research on the impact of social media on mental health

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• Published: 07 September 2022

The mental health and well-being profile of young adults using social media

• Nina H. Di Cara 1 , 2 ,
• Lizzy Winstone 1 ,
• Luke Sloan 3 ,
• Oliver S. P. Davis 1 , 2 , 4   na1 &
• Claire M. A. Haworth 4 , 5   na1  

npj Mental Health Research volume  1 , Article number:  11 ( 2022 ) Cite this article

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• Human behaviour
• Interdisciplinary studies
• Medical research
• Psychiatric disorders

The relationship between mental health and social media has received significant research and policy attention. However, there is little population-representative data about who social media users are which limits understanding of confounding factors between mental health and social media. Here we profile users of Facebook, Twitter, Instagram, Snapchat and YouTube from the Avon Longitudinal Study of Parents and Children population cohort ( N  = 4083). We provide estimates of demographics and mental health and well-being outcomes by platform. We find that users of different platforms and frequencies are not homogeneous. User groups differ primarily by sex and YouTube users are the most likely to have poorer mental health outcomes. Instagram and Snapchat users tend to have higher well-being than the other social media sites considered. Relationships between use-frequency and well-being differ depending on the specific well-being construct measured. The reproducibility of future research may be improved by stratifying by sex and being specific about the well-being constructs used.

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Introduction.

The trails of data left online by our digital footprints are increasingly being used to measure and understand our health and well-being. Data sourced from social media platforms has been of particular interest given their potential to be used as a form of ‘natural’ observational data about anything from our voting intentions to symptoms of disease. There is not a single, widely agreed definition of the term ‘social media’ 1 , but for the purposes of this study we understand it to be a broad category of internet-based platforms that allow for the exchange of user-generated content by ‘users’ of that platform 2 . Both the huge volumes of data available on such platforms, and their increasing uptake across the population 3 have led to two main fields of interest in the intersections of social media and mental health. These are the prediction of mental health and well-being from our online data 4 and, somewhat reciprocally, the influence of social media on our mental health, particularly in the case of children and young people 5 , 6 . These fields both ask fundamental questions about the mental health and well-being of social media users, to either understand the ways our mental health influences our social media behaviour, or how our social media behaviours influence our mental health.

Across both contexts a wide range of psychological outcomes have been studied, including predicting suicide at a population-level 7 and individually 8 , mapping the influences of social media platforms on disordered eating 9 and self-harm 10 , understanding the impacts of cyberbullying through social media platforms 11 , 12 , and even ethnographic research into online support networks 13 . As highlighted in a recent review which considered research on the relationship between social media use and well-being in adolescents 14 , there has tended to be an inherent assumption that social media is the cause of harm when examining the effect of social media on our health. However, recent investigations such as those by Orben and Przybylski 15 , 16 and Appel and colleagues 17 illustrate that the role of social media in causing harm may be over-estimated. It seems likely that there is some reciprocal relationship between mental health and social media, that requires longitudinal research studies to begin to understand the complexity, coupled with large representative samples to explore the heterogeneity 18 , 19 . Further, there is increasing attention on the role of within-person effects that see impact change between contexts 20 , 21 , as well as individual differences 22 . Meanwhile, attention has also been drawn to the comparative lack of investigation into the potential benefits of social media, such as access to peer support and the ability to readily connect with friends and family, or into the psychological well-being of social media users as opposed to focusing on pathology. Similarly, most psychological prediction tasks using social media focus on predicting illness rather than wellness 4 , 23 .

Regardless of the direction of interest in the relationship between social media and psychological outcomes, researchers face common challenges, with one of the primary issues being a lack of high-quality information on the characteristics of the whole population of social media users 24 . Valuable demographic information on social media users in the United States is regularly produced by the Pew Research Centre 25 , but often researchers rely on algorithmic means to make predictions about the demographics of the groups they study online if they are not recruiting a participant sample whose demographics are known and can be recorded 4 , 24 , 26 . What we do know about social media users is that they are not homogeneous. The demographic features of populations using them vary across platforms and do not tend to be consistent with the characteristics of the general population 25 , 26 , 27 , 28 . This work on the demographic context has been important in understanding the samples that can be drawn from social media platforms, but there remains a lack of information about other characteristics of social media users that are relevant to study outcomes, including mental health and well-being. Consequently, attempts to compare user well-being and mental health between platforms may be unknowingly confounded by differences in the mental health profile of each individual platform. Mellon and Prosser 28 investigated this form of selection bias with respect to differences in political opinion between Facebook and Twitter, and noted the potential for study outcomes to be biased when the outcome variable of interest is associated with the probability of being included in the sample 29 . This also has implications for our assessment of mental health and well-being classification algorithms 30 . For instance, if using Twitter data to classify depression in a random sample of users how many of these users should we expect to be depressed? Should we expect to find more depressed users on Facebook or Instagram? This bench-marking would allow the research community, who frequently face the challenge of establishing reliable ground truth in social media research, to contextualise the sensitivity and specificity of developed models 4 , 24 .

This study aimed to address the gap in the availability of high-quality descriptive data about social media users by describing social media use in a representative UK population cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC) 31 . We aimed to profile the users of the social media platforms Facebook, Instagram, Twitter, Snapchat and YouTube by considering a range of mental health and well-being measures that are regularly studied, with the objective of better characterising social media users against variables of interest to researchers. These measures included disordered eating, self-harm, suicidal thoughts, and depression as well as positive well-being outcomes which are sometimes neglected in the context of social media research 14 , 16 , 22 like subjective happiness, mental well-being and fulfilment of basic psychological needs. In answering our research questions we also sought to illustrate how cross-sectional data from a representative population cohort can provide meaningful contextual information that informs the way we interpret past and future research about social media users and their mental health. Unlike other studies using cross-sectional data 14 we had no intention of exploring causal questions, but aimed to address unanswered questions of who social media users are, and whether selection bias across platforms may have the potential to unintentionally bias outcome statistics about mental health and well-being.

Specifically, our research questions were:

Are there demographic differences in patterns of social media use (e.g. frequency)?

Are there demographic differences in the user groups of different social media platforms?

Are there differences in the mental health and well-being of those using social media sites at different frequencies?

Are there differences in the mental health and well-being of user groups of different social media platforms?

Sample description

The sample for this study is drawn from the Avon Longitudinal Study of Parents and Children (ALSPAC) 31 , 32 , 33 . Pregnant women resident in Avon, UK with expected dates of delivery from 1st April 1991 to 31st December 1992 were invited to take part in the study. The initial number of pregnancies enrolled was 14,541. Of these initial pregnancies, 13,988 children were alive at 1 year of age. When the oldest children were ~7 years of age an additional 913 children were enrolled. The total sample size for ALSPAC of children alive at one year of age is 14,901. However, since this time there has been a reduction in the sample due to withdrawals, deaths of those in the cohort and also people simply being lost to follow-up. As such the exact number of participants invited to each data collection activity changes with time. Please note that the ALSPAC study website contains details of all the data that is available through a data dictionary and variable search tool ( http://www.bristol.ac.uk/alspac/researchers/our-data/ ). Study data were collected and managed using REDCap electronic data capture tools hosted at the University of Bristol 34 .

The analysis presented in this study is based on a sub-sample of 4083 participants who responded to a self-report questionnaire at a mean age of 24 years old in 2016/17. The survey was sent to 9211 currently enrolled and contactable participants, of whom 4345 (47%) returned it. To maintain a consistent sample throughout the following analyses we considered the 4083 observations with complete cases for questions related to self-harm, suicidal thoughts, disordered eating, and social media use, and without the respondents who said that they ‘didn’t know’ whether they had a social media account ( n  < 5); no respondents stated that they did not have a social media account. As well as the survey at age 24, we considered the responses by those in our main sample to a survey one year previously, at age 23, which collected the well-being measures and the Moods and Feelings Questionnaire, matched to their social media use responses at age 24. This resulted in a sub-sample of 2991 participants who had responded to both surveys. Table 1 gives a comparison of the demographic breakdowns across these samples.

This study considered the participants’ responses to a range of mental health and well-being measures, as well as demographic data. A brief overview of each of the measures used is given below.

Throughout this paper, we used Male and Female to refer to the participant’s assigned sex at birth. Participant ethnicity was reported by their parent/s, and is available in the data as White , Ethnic Minority Group , or Unknown , where Ethnic Minority Group was only available as one group rather than broken down into specific ethnicities. There were two variables relevant to socio-economic status. The first was whether the participant had achieved an A Level or equivalent qualification by age 20, the second was their parents’ occupation. Parental occupation was measured using the Registrar General’s Social Class schema 35 , and was collected prior to the birth of the index cohort; we took the higher occupational class of the participant’s parents where available and grouped the overall schema of six categories into those in manual work , and those in non-manual work .

Social media use was measured using three questions. These were: (1) Do you have a social media profile or account on any sites or apps? with possible responses of ‘Yes’, ‘No’ or ‘Don’t know’; (2) Given a list of social media sites, Do you have a page or profile on these sites or apps, and how often do you use them? , where the social media sites were listed and response options were ‘Daily’, ‘Weekly’, ‘Monthly’, ‘Less Than Monthly’ or ‘Never’; (3) How often do you visit any social media sites or apps, using any device? with response options being ‘More than 10 times per day’, ‘2 to 10 times per day’, ‘Once per day’ or ‘Less than once per day’. Here, the definition of ‘social media sites’ in questions (1) and (3) was left to the participant to interpret, whereas in (2) a specific list was provided. In the following analyses, we have summed responses for the use frequencies per platform from question (2) so that ‘Weekly’, ‘Monthly’ and ‘Less than monthly’ are combined to represent ‘Less than daily’.

Depressive symptoms were measured using the short Mood and Feelings Questionnaire (MFQ) 36 , a 13-item scale that has been validated for measuring depressive symptoms in adolescents 37 and in young adulthood 38 . It asks respondents to rate statements, such as I cried a lot and I thought nobody really loved me , as Not true , Sometimes or True based on how they felt over the past two weeks. Missing items were filled with the mode of the individual’s other responses, provided 50% or more of the items were completed. Scores range from 0 to 26, with a higher score indicating more severe depressive symptoms 37 . Here we applied a cut-off score of 12 or above as indicating depression 38 .

Suicidal thoughts were assessed with the question Have you ever thought of killing yourself, even if you would not really do it? with those who indicated that they had ‘within the past year’ being included. Similarly, intentional self-harm was assessed by asking if participants had hurt [themselves] on purpose in any way and we included those who said this had happened at least once within the last year.

Disordered eating was a composite variable that included participants who indicated that they had been told by a healthcare professional that they had an eating disorder (anorexia nervosa, bulimia nervosa, binge eating disorder or another unspecified eating disorder). Participants were also included if they indicated they had engaged in any of the following behaviours at least once a month over the past year with the intention of losing weight or avoiding weight gain: fasting, throwing up, taking laxatives or medication. This classification of disordered eating followed a similar methodology to that used by Micali and colleagues 39 .

Well-being was measured using seven questionnaires. The Warwick Edinburgh Mental Well-being Scale (WEMWBS) is a fourteen-item questionnaire that has been validated for measuring general well-being in the general population 40 , 41 , as well as in young people 42 , 43 . It asks respondents to rate statements such as I’ve been dealing with problems well and I’ve been feeling cheerful , on a five-point Likert-type scale. The total score is between 14 and 70. All items in the WEMWBS are positively worded, and it is focused on measuring positive mental health.

The Satisfaction with Life Scale 44 , 45 is five-item questionnaire designed to measure global cognitive judgements of satisfaction with one’s life, which includes statements such as If I could live my life over, I would change almost nothing . Each question uses a seven-point Likert-type measure and the total score is between 5 and 35. The Subjective Happiness Scale 46 is a four-item questionnaire based on seven-point Likert-type questions, with the overall score being a mean of the four questions, lying in the range of 1 to 7. Respondents answer questions such as whether they consider themselves to be more or less happy than their peers.

The Gratitude Questionnaire (GQ-6) is a six-item measure that uses a seven-point Likert-type scale to assess individual differences in proneness to experiencing gratitude in daily life 47 . This scale includes statements such as I have so much in life to be thankful for and I am grateful to a wide variety of people . Each score is summed to a total between 6 and 42. The Life Orientation Test (LOT-R) is a measure of dispositional optimism that has ten items asked on a 5-point Likert-type scale 48 , though only four of these items are ‘filler’ questions that do not contribute to the final score. The overall score is in the range of 0 to 24, and items that contribute to this include In uncertain times, I usually expect the best and I hardly ever expect things to go my way .

