is divided into 16 chapters, which corresponds seamlessly with a 16-week semester. This enables instructors to cover one chapter per week, if they so desire, or optionally spend more time on chapters relevant to their course and exclude others. As mentioned earlier, the logical division of the text chapters into the areas of theory, research design, data collection and data analysis, lends to a soundly-structured course and facilitates the assignment of readings and other coursework.

I did not experience any issues with the text's interface, navigation or displays of images/illustrations. The text is in PDF format.

I did not notice any grammatical errors that impeded reading of the text.

I did not come across any culturally-insensitive or offensive passages in the text.

Reviewed by Peter Harris, Assistant Professor, Colorado State University on 12/5/16

This is a comprehensive overview of research design and research methods in the social sciences. The book's introductory sections offer a discussion of the philosophy of science, the history of science, and definitions of some key terms and concepts, which will help students to contextualize their own endeavors - and their own discipline(s) - inside a larger framework. It also tackles the more familiar topics of research design - conceptualization, measurement, sampling, and so forth - and several specific approaches to data-collection. Overall, then, the book is to be commended for tackling both the philosophical issues at stake in research design as well as the 'nuts and bolts' (or 'brass tacks') of actually doing research.

One of the book's touted selling-points is its focus on phases of research that precede data collection. That is, the book aims to train students not only in research methods, but also in the critical tasks of theorizing problems, generating research questions, and designing scientific inquiries - what the author refers to as 'thinking like a researcher.' This is certainly a welcome addition to a textbook on research design, and ought to help students to overcome some familiar stumbling blocks that seem to present themselves during graduate programs.

Because of its breadth, however, parts of the book can sometimes seem thin and underdeveloped. In particular, the chapters on data collection (specific research methods) are less detailed and comprehensive than other books manage to provide. It is hard to give a detailed 'how to' guide to either survey research, experiments, case studies, or interpretive methods in just 10 pages. As a result, instructors will almost certainly want to supplement this book with more detailed material, perhaps tailored to their specific discipline.

Even so, this book is an excellent backbone for an undergraduate or graduate class on research methods. It will have to be read in conjunction with discipline-specific guides to conducting research (and, most likely, alongside examples of good and bad research), but this does nothing to detract from the book's own value: it will certainly offer a valuable overview of key concepts, ideas, and problems in research design and data-collection, and will serve students throughout the duration of their studies and not just for one class.

This book is accurate, error-free, and as unbiased as it is possible to be in the social sciences. Of course, it is possible to imagine those who simply hold different views about what social science "is" or should be; some scholars might bristle at the notion that only knowledge produced according to the narrow strictures of the scientific method can be considered "scientific knowledge," for example, while others might balk at interpretivism being given parity of esteem with what they see as more rigorous methodological practices. But for the broad mainstream of the social sciences, there will be little in this book that stands out as unusual, controversial, or one-sided.

On the whole, the content of this book will remain relevant for a long time. After all, the basics of the scientific method and the fundamentals of research design seem unlikely to change in the foreseeable future. New and cutting-edge strategies of data collection and theory-testing do emerge, of course, but these are probably best delivered to students in the form of discipline-specific books or articles that could be assigned to complement this textbook, which deals more with foundations than it does with current debates.

The book is organized well and information is presented in a clear way. The prose is accessible and each chapter proceeds methodically.

This text is certainly consistent, and proceeds according to a methodical and logical structure. Key terms and concepts are introduced early on, and there are no 'surprises' in later chapters.

This book is organized into chapters, each of which could be used as the keystone reading for a given class session, and each chapter is broken down in easy-to-digest sections, making the book as accessible as possible. The fact that there are 16 chapters mean that the book could support 16 separate class sessions - that is, just enough to orient classroom discussion for an entire semester. That said, each module does not comprise sufficient material for a whole week; the chapters will need to be supplemented with extra reading material, especially in graduate seminars. It is unlikely that instructors will want to assign only part of a given chapter. Overall, the text reads well as a whole and in terms of its individual chapters.

The chapters for this book are organized into five sections: the introductory section, a section dealing with the basics of empirical research, sections on data collection and data analysis, and a final section that deals with ethics in research. This is a sensible and logical structure for the book, and nothing seems out of place. Again, the book is an accessible and smooth read; it will pose no challenges to an informed reader, and there will be nothing in the organization of the book that will be distracting or irritating.

As a single PDF, this book is easy to navigate.

I noticed no spelling or grammatical errors in this well-written book.

I can detect no culturally insensitive or offensive remarks in this book.

It is worth mentioning that this text ought to serve students well throughout their undergraduate studies, graduate careers, and beyond. It is a timeless - if necessarily limited - resource, and be returned to again and again.

Reviewed by Tamara Falicov, Associate Professor, University of Kansas on 8/21/16

The book is divided into sixteen chapters, which seemed a bit intimidating at first. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. This makes the book quite comprehensive in that the book could be used for the length of the semester, one chapter per week. This is a useful model and one can add or subtract if needed. For example, the beginning chapter which discusses what science is and uses vocabulary from the hard or natural sciences may not necessarily be relevant in a social science course, but the author is being comprehensive by explaining the origins of science and the creation of the scientific method.The vocabulary in bold is extremely effective throughout the book.

The book is meticulously researched and I did not note any egregious statements or inaccuracies. There was one strange sentence when the author was trying to contrast a liberal to a conservative’s viewpoint on page 18 that made this reader feel a bit uncomfortable in how one ideological viewpoint was portrayed, but I’m not sure it was necessarily bias; perhaps just the writing was a bit heavy handed

The book makes sure of updated case examples, discusses how students utilize the internet for research, etc. The theories outlined here are the classic important debates, and the breadth of knowledge the author imparts is extremely comprehensive and up to date. this book could definitely stand on its own for many years before changes in the field might necessitate updating.

I found the textbook to be a refreshing read. The writing is very accessible and clear, but can be dense at times (though not in a problematic way—it means that with some of the more challenging material, the students will have to dig a little deeper to glean the information. The writing was very crisp, and to the point.

The book is written in a careful, consistent manner. As mentioned earlier, the vocabulary words in bold are consistent signposts, and there are citations (not too many, not too few) that help structure the book and provide a cogent framework. Sometimes there are summaries and bullet points, and other times there aren’t, so this is not exactly consistent, but it doesn’t detract from the overall work.

The chapters are excellent stand alone essays that could be used interchangeably. Some of them, such as the first chapter, is historical and philosophical, but not essential to understanding social science research methods. The second and third chapters are excellent for the researcher who is just starting out to formulate a research question. It helps them to think about the various theories and approaches available to them in terms of the angle, focus and methodology selected. The later chapters explain in greater detail various kinds of methods such as how to measure constructs, and scale reliability. These are higher order concepts which would be useful to graduate students—chapters 1-3 could not only work for graduate students, but also for upper division undergraduates.

The book was structured in a logical progression. There were no problems there. There was some repetition with various terms such as Occum’s razor, but this is because there is some overlap with concepts which I think is fine, given that some chapters may not be used in the course of a semester.

No problems with typeface, the diagrams and graphs are incredibly useful in breaking down more complex research methods.

There were no problems with syntax, grammar, spelling that I came across, except for a minor typo in chapter 9 in the table of contents.

I felt that the author was careful in his selection of case students to try to be inclusive and culturally sensitive. There was that one sentence that raised eyebrows about liberals versus democrats that I mentioned previously, but it wasn’t a major deal.

I found this book to be extremely useful and of high quality. I will to recommend it to a colleague who is teaching research methods next semester in a different department.

Reviewed by Yen-Chu Weng, Lecturer, University of Washington on 8/21/16

Dr. Bhattacherjee’s book, Social Science Research, is a good introductory textbook for upper-level undergraduate students and graduate students to learn about the research process. Whereas most research methods textbooks either focus on “research design” or on “data analysis”, this book covers the whole research process – from theories and conceptual frameworks to research design, data collection, and analysis. This book is structured as four modules and is very adaptable to instructors who want to teach any portions of the book.

Social science is a quite diverse field, including studies of socio-economic data, human behaviors, values, perceptions, and many others. Not only are the topics wide-ranging, but the research methods and the underlying philosophy of science also vary. Therefore, it is extremely difficult to write a textbook that includes everything. Dr. Bhattacherjee’s book is a nice overview of all these different methods commonly used in the social sciences. It aims for breadth, but not depth. Once could use this book as an entry to the field, but would need to seek additional resources for specific methods or analytical skills.

Based on my review of the book, the content is accurate, error-free and unbiased. However, better consistency with terminology often used in other related fields (such as statistics) would lessen students’ confusion with concepts.

Research methods are not time-sensitive topics and are not expected to change much in the near future. The inclusion of some cases or examples showcasing how social science research methods can be applied to current events or topics would help illustrate the relevance of this book (and social science research).

The book is very clear and accessible. It’s written in a way that is easy to understand. Important terminologies are bolded and these are good signposts for key concepts. A glossary summarizing definitions for the key terminologies would help students understand these key concepts. The book includes some helpful figures illustrating concepts in research design and statistics.

Overall, the book is very consistent.

The author, Dr. Bhattacherjee, structured the book following the research process – from theories, to research design, data collection, and analysis. Each module can be a standalone unit and is very adaptable to instructors who want to teach with either the whole book or individual modules. Although each module is mostly self-contained, it is impossible not to refer to other chapters since research is an iterative process. However, I do not expect this to be a huge problem for someone who wants to teach only a section of the book.

The fact that this book is structured as modules also makes it expandable. For those who want to teach only the philosophy of science or only the research design portion, they can add more details and in-depth discussion to these topics.

The book is well-organized and flows well with the research process. The chapters are clearly titled as well as the subheadings. Some numbering with the subheadings would help with navigation. In addition, a chapter summary/conclusion would also help with summarizing the main concepts of a chapter (some chapters do have a summary, but not all chapters).

The flow of the first module (Introduction to Research) is sometimes confusing – the book jumps between big ideas (scientific reasoning, conceptual framework) and specific details (variables, units of analysis) several times in the first four chapters. I thought that reorganizing the chapters as Ch1, Ch4, Ch3, Ch2 would flow better (from big ideas to specific details).

Since the book is organized by the research process, not by the type of research (qualitative vs. quantitative), Module 3 (Data Collection) and Module 4 (Data Analysis) cover both types of research. As a result, the flow/connection between each chapter are less clear. By reorganizing these two modules into “qualitative research methods and data analysis” and “quantitative research methods and data analysis”, not only would improve the flow of the book, but also better serve researchers who are interested in a particular type of research.

There are no major problems with the book’s interface. Each chapter is clearly titled. I would like to see the subheadings being numbered as well. If the PDF could have the Table of Contents on the sidebar, it would improve the navigation even more.

There are no grammatical errors noticed.

There are no culturally insensitive or offensive materials noticed. The few examples used in the book are very general and not controversial.

This book is a nice walk-through guide for researchers new to the field of social science research. One thing I would recommend adding is examples and cases. With more examples and cases, students would be able to put research methods into context and practice how they can apply the methods to their own research projects.

Reviewed by Dana Whippo, Assistant Professor of Political Science and Economics, Dickinson State University on 1/7/16

For its purpose, as introduced by the author, this is appropriately comprehensive. However, it is much more brief, more concise, than traditional research methods texts for undergraduates – which the text does not claim to be. It lays a sufficient foundation, with room and expectation for the professor to supplement with additional materials. Supplementing would be important if using this in an undergraduate classroom. I appreciate that the author emphasizes the process of research, and takes the time to address, in the first four chapters, the logic and process of research in a way that allows the text to be used in multiple disciplines. Indeed, this is one of the strengths of the book: that it can be used broadly within the social sciences. The text does not provide either an index or a glossary. This is more challenging when planning for its use in an undergraduate research methods class; however, I think that the strengths of this book outweigh the weaknesses.

I have not noticed any errors or bias. The only issue I’ve noticed, as indicated in other parts of the review, is depth. Doctoral students would bring in a sufficient foundation for reading this on their own; undergraduates will need scaffolding and additional resources to competently understand the complexity inherent in research.

The content does not read in a way that seems (either now or in the future) likely to read as dated or obsolete. The discussion of survey methodology and analysis programs will change with technology, but that should be easy to update. One of the book’s strengths is its focus on the foundation of research methods: the relationship between theory and observation, the understanding of science, and the logic that underlies the process of research.

The book is well-written and concise. Bearing in mind the author’s stated target audience of graduate and doctoral students, it is entirely reasonable that this would require additional work and instructor support (extra time and explanations for definitions and examples, for instance) when used in an undergraduate classroom.

The terminology is consistent throughout.

Faculty would be able to easily divide the text into smaller sections, which would be useful as those smaller reading sections could be combined with targeted supplementary materials.

The topics generally flow well as presented; the only exception is having the section on research ethics at the end. However, this chapter would be easy to assign earlier in the semester.

I did not have any problems with respect to interface issues.

I did not notice any grammatical errors that interfered with the reading process.

I did not notice any offensive comments or examples. The book is brief by design; it does not include the numerous examples that populate the traditional undergraduate research methods text. I did not find it offensive or insensitive.

Reviewed by Andrew Knight, Assistant Professor of Music Therapy, Colorado State University on 1/7/16

I have not seen a more comprehensive text for this topic area, and yet it retains a concision that I would have appreciated as a PhD student when I took courses in research methods. I think that the text may lend itself to several different types of courses. The early chapters can by used for more theoretical research courses, especially for new researchers and fundamentals of research courses. The later chapters can be used for "nuts and bolts" courses for addressing specific methodological issues. The appendices are an especially nice touch and added value for faculty to understand how the author uses this text and creates a syllabus to complement it.

There are very few typographical errors, and overall, the text is rigorously unbiased in its scientific method claims and explanations.

The overwhelming majority of the content in this text is classical understandings of research and methodologies that are essential to all graduate students, particularly in business and the social sciences. There is no indication that any of the content will suffer from claims that it is obsolete or irrelevant.

The clarity of the text is sound partly due to the concision of the book. Shorter chapters, easily navigable paragraphs, and other compositional devices make the text accessible to most levels of graduate students. The bolded words invite the reader to create a self-guided glossary, not any different than a textbook in an 8th grade student collection, which is helpful to counter the sometimes sophisticated nature of research theory.

No consistency issues noted.

The chapters have a nice flow to them, and can be "chunked" out for use in more beginner or more advanced courses. One preference of this reviewer would be to assign the ethics in research chapter earlier in the course calendar, and thus earlier in the textbook, so it is part of the foundational aspects of understanding social science inquiry. Meanwhile, the qualitative and two separate quantitative chapters play well together for students who will want to review them before exams or after the course is finished while they pursue a thesis/dissertation.

Again, I think the ethics chapter should be earlier, but that is simply a personal choice and can be altered by my syllabus. One issue that I wonder if graduate students might prefer is if they are not already 13 chapters into a text/course and only then are they getting to a basic concept such as measures of central tendency. Offering some of the nuts and bolts of research methods earlier in the text and tying them into the more theoretical concepts might help with clarity of flow for the typical graduate student.

No issues, nice charts and graphics throughout.

Very few noted.

This text is not insensitive in any way. As a matter of fact, pointing out historical issues in research ethics using some sensitive vignettes actually heightens the importance of research in everyday life.

I'm looking forward to adopting it for courses and using it for my own reflections on research!

Reviewed by Allison White, Assistant Professor, Colorado State University on 1/7/16

This text covers a wide array of topics relevant to social science research, including some that are not traditionally included but are welcome additions, such as a chapter dedicated to research ethics. A sample syllabus for a graduate course on research design is also offered at the end of the book, facilitating course development. The book is comprehensive in its treatment of the central components of research design and the different methodological strategies that researchers can leverage to investigate various research questions. Notably absent, however, is an index, glossary of terms, or questions for discussion, which are frequently included in textbooks devoted to research design.