The Meaning in Life questionnaire has 10 items designed to measure two dimensions of meaning in life: (1) Presence of Meaning (how much respondents feel their lives have meaning), and (2) Search for Meaning (how much respondents strive to find meaning and understanding in their lives) 49 . Statements include I understand my life’s meaning in the Presence sub-scale, and I am looking for something that makes my life feel meaningful in the Search sub-scale. Respondents answered each item on a 7-point Likert-type scale, with the two sub-scales scored in total between 5 and 35.

The psychological constructs of autonomy, competence and relatedness associated with self-determination theory were measured using the Basic Psychological Needs in General (BPN) questionnaire 50 . This questionnaire has 21 seven-point Likert-style questions with the final score for each of the three sub-domains being the mean of the responses for that sub-domain. As such each of autonomy, competence and relatedness were scored overall from 1 to 7. Example items include People in my life care about me and I often do not feel very capable .

For all measures missing items were filled with the person-level average, provided that half or more of the items were completed. All of the well-being measures listed were scored in a positive direction, where higher scores indicate higher alignment with the construct being measured.

The descriptive statistics were calculated using the R programming language (v4.0.1) 51 in RStudio (v1.3), primarily using the tidyverse (v1.3.0) package 52 for data manipulation and ggplot2 (v3.3.1) 53 for visualisation. A reproducible version of the manuscript and supporting code can be found from the Code availability statement.

Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees. Informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC Ethics and Law Committee at the time. The full list of ethical approval references for ALSPAC can be found on their website ( https://www.bristol.ac.uk/alspac/researchers/research-ethics/ ).

Demographics

We first consider the demographics of social media users across different frequencies of use, and across the five social media platforms: Facebook, Twitter, Instagram, Snapchat and YouTube. These are both taken from the main sample, as described in our ‘Methods’. Table 2 presents the frequency that participants reported using any social media sites each day, based on sex, ethnicity, education, and their parents’ occupational group.

Table 3 gives the percentage of participants from each demographic group who reported being a user of each platform with any use frequency.

The breakdown of every demographic by frequency of use on each platform is provided in full in Supplementary Table 1 . Figure 1 illustrates this breakdown for sex, which is the demographic by which all our following results are stratified due to the imbalance in our sample and the results in Tables 2 and 3 . Social media use and mental health and well-being outcomes are also known to vary according to gender 54 , 55 , 56 .

All social media users in the sample ( N   =  4083) are split by female ( N   =  2698) and male ( N   =  1385), and the frequency with which they use each social media platform given as either ‘Daily’, ‘Less than daily’ or ‘Never’. Labels on the stacked charts give the precise percentage of the group in each of the frequencies for each platform.

Mental health and well-being

First we will consider well-being and indicators of poor mental health across different use frequencies. Figure 2 shows how indicators of poor mental health vary across the three frequencies of use, which are more than 10 times a day, 2–10 times a day and once per day or less; no participants reported using no social media at all. These frequencies are contextualised by the prevalence of each outcome in all users of social media. This figure shows that the lowest category of social media use, that is once per day or less, has the highest proportions of disordered eating, self-harm and suicidal thoughts among women. As seen in Table 2 , only 7.1% of women and 12% of men used social media less than once per day, and so these measurements are subject to wider confidence intervals. Here, depression is defined as being present in those who scored above the cut-off score of 12 in the Short Mood and Feelings Questionnaire (MFQ) 38 . Additional descriptive data about mental health outcomes in the sample is also available in Supplementary Figure 1 and in Supplementary Tables 2 to 6 .

The frequency with which participants used any social media is reported as ‘more than ten times a day’, ‘between two and ten times a day’ or ‘once or less per day’, and the percentage of participants in that group who reported each mental health outcome is given in each sub-plot, with 95% confidence intervals. Disordered eating, self-harm and suicidal thoughts were assessed in the main sample alongside the social media questions ( N   =  4083) and included for those participants who reported them in the past year. Depression ( N   =  2991) was measured in the sub-sample with the Moods and Feelings questionnaire in the year prior to the social media measurement, and uses a cut off of 12 or more to indicate the presence of depression.

Similarly, each well-being construct is presented in Fig. 3 , and contextualised by the result for all users of social media, regardless of frequency. Separate outcomes are presented for the three sub-scales of the Basic Psychological Needs (BPN) scale and the two sub-scales of the Meaning in Life (MIL) scale. The Life Orientation Test measures optimism, and the Warwick Edinburgh Mental Well-being Scale (WEMWBS) measures overall positive well-being.

Each sub-graph presents each of the seven well-being measures, including the Basic Psychological Needs scale (BPN) sub-scales autonomy, relatedness and competence, and the Meaning In Life (MIL) scale’s two sub-scales of presence and search. Satisfaction With Life, the Life Orientation Test, the Gratitude Questionnaire, Subjective Happiness Scale and the Warwick Edinburgh Mental Wellbeing Scale (WEMWBS) are also included. The mean of each scale is given for all participants ( N   =  2991) with 95% confidence intervals, split by male and female, and then for each dichotomous category of use-frequency which is one of ‘more than ten times a day’, ‘between two and ten times a day’ or ‘once or less per day’.

Next we consider the characteristics of daily users of each platform. The relative percentage of daily users against other types of users for each platform can be referred to in Fig. 1 , and versions of Figs. 4 and 5 for all users of each platform are given in Supplementary Figures 2 and 3 .

The percentage of daily users of each platform who have reported each symptom is given in each sub-graph, with 95% confidence intervals. Disordered eating, self-harm and suicidal thoughts were assessed in the main sample alongside the social media questions ( N   =  4083) and included for those participants who reported them in the past year. Depression ( N   =  2991) was measured in the sub-sample with the Moods and Feelings questionnaire in the year prior to the social media measurement, and uses a cut off of 12 or more to indicate the presence of depression. Participants can belong to the daily user group of more than one platform.

Each sub-graph presents each of the seven well-being measures, including the Basic Psychological Needs scale (BPN) sub-scales autonomy, relatedness and competence, and the Meaning In Life (MIL) scale’s two sub-scales of presence and search. Satisfaction With Life, the Life Orientation Test, the Gratitude Questionnaire, Subjective Happiness Scale and the Warwick Edinburgh Mental Wellbeing Scale (WEMWBS) are also included. The mean of each scale is given for all daily users of each platform from the sub-sample ( N   =  2991) with 95% confidence intervals, split by male and female.

Finally Fig. 5 gives the mean well-being score across each platform for each of the seven well-being measures.

This study used data from a UK population cohort study to describe the demographics and key mental health and well-being indicators of social media users by their self-reported frequency of using social media and five different platforms used at ages 23 and 24. Overall, we saw that there were differences in demographics and mental states of users across use-patterns and platforms used. In the following sections, we detail and discuss the implications of these findings for future research across the themes of demographics, use-frequency and platform used.

In general, just over half of participants reported using social media 2–10 times per day, with more than ten times per day still being common at 39%, and only approximately one in ten participants using social media once per day or less. The results showed that those who rated their social media use at the highest frequency (more than ten times per day) were more likely to be women, more likely to be White and more likely have parents who worked in manual occupations. However, sex was the only demographic that appeared to have a statistical relationship with frequency of use, based on a Chi-squared test. Davies and colleagues 57 saw similar results from a Welsh population survey of social media use that found there was a difference in social media use across genders, but not by measures of deprivation.

Figure 1 showed that Facebook is, unsurprisingly, the most popular platform both in being used by 97% of the participants and being the most used platform on a daily basis. Instagram and YouTube showed substantial differences in use patterns across male and female users, with approximately double the percentage of women using Instagram daily as men and, conversely, approximately double the percentage of men using YouTube daily as women. Snapchat also saw higher proportions of daily and overall female users, though this difference between sexes was not as dramatic as for Instagram and YouTube. These patterns of use generally agree with the demographics of users on these sites reported for 18–29-year-old US adults by the Pew Research Center 25 , although our sample saw slightly more Twitter users than their estimated 38%, and fewer YouTube users than their estimated 91% (see Table 3 ). This difference in YouTube users may be partly explained by the fact that it is the only platform with a substantially higher proportion of men than women using it (68% of women vs 83% of men), and that men were under represented in our sample overall compared to women. This emphasises the importance of stratifying results by sex.

Previous research into the demographics of UK Twitter users also aligns with our findings that men and people from higher socio-economic backgrounds are more likely to be Twitter users than women 26 , 28 . Here, we also saw that those from ethnic minority groups are more likely to be Twitter users than White participants, though this is limited by the fact that we could not further separate out results for people with different ethnicities due to the variables available. Across our sample, Twitter was the only social media platform that had a noticeably higher proportion of both A Level educated participants and parents in non-manual occupations. Snapchat saw the reverse pattern with a higher proportion of participants who did not have A Level qualifications and a higher proportion of participants whose parents worked in manual occupations.

Overall, the sex differences between all male and female users varied across outcomes. For instance, a higher percentage of women experienced depression, disordered eating and self-harm overall, but the gap in the prevalence of suicidal thoughts between men and women was much smaller. This concurs with evidence from the last UK-wide psychiatric morbidity survey, in that ‘common mental health disorders’ are more prevalent in women than men 58 . When it came to well-being, we saw that women also displayed higher mean levels of well-being across most measures. Exceptions were the Life Orientation Test, which showed men generally had higher levels of optimism, the Subjective Happiness Scale where scores were roughly equivalent, and the WEMWBS where men’s general well-being was slightly higher. These results, apart from the WEMWBS, are consistent with findings on UK-wide well-being at the time of the survey, and that men tend to have higher optimism in general 59 , 60 . Previous research into the WEMWBS has not generally found large sex differences, but there is evidence that in younger samples there are differences that may be explained by socio-economic status 40 , 41 , 61 ; we note that higher attrition of men in our sample was likely to lead to a bias towards men who are more socio-economically privileged, which may explain why they had higher well-being.

The patterns of mental health outcomes by use frequency displayed in Fig. 2 showed some support for the so-called ‘Goldilocks theory’ of social media use that hypothesises a quadratic, rather than linear, stimulus-response relationship between social media use and mental well-being 62 . This would mean that moderate use of social media, rather than very little or excessive use, is best for well-being. However, this pattern did not consistently apply. For instance, there was an inverse relationship between social media use and percentage of women who self-harm, and in men only the group with the highest level of social media use had more severe depressive symptoms. Previous research has found that in young women higher social media use was associated with increased risk of self-harm 63 , which is in contrast to our results. Similarly, research using the Millennium Cohort Study also found an increasing relationship between objectively measured number of hours spent on social media and how many respondents had clinically relevant symptoms of depression 64 , with a greater increase for girls than boys. Our findings roughly concur with those for the boys, but in women we found that those who used social media the least had the highest rates of depression. However, these differences in findings could reflect the difference in the age of participants or the ways that social media was measured differently across studies. Here we were using use-frequency as categorised into three groups which, as we discuss further in our limitations, may be more reflective of the individual’s mental health and relationship with social media than how frequently they use it 65 .

When considering the results by well-being measure in Fig. 3 we saw that subjective happiness and optimism as measured by the Life Orientation Test both appeared relatively consistent across use categories. Relatedness presented the clearest difference across use categories, with relatedness in women being higher for the two most frequent use frequencies. However, perhaps the most notable outcome was the inconsistency between well-being scales which implies that the choice of scale could affect the interpretation of the impact of well-being on social media use. Research into the relationship between social media use and well-being has been said to suffer from what is known as the ‘jingle-jangle’ paradox where the term ‘well-being’ is used as a catch-all for anything from depression rates to life satisfaction 66 , 67 . This conflation of different well-being measures leads to comparisons of different psychological constructs which may interact differently with social media use: this is hypothesised as one of the reasons that researchers find conflicting evidence for this relationship 66 , which our results support. This also adds to the picture of researcher degrees of freedom in choosing how to measure psychological constructs, which has been shown to have a substantial impact on the outcome of analyses of social media and mental health 15 . Subjective well-being is a complex and multi-faceted psychological concept 68 , 69 , and these findings illustrate the importance of recognising that different measures of well-being could imply different relationships between social media and “well-being”.

When considering participant outcomes by daily users of each platform more consistent patterns emerge than for use-frequencies. We saw that, particularly for women, YouTube had the highest proportion of users reporting disordered eating, self-harm, suicidal thoughts and depression, with higher prevalence of depression in female users of YouTube compared to male users (Fig. 4 ). Whilst overall mental well-being across platforms, as measured by the WEMWBS in Fig. 5 , shows YouTube as being marginally but not drastically lower than other platforms, other well-being measures illustrated some key differences. For instance, YouTube users had lower life satisfaction, relatedness and, particularly for female users, levels of competence (Fig. 5 ). Conversely, daily users of Instagram, and in some cases Snapchat, appeared to have the highest subjective well-being across most measures, with this being particularly noticeable for relatedness, gratitude and happiness (Fig. 5 ). The role of self-determination theory in social media use has previously been explored for Facebook and social media in general 70 with relatedness hypothesised as a key motivating factor for social media use. Previous findings have shown that Instagram and Snapchat are used more for social interaction than Twitter and Facebook 71 , and so our results may corroborate the importance of relatedness in the use of particular platforms. Regardless of the specific measure, our results have illustrated that there is variation amongst platforms which further challenges the idea that ‘social media’ or ‘social networking sites’ are a homogeneous group, and reiterates the importance of understanding the context of research about or using social media 28 , 71 .