The content is accurate and unbiased, which may be particularly important for texts on research design, as many fields within social science are intractably polarized between quantitative and qualitative approaches. The book goes a long way toward bridging that gap by treating the multitude of methodological orientations fairly and without obvious preference for one or another.

This book will stand the test of time due to its comprehensiveness and fair and balanced approach to research design. Both cutting-edge and classic approaches to research are discussed and the book may be easily updated as warranted by important developments in the social sciences.

The text is written clearly and accessibly, providing adequate context for most of the jargon and technical terminology that is covered. For this reason, it seems suitable for a variety of graduate-level courses, including research design survey courses and more advanced courses focusing on specific approaches.

The text is internally consistent in terms of terminology and framework.

The book neatly compartmentalizes the topics, making it easily divisible into smaller reading sections that can be assigned at different points within the course. The individual chapters stand on their own and do not require contextualization. Numerous sub-headings throughout each chapter flag the central themes.

The topics in the text are presented in a logical, clear fashion. The topics build productively throughout the textbook, beginning with the basic concepts of research design and culminating with different strategies to approach research.

The book's interface is seamless. Charts and images appear appropriately sized and undistorted and the text is free from navigation problems.

The text does not contain conspicuous grammatical errors.

The text and examples provided in it are not culturally insensitive or offensive in any way. Examples are drawn from universal theories rather than research that is culturally-specific.

Reviewed by Jim Hutchinson, Lecturer, University of Minnesota on 6/10/15

This text covers all the basic concepts expected in a book on social science research. However, it does so at a fairly superficial level. The author says this was intentional in order to provide coverage of essential topics and not distract students. As such, the book seems to do a good job introducing all the essential concepts for graduate research, but supplemental materials are likely needed depending on instructor or student needs.

The book seems to free of errors and bias.

Social science research isn't likely to change greatly so this text should remain relevant for some time and can easily be updated to accommodate new techniques as they arise.

The book is generally well-written and accessible. The writing is clear and there are sufficient examples to help students grasp concepts.

The text appears consistent with others in the field.

The text may be best used as an overview of the research process in social sciences rather than a reference. However, various chapters could also be used alone or as supplement to other materials and excluding chapters not relevant to a particular course should not cause any issues. The author even mentions excluding certain chapters that are actually full courses where he teaches.

The organization and sequence seems very logical.

I accessed the PDF version and did not experience any issues with text or graphics.

I think a good proofread would help. There are a number of places where extraneous words were left in (perhaps when rewriting and changing the structure of a sentence) or where words are not quite right. For example:

"...a researcher looking at the world through a “rational lens” will look for rational explanations of the problem such as inadequate technology or poor fit between technology and the task context where it is being utilized, while another research[er] looking at the same problem through a “social lens” may seek out social deficiencies..."

Such errors are not really problematic but they are a bit distracting at times.

I did not find the book to be insensitive or offensive. Examples used are fairly benign. For example, when discussing the tendency of lay people to view a scientific theory as mere speculation the author uses an example of teacher practice instead of a more charged example such as evolution.

Overall, this is a good book to introduce graduate (and even undergraduate) students to social science research. It is not comprehensive enough to be the only text students encounter, but it would be sufficient for say master's level programs that focus more on capstone or practical "informed by research" projects. Students planning to conduct original research, analyze data and interpret results will likely find this insufficient.

Reviewed by Paul Goren, Professor, University of Minnesota on 7/15/14

This text introduces social science doctoral students to the research process. It can be used in sociology, political science, education public health, and related disciplines. The book does an excellent job covering topics that are too often neglected in research methods classes. Standard texts devote most of their attention to different modes of data collection (e.g, lab experiments, field experiments, quasi-experiments, survey research, aggregate data collection, interpretive and case study methods, etc.). This book covers these materials but also devotes a lot of time to steps in the research process that precede data collection. These steps include formulating a research question, concept definition, theory elaboration, measurement (including reliability and validity) and sampling. There is also cursory coverage of descriptive statistics and inferential statistics (a chapter on each) as well as chapter on research ethics. In terms of coverage, then, the text can be described as comprehensive in terms of topics. In terms of depth of coverage of the topics, the text takes a minimalist approach. That is, the fundamentals of each topic are covered, but there is little discussion beyond the basics. Teachers looking for the perfect text that nails all the key points should look elsewhere or make heavy use of supplements. For instance, in the discussion on concepts, constructs, and variables, the text does not distinguish between latent variables, which are unobservable, and manifest variables, which are observable, as is common in the structural equation modeling tradition used in sociology and psychology. This is a minor omission and there are others one might quibble with. The bottom line is that most key topics in the research process are covered, but the coverage is not terribly deep.

From what I can tell, the book is accurate in terms of what it covers. There are some things that should probably be included in subsequent revisions.

The social science research process is unlikely to change in any signfiicant way for some time; therefore, I suspect the book will be relevant for years to come. The key will be ensuring that the latest research trends/improvements/refinements are added to the book. For instance, internet sampling techniques have come a long way over the past decade and there are now pollng firms that can admister online surveys to representative samples of the broader U.S. population. So long as the author keeps on these develops, this will serve as a useful introductory text for the foreseable future.

This text is extremely and unusually well-written and clear. This is one of the text's greatest selling points. No complaints on this score.

The book is very consistent from what I can see.

This book can work in a number of ways. A teacher can sample the germane chapters and incorporate them without difficulty in any research methods class.

The organization is fine. The book presents all the topics in an appropriate sequence.

The interface is fine. I didn't experience any problems.

I didn't see any errors, it looks fine.

The book is not culturally offensive.

Teachers looking for a text that they can use to introduce students to the research process and cover the foundational components of the research process should find this manuscript sufficient for their needs. Simple additions on slides or class room commentary can easily take care of the various omissions that pepper the text. Indeed, one could use this text in conjunction with discipline specific supplements quite effectively. For instance, in chapter 3 on the research process, the author devotes 5 paragraphs to common mistakes in the research process, such as pursuing trivial research questions or blind data mining. I can see how psychologists, sociologists and political scientists could provide discipline-specific examples to tailor this to their students particular needs. More generally, I suspect that the text could be used in conjunction with germane discipline specific materials quite effectively in research methodology classes. The book is not perfect. I wish there was more discussion on field experiments in the experiment chapter. Other than a brief mention that these are relatively rare, there was nothing. These are indeed relatively rare but that seems to be changing in some fields (e.g. economic, political science), and I think more discussion of this technique is warranted. The chapter on case study methods would benefit from discussion on the historical and comparative methods that are used in various social science disciplines, as well as some discussion on case selection methods. The statistical coverage is very thin and should not serve as the primary source material in any class that covers statistics. For instance, the discussion on the empirical assessment of reliability (for items or scales) does not discuss in depth the assumptions that underlie the various methods nor the modifications that need to be made across different levels of measurement. To take another example, the author presents the formulae for the variance and standard deviation on p. 122 with the customary n-1 in the denominator. Students often ask me why we divide the mean squared deviation by n-1 instead of n, which is what we do for the mean. Professors will need to make sure that their slides include discussion of the degrees of freedom idea and perhaps some discussion on unbiasedness as well. In the inferential statistics chapter there's no discussion on desirable properties of estimators (unbiasedness and efficiency). This is an unfortunate oversight. These could be added very easily using simple graphs. One thing that's lacking is a chapter on statistical graphics. The book makes great use of graphics and other visual aids throughout the chapters, but I wish there as a standalone chapter that introduces simple plots for univariate and bivariate data. This can be supplemented easily enough, but the omission seems odd. Again, this book can serve as an compact introduction in a graduate research methodology class for students across the social sciences, but it would work best in conjunction with deeper and more discipline specific materials prepared by the professor.

Reviewed by Anika Leithner, Associate Professor, California Polytechnic State University on 7/15/14

This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. What I liked in particular is that the author includes information on the ENTIRE research process, including critical thinking and research ethics, in addition to the "nuts and bolts" of research such as operationalization, data collection, and data analysis. I also find it useful that the author includes sections on both qualitative and quantitative research, which is great for an introductory level course. In general, readers can expect to find information on theory- and hypothesis building, operationalization/measurements, sampling, research design, various data collection strategies (e.g. surveys, experiments, etc.), as well as data analysis. The primary reason I did not give this text 5 stars is that the author does not provide a great amount of detail for a lot of the book's sections. He explains in the preface that he purposefully chose to reduce the text to the basics in order to keep the text compact and clutter-free. In general, I tend to agree with this approach, as so many methodology textbooks seem to get lost in examples and case studies without clearly illustrating the research process as a whole. However, as I was reading through this book, I kept thinking that I would need to supplement multiple areas of this book with more information in order to make it truly accessible to my students. To be fair, I think that A) anyone who has taught methods before would be able to use the "bones" of this book to prepare students sufficiently well for class and then easily fill in the blanks, and B) it appears that this text was written primarily with graduate students in mind, whereas I most teach undergraduates. In all, I still think that this is a great free alternative to many textbooks out there, but if your teaching style depends on your text including a lot of explanation and examples (or even applications), then this is likely not the text for you. Finally, this book does NOT include an index or a glossary. Personally, I did not find this to be a problem, as the outline/table of contents is very useful, but perhaps students using the text could benefit from an index that would allow them to quickly look up what they need to know.

I did not detect any errors or any purposeful bias in this textbook! Some readers might find that the author's choice of terminology does not necessarily match what I would consider standard practices in the broader social sciences (e.g. the use of the term "mediating variables" instead of "intervening variables"), but it is always clear what the book is referring to and it shouldn't be too difficult to bridge this "terminology gap." Occasionally, I was a bit puzzled by a definition or an explanation. For instance, the author states that "control variables" are not pertinent to explaining the dependent variable, but need to be taken into consideration because they may have "some impact" on it. I'm assuming the author means that they are not pertinent to the hypothesis being tested (as opposed to them not being pertinent to the explanation of the dependent variable). This type of ambiguity does not occur very often in the textbook and it does not necessarily represent an error. It merely seems to be an issue of miscommunication. Overall, I very much liked this text for its accuracy.

Luckily, research methods do not change drastically in a short period of time, so I expect the longevity of this book to be very high. In my experience, the biggest factor that can make a research text outdated is the use of up-to-date examples and case studies. This text includes very few of either, so I think this text could be used for many years to come.

The book is very clear and accessible, probably largely due to its minimalist approach. Aside from the above-mentioned deviations from broader social sciences terminology on a few occasions, I did not encounter any problems with the jargon/technical terminology used. The only minor problem I noted (which made me I've a ranking of 4 as opposed to 5) was a certain amount of repetitiveness in the earlier chapters, specifically with regard to positivism/post-positivism and the discussion of theory/hypothesis creation and testing.

The book is very consistent. It has a clear outline that matches the natural research process and the author very consistently adhere to this outline. Chapters naturally flow from one another and are logical.

This book is very well organized and easily accessible due to its division into logical chapters and sub-sections. In addition, the author highlights important concepts in bold, making it even easier to follow along. I would have no problem assigning smaller reading sections throughout the quarter/semester.

As mentioned above, the text is very well organized and flows naturally/logically. It follows the research process from critical thinking, conceptualization, to operationalization/measurements, research design, data collection, and data analysis. Research ethics are discussed in an appendix/addendum.

There are no major problems with the book's interface. Occasionally, graphs and tables are not as crisp and visually appealing as they might be in an expensive textbook, but personally, the ability to assign an open source text to my students far outweighs any concerns I might have about the visual attractiveness of a book. This text is easy to read and quite user-friendly.

I detected no grammatical errors.

The text includes very few examples and it is hard to imagine how research methods in general could be offensive to anyone (unless it is the practice of science itself that offends them), but for completeness' sake, allow me to state that I found no instances of insensitivity or offense in this textbook.

This text covers all the basics of the research process. It does not contain a lot of the "bells and whistles" that the expensive traditional textbooks have (e.g. lots of examples, fancy graphs, text boxes with case studies and applications, etc.), but it certainly gets the job done. Personally, I appreciate the compact nature of this text and I would much rather fill in a few gaps on my end, if it means that I can assign my students an open textbook.

Reviewed by Brendan Watson, Assistant Professor, University of Minnesota on 7/15/14

See overall comments. read more

See overall comments.

Dr. Bhattacherjee's "Social Science Research: Principles, Methods, and Practices," is a comprehensive, but a bare-boned (and generic) introduction to social science research. In this case "generic" is actually a positive attribute: because the text covers social science research broadly, rather than sociology, psychology, etc. specifically, this text can easily be adapted to the needs of basic research methods courses in allied disciplines. (I teach an introductory quantitative research course for master's and Ph.D. students in a School of Journalism & Mass Communication). I describe the text as comprehensive, because if my students got a basic grasp of all of the concepts in the book, they'd be well positioned to continue on to more advanced research courses (though the text is less valuable as a reference than more comprehensive introductory texts). But while Dr. Bhattacherjee's introduction says that the book is bare-boned by design -- "I decided to focus only on essential concepts, and not fill pages with clutter that can divert the students' attention to less relevant or tangential issues" -- some topics deserve more attention. For example, Institutional Review Boards (IRB) receive only two short paragraphs, and there is no mention of the history of why such boards were deemed necessary and play an important role in the research process. I'd consider such knowledge essential for students, and this is the type of information I would like a text to focus on so that I can spend class time reviewing more complicated concepts students might have trouble grasping on their own. (Generally I found the writing to be approachable, and concepts to be well explained, though extensive examples are also part of the "clutter" omitted from this book). Another topic I would have liked to see developed further - and perhaps is especially important to the more digitally-savvy crowd interested in the open textbook movement - is the expanding role of the Internet and digital technologies in the research process itself, particularly in the era of "big data." The text, for example, mentions Internet surveys, but there is no conversation about tools one can use to build an Internet survey; how Internet surveys differ from traditional modes of surveying; or the practice of weighting Internet survey results to make them "representative" of the larger population. That said, I am balancing using this text versus a more comprehensive, but much more expensive, commercially produced text. Another thing that this book is missing are instructional resources that commercial publishers provide, but ultimately by using this text I can contribute to creating greater value for my students. However, it would have to be supplemented heavily with other materials, as well as lectures, which is not without a trade-off cost. It's certainly doable, but ultimately means a greater investment of my time, and I have to weigh investing my time in creating hands-on learning opportunities and providing students with thorough feedback on their work with the time I'd have to invest in using a text that is complete, but needs to be much more heavily supplemented with additional materials. Ideally, several faculty with similar teaching needs would team up to combine and adapt several open texts to their courses' needs. Adapting and supplementing this text for my purposes by myself, however, remains a steep, if not insurmountable task for a tenure-track professor. This text, however, is thorough enough to maintain my interested in trying to find a way to make it work.

About the book.

Part I. Main Body

Science and scientific research
Thinking like a researcher
The research process
Theories in scientific research
Research design
Measurement of constructs
Scale reliability and validity
Survey research
Experimental research
Case research
Interpretive research
Qualitative analysis
Quantitative analysis: Descriptive statistics
Quantitative analysis: Inferential statistics
Research ethics

Ancillary Material

This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently being used as a research text at universities in 216 countries, across six continents and has been translated into seven different languages. To receive updates on this book, including the translated versions, please follow the author on Facebook or Twitter @Anol_B.

About the Contributors

Anol Bhattacherjee is a professor of information systems and Citigroup/Hidden River Fellow at the University of South Florida, USA. He is one of the top ten information systems researchers in the world, ranked eighth based on research published in the top two journals in the discipline, MIS Quarterly and Information Systems Research , over the last decade (2001-2010). In a research career spanning 15 years, Dr. Bhattacherjee has published over 50 refereed journal papers and two books that have received over 4,000 citations on Google Scholar. He also served on the editorial board of MIS Quarterly for four years and is frequently invited to present his research or build new research programs at universities all over the world. More information about Dr. Bhattacherjee can be obtained from his webpage at http://ab2020.weebly.com .