At face value, our results appear to directly contrast with the outcomes of the Status of Mind report published by the Royal Society for Public Health 72 , where young people rated YouTube as being the most beneficial site for their well-being and Instagram as the worst, based on health-related outcomes such as their anxiety and depression. Our findings that a higher prevalence of YouTube users suffer from poorer mental health and well-being may mean that whilst some platforms are seen as ‘worse’ for young people’s mental health, that does not equate to finding more unwell young people on those platforms. One explanation may be that those experiencing poorer mental health are more likely to use YouTube because they experience more benefits to their mental health from YouTube, such as community building and peer support 13 , than they do from spending time on sites like Instagram. However, this is certainly an interesting area for further exploration in future quantitative and qualitative research.

Whilst this research draws evidence from a robust and well-documented study and the sample being from a birth cohort means that our results are not confounded by age, there are limitations to the cohort sample that we have used. Firstly, the cohort measures a specific age group so we can only infer information about a single age group at each measurement time point. We suspect that different patterns might be found at different ages, knowing that rates of various mental health conditions such as anxiety, depression and suicidality change over the course of childhood, adolescence and adulthood 73 , and since each generation may use social media differently 74 . It is also important to note that the two data collection points used in this study were taken a year apart, and so not all measures were taken exactly at the same time. This means that although we have primarily considered the data cross-sectionally there is a potential for some longitudinal effects to have influenced the data. Secondly, as discussed in the ‘Methods’ section, there was also a limitation in that ethnicity was only available as two categories (White or Ethnic Minority Groups) and so it was not possible to look further into differences in social media by users of difference ethnicities. Additionally, the make up of the area of Bristol that ALSPAC represents is predominantly White. Given these limitations of the sample it would be valuable to conduct similar research in other cohorts that represent more diverse areas. Thirdly, ALSPAC has seen differential attrition over time and so, as seen in Table 1 , the sample for this study when the index cohort were in their early twenties has fewer men than women, and more participants from privileged socio-economic groups in terms of education and class background 31 . As well as this, typical social media use changes over time and by age 25 , and so further assessment of social media use across a variety of population-representative age groups would be the most effective way to understand differences between generations.

Another limitation of this study is a lack of specificity about the nature of social media use that participants are referring to when responding. It is possible that activities related to ‘using’ social media, such as posting content versus passive use, change depending on platform used and that there are individual preferences to account for 54 , 71 , 75 , 76 . For instance, YouTube is distinct from other platforms in this study in that its primary function is passive content consumption as opposed to social networking. Previous research has suggested a reciprocal association between passive social media use and lower subjective well-being 75 , whilst using social media for direct communication has been positively associated with perceived friend support 77 . This may better reflect the uses of platforms like Snapchat. As well as the subjective nature of ‘use’, there are also ongoing concerns about using self-reported measures of use-frequency to measure social media behaviours 78 , 79 , 80 . Emerging evidence is showing that self-reports do not align well with objective measurement due to recall bias and differences in interpreting how to include notifications or fleeting checks of social media 79 , 80 with self-reported smartphone pickups underestimating associations with mental health compared to objective measures of use 65 . It might be that different ways of measuring social media use, such as types of use, are more useful when considering associations with mental health and well-being outcomes 54 . It is worth noting that the use-frequency measures used in this study are distinct from screen-time, and equivalent use-frequency across platforms may have different time implications; someone may spend short amounts of time on Instagram or Snapchat checking notifications, but do so frequently, versus visiting YouTube once in a day but spending several hours watching content. These nuances are challenging to capture, but by reporting on mental health prevalence across the available responses in a cohort study we can add to the growing understanding of how self-reported social media use frequency is related to mental health. Statistical modelling to test the extent of the differences observed between mental health constructs, use-frequencies and platforms would be valuable future research.

In summary, our results amplify the importance of attending to complexity when measuring and analysing social media use and mental health and well-being. It is important to note that our results do not, and cannot, imply that different types of social media use cause poorer or better health outcomes in young people, but they do provide vital contextual information on user groups that can help us better understand the reasons that previous research has found conflicting results. We have provided estimates of seven well-being measures and the prevalence of four key mental health outcomes (depression, disordered eating, suicidal thoughts and self-harm) across the five platforms Facebook, Twitter, Instagram, Snapchat and YouTube, as well as across three use frequencies. Our findings have shown that the demographic and mental health foot-print of each platform is different. Primarily users differ by sex, but when it comes to platforms YouTube is particularly likely to have both male and female users with poorer mental health and well-being across a range of indicators, alongside evidence that daily Instagram users have better overall well-being than daily users of other platforms. Our findings also indicate that relationships between use-frequency and multiple mental health and well-being outcomes are often non-linear, which supports the importance of considering non-linear dose-response relationships between social media and mental health and well-being in future research. Lastly, we saw that the relationship between use-frequencies and well-being changes depending on the measure of well-being used. This means that we cannot conflate different types of well-being, and doing so will likely result in low replicability.

This research has implications for both those who conduct research on the relationship between social media and mental health, and those who study mental health prediction. We must ensure we are considering both platform-specific and outcome-specific effects rather than conflating types of social media use, social media sites and well-being as single entities. Future research should also stratify results by sex since it is unlikely that studies with differently balanced samples will replicate. Our findings on use-frequencies also suggest that we cannot assume linear relationships between social media use and mental health. Our understanding of these methodological issues would be improved by examining profiles of different user age-groups, as well as examining relationships between these variables longitudinally to understand the potential for reciprocal effects. The differences between platforms should be further considered too, as to how different content types and communication modes on different platforms may affect mental health differently.

Data availability

The datasets analysed during the current study are not publicly available as the informed consent obtained from ALSPAC participants does not allow data to be made freely available through any third party maintained public repository. However, data used for this submission can be made available on request to the ALSPAC Executive, with reference to project number B3227. The ALSPAC data management plan describes in detail the policy regarding data sharing, which is through a system of managed open access. Full instructions for applying for data access can be found here: http://www.bristol.ac.uk/alspac/researchers/access/ . The ALSPAC study website contains details of all the data that are available ( http://www.bristol.ac.uk/alspac/researchers/our-data/ ).

Code availability

The code used to produce the results in this study can be found at https://doi.org/10.17605/OSF.IO/RKXM6 .

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Acknowledgements

We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ). The data used in this research was specifically funded by the NIHR (1215-20011), the Wellcome Trust (SSCM.RD1809) and the MRC (102215/2/13/2, MR/M006727/1). N.D. is supported by an MRC GW4 BioMed studentship in Data Science and AI (MR/N013794/1). C.M.A.H. is supported by a Philip Leverhulme Prize. N.H., O.S.P.D. and C.M.A.H. will serve as guarantors for the contents of this paper.

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These authors jointly supervised this work: Oliver S. P. Davis, Claire M. A. Haworth.

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Department of Population Health Science, University of Bristol, Bristol, UK

Nina H. Di Cara, Lizzy Winstone & Oliver S. P. Davis

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK

Nina H. Di Cara & Oliver S. P. Davis

Cardiff University, Cardiff, Wales, UK

The Alan Turing Institute, London, UK

Oliver S. P. Davis & Claire M. A. Haworth

Department of Psychological Science, University of Bristol, Bristol, UK

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N.D. was responsible for data curation, formal analysis, investigation, methodology, visualisation and writing (original draft and reviewing and editing). L.W. was responsible for methodology, investigation and writing (reviewing and editing). L.S. was responsible for methodology, investigation, supervision and writing (reviewing and editing). O.D. and C.H. were responsible for funding acquisition, conceptualisation, methodology, investigation, supervision and writing (reviewing and editing).

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Di Cara, N.H., Winstone, L., Sloan, L. et al. The mental health and well-being profile of young adults using social media. npj Mental Health Res 1 , 11 (2022). https://doi.org/10.1038/s44184-022-00011-w

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Social media harms teens’ mental health, mounting evidence shows. what now.

Understanding what is going on in teens’ minds is necessary for targeted policy suggestions

Most teens use social media, often for hours on end. Some social scientists are confident that such use is harming their mental health. Now they want to pinpoint what explains the link.

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By Sujata Gupta

February 20, 2024 at 7:30 am

In January, Mark Zuckerberg, CEO of Facebook’s parent company Meta, appeared at a congressional hearing to answer questions about how social media potentially harms children. Zuckerberg opened by saying: “The existing body of scientific work has not shown a causal link between using social media and young people having worse mental health.”

But many social scientists would disagree with that statement. In recent years, studies have started to show a causal link between teen social media use and reduced well-being or mood disorders, chiefly depression and anxiety.

Ironically, one of the most cited studies into this link focused on Facebook.

Researchers delved into whether the platform’s introduction across college campuses in the mid 2000s increased symptoms associated with depression and anxiety. The answer was a clear yes , says MIT economist Alexey Makarin, a coauthor of the study, which appeared in the November 2022 American Economic Review . “There is still a lot to be explored,” Makarin says, but “[to say] there is no causal evidence that social media causes mental health issues, to that I definitely object.”

The concern, and the studies, come from statistics showing that social media use in teens ages 13 to 17 is now almost ubiquitous. Two-thirds of teens report using TikTok, and some 60 percent of teens report using Instagram or Snapchat, a 2022 survey found. (Only 30 percent said they used Facebook.) Another survey showed that girls, on average, allot roughly 3.4 hours per day to TikTok, Instagram and Facebook, compared with roughly 2.1 hours among boys. At the same time, more teens are showing signs of depression than ever, especially girls ( SN: 6/30/23 ).

As more studies show a strong link between these phenomena, some researchers are starting to shift their attention to possible mechanisms. Why does social media use seem to trigger mental health problems? Why are those effects unevenly distributed among different groups, such as girls or young adults? And can the positives of social media be teased out from the negatives to provide more targeted guidance to teens, their caregivers and policymakers?

“You can’t design good public policy if you don’t know why things are happening,” says Scott Cunningham, an economist at Baylor University in Waco, Texas.

Increasing rigor

Concerns over the effects of social media use in children have been circulating for years, resulting in a massive body of scientific literature. But those mostly correlational studies could not show if teen social media use was harming mental health or if teens with mental health problems were using more social media.

Moreover, the findings from such studies were often inconclusive, or the effects on mental health so small as to be inconsequential. In one study that received considerable media attention, psychologists Amy Orben and Andrew Przybylski combined data from three surveys to see if they could find a link between technology use, including social media, and reduced well-being. The duo gauged the well-being of over 355,000 teenagers by focusing on questions around depression, suicidal thinking and self-esteem.

Digital technology use was associated with a slight decrease in adolescent well-being , Orben, now of the University of Cambridge, and Przybylski, of the University of Oxford, reported in 2019 in Nature Human Behaviour . But the duo downplayed that finding, noting that researchers have observed similar drops in adolescent well-being associated with drinking milk, going to the movies or eating potatoes.

Holes have begun to appear in that narrative thanks to newer, more rigorous studies.

In one longitudinal study, researchers — including Orben and Przybylski — used survey data on social media use and well-being from over 17,400 teens and young adults to look at how individuals’ responses to a question gauging life satisfaction changed between 2011 and 2018. And they dug into how the responses varied by gender, age and time spent on social media.

Social media use was associated with a drop in well-being among teens during certain developmental periods, chiefly puberty and young adulthood, the team reported in 2022 in Nature Communications . That translated to lower well-being scores around ages 11 to 13 for girls and ages 14 to 15 for boys. Both groups also reported a drop in well-being around age 19. Moreover, among the older teens, the team found evidence for the Goldilocks Hypothesis: the idea that both too much and too little time spent on social media can harm mental health.

“There’s hardly any effect if you look over everybody. But if you look at specific age groups, at particularly what [Orben] calls ‘windows of sensitivity’ … you see these clear effects,” says L.J. Shrum, a consumer psychologist at HEC Paris who was not involved with this research. His review of studies related to teen social media use and mental health is forthcoming in the Journal of the Association for Consumer Research.

Cause and effect

That longitudinal study hints at causation, researchers say. But one of the clearest ways to pin down cause and effect is through natural or quasi-experiments. For these in-the-wild experiments, researchers must identify situations where the rollout of a societal “treatment” is staggered across space and time. They can then compare outcomes among members of the group who received the treatment to those still in the queue — the control group.