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Social science research plays a vital role in understanding and addressing complex issues within the field of public health. While medical advancements and analysis of disease data contribute significantly to healthcare improvements, social science research, including the use of qualitative methods, brings a ...

Keywords : mixed methods, qualitative research, anthropology, risk communication, social science, behaviour change, knowledge, attitudes, behaviours, health, public health

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Published: 24 September 2018

Showcasing the contribution of social sciences to health policy and systems research

Stephanie M. Topp ORCID: orcid.org/0000-0002-3448-7983 1 , 2 ,
Kerry Scott 3 , 4 ,
Ana Lorena Ruano 5 , 6 &
Karen Daniels 7 , 8

International Journal for Equity in Health volume 17 , Article number: 145 ( 2018 ) Cite this article

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This collection of articles is presented by SHAPES, the thematic working group of Health Systems Global focused on social science approaches to research and engagement in health policy and systems. The issue aims to showcase how qualitative and theory-driven approaches can contribute to better promoting equity in health within the field of HPSR.

This issue builds on growing recognition of the complex social nature of health systems. The articles in this collection underscore the importance of employing methods that can uncover and help explain health system complexities by exploring the dynamic relationships and decision-making processes of the human actors within. Articles seek to highlight the contribution that qualitative, interpretivist, critical, emancipatory, and other relational methods have made to understanding health systems, health policies and health interventions from the perspective of those involved. By foregrounding actor perspectives, these methods allow us to explore the impact of vital but difficult-to-measure concepts such as power, culture and norms.

This special issue aims to highlight the critical contribution of social science approaches. Through the application of qualitative methods and, in some cases, development of theory, the articles presented here build broader and deeper understanding of the way health systems function, and simultaneously inform a more people-centred approach to collective efforts to build and strengthen those systems.

This Special Issue represents a critical response to the frequent silencing of qualitative social science research approaches in mainstream public health journals, particularly in those that inform the field of health policy and systems research (HPSR), and the study of equity in health [ 1 , 2 , 3 ]. The issue is presented by SHAPES, a thematic working group of Health Systems Global (a membership-based society which aims to convene researchers, policymakers and implementers to develop the field of HSPR) focused on social science approaches.

By bringing together this collection of articles, the special issue highlights the critical contribution of qualitative social sciences including interpretivist, critical, emancipatory, and other relational methods to our understanding of health systems, policies and interventions. Today, political, professional and disciplinary structures continue to privilege positivist research and quantitative methods, attributing greater evidential value to the knowledge produced by these approaches. This issue builds on growing recognition of the complex social nature of health systems [ 4 ] and on the understanding that utilizing only positivist research approaches in the study of health and health systems contributes to stripping away human experience and context. Articles in this issue demonstrate the importance of employing qualitative social science methods to explore the perspectives, experiences, relationships and decision-making processes of human actors within health systems, and in so doing, help uncover and explain the impact of vital but difficult-to-measure issues such as power, culture and norms. Through their application of qualitative methods and, in some cases, development of theory, they help build a broader and deeper understanding of the way various health systems function, and simultaneously inform a more people-centred approach to collective efforts to build and strengthen those systems.

Linked by two important themes, this initial collection of six research papers and two commentaries cut across a range of social science approaches and include policy analysis, rapid ethnography, and theory driven sociological enquiry. Future papers will be added to an online thematic collection on a rolling basis.

Global policies, local realities

The ways in which global health policies are absorbed into national and subnational health systems, and their impact as they interact with local realities is a strong theme running through the issue.

Contractor, et al. [ 5 ] use rapid ethnography to explore the dissonance between tribal women’s perception of pregnancy and childbirth, and the Indian health system’s approach to maternity care in the context of a national policy that strongly incentivises facility-based birth. Drawing on five months of data collection in Odisha state, this exploratory study used qualitative methods to document how different actors perceived and experienced the policy. Unstructured group discussions explored community perceptions around pregnancy and childbirth; in-depth interviews explored women’s actual experiences and practices of pregnancy and childbirth; key informant interviews with service provides yielded contextual information about the field area and views from within the health system; and observations enabled triangulation and produced first-hand information about the location and conditions of health services and tribal areas. The authors highlight the tensions between priorities embedded within national-level policies and tribal women’s own preferences and needs when it comes to childbirth. Their narratives demonstrate how multiple financial, geographic, social and cultural factors mitigate against uptake of facility-based maternity services, and result in pressure, sometimes coercion, by local health system actors, to comply. The article demonstrates the importance of qualitative methods and grounded analysis for surfacing the unintended consequences of blanket state policies through documentation of its impacts on so-called beneficiaries.

Also focussing on India, Sriram, et al. [ 6 ] present a nuanced, contextually rich analysis, reflecting on the way that actors from high-income countries and members of the extended Indian diaspora contribute to socialisation and legitimation of a new medical speciality (emergency medicine). The research draws on a full year of qualitative data collection conducted by the first author including interviews with 76 participants across 11 towns/cities within India, review of 248 documents and observation of 6 meetings. The authors use framework analysis, applying concepts from the literature to insights emerging from the reading of the data, and brought both emic (subject; the first author is a member of the diaspora) and etic (observer) perspectives in making sense of the data. They point to the way power within these networks resulted in the rapid growth of the speciality of emergency medicine, but also influenced its evolution as a highly medicalised, tertiary-level form of care, inaccessible to the majority of Indians for structural reasons including affordability and availability. The authors note that the socialisation of domestic Indian stakeholders in this field ‘flows from a long history of LMIC (low- and middle-income country) stakeholders adopting ideas from high-income countries, driven by undercurrents of globalization and innovations in communication and technology’. Through the personal accounts of stakeholders with a range of perceptions and experiences in relation to the growth of emergency medicine, the authors interrogate and debunk the positive narrative of knowledge flow from high-income countries to LMICs. The qualitative analysis presented instead paints a complex picture, in which power influences knowledge transfer, the outcome of which is not always experienced as beneficial or positive.

Lodenstein, et al. [ 7 ] describe the contradictory role played by traditional leaders in Malawi in the pursuit of improved reproductive health outcomes. They bring attention to the power of traditional leaders, who are regarded as key to facilitating community adoption of positive public health norms including earlier and more frequent attendance at clinic-based antenatal visits. In recent times, the adoption of public health norms in Malawi has been driven by by-laws, set by traditional leaders and with often punitive consequences for those who do not comply; for example imposing fines on women who do not attend antenatal care or who are not accompanied by their husbands on those visits. While some have heralded the success of such by-laws, the authors use qualitative methods and a gendered perspective to explore these as a social process of norm formulation from the perspective of stakeholders involved in by-law creation, as well as the perspective of those affected by them. Recognising that norms are expressed in multiple ways (rules, behaviours, narratives and mechanisms of enforcement), the authors collected data from various sources (documents, observations, and interviews), so as to explore this range of expression. They show that although by-laws were meant to strengthen service uptake and improve health outcomes for pregnant women, they also resulted in the most vulnerable women bearing the moral and material responsibility for any perceived failure to meet reproductive health policy and targets. This study, which is grounded in rich contextual experience, provides important information to national and global health systems decision makers who may be considering using traditional lines of authority to enhance uptake of public health interventions.

Resources and mechanisms of redress

While the above papers describe, and to differing extents deconstruct, the ways in which health systems interact with and exacerbate broader social and structural inequities, a second harmonizing theme in this collection is the way different resources and mechanisms can be mobilised as a form of redress to such inequities.

Spanning both themes showcased in this issue, Turcotte-Tremblay, et al. [ 8 ] describe the local effects of a globally touted performance-based financing (PBF) policy in Burkina Faso. The authors examine the equity measures (such as user fee exemptions available to those holding an indigent card) within PBF, which were introduced to address inequitable access. The study is framed using Rogers’ diffusion of innovations theory. In a comparative case study design across four primary health services, the authors utilise empirical methods, including 93 interviews, discussions, observation and document analysis. Using primary data the authors are able explore the way multiple local actors, including members of local indigent selection committees, re-invented elements of the PBF equity measures over which they had control, to either increase their relative advantage or to adapt to implementation challenges and context. For example, distributing free or very low-cost medications led to financial difficulties and drug shortages at some clinics and compensatory actions intended to resolve these problems by the ‘street level bureaucrats’ running front-line services led to adverse knock-on impacts for clients. Ultimately, the authors demonstrate how local knowledge of what it means to be indigent, and the power dynamics inherent within the health services, interacted with PBF implementation to result in both ‘uncertain and unequal’ coverage of the policy.

Topp, et al. [ 9 ] report on an empirical study of a policy-driven effort to improve the social accountability of prison health services in Zambia through the establishment of prison health committees. Locating their work in the discipline of public policy, the authors use a combination of interviews, focus groups and ethnographic observation, and begin by exploring Joshi’s three domains of impact for social accountability interventions: state responsiveness (represented by facility-based prison officials), societal impact (represented in this study by inmates), and state-society relations. (represented by relations between inmates and prison officials). Their analysis reflects on the ways in which power relations became less hierarchical, and how health outcomes improved in one particular prison after the introduction of a staff-inmate committee. A second phase of analysis draws on a more theoretical and (hence) more widely generalisable model comprising three intersecting ‘axes’ of accountability: power, ability and justice [ 10 ], using these axes to examine the depth and breadth of committee impact. The authors conclude that in relation to prison health care, local context as well as national level politics and legislative reforms, “will be crucial to support democratic decision-making, authentic engagement and appropriate action” in prison health services in low-income settings.

Kapilashrami and Marsden [ 11 ] report a study of access to health-enabling resources by multiply-disadvantaged groups in a deprived part of Scotland. Drawing on human geography and political science, their research uses the theoretical concept of intersectionality – that is, “the multiple interacting influences of social location, identity and historical oppression” – and a combination of standard qualitative tools (interviews, focus groups) and more contemporary and participatory methods (notably collaborative health resource mapping). The authors find that health-enabling resources were variously material, environmental, cultural or affective, with the combined influence of these resources playing out differently for different individuals. Amartya Sen observed in his health capabilities framework, the need to consider both individual choices and societal chances [ 12 ]. Through their use of multiple qualitative methods and the application of intersectionality, the authors demonstrate how individual responsibility, and blame, for health-related behaviour choices is an impoverished explanatory framework because it overlooks the institutional, structural and environmental influences on such behaviours.

While methodologically heterogenous, the articles in this issue showcase just some of the ways in which qualitative social science methods generate important new knowledge that is sensitive to context and which can act as a means to ‘un-silencing’ voices on the margins. Greenhalgh [ 13 ] in her commentary highlights these points, discussing the important role of critical social science as an underutilised method of social critique and emancipation of oppressed groups. She notes that methods such as these ask, “whose definitions count?”; “who makes the rules?”; and “whose voice is not being heard?”

In their commentary too, Lewin and Glenton [ 14 ] note that perhaps the key role of qualitative social sciences is to represent “the views and experiences of stakeholders, including vulnerable and marginalised groups who are often not represented directly.” And indeed, this collection represents a clear body of evidence that health policies and system levers require much work. Contractor, et al. [ 5 ], Kapilshrami, et al. [ 11 ] and Lodenstein, et al.’s [ 7 ] articles, in particular, demonstrate how qualitative social science research can surface issues experienced by, and present the voices of, people on the ground, helping to hold to account global and national health systems leaders responsible for health policy and planning. In order to realise the full value of this type of evidence, however, Lewin and Glenton [ 14 ] also argue the need for more investment in our collective capacity to synthesise the knowledge generated, and to work more closely with policy users and other stakeholders to build their capacity for evidence use.

Articles in this issue demonstrate how qualitative social science methods may be used to engage and participate with actors to co-produce knowledge, evidence and even solutions for change [ 1 ]. At inception, the idea for this special issue also encompassed ambitious plans to model a participatory and empowering approach through mentorship of early career authors, as well as for those based in LMICs. These ideas align with the values of people-centredness and equity that underpin the broader mission of Health Systems Global. Many of the lead authors in this issue are early career researchers, although most are either based in, or receive substantial support from institutions in high-income settings. We therefore believe more personal and institutional investment in learning opportunities through webinars, online teaching, and one-to-one mentoring needs to be made available. This has been recently modelled through various initiatives undertaken by HSG members, affiliates, and thematic working groups. We also acknowledge the ongoing challenges experienced specifically by health system actors who work in, or alongside, services to find the time or receive the guidance necessary to write about what they do. Questions that arose in the process of collating this issue, and which require more, and deeper examination include: how should rich (practitioner) experiences be documented? Should such documentation be acknowledged as a form of research? And if so, where does it belong in a saturated, but often siloed, publication world?

Critically engaging with issues of inclusion, voice and power is vital to building equitable and people-centred health systems and must be at the heart of the research processes that support these systems. As showcased in this special issue, robust qualitative social science research is ideally suited to understanding the social systems that generate or limit opportunities for equity in health, and that must be engaged with and transformed to build truly people-centred health systems.

Abbreviations

health policy and systems research

Health Systems Global

Low- and Middle Income Countries

performance based financing

social science approaches for research and engagement in health policy & systems

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Acknowledgements

We thank Health Systems Global for its support of this and several other articles in this special issue .

Health Systems Global supported this work through payment of the Article Processing Charge.

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Stephanie M. Topp

Nossal Institute for Global Health, University of Melbourne, Melbourne, 3002, VIC, Australia

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Kerry Scott

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Topp, S.M., Scott, K., Ruano, A.L. et al. Showcasing the contribution of social sciences to health policy and systems research. Int J Equity Health 17 , 145 (2018). https://doi.org/10.1186/s12939-018-0862-5

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Social Science Research Topics for Global Health and Wellbeing

Table of contents.

Open Philanthropy strives to help others as much as we can with the resources available to us. To find the best opportunities to help others, we rely heavily on scientific and social scientific research.

If you know of any research that touches on these questions, we would welcome hearing from you. At this point, we are not actively making grants to further investigate these questions. It is possible we may do so in the future, though, so if you plan to research any of these, please email us .

Land Use Reform

Open Philanthropy has been making grants in land use reform since 2015. We believe that more permissive permitting and policy will encourage economic growth and allow people to access higher-paying jobs. However, we have a lot of uncertainty about which laws or policies would be most impactful (or neglected/tractable relative to their impact) on housing production.