That was the approach Makarin and his team used in their study of Facebook. The researchers homed in on the staggered rollout of Facebook across 775 college campuses from 2004 to 2006. They combined that rollout data with student responses to the National College Health Assessment, a widely used survey of college students’ mental and physical health.

The team then sought to understand if those survey questions captured diagnosable mental health problems. Specifically, they had roughly 500 undergraduate students respond to questions both in the National College Health Assessment and in validated screening tools for depression and anxiety. They found that mental health scores on the assessment predicted scores on the screenings. That suggested that a drop in well-being on the college survey was a good proxy for a corresponding increase in diagnosable mental health disorders. 

Compared with campuses that had not yet gained access to Facebook, college campuses with Facebook experienced a 2 percentage point increase in the number of students who met the diagnostic criteria for anxiety or depression, the team found.

When it comes to showing a causal link between social media use in teens and worse mental health, “that study really is the crown jewel right now,” says Cunningham, who was not involved in that research.

A need for nuance

The social media landscape today is vastly different than the landscape of 20 years ago. Facebook is now optimized for maximum addiction, Shrum says, and other newer platforms, such as Snapchat, Instagram and TikTok, have since copied and built on those features. Paired with the ubiquity of social media in general, the negative effects on mental health may well be larger now.

Moreover, social media research tends to focus on young adults — an easier cohort to study than minors. That needs to change, Cunningham says. “Most of us are worried about our high school kids and younger.” 

And so, researchers must pivot accordingly. Crucially, simple comparisons of social media users and nonusers no longer make sense. As Orben and Przybylski’s 2022 work suggested, a teen not on social media might well feel worse than one who briefly logs on. 

Researchers must also dig into why, and under what circumstances, social media use can harm mental health, Cunningham says. Explanations for this link abound. For instance, social media is thought to crowd out other activities or increase people’s likelihood of comparing themselves unfavorably with others. But big data studies, with their reliance on existing surveys and statistical analyses, cannot address those deeper questions. “These kinds of papers, there’s nothing you can really ask … to find these plausible mechanisms,” Cunningham says.

One ongoing effort to understand social media use from this more nuanced vantage point is the SMART Schools project out of the University of Birmingham in England. Pedagogical expert Victoria Goodyear and her team are comparing mental and physical health outcomes among children who attend schools that have restricted cell phone use to those attending schools without such a policy. The researchers described the protocol of that study of 30 schools and over 1,000 students in the July BMJ Open.

Goodyear and colleagues are also combining that natural experiment with qualitative research. They met with 36 five-person focus groups each consisting of all students, all parents or all educators at six of those schools. The team hopes to learn how students use their phones during the day, how usage practices make students feel, and what the various parties think of restrictions on cell phone use during the school day.

Talking to teens and those in their orbit is the best way to get at the mechanisms by which social media influences well-being — for better or worse, Goodyear says. Moving beyond big data to this more personal approach, however, takes considerable time and effort. “Social media has increased in pace and momentum very, very quickly,” she says. “And research takes a long time to catch up with that process.”

Until that catch-up occurs, though, researchers cannot dole out much advice. “What guidance could we provide to young people, parents and schools to help maintain the positives of social media use?” Goodyear asks. “There’s not concrete evidence yet.”

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Article Contents

The link between social media and adolescent mental health, recommendations for a better social media use, supplementary material, social media and adolescent mental health: a consensus report of the national academies of sciences, engineering, and medicine.

Competing Interest: S.G. is an Associate Editor of PNAS Nexus and served as chair of the consensus committee responsible for the report discussed in this editorial.

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Sandro Galea, Gillian J Buckley, Social media and adolescent mental health: A consensus report of the National Academies of Sciences, Engineering, and Medicine, PNAS Nexus , Volume 3, Issue 2, February 2024, pgae037, https://doi.org/10.1093/pnasnexus/pgae037

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A range of digitally mediated communication platforms—loosely called as a group, social media—have transformed how the world communicates and interacts over the past decade and a half. The rise in popularity of some social media platforms has been nothing short of extraordinary. For example, Facebook, introduced in 2004, now has 2.9 billion regular users ( 1 , 2 ). Snapchat has 397 million regular users, and TikTok, introduced only in 2018, has 1.7 billion regular users ( 2 ). As with all new technologies, the most common users of new social media platforms have been young people, with adolescents being the fastest adopters of these technologies and their most avid users.

At the same time as the world has witnessed this rise in social media use, the US has seen an increase in mental disorders overall, and among adolescents in particular. Rates of mental health problems have increased over the past decade, as have suicidal ideation and completed suicides in this group ( 3 , 4 ). This has led, not unreasonably, to concern that this worsening in adolescent mental health is linked to the rise in social media use. This thesis has been proposed in academic writing ( 5 , 6 ), featured in a number of prominent books and articles for a broader public audience ( 7–10 ). Concern about this connection was fueled by the release of documents from Facebook by a whistleblower that showed both that social media platforms were aware of the risks of worsening mental health and that these same companies made concerted efforts to ensure continued and ever greater engagement with their platforms ( 11–13 ).

With this potential link in mind, the National Academies of Sciences, Engineering, and Medicine convened a consensus committee with a charge to disentangle the links between social media use and adolescent mental health and to articulate recommendations accordingly. The committee's Statement of Task and membership are provided in Appendixes A and B . This work culminated in a report that was just released ( 14 ). We summarize here both the report's main findings and the recommendations that emerged from the committee's deliberations.

The question that has animated such public discussion and debate—the potential link between social media and adolescent mental health—turns out to be far more complex than might appear at first glance, and there is no easy answer to whether increasing social media use is associated with growing mental distress for adolescents. There are three principal reasons for the challenge in answering this question.

First, the term social media is broad, and there is no easy catchall that can describe the range of interactive digital tools that are popularly called “social media.” For the purposes of its deliberation, the committee relied on a definition adapted from the American Psychological Association, referring to social media as the set of “interactive technologies that facilitate the creation and sharing of information, ideas, interests, and other forms of expression through virtual communities and networks” ( 15 ). This definition encompasses a broad range of tools, and each of these tools operate in different ways. Importantly, the notion of use of social media encompasses a range of behaviors that are irreducible to simple reductions (use vs. nonuse) and must be understood as a heterogenous set of exposures. For example, simply focusing on length of time that adolescents use a particular social media platform does not account for whether that adolescent is using that time to stream movies in their spare time, to connect to communities of peers who may share interests productively, or to engage in exchanges that may expose adolescents to risk of exacerbating negative body image. Therefore, the question posed at the outset is virtually unanswerable without a careful assessment of the types of engagements adolescents have with social media and linking those engagements to specific mental health indicators.

Second, and relatedly, the literature is quite far from being able to provide confidence that particular behaviors—with the exception of some explicitly harmful engagements as noted below—are linked to adverse mental health. This challenge emerges from a limited literature, characterized by a paucity of longitudinal studies, and by, in the main, use of crude exposure measures that fail to differentiate between specific behaviors while adolescents engage with social media. This suggests that much more work is needed to appropriately determine which behaviors, when, and by whom might be associated with mental health harms among adolescents.

Third, while this report was catalyzed by concern about the effect of social media on adverse mental health, it is apparent that entertainment, giving pleasure, and providing connections are important benefits of social media, particularly for isolated adolescents (e.g. adolescents with disabilities, or LGBTQ+ adolescents living in rural areas). Hence, in the big picture, any assessment of overall harms—and efforts to restrict social media use commensurately—must be balanced with the clear benefits that many users of social media derive from engagement with these platforms.

It is however apparent that some behaviors—even if rare—are explicitly harmful and emerge from social media exposure by adolescents. These behaviors, including cyber-stalking and harassment, are well documented and most troubling because of the difficulty that social media has in policing these behaviors—or even in providing opportunities for adolescents who experience them to report these behaviors or shield themselves from them.

The committee developed a set of recommendations that aim to help better understand the question at hand, deal with immediate challenges, and establish the foundations for healthier social media use going forward.

First, the committee noted the need for much more research in the area. It is astonishing that social media have become so ubiquitous without any careful consideration about its potential impact on health, particularly the health of adolescents who are deeply influenced by such exposure at a formative stage in their life. By way of analogy, it is as though a brand-new food group were released into the public, that essentially everyone consumes every day, without any investigation into its safety. This therefore calls for the need for much more research in the area, particularly longitudinal research that allows for the measurement of specificity of exposure so that we can discern which elements of social media use are harmful and which are not. In parallel, the committee recommended that the International Organization for Standardization should convene an ongoing technical working group that includes industry representatives, civil society, and academic stakeholders to develop standards for social media platform design, transparency, and data use that can, through emerging data, ensure best practices in social media platforms toward mitigating potential harms.

Second, the committee felt strongly that enough is known about the harms of cyber-harassment that efforts do need to be expended to mitigate this harm. This includes the development of systems for reporting, follow-up, and adjudication for cases of online harassment and abuse. These systems should be easy to use, universal, accountable, and transparent. In addition, the committee suggested that the US Substance Abuse and Mental Health Services Administration should have intervention programs for children and adolescents who experience digital abuse. This would be a step toward creating an infrastructure of support for an experience that is becoming distressingly common and casting a pall on social media use that may, in the main, be otherwise benign.

Third, given the ubiquity of social media use, it is somewhat remarkable that the country has not engaged in any formal efforts to teach safe, healthy, social media use by adolescents. This can only be done in the schools, and the committee recognized that as such teachers need to be prepared to engage in teaching in this area. This will require that state boards of education set standards for comprehensive digital media literacy education in grades K through 12. In addition, the Council for the Accreditation of Educator Preparation would need to set requirements for media literacy education for student teachers and as part of ongoing professional development for veteran teachers. An extension of this includes the training of medical providers—through relevant bodies—in understanding social media and its consequences, so that clinical providers are in a position to counsel patients on social media use and spot potential warning signs.

Informed by the rapid spread of social media, and the co-occurring crisis in adolescent mental health, the National Academies of Sciences, Engineering, and Medicine consensus committee was tasked with addressing whether the former is leading to the latter. The answer turns out to be nowhere near as simple as we might hope. The question does, however, prompt the need for careful research in the area, elevate the importance of short-term tackling of harassment through social media, and encourage the establishment of pathways to ensure teaching about social media in schools and counseling about social media use by medical providers.

Supplementary material is available at PNAS Nexus online.

The authors declare no funding.

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Social Media Use and Mental Health: A Global Analysis

Affiliations.

• 1 Department of Public Health & Prevention Science, Baldwin Wallace University, Berea, OH 44017, USA.
• 2 Department of Sociology and Anthropology, St Louis University, St. Louis, MO 63108, USA.
• 3 Department of Business Development, Ofogh Kourosh Chain Stores, Tehran 1433894961, Iran.
• 4 Department of Public Health, Amherst College, Amherst, MA 01002, USA.
• 5 Department of Biostatistics and Epidemiology, University of North Texas Health Science Center, North Texas, Fort Worth, TX 76107, USA.
• PMID: 36417264
• PMCID: PMC9620890
• DOI: 10.3390/epidemiologia3010002

Research indicates that excessive use of social media can be related to depression and anxiety. This study conducted a systematic review of social media and mental health, focusing on Facebook, Twitter, and Instagram. Based on inclusion criteria from the systematic review, a meta-analysis was conducted to explore and summarize studies from the empirical literature on the relationship between social media and mental health. Using PRISMA guidelines on PubMed and Google Scholar, a literature search from January 2010 to June 2020 was conducted to identify studies addressing the relationship between social media sites and mental health. Of the 39 studies identified, 20 were included in the meta-analysis. Results indicate that while social media can create a sense of community for the user, excessive and increased use of social media, particularly among those who are vulnerable, is correlated with depression and other mental health disorders.

Keywords: Facebook; Instagram; Twitter; mental health; social media; systematic review.

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Conflict of interest statement

The authors declare no conflict of interest.

PRISMA 2009 flowchart showing research…

PRISMA 2009 flowchart showing research of records.

Forest plot of the studies.

Forest plot of the studies.…

Forest plot of the studies. Grouped by social media platforms.

Forest plot of the studies. Grouped by sample size.

Forest plot of the studies. Grouped by year of publication.

Funnel plot for publication bias.

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Teens are spending nearly 5 hours daily on social media. Here are the mental health outcomes

Forty-one percent of teens with the highest social media use rate their overall mental health as poor or very poor

Vol. 55 No. 3 Print version: page 80

• Social Media and Internet

Percentage of teens with the highest social media use who rate their overall mental health as poor or very poor , compared with 23% of those with the lowest use. For example, 10% of the highest use group expressed suicidal intent or self-harm in the past 12 months compared with 5% of the lowest use group, and 17% of the highest users expressed poor body image compared with 6% of the lowest users.