Why we care: We think that permitting speed might be an important category to target, but have high uncertainty about this.
What we know: There are a number of different studies of the effects of changes in zoning/land use laws (e.g. see a summary here in Appendix A), but we’re not aware of studies that attempt to disentangle any specific changes or rank their importance. We suspect that talking to advocates (e.g. CA YIMBY) would be useful as a starting point.
Ideas for studying this: It seems unlikely that there have been “clean” changes that only affected a single part of the construction process, but from talking to advocates, it seems plausible that it would be possible to identify changes to zoning codes that primarily affect one parameter more than others. It also seems plausible that this is a topic where a systematic review, combining evidence from many other studies, would be unusually valuable.
Why we care: We are highly uncertain about how to best encourage more construction, and thus about where to target our grants.
What we know: there have been many recent changes to permitting requirements, such as the California ADU law that requires cities to respond to permit requests within 60 days and a new law in Florida that requires cities to respond to permit requests quickly or return permitting fees. This blog post by Dan Bertolet at Sightline predates those changes, but is the best summary we’ve seen on the impacts of permitting requirements.
Ideas for studying this: one might compare projects that fall right below or above thresholds for permitting review (e.g. SEPA thresholds in Washington state), and try to understand how much extra delay projects faced as a result of qualifying for review. It could also be valuable to analyze the effects of the Florida law (e.g. a difference-in-difference design looking at housing construction in places that had long delays vs. short delays prior to the law passing).
Why we care: Currently, estimates of this value are typically made at the level of the metro area, but it seems plausible that we should be differentiating more – e.g. putting higher values on units built in Manhattan relative to those built in Westchester.
What we know: there’s a lot of work on the gradient of land/house prices with regards to transit costs across metro areas, but we aren’t aware of work that explicitly tries to estimate within-metro differences ( in the vein of Card, Rothstein, and Yi (2023) , for example) .
Ideas for studying this: it should be possible to use similar designs looking at moves at a more granular level (e.g. rather than defining effects at the metro level, use changes in distance-weighted job availability). There may also be ways to directly use the land price gradient to estimate this (though in general that will also reflect amenity values).
Why we care: Some people have proposed that a land value tax could encourage land redevelopment and reduce the economic inefficiency of taxation, but we do not know how well this reflects the real-world impact of land value taxes.
What we know: Land value taxes have been used in some Pennsylvania cities, and in some countries outside the US. There has also been increasing interest in implementing a land value tax in other places (e.g. this FT editorial ). See here for many more arguments and references related to land value taxation.
Ideas for studying this: one could use a difference-in-difference design looking at when cities adopt a land value tax (or a split value tax) and examine changes in construction or other outcomes (e.g. volume of land transactions). Alternatively, one could also try a border regression discontinuity looking at differences in land transactions or other metrics at the border between a place that implements a land value tax and one that does not.

Treatments now potentially within reach may extend the human lifespan and improve quality of life. We aim to support tractable and cost-effective research on the world’s most burdensome diseases , including cardiovascular disease, infectious diseases, malaria, and others.

Why we care: Open Philanthropy makes many grants focused on South Asian air quality . However, we still have a lot of uncertainty about the impacts of air pollution. One potentially important variable is the type of pollutant; it would be important for our grantmaking to know if some forms of pollution were much more impactful to reduce than others.
What we know: We know that the components of PM 2.5 pollution can vary substantially by location. There has been some associational work done on this in the US context, but we are more interested in areas with high baseline PM 2.5 levels.
Ideas for studying this: there is some existing data on how the components of PM 2.5 pollution vary across India. This could be linked with mortality data for associational studies. One could also use policy changes that changed the makeup of particulate emissions in a certain area as a natural experiment.
Why we care: Open Philanthropy has made some grants attempting to influence public health regulation. We are interested in knowing how successful other philanthropists have been when making similar grants, and are particularly interested in knowing the effects of Bloomberg’s anti-tobacco advocacy, which we see as one of the most focused (and promising) programs of its type.
What we know: there has been substantial research on the effects of tobacco policy, but we are not aware of any work that focuses specifically on the effect of Bloomberg’s investments.
Ideas for studying this: some of Bloomberg’s grantmaking in tobacco is public ; one could use a variety of approaches to assess the impact of those grants (e.g. a synthetic control).
Why we care: we have made grants on reducing lead exposure in low-income countries in the past and are likely to make more in the future. These grants are made assuming that lead affects both health and income, but we are quite uncertain about the magnitude of the effect of either, especially on health (where we think there is less data). Better estimates of the effect of lead on health would reduce the level of uncertainty around the cost-effectiveness of these grants.
What we know: according to epidemiological (observational) studies , lead has negative impacts on cardiovascular health (see a helpful systematic review here ). However, there is limited causal evidence on the impacts of lead on cardiovascular disease in humans; our primary evidence comes from a study that leverages exposure to NASCAR races to determine changes in ischemic heart disease in the elderly, but we don’t know much about chronic exposure and are reluctant to rely heavily on a single study.
Why we care: Open Philanthropy invests in vaccines for a variety of illnesses, with the primary (though not exclusive) goal of reducing mortality. Having better estimates for how properties of vaccines translate to demand and eventual health impact will help us prioritize when to support “good” leads in clinical trials vs. hold out longer for “great” ones.
What we know: the efficacy of vaccines for different diseases varies considerably, and improved technologies can lead to more promising candidates even for diseases where one or more products are already available.
Ideas for studying this: one could interact the efficacy of a given year’s vaccine (see data here for example) with propensity to get the flu vaccine to determine how this changed flu dynamics. (Though data from South Asia or sub-Saharan Africa would be even better.)
Why we care: Much of Open Philanthropy’s grantmaking in global health R&D is focused on preventing malaria in high-risk populations (as are several charities recommended by GiveWell, with whom we work closely on global health). However, we have little causal evidence on the long-run effects of having had malaria, on either health or income. Thus, we do not have a good sense of the true (long-run) value of preventing malaria.
What we know: a Mendelian study found that the likelihood of stunting increases with each malaria infection.
Ideas for studying this: Mendelian randomization is a technique that looks at people with different genes to determine the causal impact of genes on observable outcomes. Being heterozygous for the sickle cell variant is symptomless but protective against malaria. Thus, those with sickle cell trait are less likely to get malaria and can be compared against those without the trait to understand the long-run impacts of malaria.
Why we care: Open Philanthropy is interested in cost-effectively improving health. Fractional dosing has the potential to lower cost and expand coverage of vaccines. If we had better evidence on this topic, OP could know in which cases (if any) to advocate for more fractional dosing.
What we know: a fractional dose for yellow fever and flu appeared to be non-inferior, but fractional dosing for polio was less successful.
Ideas for studying this: we are not aware of any systematic review of fractional vaccine trials, but many such trials have been run. Studying this topic could involve simply examining data from past trials, rather than running new trials.
What we know: as GBD covers all deaths and DALYs in the world, the team behind it necessarily spends limited time researching any one cause of DALYs. While GBD revisions attempt to address issues with previous estimates, we believe that there may still be substantial errors.
Ideas for studying this: one could look for sharp changes in burden figures between the current and previous GBD studies, or examine a particular cause of death in detail and compare one’s own estimates to those generated by the GBD at different levels of age or geographic aggregation.
Why we care: new medications and medical technologies can substantially improve disease burdens and make treating or eliminating an illness more cost-effective. However, different countries adopt technologies at different rates; we are interested in knowing why. Open Philanthropy might then be able to make grants to encourage adoption of particularly promising technologies in underserved areas.
What we know: it seems that patents, price regulation , and market structure affect drug adoption.
Ideas for studying this: follow up on the approach in Kyle (2007) . One could extend her estimates to estimate the diffusion of FDA-approved drugs globally via patent filings and then look at predictors of diffusion: disease burden, GDP per capita, price controls, language (English vs. not), and path dependency (whether the same companies sell to the same countries repeatedly).
Why do we care: Open Philanthropy tries to cost-effectively improve health and income. Migration is often considered to be one of the best ways to improve income; for instance, a person moving from a low-income country to a high-income country might raise their income by a factor of 50. We have previously made grants in both international and internal migration, and are interested in knowing whether there are underutilized migration channels whereby migrants might substantially increase their income. Our understanding is that aging populations are causing some HICs to offer more work visas than they previously offered, but that the uptake of these visas is poorly understood (and may be quite low).
What we know: there are some international borders that do not require authorization for labor migration (e.g. within the EU, or between India and Nepal). At least one such border includes a low-income country (India/Nepal — India’s per capita GDP is over twice that of Nepal’s), but as far as we are aware, there is no database of such borders.
Ideas for studying this: we think valuable descriptive papers could gather information on the relative usage levels of different work visas (in HICs or MICs) that could be accessible to people from LMICs, or on migration paths that don’t have caps on work visas (such as India-Nepal). Limiting to the largest HICs for ease of initial study (e.g. US, Japan, Germany, France, UK) would probably still be very valuable.
Why we care: education may be one of the best ways to increase long-run income. However, most education studies focus only on a small number of treated students; it is less clear what the general equilibrium effects are (that is, effects across an entire city/region/nation). These are important in understanding how valuable education is in raising wages — and if Open Philanthropy should consider education interventions as a cost-effective way of improving income.
What we know: this question has been examined in both Indonesia and India , but re-examination of these findings has made them seem less robust . In addition, we continue to be surprised that there are so few studies on how large schooling expansions affect wages.
Ideas for studying this: one might use other large-scale expansions of schooling, such as Ghana’s free senior high school program or the Kenyan schooling expansion studied in Mbiti & Lucas (2012) .
Why we care: we think that economic growth is likely to be very important, but it isn’t clear how best to produce higher growth rates through philanthropic funding. One idea would be to increase the supply of highly trained policymakers, who might be able to influence policy that affects many people.
What we know: we’re not aware of work trying to measure the impact of policy training programs, such as the masters program at the Williams Center for Development Economics or the MPA ID at Harvard.
Ideas for studying this: if you could get access to the admissions data for a program like one of the above examples, you could compare people who were nearly admitted to those who were actually admitted to see whether the programs have an effect on career trajectories. This wouldn’t prove anything directly about growth, but would provide evidence that the programs have some counterfactual effect.

Science and Metascience

Why we care: many of Open Philanthropy’s decisions are based on social scientific work. As such, we have a vested interest in this work being reliable and replicable. Unreliable or non-replicable work might lead us to make weaker, less impactful funding decisions.
What we know: the peer review process does not seem to weed out papers with signs of p-hacking , but pre-registration may reduce publication bias .
Ideas for studying this: one might consider the effects of efforts like the AEA pre-analysis plan registry or the Institute for Replication .
Why we care: we think that scientific progress is hugely important to growth and health advances. One issue in current science is that scientists spend a huge amount of time on high-stakes grant applications instead of doing science (and that the applications may be excessively long relative to what’s necessary for identifying the best science). If this is true, advocating for changes to the grantmaking process might be a high-leverage opportunity for Open Philanthropy.
What we know: descriptive data suggests that scientists now spend a huge amount of their time applying for grants, and that spending more time on a grant application does not increase the chance of success.
Why we care: as above, we believe scientific progress is important to growth and health advances. Therefore, we are interested in making sure scientific funding processes work as well as possible to maximize the amount of impact per federal research dollar. If there are improvements that can be made to how science is funded, Open Philanthropy might fund advocacy for such improvements.
What we know: Carson, Graff Zivin and Shrader (2023) find that reviewers would prefer to prioritize papers with more variance in review scores, and that if this preference were taken into account it would likely lead to different projects being funded. A review of the literature suggests that peer review of applications can identify some of the most promising ideas, but the level of signal is fairly weak.
Ideas for studying this: one might look at data on past applications and see how the set of funded projects would have differed given the use of different selection criteria, such as max score or random selection (among projects over a certain level of quality). Alternatively, one could randomize within a specific RFP (so that some proposals are selected under different criteria) or randomize across RFPs (so that you can also see how various selection criteria affect the kinds of applications received). The Institute for Progress is currently studying this in collaboration with NSF.
Why we care: a large share of the value of academic research comes from its ultimate impact on human decisions, but ultimate decision-makers are usually not academics who are well equipped to read and understand individual academic studies. Open Philanthropy would like to know how decision-makers use academic research, and whether there might be improvements to systematic reviews such that decision-makers could be better informed.
What we know: We know remarkably little. This study argues that academic citation networks are significantly impacted by literature reviews, and suggests that they help to organize and orient fields. This study finds that policymakers respond more to sets of studies finding the same thing across multiple settings than to individual studies – but the results are mixed.
Ideas for studying this: we think the rollout of evidence clearinghouses is likely pseudorandom across topics, such that measuring their impact may be tractable with difference-in-difference methods. For example, one could study outcomes across different disease categories as the Cochrane collective rolled out new systematic reviews, starting when it was founded in 1993.
Why we care: Open Philanthropy has occasionally run prize competitions to try and generate useful knowledge. See, for example, our Cause Exploration Prizes and AI Worldviews Contest . We may run more prizes in the future; as such, we would like to know how likely a prize competition is to gather useful information and how to best attract talented entrants.
What we know: a 2010 paper argues that proportional prize contests produce more total achievement, but another paper is less prescriptive about ideal prize structure.
Ideas for studying this: Innocentive has done a lot of prize-like competitions; they might be able to share some useful retrospective data.
Why we care: we believe that rigorous social scientific research is key to identifying the most impactful and cost-effective interventions and policies in developing countries, some of which we may go on to fund. We are interested in knowing cost-effective ways to produce more of said research. We have funded a new IPA office previously, and might fund more such work in the future if we had more evidence about its impact on research, both overall and specific to the target country.
What we know: Matt Clancy, who leads our grantmaking in innovation policy , coauthored an article on the extent to which research done in one place can be usefully applied in other places. Obstacles to this include different places having different underlying conditions, as well as evidence that policymakers prefer research conducted in their own countries. The article’s bibliography includes many relevant sources.
Ideas for studying this: Getcher and Meager (2021) collected data on the openings of developing-country offices for NGOs interested in conducting research within said countries. One could use difference-in-difference design to look at how research production (and RCT production in particular) changes when a new office opens – does it cause an increase in total research in those countries? Is there evidence of substitution from non-RCTs to RCTs? Substitution from neighboring countries to the country with a new office? Do new offices tend to produce research on different topics from existing offices (e.g. focusing more on financial inclusion instead of agriculture)?
Why we care: Open Philanthropy is often interested in influencing policy. Therefore, we want to learn about what is most likely to influence policymakers’ decision-making. We are quite uncertain what types of evidence are most likely to influence policymakers, or in what venues this evidence is likely to be presented.
What we know: Policy documents cite a relatively small number of scientific publications. In one study, policymakers do not seem to respond to strength of evidence in deciding what to implement; in another , policymakers cared more about external validity than internal validity; in another , policymakers cared substantially about sample size.
Ideas for studying this: what evidence do central banks (and other governmental institutions) cite most often, and how does this differ from academic citation practices? Is there additional evidence on what types of evidence best persuade policymakers or are most likely to get cited as part of regulatory decisions? E.g. how do citations from a government agency (e.g. the FTC ) compare to citations in academic work on similar topics?
Why we care: Open Philanthropy wants to raise income levels across society. Our previous work has suggested that public spending on R&D is one of the most effective ways for governments to increase their countries’ income levels. We are thus interested in knowing how the level of public spending on R&D is set, and if there are tractable ways that Open Philanthropy might advocate for this to be increased.
What we know: there is relatively little information available about the process of setting national-level priorities, but there is some data available about agenda-setting within NIH.
Ideas for studying this: we aren’t sure of the best approach. Focusing on particular periods of growth in R&D spending and producing case studies might yield evidence that could be explored in a quantitative way later.

Global Development

Why we care: Open Philanthropy makes grants in global aid advocacy and is interested in increasing both the amount and efficacy of rich countries’ foreign aid. We are interested to know how much influence agency leadership has on the distribution of aid in order to benchmark how much change we should expect over different time frames.
What we know: we’re not aware of any work addressing this.
Ideas for studying this: when a new Administrator is appointed, how much does the distribution of aid change across different categories? Ideally, it would be interesting to compare USAID (which is known to have many Congressional earmarks) to other countries with more flexible aid budgets.
Why we care: we believe that sustained economic growth is one of the best ways to improve health and income. We are interested in knowing how to obtain this. Growth diagnostics are a common tool for trying to select growth-friendly policies, but we are uncertain how valuable this tool is. We are interested in knowing what additional information is gained from using growth diagnostics – how useful they are, and the extent to which this suggests that countries face common vs. distinct growth challenges.
What we know: while there are many papers on growth diagnostics, we are not aware of any evaluation of growth diagnostics across countries.
Ideas for studying this: taking a large body of growth diagnostics from a common source (e.g. the World Bank or Harvard Growth Lab ); using automated methods to measure the similarity of recommendations, compare how similar they are, and determine whether that similarity varies by base GDP (e.g. do similarly rich/poor countries have similar diagnostics?) or region (e.g. do Central Asian countries have similar diagnostics?).
Why we care: many social changes — such as encouraging migration or expanding one’s moral circle to include farmed animals — are often covered in widely-viewed media channels. We are interested in knowing if such coverage changes minds.
What we know: media seems to be able to influence decision-making (as with fertility in Brazil ). Blackfish decreased attendance at Seaworld and decreased the value of the company that owned the park.
Ideas for studying this: we think there is more scope to study individual documentaries or shows (did Waiting for Superman affect views on education? Did Bowling for Columbine affect views on guns?). One could also conduct meta-analyses, looking across a variety of documentaries or shows to look for common effects.
Why we care: we believe that non-competes are likely to reduce labor mobility and decrease innovation .
What we know: there are some surveys on the prevalence of non-competes outside the US, but few are recent or comprehensive. Outside of recent work in Italy , we have little information about how prevalent non-competes are, or how harmful they are in labor markets outside the US.
Ideas for studying this: one could gather information on the prevalence of non-competes and their effects on wages in other large labor markets, like Germany, France, and Spain.