Average number of hours a day that U.S. teens spend using seven popular social media apps, with YouTube , TikTok , and Instagram accounting for 87% of their social media time. Specifically, 37% of teens say they spend 5 or more hours a day, 14% spend 4 to less than 5 hours a day, 26% spend 2 to less than 4 hours a day, and 23% spend less than 2 hours a day on these three apps.

[ Related: Potential risks of content, features, and functions: The science of how social media affects youth ]

Percentage of the highest frequency social media users who report low parental monitoring and weak parental relationships who said they had poor or very poor mental health , compared with 25% of the highest frequency users who report high parental monitoring and strong parental relationships . Similarly, 22% of the highest users with poor parental relationships and monitoring expressed thoughts of suicide or self-harm compared with 2% of high users with strong parental relationships and monitoring.

Strong parental relationships and monitoring significantly cut the risk of mental health problems among teen social media users, even among those with significant screen time stats.

Rothwell, J. (October 27, 2023). Parenting mitigates social media-linked mental health issues . Gallup. Survey conducted between June 26–July 17, 2023, with responses by 6,643 parents living with children between ages 3 and 19, and 1,591 teens living with those parents. https://news.gallup.com/poll/513248/parenting-mitigates-social-media-linked-mental-health-issues.aspx .

Rothwell, J. (2023). How parenting and self-control mediate the link between social media use and mental health . https://ifstudies.org/ifs-admin/resources/briefs/ifs-gallup-parentingsocialmediascreentime-october2023-1.pdf .

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The Impact of Social Media on Teens' Mental Health

Social media has some good intentions: connecting you with people all around the world, showing you content you are interested in, and providing endless entertainment. But there are also negative consequences to endless scrolling. Research has shown that young adults who use social media are three times as likely to suffer from depression , putting a large portion of the population at risk for suicidal thoughts and behaviors. 

In the U.S., suicide rates have declined slightly since 2019, but it continues to be a serious concern among our younger generation. According to the Centers for Disease Control and Prevention, the number of suicides in females aged 15-24 increased 87 percent over the past 20 years. And among males aged 15-24, the number of suicides rose by 30 percent over that same time period. 

Almost every teen now has an account on at least one social media platform. They use social media to reach out to friends, share experiences, and tell the world about themselves. However, without realizing it, they are managing an addiction. 

Jessica Holzbauer , a licensed clinical social worker at Huntsman Mental Health Institute , explains how our smartphones are, by design, addictive. “We get a dopamine release in our brain when we pick up our phone or log into social media,” she says. Using social apps is essentially priming your brain into thinking you are rewarding yourself every time you pick up your device. 

Negative Impacts of Social Media

Is it true that using social apps could negatively affect your mental health? 

“In short, yes, social media can have negative consequences for our mental health,” Holzbauer says. “The younger generation grew up with social media and the ability to see anything, anytime, anywhere. Our ability to tolerate the distress of waiting has been eroded because we can Google the answer to almost any question. We no longer have to wait to know who was the actor that played Ron Burgundy in Anchorman or where to find the nearest library.” 

In many ways, social media has removed the barriers between the user and the audience—with far-reaching implications. “We can act on impulse and post something to social media that may reflect a feeling or thought in the moment but may not be true to us a day later,” Holzbauer says. “When our more level-headed self is back in charge, we can feel embarrassment, shame, or regret for posting something impulsively.” 

We also know that content can be filtered, edited, and manipulated before it’s posted, which can lead to unattainable standards being broadcast to the entire world for anyone to see. Users are obsessed with instant gratification and in some instances base their worth or image off the images they see and the amount of likes they receive on their post. 

“The information teens are putting out is one factor—another is the information they are taking in,” Holzbauer says. “Social media is giving them access to images, people, and ideas they otherwise would not be able to access. This can be a very positive thing, but we know it can also have negative consequences.” 

A recent study from Facebook found Instagram to have harmful effects among a portion of its millions of young users, particularly teenage girls. Findings indicated that Instagram makes body image issues worse for one in three teenage girls. And among teenagers who reported suicidal thoughts, 6 percent in the U.S. traced them back to Instagram. 

Warning Signs Your Teen Is Struggling

This is not to say that keeping teens from social media will keep teens from having suicidal thoughts. Instead, it is a call for parents to be aware of what their kids are doing online—and to look for any changes in their child’s behavior. 

“If your child is starting to focus too much of their attention on social media at the expense of real-life interactions, parents should be concerned,” Holzbauer says. “At the very least, this should spark a conversation about the behaviors to ensure there aren’t more serious issues going on like bullying, anxiety , or other issues.”  

Parents should also look for behaviors not necessarily related to social media that may signal a problem. If a teen is acting differently, seems disinterested in life, or is talking about not wanting to live, actions should be taken. It can be a hard conversation to have —but it might save their life. 

Parents aren’t the only ones who should be on alert. Friends should also be aware when it appears someone is in trouble. They may even have more insight into the situation because they are sharing social media experiences and seeing similar content. One thing all teens should know is that if a friend appears to be considering suicide, they should not write it off as someone being “dramatic” or seeking attention. Be sure to tell someone if you see concerning behavior online and know the resources available. 

Tips for Healthy Social Media Use

We all know how the algorithm works—the more you look at your phone, the more it will send compelling content to keep your eyes from looking away. It’s hard to break habits of checking TikTok or Instagram and constantly refreshing to see more, but it’s important to take time away for our mental and physical health. Parents can set a good example through their own virtual behavior. Here are some tips for parents and their teens .

988 , the national suicide and crisis lifeline, is available anytime, anywhere. Simply call, chat, or text 9-8-8 for an immediate response from a licensed mental health professional. In Utah, students also have access to the  SafeUT app  where they can chat confidentially or submit a tip about themselves or a friend. 

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• social media

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Surgeon General Issues New Advisory About Effects Social Media Use Has on Youth Mental Health

Surgeon General Dr. Vivek Murthy Urges Action to Ensure Social Media Environments are Healthy and Safe, as Previously-Advised National Youth Mental Health Crisis Continues

Today, United States Surgeon General Dr. Vivek Murthy released a new Surgeon General’s Advisory on Social Media and Youth Mental Health . While social media may offer some benefits, there are ample indicators that social media can also pose a risk of harm to the mental health and well-being of children and adolescents. Social media use by young people is nearly universal, with up to 95% of young people ages 13-17 reporting using a social media platform and more than a third saying they use social media “almost constantly.”

With adolescence and childhood representing a critical stage in brain development that can make young people more vulnerable to harms from social media, the Surgeon General is issuing a call for urgent action by policymakers, technology companies, researchers, families, and young people alike to gain a better understanding of the full impact of social media use, maximize the benefits and minimize the harms of social media platforms, and create safer, healthier online environments to protect children. The Surgeon General’s Advisory is a part of the Department of Health and Human Services’ (HHS) ongoing efforts to support President Joe Biden’s whole-of-government strategy to transform mental health care for all Americans.

“The most common question parents ask me is, ‘is social media safe for my kids’. The answer is that we don't have enough evidence to say it's safe, and in fact, there is growing evidence that social media use is associated with harm to young people’s mental health,” said U.S. Surgeon General Dr. Vivek Murthy . “Children are exposed to harmful content on social media, ranging from violent and sexual content, to bullying and harassment. And for too many children, social media use is compromising their sleep and valuable in-person time with family and friends. We are in the middle of a national youth mental health crisis, and I am concerned that social media is an important driver of that crisis – one that we must urgently address.”

Usage of social media can become harmful depending on the amount of time children spend on the platforms, the type of content they consume or are otherwise exposed to, and the degree to which it disrupts activities that are essential for health like sleep and physical activity. Importantly, different children are affected by social media in different ways, including based on cultural, historical, and socio-economic factors. Among the benefits, adolescents report that social media helps them feel more accepted (58%), like they have people who can support them through tough times (67%), like they have a place to show their creative side (71%), and more connected to what’s going on in their friends’ lives (80%).

However, social media use can be excessive and problematic for some children. Recent research shows that adolescents who spend more than three hours per day on social media face double the risk of experiencing poor mental health outcomes, such as symptoms of depression and anxiety; yet one 2021 survey of teenagers found that, on average, they spend 3.5 hours a day on social media. Social media may also perpetuate body dissatisfaction, disordered eating behaviors, social comparison, and low self-esteem, especially among adolescent girls. One-third or more of girls aged 11-15 say they feel “addicted” to certain social media platforms and over half of teenagers report that it would be hard to give up social media. When asked about the impact of social media on their body image, 46% of adolescents aged 13-17 said social media makes them feel worse, 40% said it makes them feel neither better nor worse, and only 14% said it makes them feel better. Additionally, 64% of adolescents are “often” or “sometimes” exposed to hate-based content through social media. Studies have also shown a relationship between social media use and poor sleep quality, reduced sleep duration, sleep difficulties, and depression among youth. 

While more research is needed to determine the full impact social media use has on nearly every teenager across the country, children and adolescents don’t have the luxury of waiting years until we know the full extent of social media’s effects. The Surgeon General’s Advisory offers recommendations stakeholders can take to help ensure children and their families have the information and tools necessary to make social media safer for children:

• Policymakers can take steps to strengthen safety standards and limit access in ways that make social media safer for children of all ages, better protect children’s privacy, support digital and media literacy, and fund additional research.
• Technology companies can better and more transparently assess the impact of their products on children, share data with independent researchers to increase our collective understanding of the impacts, make design and development decisions that prioritize safety and health – including protecting children’s privacy and better adhering to age minimums – and improve systems to provide effective and timely responses to complaints.
• Parents and caregivers can make plans in their households such as establishing tech-free zones that better foster in-person relationships, teach kids about responsible online behavior and model that behavior, and report problematic content and activity.
• Children and adolescents can adopt healthy practices like limiting time on platforms, blocking unwanted content, being careful about sharing personal information, and reaching out if they or a friend need help or see harassment or abuse on the platforms.
• Researchers can further prioritize social media and youth mental health research that can support the establishment of standards and evaluation of best practices to support children’s health.

In concert with the Surgeon General’s Advisory, leaders at six of the nation’s medical organizations have expressed their concern on social media’s effects on youth mental health:

“Social media can be a powerful tool for connection, but it can also lead to increased feelings of depression and anxiety – particularly among adolescents. Family physicians are often the first stop for parents and families concerned about the physical and emotional health of young people in their lives, and we confront the mental health crisis among youth every day. The American Academy of Family Physicians commends the Surgeon General for identifying this risk for America's youth and joins our colleagues across the health care community in equipping young people and their families with the resources necessary to live healthy, balanced lives.” – Tochi Iroku-Malize, M.D., MPH, MBA, FAAFP, President, American Academy of Family Physicians

“Today’s children and teens do not know a world without digital technology, but the digital world wasn’t built with children’s healthy mental development in mind. We need an approach to help children both on and offline that meets each child where they are while also working to make the digital spaces they inhabit safer and healthier. The Surgeon General’s Advisory calls for just that approach. The American Academy of Pediatrics looks forward to working with the Surgeon General and other federal leaders on Youth Mental Health and Social Media on this important work.” – Sandy Chung, M.D., FAAP, President, American Academy of Pediatrics

“With near universal social media use by America’s young people, these apps and sites introduce profound risk and mental health harms in ways we are only now beginning to fully understand. As physicians, we see firsthand the impact of social media, particularly during adolescence – a critical period of brain development. As we grapple with the growing, but still insufficient, research and evidence in this area, we applaud the Surgeon General for issuing this important Advisory to highlight this issue and enumerate concrete steps stakeholders can take to address concerns and protect the mental health and wellbeing of children and adolescents.We continue to believe in the positive benefits of social media, but we also urge safeguards and additional study of the positive and negative biological, psychological, and social effects of social media.”— Jack Resneck Jr., M.D., President, American Medical Association

“The first principle of health care is to do no harm – that’s the same standard we need to start holding social media platforms to. As the Surgeon General has pointed out throughout his tenure, we all have a role to play in addressing the youth mental health crisis that we now face as a nation. We have the responsibility to ensure social media keeps young people safe. And as this Surgeon General’s Advisory makes clear, we as physicians and healers have a responsibility to be part of the effort to do so.” – Saul Levin, M.D., M.P.A., CEO and Medical Director, American Psychiatric Association

“The American Psychological Association applauds the Surgeon General's Advisory on Social Media and Youth Mental Health, affirming the use of psychological science to reach clear-eyed recommendations that will help keep our youth safe online. Psychological research shows that young people mature at different rates, with some more vulnerable than others to the content and features on many social media platforms. We support the advisory's recommendations and pledge to work with the Surgeon General's Office to help build the healthy digital environment that our kids need and deserve.” – Arthur Evans, Jr., Ph.D., Chief Executive Officer and Executive Vice President, American Psychological Association.