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15 May 2024

Neglecting sex and gender in research is a public-health risk

Sue Haupt 0 ,
Cheryl Carcel 1 &
Robyn Norton 2

Sue Haupt is an honorary senior research fellow at Peter MacCallum Cancer Centre in Melbourne, Australia, and a research associate at The George Institute for Global Health, Women’s Health Program, Centre for Sex and Gender Equity in Health and Medicine, University of New South Wales (UNSW) Sydney, Australia.

You can also search for this author in PubMed Google Scholar

Cheryl Carcel is the head of the brain health programme at The George Institute for Global Health UNSW Sydney, Australia.

Robyn Norton is a founding director of The George Institute for Global Health, a professor of public health at UNSW Sydney and chair of global health at Imperial College London, UK.

Illustration: Sophi Gullbrants

You have full access to this article via your institution.

In 2022, clinical trials indicated that a drug called lecanemab could slow cognitive decline in people with Alzheimer’s disease; soon after the results were published, the global Alzheimer’s community heralded lecanemab as a momentous discovery. However, closer inspection of the data by independent investigators revealed that the drug might significantly help men, but not women 1 .

The finding is a reminder that, even though tremendous advances are being made in the clinical application of cutting-edge technologies, such as gene editing and artificial intelligence (AI), there is a remarkable lack of understanding about how many aspects of human health are affected by variables as seemingly basic as sex and gender.

Sex and gender in science

Over the past decade or so, funders and publishers have made extensive efforts to encourage researchers to address the effects of sex and, in human studies, gender where appropriate. Thanks in part to these efforts, more insights are beginning to emerge. For Alzheimer’s and many other diseases that are common causes of death, including cardiovascular diseases, cancer, chronic respiratory conditions and diabetes, a person’s sex and gender can influence their risk of developing the disease, how quickly and accurately they are diagnosed, what treatment they receive and how they fare.

But even for the most-studied conditions, many questions remain. Few investigators have begun to probe the interrelationships between sex and gender , for example. And in cases in which researchers are managing to unpick the multifaceted effects of sex, this knowledge is not being sufficiently incorporated into the design of clinical trials or adequately changing the practice of medicine.

The consideration of sex and, where appropriate, gender in biological research must become routine — especially as molecular genetics, biomedical engineering and AI open up possibilities for treatments that are better tailored to the needs of individuals. Likewise, the culture of medicine must be transformed so that approaches to treatment evolve in response to the data. This will require further engagement from funders and publishers, but action from many other players, too. Pharmaceutical companies and intergovernmental organizations, among others, must acknowledge three things: how sex and gender can have huge effects on health outcomes; how these effects are often disregarded in basic research and clinical trials; and that change can come only through increasing awareness among all stakeholders of the importance of shifting the dial.

Health outcomes affected

In most human clinical records so far, sex is reported by physicians or participants in studies ticking one of two boxes: ‘female’ or ‘male’. In those clinical studies in which data are collected on chromosomes, hormone levels, reproductive anatomy or other sex characteristics, these features will frequently reflect a person’s sex assigned at birth. But this is not always the case. Added to this, sex and gender have often been used interchangeably, but they are not the same and they do not always align. Current definitions of gender include the social, psychological, cultural and behavioural aspects of being a man or woman (whether cisgender or transgender), non-binary or identifying with one or more other evolving terms 2 .

In several countries, new recommendations about how researchers should obtain data on people’s sex and gender should mean that, in the future, investigators will be able to more-accurately probe the roles of both in human health. But in general, there has been incomplete capture of information for sex and gender so far, including for individuals whose sex characteristics and/or gender identities don’t fall into a binary categorization scheme.

A medical worker transports a patient on a wheeled stretcher from an ambulance

Women are more likely to die after a severe heart attack than are men. Credit: Simon Dawson/Reuters

In this article, consistent with much of the published population-wide data, we refer to a woman as someone who identifies with that gender and was assigned female sex at birth (a cis woman), and a man as someone who identifies with that gender and was assigned male sex at birth (a cis man). But we recognize that participants in the studies we describe might not have been asked about both their gender and their sex.

For all sorts of non-communicable diseases, there are differences between men and women in the average age at which they are diagnosed, the average age at which they die and even in their rates of death.

We need more-nuanced approaches to exploring sex and gender in research

Such variations, from the earlier onset of cardiovascular diseases in men to the more frequent occurrence of Alzheimer’s disease in women, might stem from differences in biology, which can affect people’s likelihood of developing a disease and how they respond to treatment. Or these discrepancies might stem from variation in people’s exposure to the environmental factors that trigger the disease, how they manage their condition, how they are treated by carers and so on, all of which can be influenced by a person’s gender. Often, a combination of factors will be at work.

Take heart attacks. Studies conducted over the past decade have revealed extensive sex differences in the expression of certain genes in heart tissue, which in turn affect the type and function of the cells that make up the heart.

Such variation could help to explain why men are likely to have a heart attack for the first time around six years earlier than women — in the United States, at 65.6 years old in men compared with 72 years old in women 3 — and why (in Australia, at least) heart attacks are at least twice as common in men relative to women of comparable ages (see go.nature.com/3qbvrxq ). Likewise, although mechanisms are yet to be fully understood, it is plausible that differences in people’s biology help to explain why women are more likely to experience pain between their shoulder blades, nausea or vomiting and shortness of breath during a heart attack; why men are more likely to experience chest pain and increased sweating; and why women are nearly twice as likely as are men to die after a severe heart attack.

Yet, when it comes to the risk of dying, social and environmental factors — shaped by gender — also seem to be important.

Tobacco consumption increases a person’s risk of having a heart attack, and smoking is much more common among men globally. Worldwide, around 37% of men smoke compared with around 8% of women . Also, in part because health-care professionals and others are more familiar with the heart attack symptoms commonly seen in men, when women have a heart attack, they are more likely to delay seeking help, and carers are often slower to intervene 4 . In fact, in a study of more than 500,000 people who experienced a heart attack and were admitted to hospital in the United Kingdom between 2004 and 2013, women were 37% more likely to receive an incorrect initial diagnosis after a severe heart attack than were men 5 . Even when women tell their physicians that they have chest pain, they are two to three times less likely to be referred to a cardiologist than are men 6 .

A similarly complicated picture has been emerging in relation to strokes 7 — another cardiovascular disease — and, in the past few years, in relation to cancer.

Three men smoke cigarettes at a designated outdoor smoking area in Tokyo

Smoking is more common among men than women globally. Credit: Behrouz Mehri/AFP/Getty

Most cancers that occur in non-reproductive organs develop earlier in men than they do in women. In the United States, oesophageal cancer is 4.5 times more likely to occur and cause death in men than in women, for example, and lung cancers, the most common drivers of cancer-associated deaths worldwide, kill around 40% more men than women 8 .

Just as with heart disease and stroke, some of this variation seems to stem from behavioural differences. Tobacco consumption increases a person’s risk of developing several cancers 7 . For thyroid cancers, however, women are more likely to develop the disease than are men — three times more likely in some places — which suggests that other factors might drive the different rates of this particular cancer in women and men 9 . But tumours typically arise because of problems with cells’ genetic-repair systems, together with inadequate damage clearance, and genetic differences between men and women that affect cancers are beginning to emerge.

Male–female comparisons are powerful in biomedical research — don’t abandon them

Much more research is needed to understand how sex affects the rate at which genes mutate, cells’ capacities to repair and clear damaged DNA, and when genetic damage starts causing disease. Yet research led by one of us (S.H.) on lung adenocarcinoma, the most common type of lung cancer, suggests that women can survive for longer than men after they are diagnosed, in part thanks to cancer-defence genes in women driving more-robust immune responses 10 . X chromosomes encode many genes that are linked to immunity, and women with two X chromosomes might express these genes at higher levels than men with XY chromosomes.

Responses to cancer treatments also differ between men and women. Chemotherapies tend to work better in women than in men. This could be because it can take longer for women’s bodies to clear certain drugs, which could partly explain why women are also 34% more likely than men to experience harmful side effects 11 . Moreover, women with lung cancer typically have better outcomes after surgery, which they undergo more often than men 8 . This is probably due, at least in part, to women having less advanced disease when they are diagnosed than men do 12 . But the generally stronger immune responses in women might also help their recovery 8 .

Too often ignored

Despite these compelling indications that sex and gender matter, when it comes to many diseases that are leading causes of death, many researchers and health practitioners still fail to adequately take sex and gender into account. They might also be influenced by conscious or unconscious bias.

In the case of heart disease, the differences in gene expression and cellular make-up and activity found in men and women’s hearts highlight the need for sex-specific cardiac tissue models, sustained by sex-appropriate vasculature 13 . (Women on average have smaller hearts with narrower vessels compared with men.) Currently, researchers tend to construct heart models using either animal or human cells, but without necessarily ensuring that cells are sourced from individuals of only one sex per model. In fact, identifying sex disparities in basic heart biology is crucial to engineering relevant heart models with stem cells, for example, which investigators are now developing to aid the study of heart disease 13 .

For both heart disease and stroke, because of decades of under-representation of women in clinical trials, many of today’s standard treatments are based on studies of what happens in men who weigh around 70 kilograms. In clinical trials conducted for stroke and heart conditions between 2010 and 2017, women worldwide were under-enrolled relative to the prevalence of these diseases in the general population — by around 20% 14 . There is also significant underfunding of research for many conditions that are more prevalent in women compared with those that are more common in men (see ‘Disparities in health and disease’).

Disparities in health and disease. Stacked bar chart showing the overfunding totals for female and male-dominated diseases and conditions and how more is overspent on male-dominated diseases.

Source: A. A. Mirin J. Womens Health 30 , 956–963 (2021).

Basic research on cancer is similarly riddled with problems. Take the sex of the cell lines that are stored in commercial cell banks, which have been studied for decades and are the source of much of today’s textbook knowledge. For lung cancers, male lines outnumber female lines by two to one. For liver cancers, the ratio is seven to one. Until a few years ago, few researchers studying cancer in cultured cells in the lab even considered the sex of the cells they were studying. Also, the standard media in which cells are grown is frequently supplemented with fetal calf serum from a mixture of male and female calves, and so contains both male and female sex hormones. And phenol red, a dye commonly used to monitor the pH of tissue culture media mimics the hormone oestrogen 8 .

To add to the difficulties, research findings that emerge from the use of these cell lines are often tested in mice of only one sex. The results of these studies are then used to guide human trials that include both men and women participants. And in oncological clinical trials, just as with stroke and heart disease, women are still under-enrolled relative to the burden of disease they experience 7 .

Inclusivity in human trials will ensure the best possible outcomes for all participants, including cis and trans women and men, gender-diverse and intersex people (see ‘Inclusivity in practice’). Studies are showing, for example, that circadian rhythms — which can affect heart function and might impact how drugs are metabolized — differ between men and women 15 . So how might they compare in non-binary or transgender people? Likewise, knowledge about the immune responses of people with atypical numbers of sex chromosomes is likely to be crucial when it comes to the use of immune checkpoint inhibitors and other immune therapies for treating cancer. Those with Klinefelter syndrome, for example, who, similar to cis women, are at a higher risk of developing breast cancer than are cis men, have multiple X chromosomes that are rich in genes involved in the immune response.

Inclusivity in practice

How researchers include diverse groups of people in clinical trials with enough participants to be able to uncover between-group differences is a challenge.

Women represent nearly half of the population, but they are still under-represented in many clinical trials for numerous diseases, even in cases in which disease prevalence for women has been measured. For smaller population groups, such as transgender people, there are not enough data to even know what representative inclusion looks like. In fact, even if participation does reflect the prevalence of disease in the broader population in any one trial, teasing out effects might require combining the results of multiple studies in meta-analyses.

Advisory governing boards for pharmaceutical companies, such as the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use, funders and regulatory agencies could help with this by ensuring that terminology is adequately and consistently defined, and that populations are properly profiled.

Heightened awareness

Routinely taking sex and gender into account in research and using that knowledge to change health care could benefit billions of people. So what’s needed to make this happen?

Policy changes — such as the US National Institutes of Health’s 2016 call for the inclusion of male and female sexes in studies involving cells, tissues and animals — are crucial. But for many researchers, such calls seem burdensome, especially because studying more than one sex can increase costs. ( Sample sizes might need to be increased to achieve sufficient statistical power when comparing groups.)

Alongside initiatives from funders and publishers, awareness must be built — among students, researchers, clinicians, medical ethics committees, research governance bodies and community groups — of the ramifications of failing to consider sex and gender, and how to correct the problem.

Accounting for sex and gender makes for better science

Efforts led by the Canadian Institutes of Health Research (CIHR) are encouraging. Even though the permeation of knowledge from research to health care has been glacial, between 2011 and 2019, the proportion of all research grant applications submitted to the CIHR that took sex into consideration increased from around 22% to 83%. Gender as a variable is now also included in many of the human studies funded by the CIHR .

Several initiatives have contributed to this. As an example, as well as asking grant applicants to include a section in their research proposals on whether they are considering sex and gender and how they will do so, or why this is not considered applicable, the CIHR has provided training for scientists and organized workshops involving researchers and specialists in sex and gender. Applicants are more likely to receive funding if they provide a satisfactory rationale for their choices.

Convincing people in leadership roles — in governments, laboratories, medical ethics boards, education and so on — of the importance of including sex and gender in research is especially crucial. More studies demonstrating the financial costs of not doing so could help. Between 1997 and 2000, for instance, eight prescription drugs were retracted from the US market because inadequate clinical testing in women had failed to identify that the drugs put women at greater risk of developing health problems than men. This error cost pharmaceutical companies and taxpayers an estimated US$1.6 billion per drug 16 .

The scale of transformation needed will also require more engagement from global players.

Even as far back as 2007, the 60th World Health Assembly — the decision-making body of the World Health Organization (WHO) — passed a resolution to urge researchers to split their data according to sex and to include gender analyses where appropriate. Steps to improve care for transgender people or those with diverse genders are also starting to be taken; in December last year, the WHO established a Guideline Development Group, to provide recommendations on how to address the health of transgender and gender-diverse people . But more extensive efforts, comparable to all United Nations member states committing to target 5.b of the 2015 Sustainable Development Goals by 2030, will be crucial. (This target is to “enhance the use of enabling technology, in particular information and communications technology, to promote the empowerment of women”.)

Lastly, under the guidance of regulatory bodies such as the European Medicines Agency and the scientific entrepreneur community, the pharmaceutical industry must do more to ensure that preclinical work is robust, and that products are tested on enough people of different sexes and genders. Many leading pharmaceutical companies acknowledge on their websites the importance of including diverse groups in clinical trials , but evidence of actions to address the issue is only just emerging.