“Social media use by young people is pervasive. It can help them, and all of us, live more connected lives – if, and only if, the appropriate oversight, regulation and guardrails are applied. Now is the moment for policymakers, companies and experts to come together and ensure social media is set up safety-first, to help young users grow and thrive. The Surgeon General’s Advisory about the effects of social media on youth mental health issued today lays out a roadmap for us to do so, and it’s critical that we undertake this collective effort with care and urgency to help today’s youth.” – Susan L. Polan, Ph.D., Associate Executive Director, Public Affairs and Advocacy, American Public Health Association

The National Parent Teacher Association shared the following:

“Every parent’s top priority for their child is for them to be happy, healthy and safe. We have heard from families who say they need and want information about using social media and devices. This Advisory from the Surgeon General confirms that family engagement on this topic is vital and continues to be one of the core solutions to keeping children safe online and supporting their mental health and well-being.” – Anna King, President of the National Parent Teacher Association .

In December 2021, Dr. Murthy issued a Surgeon General’s Advisory on Protecting Youth Mental Health calling attention to our national crisis of youth mental health and well-being. Earlier this month, he released a Surgeon General’s Advisory on Our Epidemic of Loneliness and Isolation , where he outlined the profound health consequences of social disconnection and laid out six pillars to increase connection across the country, one of which being the need to reform our digital environments. The new Surgeon General’s Advisory on Social Media and Youth Mental Health is a continuation of his work to enhance the mental health and well-being of young people across the country.

The full Surgeon General’s Advisory can be read here . For more information about the Office of the Surgeon General, visit www.surgeongeneral.gov/priorities .

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What research actually says about social media and kids’ health

There is no clear scientific evidence that social media is causing mental health issues among young people. Here’s what we do know.

There is no clear scientific evidence that social media is causing mental health issues among young people. Public health officials are pushing for regulation anyway.

U.S. Surgeon General Vivek H. Murthy on Monday called for social media platforms to add warnings reminding parents and kids that the apps might not be safe, citing rising rates of mental health problems among children and teens. It follows an advisory Murthy issued last year about the health threat of loneliness for Americans, in which he named social media as a potential driver of social isolation.

But experts — from leading psychologists to free speech advocates — have repeatedly called into question the idea that time on social media like TikTok, Instagram and Snapchat leads directly to poor mental health. The debate is nuanced, they say, and it’s too early to make sweeping statements about kids and social media.

Here’s what we do know about children and teens, social media apps and mental health.

Why it’s hard to get a straight answer

There is evidence that adverse mental health symptoms among kids and teens have risen sharply, beginning during the global financial crisis in 2007 and skyrocketing at the beginning of the pandemic. But research into social media’s role has produced conflicting takeaways.

While many studies have found that social media use is correlated with dips in well-being , many others have found the opposite . One problem may be that terms such as “social media use” and “mental health” have been defined broadly and inconsistently, according to analyses of existing studies . Whatever the reason, it’s challenging for researchers to find causal relationships (meaning A causes B) between social media and mental health without closely controlling children’s behavior.

That hasn’t stopped health organizations from issuing warnings, such as a 2011 statement from the American Academy of Pediatrics Council on Communications and Media urging parents to look out for “Facebook depression.” A 2013 study suggested such warnings were “premature.”

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To help answer the question, “How does social media impact kids?” researchers need more robust data.

In a Monday opinion essay in the New York Times , Murthy also called for social media companies to share data and research into health effects so independent experts can examine it. “While the platforms claim they are making their products safer, Americans need more than words. We need proof,” he wrote.

Vulnerable kids are more likely to struggle

Sometimes, social media appears to boost anxiety and depression. Other times, it appears to boost well-being and connectedness, according to a 2022 analysis of 226 studies .

So when we ask whether social media is a community hub for LGBTQ+ youths or a rabbit hole of warped information, the answer can be “both.” Bigger factors may be a teen’s existing vulnerabilities and what they’re actually doing on social media apps, American Psychological Association Chief Science Officer Mitchell Prinstein has said .

Some studies have found that kids and teens who already struggle with their mental or emotional health are more likely to come away from social media feeling anxious or depressed. It’s hard to determine whether social media is causing depressive symptoms. One 2018 study found that while time on social media didn’t correlate with depression, young women with depression tended to spend more time on the apps.

It’s not clear why social media might affect mental health

Social media leaves some people feeling bad , some studies suggest , but scientists still don’t understand why.

David Yeager, a developmental psychologist at the University of Texas at Austin, said some possible contenders are social comparison, where we weigh our own life next to another person’s. Or maybe it’s guilt, where we feel lazy or unproductive after spending time scrolling. Of course, disappointment and guilt are age-old feelings, but social media may provoke them, Yeager said.

Social media isn’t the first new technology to raise concerns. A newspaper clipping from 1882 shows an author claiming the telephone was “an aggravation of so monstrous a character as to merit public denunciation.” People in the 1920s were worried that the radio would make people stop socializing in person.

Instead of fighting about whether social media is good or bad, it’s more important to figure out how to minimize the harm of social media’s negative elements and maximize the benefit of its good ones, Yeager said.

“Our technology has changed, but human nature hasn’t,” he said. “The things that drive us, compel us and trap us are still the same.”

Social media companies design products to keep us scrolling

Like all businesses, social media companies exist to make money. That means creating experiences to keep users scrolling on their apps — and viewing advertisements.

One way they accomplish that is by gaming our attention or emotions. Washington Post reporting has shown, for instance, that Facebook’s algorithm at one point weighed the anger reaction more strongly than a “like” because outrage tended to create more engagement.

“Rather than scaring kids and parents with half-truths, we should demand policies that force companies to end harmful business practices like surveillance advertising and manipulative design features,” said Evan Greer, director at the digital rights nonprofit Fight for the Future. Surgeon General Murthy called for similar measures in his Times essay.

Why some people are playing up (or downplaying) risks and worries

Most experts call for a measured approach to discussing social media’s potential health impacts, but not all. For example, social scientist Jonathan Haidt recently published “The Anxious Generation,” a book that attributes poor mental health among teens to social media. In it, Haidt calls for parents to keep kids off the apps before high school and off smartphones altogether until age 16. Other researchers, including University of California at Irvine psychologist Candice Odgers, have said the book misinterpreted existing studies to fuel a moral panic.

“This book is going to sell a lot of copies, because Jonathan Haidt is telling a scary story about children’s development that many parents are primed to believe,” Odgers wrote in an essay for Nature . Some of Haidt’s readers, meanwhile, celebrated what felt like direct acknowledgment of a difficult problem.

Future research may come at this contested question from new directions. An article published in Nature last month, for instance, recommended researchers consider how changes to behavior and cognition during adolescence might interact with social media and put mental health at risk.

Taylor Lorenz contributed to this report.

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Surgeon general’s call for warning labels on social media underscores concerns for teen mental health

Assistant Professor of Psychiatry, University of Colorado Anschutz Medical Campus

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Emily Hemendinger does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

University of Colorado Anschutz Medical Campus provides funding as a member of The Conversation US.

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Amid growing concerns over the effects of social media on teen mental health, on June 17, 2024, U.S. Surgeon General Vivek Murthy called for warning labels to be added to social media platforms, similar to surgeon general warnings on cigarettes and alcohol.

Murphy’s warning cited research showing that teens who use more than three hours of social media a day face double the risk of mental health problems .

This comes a year after Murphy issued a major public advisory over the links between social media and youth mental health.

As a specialist in eating disorders and anxiety , I regularly work with clients who experience eating disorder symptoms, self-esteem issues and anxiety related to social media .

I also have firsthand experience with this topic : I am 16 years post-recovery from an eating disorder, and as a teenager, I grew up when people were beginning to widely use social media. In my view, the impact of social media on mental health, especially on diet and exercise patterns, cannot simply be mitigated with a warning label. However, it is an important starting point for raising awareness of the harms of social media.

Links, associations and causal effects

Experts have long suspected that social media may be playing a role in the growing mental health crisis in young people . However, the surgeon general’s 2023 warning was one of the first government warnings supported by robust research .

Critics of the call for warning labels argue that it oversimplifies a complex issue and that limiting social media access in any way would do more harm than good. Some supporters feel that it is a step in the right direction and far less restrictive than trying to start with more widespread privacy regulations.

And so far, calls for action over regulating social media have fallen flat .

Researchers are limited to only studying associations, which make causal links difficult to establish. But there are numerous studies that do show a relationship between viewing media and worsened self-esteem, body image and mental health.

Additionally, there is scientific data that has shown the effectiveness of including warning labels to deter use of substances such as tobacco and alcohol .

However, the strategy of warning labels has been used for eating disorder content and digitally altered images on the internet, with mixed results . These studies showed that the warning labels do not reduce the negative impact of the media on body image. Some of the research even found that the warning labels might increase body and appearance comparisons , which are thought to be key reasons why social media can be harmful to self-esteem.

Potential harms

Research shows that images of beauty as depicted in movies, social media, television and magazines can lead to mental illness , issues with disordered eating and body image dissatisfaction .

Body dissatisfaction among children and adolescents is commonplace and has been linked to decreased quality of life, worsened mood and unhealthy eating habits.

The mental health of adolescents and teens has been declining for the past decade , and the COVID-19 pandemic contributed to worsening youth mental health and brought it into the spotlight. As the mental health crisis surges, researchers have been taking a close look at the role of social media in these increasing mental health concerns.

The pros and cons of social media

About 95% of children and adolescents in the U.S. between the ages of 10 and 17 are using social media almost constantly . A 2023 study found that teens spend about five hours per day on social media.

Research has shown that social media can be beneficial for finding community support . However, studies have also shown that the use of social media contributes to social comparisons, unrealistic expectations and negative mental health effects .

In addition, those who have preexisting mental health conditions tend to spend more time on social media. People in that category are more likely to self-objectify and internalize the thin body ideal . Women and people with preexisting body image concerns are more likely than others to feel worse about their bodies and themselves after they spend time on social media.

A breeding ground for eating disorders?

A recent review found that, as with mass media, the use of social media is a risk factor for the development of an eating disorder , body image dissatisfaction and disordered eating. In this review, social media use was shown to contribute to negative self-esteem, social comparisons, decreased emotional regulation and idealized self-presentation that negatively influenced body image.

Another study, called the Dove Self-Esteem Project , published in April 2023, found that 9 in 10 children and adolescents ages 10 to 17 are exposed to toxic beauty content on social media, and 1 in 2 say that this has an impact on their mental health.

Researchers have also found that increased time at home during the pandemic led to more social media use by young people and therefore more exposure to toxic body image and dieting social media content.

While social media alone will not cause eating disorders, societal beliefs about beauty , which are amplified by social media, can contribute to the development of eating disorders.

‘Thinspo’ and ‘fitspo’

Toxic beauty standards online include the normalization of cosmetic and surgical procedures and pro-eating-disorder content, which promotes and romanticizes eating disorders. For instance, social media sites have promoted trends such as “thinspo,” which is focused on the thin ideal, and “fitspo,” which perpetuates the belief of there being a perfect body that can be achieved with dieting, supplements and excessive exercise.

Research has shown that social media content encouraging “clean eating ” or following a diet based on pseudoscientific claims can lead to obsessive behavior around food. These unfounded “wellness” posts can lead to weight cycling, yo-yo dieting , chronic stress, body dissatisfaction and higher likelihood of muscular and thin-ideal internalization .

Some social media posts feature pro-eating-disorder content , which directly or indirectly encourages disordered eating. Other posts promote deliberate manipulation of one’s body, using harmful quotes such as “nothing tastes as good as thin feels.” These posts provide a false sense of connection, allowing users to bond over a shared goal of losing weight, altering their appearance and continuing patterns of disordered eating.

While young people can often recognize and understand toxic beauty advice’s effects on their self-esteem, they may still continue to engage with this content. This is in part because friends, influencers and social media algorithms encourage people to follow certain accounts.

Phone-free zones

Small steps at home to cut down on social media consumption can also make a difference. Parents and caregivers can create phone-free periods for the family. Examples of this include putting phones away while the family watches a movie together or during mealtimes.

Adults can also help by modeling healthy social media behaviors and encouraging children and adolescents to focus on building connections and engaging in valued activities .

Mindful social media consumption is another helpful approach. This requires recognizing what one is feeling during social media scrolling. If spending time on social media makes you feel worse about yourself or seems to be causing mood changes in your child, it may be time to change how you or your child interact with social media.

This is an updated version of an article originally published on June 7, 2023 .

• Social media
• Eating disorders
• Youth mental health
• Self-esteem
• Warning labels
• Social media use
• Body dysmorphia
• Eating disorders in teens

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Surgeon general’s call for warning labels on social media underscores concerns for teen mental health

Amid growing concerns over the effects of social media on teen mental health, on June 17, 2024, U.S. Surgeon General Vivek Murthy called for warning labels to be added to social media platforms, similar to surgeon general warnings on cigarettes and alcohol.

Murphy’s warning cited research showing that teens who use more than three hours of social media a day face double the risk of mental health problems .

This comes a year after Murphy issued a major public advisory over the links between social media and youth mental health.

As a specialist in eating disorders and anxiety , I regularly work with clients who experience eating disorder symptoms, self-esteem issues and anxiety related to social media .

I also have firsthand experience with this topic : I am 16 years post-recovery from an eating disorder, and as a teenager, I grew up when people were beginning to widely use social media. In my view, the impact of social media on mental health, especially on diet and exercise patterns, cannot simply be mitigated with a warning label. However, it is an important starting point for raising awareness of the harms of social media.

Links, associations and causal effects

Experts have long suspected that social media may be playing a role in the growing mental health crisis in young people . However, the surgeon general’s 2023 warning was one of the first government warnings supported by robust research .

Critics of the call for warning labels argue that it oversimplifies a complex issue and that limiting social media access in any way would do more harm than good. Some supporters feel that it is a step in the right direction and far less restrictive than trying to start with more widespread privacy regulations.

And so far, calls for action over regulating social media have fallen flat .

Researchers are limited to only studying associations, which make causal links difficult to establish. But there are numerous studies that do show a relationship between viewing media and worsened self-esteem, body image and mental health.

Additionally, there is scientific data that has shown the effectiveness of including warning labels to deter use of substances such as tobacco and alcohol .

However, the strategy of warning labels has been used for eating disorder content and digitally altered images on the internet, with mixed results . These studies showed that the warning labels do not reduce the negative impact of the media on body image. Some of the research even found that the warning labels might increase body and appearance comparisons , which are thought to be key reasons why social media can be harmful to self-esteem.

Potential harms

Research shows that images of beauty as depicted in movies, social media, television and magazines can lead to mental illness , issues with disordered eating and body image dissatisfaction .

Body dissatisfaction among children and adolescents is commonplace and has been linked to decreased quality of life, worsened mood and unhealthy eating habits.

The mental health of adolescents and teens has been declining for the past decade , and the COVID-19 pandemic contributed to worsening youth mental health and brought it into the spotlight. As the mental health crisis surges, researchers have been taking a close look at the role of social media in these increasing mental health concerns.

The pros and cons of social media

About 95% of children and adolescents in the U.S. between the ages of 10 and 17 are using social media almost constantly . A 2023 study found that teens spend about five hours per day on social media.

Research has shown that social media can be beneficial for finding community support . However, studies have also shown that the use of social media contributes to social comparisons, unrealistic expectations and negative mental health effects .

In addition, those who have preexisting mental health conditions tend to spend more time on social media. People in that category are more likely to self-objectify and internalize the thin body ideal . Women and people with preexisting body image concerns are more likely than others to feel worse about their bodies and themselves after they spend time on social media.

A breeding ground for eating disorders?

A recent review found that, as with mass media, the use of social media is a risk factor for the development of an eating disorder , body image dissatisfaction and disordered eating. In this review, social media use was shown to contribute to negative self-esteem, social comparisons, decreased emotional regulation and idealized self-presentation that negatively influenced body image.

Another study, called the Dove Self-Esteem Project , published in April 2023, found that 9 in 10 children and adolescents ages 10 to 17 are exposed to toxic beauty content on social media, and 1 in 2 say that this has an impact on their mental health.

Researchers have also found that increased time at home during the pandemic led to more social media use by young people and therefore more exposure to toxic body image and dieting social media content.

While social media alone will not cause eating disorders, societal beliefs about beauty , which are amplified by social media, can contribute to the development of eating disorders.

‘Thinspo’ and ‘fitspo’

Toxic beauty standards online include the normalization of cosmetic and surgical procedures and pro-eating-disorder content, which promotes and romanticizes eating disorders. For instance, social media sites have promoted trends such as “thinspo,” which is focused on the thin ideal, and “fitspo,” which perpetuates the belief of there being a perfect body that can be achieved with dieting, supplements and excessive exercise.

Research has shown that social media content encouraging “clean eating ” or following a diet based on pseudoscientific claims can lead to obsessive behavior around food. These unfounded “wellness” posts can lead to weight cycling, yo-yo dieting , chronic stress, body dissatisfaction and higher likelihood of muscular and thin-ideal internalization .

Some social media posts feature pro-eating-disorder content , which directly or indirectly encourages disordered eating. Other posts promote deliberate manipulation of one’s body, using harmful quotes such as “nothing tastes as good as thin feels.” These posts provide a false sense of connection, allowing users to bond over a shared goal of losing weight, altering their appearance and continuing patterns of disordered eating.

While young people can often recognize and understand toxic beauty advice’s effects on their self-esteem, they may still continue to engage with this content. This is in part because friends, influencers and social media algorithms encourage people to follow certain accounts.

Phone-free zones

Small steps at home to cut down on social media consumption can also make a difference. Parents and caregivers can create phone-free periods for the family. Examples of this include putting phones away while the family watches a movie together or during mealtimes.

Adults can also help by modeling healthy social media behaviors and encouraging children and adolescents to focus on building connections and engaging in valued activities .

Mindful social media consumption is another helpful approach. This requires recognizing what one is feeling during social media scrolling. If spending time on social media makes you feel worse about yourself or seems to be causing mood changes in your child, it may be time to change how you or your child interact with social media.

This is an updated version of an article originally published on June 7, 2023 .

This article is republished from The Conversation , a nonprofit, independent news organization bringing you facts and trustworthy analysis to help you make sense of our complex world. It was written by: Emily Hemendinger , University of Colorado Anschutz Medical Campus

‘It is hijacking my brain’ – a team of experts found ways to help young people addicted to social media to cut the craving

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Facebook’s own internal documents offer a blueprint for making social media safer for teens

Emily Hemendinger does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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Impact of Social Media Use on Mental Health within Adolescent and Student Populations during COVID-19 Pandemic: Review

Marija draženović.

1 Leadership and Management of Health Services, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia

Tea Vukušić Rukavina

2 Andrija Štampar School of Public Health, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia

Lovela Machala Poplašen

Associated data.

Data are contained within the article.

The COVID-19 pandemic has drastically changed our lives. By increased screen time during the pandemic, social media (SM) could have significantly impacted adolescents’ and students’ mental health (MH). This literature review aims to synthesize the research on the impact of SM usage on MH of adolescents and students during the first year of the COVID-19 pandemic. A review of the published literature was conducted in April 2021, through a search of PubMed and Web of Science Core Collection databases. The search yielded 1136 records, with 13 articles selected for this review. Most of the included studies observed the negative impact of SM use on MH of adolescents and students, most noticeably observed were anxiety, depression and stress. More active and prolonged SM usage was associated with a negative impact on MH of adolescents and students. Two studies recorded some potentially positive effects, such as support in coping and providing a sense of connection for those who were isolated due to social distancing measures. Since this review focuses on the early period of the pandemic, future studies should investigate the long-term impact of SM use on adolescents and students MH, with all relevant elements that can enable adequate public health response.

1. Introduction

The COVID-19 pandemic is not the first pandemic in the history of humanity, but it is undoubtedly the most severe one since the influenza pandemic in 1918. It has led to unprecedented mitigation efforts that disrupted the daily lives of most of the world’s population.

Beyond the general health repercussions of the pandemic itself, these mitigation mandates, including school closures and widespread lockdowns, combined with economic instability, fear of infection and uncertainty for the future, also present a challenge to the mental health (MH) of many [ 1 ]. In particular, this might affect adolescents and students, who highly rely on social contact with their peers [ 2 ].

MH is most affected by internal and external stressors during adolescence. The effect of stress in adolescents is exacerbated when accompanied by other stressors, such as the lack of sufficient internal or external resources or poorly developed coping skills [ 3 ]. Being deprived of social contacts and forced to adjust to online education, while going through a critical developmental stage, adolescents and students might suffer more severe effects of the COVID-19 pandemic-related stressors than the general population [ 4 ].

As reported by UNESCO, at its peak, the pandemic had a significant worldwide impact on the lives of more than 1.6 billion students [ 5 ]. In China, nearly 40.4% of the sampled youth were prone to psychological problems, and 14.4% suffered from post-traumatic stress disorder (PTSD) symptoms [ 6 ]. Social media (SM) has been gaining an increasingly prominent role in adolescents’ lives in recent decades, especially in recent years. In 2018, 45% of teens said they use the internet “almost constantly”, a figure nearly doubling from the 24% in the 2014–2015 survey. An additional 44% said they go online several times a day, indicating that roughly nine-in-ten teens go online at least multiple times per day [ 7 ].

SM has become an increasingly important part of adolescents’ daily lives [ 7 ] and the COVID-19 pandemic has further accelerated this trend [ 8 , 9 ]. Many adolescents and students have turned to SM to stay connected with their friends and peers and access information and entertainment during a time when in-person interactions have been greatly restricted [ 10 , 11 ].

SM provides data on the pandemics, but also makes available lots of misinformation. The positive impact of SM during the lockdown is the provision of valuable means for social contact. Still, it can also cause poorer sleep quality, lower self-esteem and higher levels of anxiety and depression [ 12 ]. US-based research [ 7 ] investigating the impact of SM on teen lives, found that a plurality of teens (45%) believe SM has neither positive nor negative effect on people of their age. Roughly three-in-ten teens (31%) say SM impacts mostly positively while the remaining 24% describe its effect as mostly negative. The most significant positive impact of SM use is connecting with friends and family [ 7 ]. The study by Coyne et al. [ 13 ] found that the time spent using SM was unrelated to individual changes in depression or anxiety. Contrariwise, a study by O’Reilly et al. [ 14 ] observing adolescents between 11–18 years suggested that adolescents perceived SM as a threat to mental well-being. SM can provide a sense of connection using technology to connect and support those isolated or feeling isolated due to physical social distancing measures [ 15 ]. It can also be a useful tool for staying informed about the latest developments related to the pandemic and accessing resources and support [ 16 ]. In contrast, the main negative impacts include bullying/rumor spreading, harm to relationships due to lack of individual contact, unrealistic views of others’ lives and the onset of distraction/addiction [ 7 ].

This study aims to synthesize the existing research on the impact of SM use during the first year of the COVID-19 pandemic, related to the MH of adolescents and students. The following questions guided our inquiry: Does SM use during the first year of the COVID-19 pandemic have a predominantly positive or negative impact on MH within the adolescent and student population? Which MH components have been impacted the most by SM use during the first year of the COVID-19 pandemic within the adolescent and student population?

2. Materials and Methods

2.1. design.

This literature review was conducted in accordance with the guidelines for the preferred reporting items for systematic reviews and meta-analyses [ 17 ], with minor modifications where appropriate.

The need to assess the impact of SM use during the first year of the COVID-19 pandemic on MH of adolescents and students is an important health issue. The narrative qualitative synthesis was undertaken with the guidance of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 Statement [ 18 ].

2.2. Search Strategy

A literature search was performed on 30 April 2021 using two databases, PubMed and Web of Science Core Collection.

The searches were conducted using the following defined search terms: (“covid 19” [MeSH Terms] OR “covid 19 vaccines” [MeSH Terms] OR “covid 19 serotherapy” [All Fields] OR “covid 19 nucleic acid testing” [MeSH Terms] OR “covid 19 serological testing” [MeSH Terms] OR “covid 19 testing” [MeSH Terms] OR “sars cov 2” [MeSH Terms] OR “severe acute respiratory syndrome coronavirus 2” [All Fields] OR “ncov” [All Fields] OR “2019 ncov” [All Fields] OR “coronavirus” [MeSH Terms] OR “cov” [All Fields]) AND (“social media” [MeSH Terms] OR “social networking” [MeSH Terms] OR “twitter” [All Fields] OR “youtube” [All Fields] OR “WeChat” [All Fields] OR “Sina” [All Fields]) AND (“mental health” [MeSH Terms]). The search strategy was limited to studies published in English. The full search strategy used for each database has been included in Supplementary Table S1 .

2.3. Study Inclusion and Exclusion Criteria

Studies were included in this review if they were original research focused primarily on the impact of SM use during the first year of the COVID-19 pandemic, related to the MH of adolescents and students.

Studies were excluded from this review if they were not in English; were not original primary research: reviews, reports, abstracts only, case studies, letters, opinions, commentaries, policies, guidelines or recommendations; did not focus primarily on the SM use effect on MH of adolescents or students; and if SM posts were used for content analysis, which was not focused on MH issues.

2.4. Data Collection Process and Extraction

Following the search, conducted by an information retrieval specialist (LMP), all references captured by the search engine were uploaded into the reference management software Zotero 6.2 (the Corporation for Digital Scholarship, Virginia, and the USA). Duplicates were identified and removed by MD. The remaining references were uploaded into the Rayyan collaborative tool [ 19 ]. Rayyan is a web application and mobile app for systematic reviews. It eases the process of the initial screening of abstracts and titles and helps researchers save time when they share and compare include-exclude decisions.