Awareness of the problems around sex and gender is growing fast. And although many are concerned that medical applications of AI will perpetuate already existing biases 17 , promising developments are emerging in the use of machine learning to make diagnoses that are appropriate for people’s sex and gender.

For decades, for instance, physicians worldwide have been determining whether a person has had a heart attack by using the Global Registry of Acute Coronary Events (GRACE) score, which was derived from trials mainly involving men. In 2022, the application of machine learning to data that had been split for men and women refined the predictors for women. And these revised predictors did a better job of matching individuals to appropriate interventions 18 .

Greater awareness, the wealth of data now emerging and the possibilities presented by new tools, from AI to gene editing, could mean a new era for research and medicine.

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Mental disorders may spread in young people's social networks

Using population-wide registry data, researchers from the University of Helsinki, the Finnish Institute for Health and Welfare, the University of Jyväskylä and the University of Manchester investigated whether mental disorders can be transmitted within social networks formed by school classes.

The study is the largest and most comprehensive so far on the spread of mental disorders in social networks, with more than 700,000 ninth-grade pupils from 860 Finnish schools participating. The adolescents were followed from the end of ninth grade for a median of 11 years.

The researchers demonstrated that the number of classmates diagnosed with a mental disorder was associated with a higher risk of receiving a mental disorder diagnosis later in life.

"The observed link was the strongest during the first year of follow-up in the study. This was not explained by a number of factors related to parents, school and residential area. The link was most pronounced in the case of mood, anxiety and eating disorders," says Associate Professor Christian Hakulinen of the University of Helsinki.

Research enabled by comprehensive Finnish registers

According to Hakulinen, prior studies have yielded similar results: for example, American researchers have observed indications of depressive symptoms potentially being transmitted from one individual to another in social networks.

In prior research, however, social networks have typically been chosen independently by the research subjects, which may result in bias in the data. Hakulinen points out that school classes are social networks well suited to research, as people are usually not able to choose their classmates.

"Defining the social networks and following adolescents were made possible by extensive Finnish registers. The findings significantly deepen our understanding of how mental health problems develop and affect other people in our social networks," he says.

Hakulinen nevertheless notes that the connection observed in the study is not necessarily causal. Furthermore, the study did not investigate how mental disorders can potentially be transmitted between individuals.

"It may be possible, for instance, that the threshold for seeking help for mental health issues is lowered when there are one or more people in your social network who have already sought help for their problems. In fact, this kind of normalisation of diagnosis and treatment can be considered beneficial contagion of mental disorders," Hakulinen says.

More preventive measures?

Mental disorders are a significant global challenge, adversely affecting individuals, society and the economy. According to Hakulinen, anxiety and mood symptoms in particular have in recent years increased among young people.

Previous studies have shown that, in roughly half of all cases, the onset of mental disorders in adulthood occurs when people are under 18. In fact, Hakulinen emphasises the importance of preventive measures and early intervention.

"When taking preventive measures, it's worthwhile considering that mental disorders can spread from one adolescent to another," Hakulinen says.

The study involved a total of 713,809 Finnish citizens born between 1985 and 1997. The adolescents were investigated from the end of comprehensive school until they received their first mental disorder diagnosis, relocated from the country or died. At the latest, the follow-up was discontinued at the end of 2019, resulting in a median follow-up period of 11.4 years.

The study received funding from the European Research Council (ERC) and the Research Council of Finland.

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Journal Reference :

Jussi Alho, Mai Gutvilig, Ripsa Niemi, Kaisla Komulainen, Petri Böckerman, Roger T. Webb, Marko Elovainio, Christian Hakulinen. Transmission of Mental Disorders in Adolescent Peer Networks . JAMA Psychiatry , 2024; DOI: 10.1001/jamapsychiatry.2024.1126

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Public’s Positive Economic Ratings Slip; Inflation Still Widely Viewed as Major Problem

2. top problems facing the u.s., table of contents.

Views of top problems facing the nation
Americans’ views of the state of the nation
Similar shares in both parties view personal financial situation positively
Americans’ views on the future of the economy and their financial situation
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Inflation and the affordability of health care top the public’s list of the biggest problems facing the country, with 62% of Americans describing inflation as a very big problem and 60% saying this about health care costs.

Chart shows Inflation, affordability of health care top Americans’ list of top problems facing the country

Narrower majorities say that partisan cooperation (57%), drug addiction (55%) and gun violence (53%) are very big problems in the country today.

And roughly half say that violent crime (51%), the federal budget deficit (49%), the state of moral values (48%) and the quality of public K-12 schools (46%) are each very big problems.

Illegal immigration, climate change and racism each rate lower on the public’s list of the country’s top problems, though majorities rate these and several other issues included in the survey as at least moderately big problems.

Inflation ranked as the country’s top issue in Pew Research Center surveys from 2023 and 2022 , though its perceived importance is lower than it was in 2022. Today, 62% of Americans say inflation is a very big problem, down from 70% in 2022.

Partisan differences in views of inflation

Chart shows Fewer Democrats now see inflation as a big problem, while share of Republicans saying this ticks back up

Eight-in-ten Republicans and independents who lean to the Republican Party say that inflation is a very big problem. A far smaller share of Democrats and Democratic leaners – 46% – say the same.
The share of Republicans who see inflation as a big problem is up slightly over the past year (from 77% to 80%). In contrast, the share of Democrats seeing inflation as a very big problem for the country has decreased by 6 percentage points over this period.

Federal budget deficit

A narrow majority of the public (53%) says the federal budget deficit is a very big problem. This is little changed in recent years.

Since Joe Biden took office in 2021, Republicans have consistently been about twice as likely as Democrats to describe the federal budget deficit as a very big problem for the country. Roughly seven-in-ten Republicans (71%) say this, compared with 35% of Democrats. During the Trump administration, there was no partisan gap in these views.

Unemployment

Just a quarter of Americans – including similar shares of Republicans (27%) and Democrats (22%) – describe unemployment as a very big problem. The share who view unemployment as a very big problem is essentially unchanged since 2022.

Illegal immigration

The share of the public that views illegal immigration as a very big problem has increased slightly in the past year, to 51% from 47%.

Chart shows Declines in shares naming gun violence and violent crime as very big problems

Nearly eight-in-ten Republicans (78%) say illegal immigration is a very big problem, up from 70% a year ago. In contrast, just 27% of Democrats say this, almost unchanged from the 25% of Democrats who said illegal immigration was a very big problem a year ago.

Crime and gun violence

Americans are less likely to view both gun violence and violent crime as very big problems than they were a year ago. The shares of both Republicans and Democrats who describe each of these as a very big problem are down somewhat over this period.

Democrats are still far more likely than Republicans to see gun violence as a very big problem (68% of Democrats say this vs. 27% of Republicans). And it ranks as one of the top national problems seen by Democrats (as it did in 2023).

And Republicans continue to be more likely than Democrats (56% vs. 39%) to view violent crime as a very big problem for the country.

Climate change

About a third of Americans (36%) say climate change is a very big problem, down 11 points since 2021.

Democrats are 13 points less likely to say this than they were in 2021, when 71% of Democrats described climate change as a very big problem. Republicans’ views of the importance of climate change have declined by 7 points since 2021.

Overall, 29% of Americans say racism is a very big problem. This is a substantial decline since 2021, when 45% said this. Among Democrats, the decline is particularly steep: 42% of Democrats now say that racism is a very big problem in the country today, down from 67% in 2021.

(For Republicans’ and Democrats’ views of all problems asked about in this survey, please visit the overview of this report .)

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National Research Council (US) Committee for Monitoring the Nation's Changing Needs for Biomedical, Behavioral, and Clinical Personnel. Advancing the Nation's Health Needs: NIH Research Training Programs. Washington (DC): National Academies Press (US); 2005.

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3 Behavioral and Social Sciences Research

The behavioral and social sciences cover a wide spectrum of health-relevant research areas. One end of the spectrum has a focus on the individual, including such areas as psychology, behavioral and cognitive neuroscience, and cognitive science. Here the focus is on the individual's behavior, with a direct relevance for mental health and mental disorders and a strong relevance for major health problems such as obesity; drug, alcohol, and tobacco abuse; and propensity for violent behavior and crime. The other end of the spectrum has a focus on interpersonal, group, and societal behavior, including sociology, economics, education, and political science. Research in these sciences has an equally important role in identifying key factors that underlie the complex health problems besetting our society.

The behavioral and social sciences are far more complex and variable than some of the natural sciences; not only is there an almost uncountable number of factors affecting individual and social behavior, but these factors combine and interact in extremely complex and mutable ways. Partly for this reason and partly for historical and cultural reasons, research support and research training in these areas lag well behind those in other sciences. While the behavioral and social sciences have addressed fundamental health care question for decades, methods and tools developed in recent years have provided useful and effective answers to some of the nation's most pressing health care problems.

At the same time that these sciences have been maturing, society has come to realize the absolute necessity of their research findings for the understanding, treatment, and prevention of its health problems. As a result, the behavioral and social sciences have been called on for advice to an ever-increasing degree by government agencies. This is evidenced by the number and range of government-commissioned committees, panels, and reports assigned to the Division of Behavioral and Social Sciences and Education (DBASSE) of the National Research Council. In the past 10 years, there have been over 300 publications resulting from DBASSE assignments that cover a wide range of areas directly or indirectly related to health concerns, including children and families; education, employment, and training; the environment; health and behavior; human performance; international studies; law and justice; national statistics; and population and urban studies. These studies range in scope from the level of the individual to the level of society and cover the entire range of social and behavioral sciences and extend to related fields (such as ecology and criminology). 1

The social and behavioral sciences deal with many of the most complex and least predictable phenomena that affect people's health. Mental health, for example, is an important concern at the National Institutes of Health (NIH; particularly the National Institute of Mental Health, NIMH) as well as in the government and private sector generally. Yet mental health is only one part of a much larger picture because many of the most important health problems are determined and strongly affected by behavioral, social, and economic factors. At the level of the behavior of the individual, the behavioral and social sciences produce knowledge about health issues such as drug and alcohol abuse, obesity, violent behavior, smoking, maintenance of drug treatment regimens, stress management, ability to cope with illness, and health decision making. Moreover, there are many critical health issues that emerge at a larger scale. The economics of health care and its delivery critically determines which diseases and problems are attacked, what research is carried out, and which treatments are given. The government has recognized these factors with multimillion dollar investments in surveys, such as the Health and Retirement Survey, the National Longitudinal Survey, and the National Survey of Families and Households. The behavioral and social sciences provide critical insights and knowledge. This knowledge covers a vast array of issues concerning our ability and willingness to deal with disability and our willingness to expend income and assets for health purposes, such as:

promoting well-being;
distributing health care geographically, sociologically, and economically;
using and misusing health care institutions;
monitoring health providers' behavior;
studying the psychological and social effects of morbidity and mortality;
tracking the social and psychological effects on treatment and recovery;
transferring assets and beliefs across generations;
documenting social support mechanisms;
measuring the economics of alternative health care systems;
verifying the effects of approaches to care and bereavement; and
making health decisions.

Societal, behavioral, and economic factors work together to produce such problems as drug abuse, smoking, alcohol abuse, anorexia/bulimia, and obesity. Once-treatable diseases are making a comeback in more virulent forms because reliable methods cannot be found to ensure that curative drugs are taken as prescribed. Social and sexually transmitted diseases, such as HIV/AIDS, continue to be an increasing menace. Even crime and violence are rooted in elements that require the expertise of behavioral and social sciences research. It is now accepted that many diseases, historically considered mainly a matter for biomedical research, such as heart and lung disease, drug addiction, tuberculosis, and malaria, cannot be understood and treated without the benefit of behavioral and social research. When these far-reaching health implications of behavioral, social, and economic factors are added to the more direct implications of research for mental illnesses such as depression, schizophrenia, and various neurological illnesses, it is no surprise that the research demand in the behavioral and social sciences has grown rapidly in recent years.

Support for research in the behavioral and social sciences at NIH resides primarily in the NIMH, secondarily in the National Institute on Aging (NIA) and the National Institute of Child Health and Human Development (NICHHD), and is scattered in other institutes (with the present exception of the National Institute of General Medicine. It should be noted that the primary mission of NIMH is research into the prevention and treatment of mental disorders, and the mission of NIA and NICHHD is research into the health problems of young and aging populations. Consequently, neither institute directly supports research into key factors underlying societal health problems, such as smoking, alcohol and drug abuse, obesity, and the like. A case could be made that research in the behavioral and social sciences needs to be augmented significantly by other NIH institutes and centers. Most NIH institutes would benefit from scientists knowledgeable in the techniques, methods, and findings of the behavioral and social sciences. In particular, empirical design and quantitative and statistical methodology that have been so effectively refined in the social and behavioral sciences would be useful. Thus at institutes and centers that do not presently have a direct focus on research in the behavioral and social sciences, at least some training needs to be directed toward researchers with this focus. In addition, some of the training given to researchers with other primary foci needs to be informed by appropriate training in the social and behavioral sciences, a point that is taken up directly in Chapter 8 .

BEHAVIORAL AND SOCIAL SCIENCES RESEARCH WORKFORCE

The behavioral and social sciences workforce is as difficult to identify as the biomedical workforce but for different reasons. In particular, it is difficult to identify scientists who are doing basic health-related research, as opposed to those who are involved in clinical practice. Past studies of research training needs in the behavioral sciences generally defined the target workforce as Ph.D.s trained in anthropology, sociology, speech and hearing sciences, and psychology, with the exception of clinical, family, and school psychology. However, since professional organizations in psychology indicate that nonresearch-oriented doctorates are now receiving doctor of psychology (Psy.D.) degrees, the category of clinical psychology is included but not the other practice-oriented fields. Appendix C lists the fields included in the behavioral and social sciences. This inclusion is also supported by an experiment in which NIH was asked to identify whether the research topics for the theses of a sample of the Ph.D. population in the above-listed fields, including clinical psychology, would be considered for NIH funding. The results of this analysis showed that about 90 percent of the thesis topics could be funded and therefore a large portion of the clinical psychology Ph.D.s could pursue research careers. This may be an overestimate of the workforce, but it might provide a more accurate assessment. Whenever possible, the identification of those who do not participate in research will be addressed in the following analysis of the workforce. In particular, attempts were made to identify institutions with professional programs in clinical psychology and to exclude their doctorates from the analysis.

The critical role played by the behavioral and social sciences workforce is increasingly recognized as a key element in both the maintenance of good health and the treatment of disease. The research workforce that addresses the types of diseases and health problems described earlier in this chapter is much broader than the behavioral and social sciences as defined for this study. For example, even in the treatment of what are often considered biologically based diseases, behavior is a factor in getting patients to take their medicine or to participate in physical activities that would help or prevent their condition. These research areas have an interdisciplinary component with the life sciences, behavioral and social sciences, and even the physical sciences. Interdisciplinarity further complicates analysis of the workforce because people trained outside the medical field are doing research important to the medical community (e.g., an economist studying the public health system). However, it would be impossible to factor these researchers into the current workforce assessment.

Another complication is how students identify their research area when they receive their doctorates. The increasing tendency for some research areas in the biomedical and behavioral sciences to converge (neuroscience is the most notable example) may lead to the classification of some doctorates in the behavioral sciences as biomedical. This factor may lead to an undercount of doctorates in the behavioral sciences and an overcount in the biomedical sciences. These difficulties notwithstanding, an attempt has been made to identify doctoral fields for analysis and potential problems in the analyses. The behavioral and social sciences workforce will consist of Ph.D. graduates from universities in the United States in the fields listed in Appendix C and of foreign graduates seeking careers in science and engineering in this country. This definition of the behavioral and social sciences workforce will provide a general estimate of the number of investigators and an indication of the major trends affecting this workforce, such as changes in size, age, and composition.

EDUCATIONAL TRENDS

The pool of college graduates in the behavioral and social sciences from which graduate programs would normally draw increased from about 74,000 in 1987 to almost 132,000 in 2001. In 1987 about 11 percent or 7,894 of these graduates matriculated to graduate programs in doctoral-granting institutions and in 2001 to about 6 percent or 8,305. The number of first-year graduate students was fairly constant during the late 1990s at about 8,500 and increased to 8,996 in 2002. This first-year enrollment resulted in a total full-time graduate enrollment of about 31,500 in 1987 and almost 40,000 in 2002. A portrait of the gender makeup of the graduate students (see Figure 3-1 ) shows a significant change from the late 1970s, when there were only a few more males than females, to 2002 when females outnumbered males by 2.5 to 1.

Graduate students in the behavioral and social sciences by gender, 1979–2002. SOURCE: National Science Foundation Survey of Graduate Students and Postdoctorates in Science and Engineering.

The picture of support for graduate education at doctoral-granting institutions in the behavioral and social sciences is very different from that in the biomedical sciences (see Figure 3-2 ). Traditionally, about half of the graduate students are supported by their own funds or other sources, because external funding from traineeships is small and declining and teaching assistantships are the major source of support.

Graduate support in the behavioral and social sciences, 1979–2002. SOURCE: National Science Foundation Survey of Graduate Students and Postdoctorates in Science and Engineering.

The fairly constant size of the graduate student population seen in Figure 3-1 is reflected in the number of doctoral degrees through 2000 (see Figure 3-3 ). However, over the period from 2000 to 2003, the number of doctorates declined by 368 or about 8.2 percent. From just a few hundred in 1970 the number of doctoral degrees granted to women grew to 2,908 in 2000 but declined slightly to 2,724 in 2003. The number of degrees granted to males dropped from a high of about 2,700 in the mid-1970s to a low of 1,411 in 2003. The decline in doctorates is a reflection of the graduate enrollment declines of the late 1990s, or the problem cited earlier with the classification of doctorates into closely related biomedical fields. On the one hand, the small increase in doctorates in 2003 may reflect the enrollment increases in the early 2000s and may predict a return to the degree production of the late 1990s in a few years. On the other hand, any increase may be temporary, since it may be a result of the national economic situation and will not continue into the future. Time to degree has increased by 3 years in total time and 2 years in registered time (see Appendix E ). These increases have been greater than in the biomedical sciences by about a half a year. Similarly, the median age at time of degree has increased to almost 33 and is one of the highest in science and engineering.

Doctorates granted in the behavioral and social sciences, 1970–2003. SOURCE: National Science Foundation Survey of Earned Doctorates, 2001.

Historically, behavioral and social sciences doctorates did not tend to go on to postdoctoral training, but this trend is changing. This fact by itself would tend to suggest that such doctorates could begin research careers earlier than biomedical doctorates, but such a trend is largely offset by the longer graduate training period. Recently, however, the fraction of doctorates planning on a postdoctoral appointment increased from about one-tenth in 1970 to more than one-third in 2003. Females are more likely to have additional research training since in recent years 15 percent of the females and 9.3 percent of the male doctorates have planned to pursue postdoctoral training. Another interesting aspect of the behavioral and social sciences doctoral population is the increased participation in postdoctoral training by individuals with degrees in clinical psychology (see Figure 3-4 ). This characteristic of clinical psychology doctorates also supports their inclusion in this assessment of personnel needs. For many years postdoctoral training was not considered essential, as was the case for other behavioral and social sciences fields, but in the early 1990s this changed and in recent years almost half of the behavioral and social sciences doctorates have planned to pursue postdoctoral training.

Doctorates planning postdoctoral training, 1970–2003. SOURCE: National Science Foundation Survey of Earned Doctorates, 2001.

The large and increasing number of female doctorates seeking postdoctoral training suggests a special concern in the behavioral and social sciences. The traditional responsibilities of women to bear children and care for their families may lead to times when highly skilled researchers need to work in a less traditional format or even be absent from the workforce. Given the rapid pace of science, NIH might consider addressing this situation not only with retraining programs but also special postdoctoral research grants to keep trained researchers in the workforce during periods in which personal priorities make it impossible to carry a full workload.

The proportion of doctorates facing potential immigration and visa difficulties is presently under 10 percent. An increasing proportion of doctorates in the biomedical sciences with temporary resident status and the problems that might occur if their residency status is jeopardized are not strongly seen in the behavioral and social sciences. Another positive development is the increase in minorities with doctorates. In the 1970s only 1 or 2 percent of the behavioral and social sciences doctorates went to minorities, but that has changed. In recent years, almost 15 percent of the doctorates have gone to minorities.

EMPLOYMENT TRENDS

The behavioral and social sciences workforce grew steadily from 27,356 in 1973 to 99,145 in 2001. Most of the growth can be attributed to the increasing number of female doctorates (see Figure 3-5 ); while they are not a majority of the workforce, their numbers have increased at an average annual rate of 11 percent since the late 1980s. In this same time period, the growth in the number of male workers was only 2 percent. If the postdoctoral population is included in the workforce, the rates of growth have not changed since they comprise only a small part of the workforce. Figure 3-6 shows the number of postdoctoral appointments by employment sector and the rapid growth in appointments in recent years. However, the number of appointments declined from its high of 2,583 in 1997 to 2,093. This decline is similar to that in the biomedical sciences and may be due to higher stipends imposed by NIH because interest on the part of new doctorates in postdoctoral training remains high, as seen by the data in Appendix E .

Behavioral and social sciences workforce (excluding postdoctorates) by gender, 1973–2001. SOURCE: National Science Foundation Survey of Doctorate Recipients.

Trends in postdoctoral appointments by sector, 1973–2001. SOURCE: National Science Foundation Survey of Doctorate Recipients.

While the academic sector accounts for three-quarters of the appointments, as was the case for the biomedical sciences, there is stronger participation in the industrial sector. The other notable difference in postdoctoral training is the citizen/permanent resident and temporary resident ratio in academic institutions. In the biomedical sciences it is 1.4 to 1 with more temporary residents, compared to the behavioral and social sciences with a ratio of 3.6 to 1 with more citizens and permanent residents. It is possible that this difference reflects a divergence in technical training at virtually all levels of education between the U.S. and foreign systems. For example, the need for researchers with technical training (including laboratory training, instrumentation abilities, computational expertise, and mathematical and modeling skills) may have led to a large infusion of foreign researchers in the biomedical fields. If so, the increasing need for such types of training in the social and behavioral sciences may produce a tendency for a movement of the pattern seen in the social and behavioral sciences to that seen in the biomedical sciences.

The distribution of the nonpostdoctoral workforce in the behavioral and social sciences is very different from that in the biomedical sciences (see Figure 3-7 ). While academic employment is still the largest sector, industrial employment is growing at a rapid rate and almost equals that in educational institutions. The nonprofit sector is comparatively larger than in the biomedical sciences. By comparison, the workforce in the behavioral and social sciences is almost as large as the biomedical sciences, with growth at about the same rate, 6.2 percent for the biomedical sciences and 5.4 percent for the behavioral and social sciences. The age distribution for the workforce, excluding postdoctoral appointees, for 1985 is similar for both the behavioral and the biomedical sciences but differs in that the median age in 2001 was 2.5 years older for the behavioral and social sciences workforce (see Table 3-1 ).

Behavioral and social sciences workforce by sector of employment, 1973–2001. SOURCE: National Science Foundation Survey of Doctorate Recipients.

Median Age Cohort for the Biomedical Sciences and the Behavioral and Social Sciences .

Another way to look at the aging of the behavioral and social sciences workforce is to compare the age distribution over time; note that there will be significant retirement in the next 10 years from the 55 to 65 age group (see Figure 3-8 ).

Age distribution of the behavioral and social sciences workforce, 1985, 1993, and 2001. SOURCE: National Science Foundation Survey of Doctorate Recipients.

Academic employment in the behavioral and social sciences more than doubled from 1975 to 2001. Much of that growth was in nontenured positions and other academic categories, which together represent about one-third of the total academic staff in 2001. The size of the tenured and tenure-track staff has been almost constant since the late 1990s and grew by only 11 percent from 1989 to 1999 (see Figure 3-9 ).

Academic employment in the behavioral and social sciences, 1973–2001. SOURCE: National Science Foundation Survey of Doctorate Recipients.

Over the past 10 years two-thirds of the doctorates have been awarded to women. This is reflected in academic appointments, with about 60 percent of nontenured positions held by women ( Figure 3-10 ). Those in tenured positions are far below their 47 percent representation in the workforce, but over time this should change as more women in tenure-track positions receive tenure.

FIGURE 3-10

Percentage of women in academic positions, 1975–2001. SOURCE: National Science Foundation Survey of Doctorate Recipients.

The number of minorities in the behavioral and social sciences workforce increased dramatically from 520 in 1975 to 8,534 in 2001 (see Appendix E ). While the number has grown in recent years by about 15 percent per year and is greater than the 5 percent growth of the total workforce, they still remain a small percentage of the overall workforce. In 2001, underrepresented minorities comprised 8.6 percent of behavioral and social scientists, compared to 1.9 percent in 1973. There are, however, twice as many in the behavioral and social sciences workforce compared to the biomedical sciences workforce, which is about the same size overall.

RESEARCH TRAINING AND THE NATIONAL RESEARCH SERVICE AWARD PROGRAM

In general, the National Research Service Award (NRSA) program plays a smaller role in research training in the behavioral and social sciences than in the basic biomedical fields. Comparing the number of awards in Table 3-2 with a similar table in Chapter 2 , the awards in the behavioral sciences are about one-tenth of those in the biomedical sciences. In terms of the percentage of students supported, less than 1 percent of the 40,000 graduate students in the behavioral and social sciences in 2002 had NRSA support. By comparison, about 9.3 percent of the biomedical sciences graduate students had NRSA support. It has been argued that much of the research in the behavioral and social sciences is not health related and that therefore, training in these research areas is not supportable under the NRSA program. The sample dissertation review, referred to at the beginning of this chapter, contradicts that reasoning because 90 percent of the reviewed dissertation abstracts were considered to be in areas fundable by NIH personnel.

National Research Service Award Predoctoral Trainee and Fellowship Support in the Behavioral and Social Sciences .

NIH's basic mission is to support health-related research, and NIH has historically tended to consider such research to lie primarily in the physical structure of the body and hence in biochemistry, genetics, and similar fields. Behavioral and social sciences research has traditionally been considered less relevant to the NIH mission. This may also be seen in the fact that NIH does not house an institute devoted to basic and applied research in the behavioral and social sciences. What research training there is in this area has tended to reside in NIMH, but NIMH has a mission to focus on mental disorders. Consequently, training in research-relevant areas for many other health problems with a social and behavioral component (such as smoking, obesity, drug abuse, violence, alcoholism) has lagged far behind society's needs. There may be added concerns for research training in the behavioral and social sciences by NIMH due to a recent decision by this institute to shift research funding to areas deemed to have more relevance to public health issues, such as neurological diseases and major mental disorders. 2

Thus, research training in the behavioral and social sciences is not supported through a dedicated NIH institute or center but instead through the coordination of training and research by the Office of Behavioral and Social Science Research (OBSSR) in the Office of the Director. In recent years NIMH has supported a majority of the predoctoral trainees and fellows, followed by NICHHD, the NIA, the National Institute on Drug Abuse, the National Institute on Alcohol Abuse and Alcoholism, and the National Cancer Institute (NCI). A review of the 1,972 T32 3 training grants in 2002 showed that 98 were primarily in the behavioral and social sciences and about 150 others had some behavioral aspects to the training. Table 3-3 shows the distribution of the 98 awards across the NIH institutes and centers. Only 8 of the 21 institutes that could support T32 training made awards. NIMH far outnumbers the other institutes and centers for making these awards. If the institutes and centers with awards that contain behavioral aspects were included, this number would increase to 11 with the addition of the National Institute of Allergy and Infectious Diseases, the National Institute on Deafness and Other Communication Disorders, and the National Institute of Neurological Disorders and Stroke.

T32 Training Grants in the Behavioral and Social Sciences, 2002 .

The institutes and centers listed in Table 3-3 are the principal supporters of behavioral and social sciences research and training, with combined expenditures of $1.7 billion in 2001. Another 14 institutes and centers also provided $295 million in support in 2001. While NCI is a major supporter of behavioral and social sciences research, it provides little NRSA program training support in this area. NCI has used the R25T training mechanism to support training programs focusing on behavioral, prevention, control, and population sciences. In 2004, NCI made six awards under this mechanism to support behavioral science training.

A particularly notable omission from the list of institutes that support training in the behavioral and social sciences is the National Institute of General Medical Sciences (NIGMS). A few behavioral and social sciences doctoral students receive NIGMS training support, but only under institutional NRSA training grants that are focused on biomedical or clinical training. At one time NIGMS did support behavioral training but now claims that such training falls outside its mission. NIGMS has resisted calls from Congress to develop collaborations with other institutes and centers at NIH to support behavioral research. 4

Institutes and centers tend to support training in the behavioral and social sciences that is directed at particular subfields and often do not require interdisciplinary or multidisciplinary aspects generally found in training grants in the biomedical or clinical sciences. In order to encourage interdisciplinarity, it should not be forgotten that training support in the behavioral and social sciences promotes outreach and collaboration with other sciences.

The lack of support notwithstanding, efforts are being made by OBSSR to foster interdisciplinarity by highlighting research that joins the behavioral and social sciences with other health sciences. In July 2002, OBSSR held a workshop on interdisciplinary training in the behavioral, social, and biomedical sciences. It addressed a variety of issues, including the type and level of training, barriers that prevent investigators from doing interdisciplinary research, relevant fields for interdisciplinary training, and what fraction of the NIH training portfolio should support interdisciplinary training. More recently a working group for the NIH Advisory Council to the Director in a draft report recommended that OBSSR coordinate transinstitute basic research initiatives, and designate a home at NIH to foster basic behavioral and social sciences research that is not linked to the mission of the categorical institutes and centers. 5

The M.D./Ph.D. programs, particularly the Medical Scientist Training Program (MSTP) at NIGMS, foster interdisciplinarity. The MSTP was recently expanded to include Ph.D. study in the computer sciences, social and behavioral sciences, economics, epidemiology, public health, bioengineering, biostatistics, and bioethics. However, only a few institutions have students pursuing dual degrees with a Ph.D. in the behavioral and social sciences. The areas of computer science, biostatistics, and bioinformatics seem to be more attractive. Some institutions with well-established programs have expressed difficulty in developing a unified M.D./Ph.D. program with their behavioral and social sciences departments. Generally, the MSTP programs are housed in a biomedical sciences department or a medical school, and as such students are more likely to pursue biomedical research paths.

As shown in Figure 3-2 , less than one-quarter of the graduate student population in doctoral-granting institutions in the behavioral and social sciences is supported by fellowships, traineeships, and research grants. While one of the missions of the National Science Foundation (NSF) is the support of the behavioral and social sciences, NSF support is only about one-tenth the total federal support and less than one-third of the support provided by NIH (see Figure 3-11 ).

FIGURE 3-11

Funding sources for graduate education in the behavioral and social sciences, 1979–2002. SOURCE: National Science Foundation Survey of Graduate Students and Postdoctorates in Science and Engineering.

It should be noted that total graduate support has declined since the 1970s and early 1980s, mainly due to reductions by the non-NIH part of the U.S. Department of Health and Human Services. The current number of graduate students supported by NIH is about the same as in the 1970s. However, the proportion with NIH support has declined due to an increase in the total number of graduate students. In proportion to the total number of graduate students, NIH support has declined since the 1970s. The form of support has also changed over time. In the 1970s and early 1980s, NIH supported mainly graduate fellowships and traineeships, but by the 1990s its support shifted to research grants. Consequently, by 2001 over two-thirds of the support provided by NIH was in the form of research grants, and in 2002 it grew again by about 15 percent (see Figure 3-12 ).

FIGURE 3-12

Graduate student support by NIH, 1979–2002. SOURCE: National Science Foundation Survey of Graduate Students and Postdoctorates in Science and Engineering.

As is the case at the predoctoral level, NRSA program support of postdoctoral training in the behavioral and social sciences is a fraction, between 10 and 15 percent, of that in the biomedical sciences (see Table 3-4 ). The decline in the number of postdoctoral positions supported by the NRSA program is similar to that in the biomedical sciences. This may be due to similar reasons: the higher stipend levels and the eligibility of individuals for NRSA support. There are no data on general postdoctoral support from NIH, but the picture for postdoctoral training support from all federal sources also shows growth in research grant support and the decline in trainee and fellowship support (see Figure 3-13 ). NIH's efforts to shift research training in the behavioral and social sciences from the predoctoral to the postdoctoral level in the late 1970s and 1980s can be seen by comparing predoctoral support level in Figure 3-12 and postdoctoral support in Figure 3-13 .

National Research Service Award Postdoctoral Trainee and Fellowship Support in the Behavioral and Social Sciences .

FIGURE 3-13

Academic postdoctoral support in the behavioral and social sciences, 1979–2002. SOURCE: National Science Foundation Survey of Graduate Students and Postdoctorates in Science and Engineering.

The discussion in Chapter 2 of an outcomes analysis for NRSA- and non-NRSA-supported researchers at the predoctoral and postdoctoral levels presented a case for reversing the trend toward more training on research grants. For the behavioral and social sciences, the same conclusions cannot be drawn. The most recent assessment of the career outcomes of NRSA predoctoral trainees and fellows in the behavioral and social sciences did not yield results that were clear-cut evidence. NRSA trainees and fellows, particularly those who received support at the start of graduate school, completed their Ph.D.s faster than other students, but there was no clear difference with regard to employment or research productivity. These findings should be interpreted with caution though since the number of trainees supported under the NRSA program is smaller in the behavioral and social sciences, and the sample used to assess the outcomes is also smaller and more prone to error.

RESEARCH LABOR FORCE PROJECTIONS

As mentioned earlier in this chapter, individuals with doctorates in clinical psychology are considered part of the research workforce and as such may tend to overestimate the size of the actual workforce. Another uncertain component of the workforce are foreign-trained researchers now in the United States. Characterizing this component has proven problematic for the other two broad fields but is less so in the behavioral and social sciences since they appear to make up a small fraction of the population. The 1990 U.S. Census data estimate this group at about 3 percent of the workforce, and data from the U.S. Department of Education Survey of Postsecondary Faculty place the faculty percentage a little lower, at about 2 percent. In either case the numbers are small and will not have a significant effect on the projections. Table 3-5 shows the change in this workforce for U.S.-educated Ph.D.s over the past decade. A comparison of this workforce with that in the other broad fields shows a similar unemployment rate for those seeking employment and a rate for those not seeking employment similar to the biomedical sciences. As expected, the proportion of postdoctoral positions is lower than in the biomedical sciences and similar to that in the clinical sciences.

Potential Workforce in the Behavioral and Social Sciences by Employment Status, 1991–2001 .

A life-table estimate of the science and engineering workforce in the behavioral and social sciences for the next 10 years is less problematic, since the variability introduced by the foreign doctorates is much less. The following is a short summary of the findings from the life-table analysis; full details can be found in the Appendix D .

Graduates from U.S. Ph.D. programs will be the major contributor to the future workforce in the behavioral and social sciences, but since that population has shown little or no growth in the past, the projected growth and that of the workforce will be small. Table 3-6 shows the results of the multistate life-table analysis for the period from 2001 to 2011 under the median scenarios.

Projected Workforce by Status for the Median Scenario, 2001–2011 .

The projected median growth scenario for Ph.D. graduates increases from 4,221 in 2001 to only 4,619 in 2011, or about 0.5 percent per year. The inflow of foreign-trained Ph.D.s is only about 100 per year. Given this and the slow growth in the number of doctorates for U.S. institutions, the employed workforce is projected to grow from 102,193 in 2001 to 119,840 in 2011. This translates into about a 17 percent growth in the workforce and an annual growth rate of about 1.5 percent. This is the lowest growth rate of the three broad fields. The other segments of the workforce, except for postdoctoral appointments, are projected to decline over the same 10-year period. Postdoctoral appointments in the behavioral and social sciences have increased over the past decade, and this is projected to continue, with about one-third more doctorates in postdoctoral positions in 2011 than in 2001. Unemployment is projected to remain low and even decline to about 0.4 percent of the potential workforce in 2011.

In assessing the overall picture for the behavioral and social sciences, the situation is similar to that for the biomedical sciences—namely, unemployment is low and the number of Ph.D.s entering the job market in the future is consonant with reasonable expectations about job availability. Appendix D discusses the uncertainties in the workforce model used to generate this conclusion. Based on this limited model, the status quo appears appropriate. However, all of these conclusions need to be placed in a broader context, which will be discussed in Chapter 10 .

Finally, the NRSA program plays a special role in setting standards and attracting people to specific fields. This is vital for the health of the training system. A marked difference in training in the behavioral and social sciences relative to the biomedical sciences is in the concentration of support in a single institute, the NIMH. Because of the interdisciplinary nature of the subject matter and its general importance to the health of the nation, this does not seem desirable. A better distribution of training support across all NIH institutes and centers (including NIGMS) would be preferable. A specific recommendation in this regard is made in Chapter 5 , but this issue also merits mention here.

RECOMMENDATIONS

Recommendation 3-1: This committee recommends that the total number of NRSA program positions in the behavioral and social sciences should remain at least at the 2003 level. Furthermore, the committee recommends that training levels after 2003 be commensurate with the rise in the total extramural research funding in the biomedical, clinical, and behavioral and social sciences.

Data on the number of predoctoral and postdoctoral traineeships in the behavioral and social sciences are incomplete after 2000. 6 In 2000 there were 434 predoctoral trainees and 240 postdoctoral trainees. There was an 8.5 percent increase in the total number of predoctoral NRSA positions from 2000 to 2003 and an 8.4 percent increase in postdoctoral NRSA training positions. Assuming these increases also held for the behavioral and social sciences, approximately 471 predoctoral and 260 postdoctoral NRSA training slots would have been filled in the behavioral and social sciences in 2003. Fellowship data are probably more current, since these awards are made to individuals in specific training areas, and the predoctoral and postdoctoral awards in 2002 were 194 and 111, respectively. This level of predoctoral support was probably also true for 2003, since there was little change in the total number of NRSA fellowships from 2002 to 2003. Therefore, the total number of individuals in the behavioral and social sciences supported by the NRSA mechanism in 2003 is about 665 at the predoctoral level. This is only a small fraction of the total support for graduate students. Much more comes from institutional support through teaching assistantships and self-support. Similarly, postdoctoral support is more likely to come from research grants and other forms of institutional support (see Figure 3-13 ).

The recommendation links the training level in the behavioral and social sciences to extramural research support across NIH, since all of the three broad fields for which NRSA training is available are becoming more interdisciplinary and training is needed to meet this trend. While NIH currently classifies research grants into a single area of research, it is also quick to recognize that the research may involve many fields and that expertise is needed in these fields to carry out the research.

The relatively low unemployment among Ph.D.s in the behavioral and social sciences suggests that having 2003 serve as a baseline for NRSA program support and having increases based on increases in extramural research support are both justified.

The discussion following Recommendation 2-1 with regard to the quality of the NRSA program and the relative balance of biomedical training to the workforce also applies to the behavioral and social sciences.

Recommendation 3-2: This committee recommends that each NIH institute and center incorporate the behavioral and social sciences into its training portfolio, including institutes and centers that have not emphasized these disciplines in the past.

The behavioral and social sciences are critical for the understanding, prevention, and treatment of most major health problems. For historical rather than rational reasons, most training has been centered in just a few NIH institutes and centers. In the case of NIGMS, Congress specifically instructed that the behavioral and social sciences be included, but this has not been done as of 2004. The result is that health decisions that arise in many institutes and centers are made without sufficient input from scientists and decision makers who have knowledge of and training in the techniques of the behavioral and social sciences.

A sample of reports directly relevant to health concerns include: Educating Children with Autism ( National Research Council, 2001a ); Informing America's Policy on Illegal Drugs: What We Don't Know Keeps Hurting Us ( National Research Council, 2001b ); Preventing HIV Transmission: The Role of Sterile Needles and Bleach ( National Research Council and Institute of Medicine, 1995 ). Preventing Reading Difficulties in Young Children ( National Research Council, 1998a ); Protecting Youth at Work: Health, Safety, and Development of Working Children and Adolescents in the United States ( National Research Council, 1998b ); Reducing Underage Drinking: A Collective Responsibility ( National Research Council, 2004b ); Understanding Risk: Informing Decisions in a Democratic Society ( National Research Council, 1996a ); Understanding Violence Against Women ( National Research Council, 1996b ); Work-Related Musculoskeletal Disorders: A Review of the Evidence ( National Research Council, 1999 ).

Agres, T. 2002 .

See Appendix B for a complete explanation of awards.

Statement from the NIGMS justifying its 2003 budget request: “The Institute's research training programs mirror the areas of science that fall within the mission of the National Institute of General Medical Sciences. Except for a few fields of inquiry, behavioral studies largely fall outside of the Institute's research mission, and are instead deemed to be within the missions of other institutes at the National Institutes of Health.” Also see http://www.psychologicalscience.org/advocacy/issues/nigms_observer.cfm .

Draft Report of the Working Group of the NIH Advisory Committee to the Director on Research Opportunities in the Basic Behavioral and Social Sciences, http://obssr.od.nih.gov/Activities/Basic%20Beh%20Report_complete.pdf , December 2, 2004.

Data on the number of NRSA trainees in the behavioral and social sciences are incomplete after 2000 since educational institutions report on the number of students trained in a field. The information is returned to NIH as much as 2 years after training, and the information was last processed in February 2003.

Cite this Page National Research Council (US) Committee for Monitoring the Nation's Changing Needs for Biomedical, Behavioral, and Clinical Personnel. Advancing the Nation's Health Needs: NIH Research Training Programs. Washington (DC): National Academies Press (US); 2005. 3, Behavioral and Social Sciences Research.
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Satabdi Samtani, PhD

Satabdi Samtani joined the Begun Center in May 2024 as a Senior Research Associate. She primarily works on the Ohio Behavioral Health Juvenile Justice (BHJJ) initiative with Dr. Jeff Kretschmar. At the Begun Center, her efforts involve rigorous research and evaluation to assess the effectiveness of the BHJJ initiative, identify best practices, and drive continuous program improvement. This work is pivotal in producing insights that benefit not only the youth directly involved in the program but also in shaping broader strategies and policies in youth justice and mental health at the state level. She also provides methodological and analytical support for other program evaluations conducted by Dr. Kretschmar's team.

Satabdi’s prior work includes evaluating behavioral health programs such as the Louisiana State Opioid Response, the Zero Suicide Model for Health Systems funded by SAMHSA, and the Pay for Success Initiative funded by the DoJ. She also has experience working on youth development programs and was the primary researcher for a national evaluation of sixteen character-focused youth programs as part of her post-doctoral experience at Montclair State University. She has also collaborated with school leaders on ethical leadership and social-emotional learning in the Greater St. Louis region during her tenure as a research scientist for the Center for Character & Citizenship at the University of Missouri-St. Louis.

Satabdi’s current research interests include behavioral health disparities, social emotional learning, and innovative mixed-method designs. She also has expertise in program evaluation and secondary data analysis.

Satabdi earned her doctorate in Human Development and Family Studies from Texas Tech University, with minors in Health Care Administration and Cross-Cultural Studies. She holds a master’s degree in International Development from the University of Sussex, UK, and another in Human Rights from the University of Calcutta, India. She completed her BS degree in Economics from the University of Calcutta.

Satabdi grew up in India and loves to keep up with global issues. In her free time, she enjoys growing plants, exploring different cuisines, listening to podcasts, and going on road trips.

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The White House 1600 Pennsylvania Ave NW Washington, DC 20500

Applying Social and Behavioral Science to Federal Policies and Programs to Deliver Better Outcomes

By Steve M. Newell, OSTP Assistant Director for Innovation and Equity

Kei Koizumi, OSTP Principal Deputy Director for Science, Society, and Policy

President Biden challenged the country’s science and technology ecosystem to guarantee that the fruits of science and technology are fully shared across America and among all Americans. On Day One of his Administration, President Biden issued an Executive Order on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government to advance equal opportunity for everyone. And in his first week, President Biden issued a memo to champion evidence-based policy decisions guided by the best available science and data . Delivering effective policies and programs that benefit everyone in America means leveraging every tool at our disposal.

Human behavior is a key component of every major national and global challenge. Social and behavioral science examines if, when, and how people’s actions and interactions influence decisions and outcomes. Understanding human behavior through social and behavioral science is vitally important for creating federal policies and programs that open opportunities for everyone.

Today, the Biden-Harris Administration shares the Blueprint for the Use of Social and Behavioral Science to Advance Evidence-Based Policymaking . This blueprint recommends actions for agencies across the federal government to effectively leverage social and behavioral science in improving policymaking to deliver better outcomes and opportunities for people all across America. These recommendations include specific actions for agencies, such as considering social and behavioral insights early in policy or program development. The blueprint also lays out broader opportunities for agencies, such as ensuring agencies have a sufficient number of staff with social and behavioral science expertise.

The blueprint includes nearly a hundred examples of how social and behavioral science is already used to make real progress on our highest priorities, including promoting safe, equitable, and engaged communities; protecting the environment and promoting climate innovation; advancing economic prosperity and the future of the workforce; enhancing the health outcomes of all Americans; rebuilding our infrastructure and building for tomorrow; and promoting national defense and international security. Social and behavioral science informs the conceptualization, development, implementation, dissemination, and evaluation of interventions, programs, and policies. Policymakers and social scientists can examine data about how government services reach people or measure the effectiveness of a program in assisting a particular community. Using this information, we can understand why programs sometimes fall short in delivering their intended benefits or why other programs are highly successful in delivering benefits. These approaches also help us design better policies and scale proven successful interventions to benefit the entire country.

For example, Head Start began in 1965 as a demonstration project, informed by the intersection of health and psychological science, aimed at addressing children’s emotional, social, health, nutritional, and educational needs. It has now grown to a national program that serves hundreds of thousands of children and families in communities across the country. In the last 60 years, the initiative grew in scope and effectiveness by leveraging social and behavioral science approaches such as descriptive surveys, case studies, and evaluations. These approaches improved program design and service delivery by identifying the parts of early childhood education that best support child and family well-being. Social and behavioral sciences revealed the most effective strategies for improving enrollment and retention for eligible families. The Head Start program represents the cycle of social and behavioral science-informed policy in the blueprint. That cycle begins with the identification of a challenge focused on human behavior and continues with analysis and revisions to the program over time.

Social and behavioral science gives us the knowledge and tools we need to support and serve communities across the country. Our national challenges are complex and pressing, which is why we must leverage available insights and approaches that can help us more effectively design, implement, and evaluate policies and programs. By continuing to integrate these insights into federal efforts, we can help ensure that all Americans have longer, healthier, more prosperous lives.

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Building a home for the social and interdisciplinary sciences and
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Discover Social Science and Health is an open access journal publishing research across the full range of disciplines at the intersection of health, social and biomedical sciences.. Indexed in SCOPUS. Integrates a social perspective and a concern for health. A Discover journal focused on speed of submission and review, service, and integrity.
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This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any ...
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