Initial screening was done by two researchers (MD and TVR) limiting results to those that complied with eligibility criteria. Full texts of 25 papers were assessed for eligibility in detail against the inclusion and exclusion criteria for the review. Thus, a total of 13 studies were finally included in this review. Any disagreements between the reviewers at each stage of the study selection process were resolved through discussion.

One author (MD) used a standardized form developed by the research team to extract the details of the included studies. Data were extracted from each study, including: (1) the first author and year of publication, (2) the study title, (3) the country of origin, (4) the study objective, (5) the study design, (6) the study method/sampling, (7) sample characteristics, (8) mental issues observed, (9) positive vs. negative SM impact on MH observed and (10) main results and conclusions relevant to the impact of SM use on MH of adolescents or students. A second author (TVR) verified the extracted information and checked for accuracy and completeness. Differences were resolved through discussion. The agreed evidence was then synthesized narratively.

2.5. Assessment of Risk of Bias

The risk of bias was graded according to the JBI Critical Appraisal tool, “Checklist for Analytical Cross-sectional Studies” and “Checklists for Cohort Studies” [ 20 ] by one experienced reviewer (TVR). The evaluation was based on answers to 8 questions (yes, no, unclear or not applicable, for cross-sectional studies) or answers to 11 questions (yes, no, unclear or not applicable, for cohort studies). The studies were classified as having low (>70%), moderate (40–70%) or high (<40%) risk of bias.

2.6. Data Synthesis

Data were analyzed according to the study outcomes and objectives. Descriptive (narrative) analyses of the included studies were conducted. A narrative synthesis was undertaken with the guidance of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) 2020 Statement [ 18 ]. A narrative synthesis accompanies the tabulated results from the study characteristics and describes: how the results relate to the review’s objective and questions; did SM use during the first year of the COVID-19 pandemic have a predominantly positive or negative impact on MH within the adolescent and student population; and what are the recognized positive and negative impacts.

3.1. Search Results

The literature search retrieved 1136 records (641 from PubMed, 495 from Web of Science Core Collection) and after removing duplicates 806 titles and abstracts were screened. Following title and abstract screening, a further 781 articles were excluded leaving 25 to be screened by full text. Twelve articles did not meet the eligibility criteria following full text screening. Thus, a total of 13 studies were finally included in this review [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ].

The PRISMA flow diagram of the study selection and review process is displayed in Figure 1 .

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) flow diagram of the study selection and review process.

3.2. Methodological Characteristics of the Studies

Characteristics of the included studies are shown in Table 1 . Out of 13 studies included in this review [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ], all are observational and the majority (11) [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 31 , 33 ] are cross-sectional. Out of a total of 11,975 participants, 584 were observed within two longitudinal studies [ 30 , 32 ].

Methodological Characteristics of Included Studies.

SM—social media; RR—response rate; OpenEpi—free and open-source software for epidemiologic statistics.

The total number of participants in these 13 studies was 11,975, ranging from 49 [ 32 ] to 2449 [ 24 ] participants in a single study.

Out of 13 eligible studies, 3 originated from the USA (observing a total of 1235 participants) [ 27 , 31 , 32 ], 2 originated from China (observing a total of 1047 participants) [ 23 , 30 ], 2 from Belgium (observing a total of 4173 participants) [ 26 , 28 ] and 1 originated from each: Bangladesh [ 21 ], Turkey [ 22 ], Japan [ 24 ], Pakistan [ 25 ], Canada [ 29 ] and Palestine [ 33 ], providing a relatively representative sample of student/adolescent population from North America [ 27 , 29 , 31 , 32 ], Asia [ 21 , 22 , 23 , 24 , 25 , 30 , 33 ] and Northwestern Europe [ 26 , 28 ] including the countries on various levels of development and wealth.

Participants in the studies were described as adolescents, elementary, high school or university students. Therefore, the participants ranged from 6 [ 33 ] to 48 [ 27 ] years old. The mean (in some cases average) age of participants (with the exclusion of studies where such data is not available) spans from 10.32 [ 30 ] to 22.92 [ 27 ] years old. Therefore, a limited number of adults [ 27 ] among the participants included in some studies is not considered a population with a significant impact on the study results. Additionally, we observed that the majority of participants in most of the studies were female [ 22 , 23 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ] (even up to 87.6%) [ 27 ].

Most studies used online questionnaires or surveys [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ], recruiting participants through the internet or social networks [ 21 , 23 , 24 , 26 , 28 , 29 , 31 , 32 , 33 ]. In some cases, the participants were recruited through institutional e-mails [ 24 ], via school [ 26 , 30 ], national news outlets [ 28 ] or within specific classes [ 27 ]. One longitudinal study [ 32 ] used individual-level online data (Google Search and YouTube) to analyze and correlate to the data collected via questionnaires before and during the pandemic.

Online questionnaires were generally organized in sections, with the first section collecting primary data on students and the following sections collecting specific data necessary for measuring behaviors that might impact MH and indicators of the MH condition. Some studies used a variety of original or somewhat modified validated questionnaires and scales (e.g., PHQ-9 [ 21 , 24 , 31 , 32 ], GAD-7 [ 21 , 26 , 31 , 32 ], RULS [ 26 , 28 , 29 ]) and DASS-21 [ 27 , 30 ]), while in the majority of the studies questionnaires and the measures used in them were a combination of validated and self-developed instruments [ 22 , 23 , 24 , 25 , 27 , 28 , 29 , 32 ]. One study used a questionnaire for which the validation status could not be established [ 33 ].

3.3. Objectives and Outcomes of Included Studies

The objectives and outcomes of included studies are shown in Table 2 . Several MH disorders or issues have been observed and measured in the papers. Depression [ 21 , 24 , 27 , 29 , 31 , 32 ], anxiety [ 22 , 26 , 27 , 29 , 31 , 32 ] and stress [ 23 , 27 , 29 ] were listed in three or more studies, while panic [ 33 ], addictive SM use [ 23 ], mental and psychological distress [ 28 , 30 ], worsening of sleep pattern, lack of motivation and family arguments [ 25 ] were connected to SM use in two or fewer studies. Additionally, a nonspecific MH disorder—MH imbalance [ 21 ]—was linked to SM use.

Objectives and Outcomes of Included Studies.

BASE-6—Brief Adjustment Scale-6, BFAS—Bergen Facebook Addiction Scale, BSI—Brief Symptom Inventory, BSMAS—Bergen Social Media Addiction Scale, CAS—Coronavirus Anxiety Scale, CBQ—College Belongingness Questionnaire, CESD—Center for Epidemiologic Studies Depression Scale, CTS—COVID Threat Scale, DASS-21—Depression Anxiety Stress Scales 21, ECS—Emotion Contagion Scale, GAD-7—The General Anxiety Disorder Scale, GHQ-12—General Health Questionnaire, ICG-RC—Inventory for Complicated Grief-Revised for Children, IGDS-SF9—Internet Gaming Disorder Scale-Short Form, ISI—Insomnia Severity Index, MH—mental health, NEG—negative, OCD—obsessive compulsive disorder, OCI-R—Obsessive Compulsive Inventory-Revised, OSSS-3—3-item Oslo Social Support Scale, PC-PTSD-5—Primary Care Post-traumatic Stress Disorder Screen for Diagnostic and Statistical Manual of Mental Disorders-5, PHQ-9—Patient Health Questionnaire-9, POS—positive, PSS—Perceived Stress Scale, RULS-Revised UCLA Loneliness Scale, SABAS—Smartphone Application-Based Addiction Scale, SITBI—Self-Injurious Thoughts and Behaviors Interview, SM—social media, SN—social network.

Active and increased, and daily use of SM was associated with an increased risk of depressive [ 24 , 27 , 29 , 31 ], anxiety [ 31 ] and stress [ 27 ] symptoms. Additionally, individuals with increasing anxiety or depressive disorders during the pandemic usually had longer sessions using SM [ 32 ].

The interaction between COVID-19 stress and SM use was also significant [ 29 ]. Individuals suffering more COVID-19 stress had an increased risk of addictive SM use, which has been fostered by active use and flow experience [ 23 ].

A significant positive statistical correlation was found between SM and spreading panic concerning COVID-19 [ 33 ].

Time spent on SM explained problematic SM use, and problematic SM use subsequently explained psychological/mental distress [ 30 ] with odds of psychological/mental distress 3-fold greater for those with an increase in SM use for more than three hours [ 28 ].

This review has found that most reviewed papers report predominantly negative impacts of SM use in the COVID-19 pandemic on MH of adolescents [ 21 , 22 , 23 , 24 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ].

Several reviewed studies revealed that increased SM use was related to the MH disorders of students, such as depression, anxiety and stress [ 22 , 23 , 24 , 27 , 28 , 29 , 31 , 32 ]. It also correlated with tiredness, lack of motivation and negative impact on family arguments [ 25 ]. Such increased SM use was found to be connected to problematic [ 30 ] and addictive SM use [ 23 ], potentially leading to mental distress [ 28 , 30 ] or MH imbalance [ 21 ], and interacting with COVID-19-related stress [ 23 , 29 ]. College belongingness, which influenced student psychological adjustment, was found to be moderated by SM addiction [ 22 ].

Two studies, however, indicated some potentially positive influences of SM on MH, such as long periods of sleep [ 25 ] and support in coping through humoristic content and positive exchange in SM [ 26 ].

Results of a few studies highlighted the gender difference, indicating that more women than men were found to experience significant mental distress [ 28 , 29 ].

Among the negative impacts of increased or problematic SM use on the MH of adolescents and students most noticeably observed are depression [ 24 , 27 , 29 , 31 , 32 ], stress [ 23 , 27 , 29 ] and anxiety [ 22 , 31 , 32 ].

3.4. Risk of Bias

The risk of bias in 85% (11/13) of the included studies was classified as low [ 21 , 24 , 26 , 27 , 28 , 29 , 31 , 32 , 33 ], according to the JBI Critical Appraisal tools [ 20 ], as presented in Table 3 a,b. In total, only two studies showed a moderate risk of bias [ 22 , 25 ].

(a) Assessment of Risk of Bias. The Joanna Briggs Institute (JBI) Critical Appraisal tool. Checklist for Analytical Cross- Sectional Studies [ 20 ]. (b) Assessment of Risk of Bias. The Joanna Briggs Institute (JBI) Critical Appraisal tool. Checklist for Cohort Studies [ 20 ].

* NA = Not Applicable. ** Low risk of bias >70%; Moderate risk of bias 40–70%; High risk of bias < 40%. The percentage was calculated according to have many “yes” each study got relative to the applicable items.

4. Discussion

4.1. principal findings.

A significant impact of SM on the lives of adolescents and students was evident even before the COVID-19 pandemic and it resulted in both positive and negative outcomes [ 2 , 3 , 14 , 34 ]. Some previous studies indicated that the influence of SM use on MH of adolescents might be mostly neutral, even for adolescents suffering from depression and anxiety [ 7 , 13 ].

The studies included in this review originate from multiple countries, providing a sample of the student/adolescent population from North America, Asia and Europe, thus including countries on various levels of development and wealth.

According to this literature review, the influence of SM use on the MH of adolescents and students during the COVID-19 pandemic has been significant. The findings of this review indicate that SM use was predominantly associated with the mental ill-being of adolescents and students during the early months of the COVID-19 pandemic [ 21 , 22 , 23 , 24 , 25 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ], most commonly related to MH problems, such as depression, anxiety and stress [ 21 , 22 , 23 , 24 , 27 , 28 , 29 , 31 , 32 ], which is in line with recent publications regarding SM use and its influence on MH of the younger population during the COVID-19 pandemic [ 35 , 36 , 37 , 38 , 39 , 40 , 41 ].

Among the articles reviewed in our study, seven studies investigated association between SM use and stress [ 21 , 23 , 27 , 28 , 29 , 30 , 31 ], but the term stress was used inconsistently. It was presented as stress in general [ 27 , 31 ], COVID related stress [ 23 , 29 ] or within constructs of mental distress [ 28 ], psychological distress [ 30 ] or MH imbalance [ 21 ].

Two studied stress described as COVID-19 related, either as stressful events [ 30 ] or reported stress associated with the initial COVID-19 crisis [ 29 ].

Zhao et al. [ 23 ] assessed participants experience of COVID-19 related stressful events. COVID-19 stress was significantly positively correlated with active use, SM flow and addictive SM use. Ellis et al. [ 29 ] assessed COVID-19 stress, using an adopted version of the Swine Flu Anxiety scale. Items were designed to assess fear about the spread of COVID-19 and the possibility of being infected and specific adolescents concerns that may result from physical distancing. They have also assessed depression (using six-item depression subscale of the Brief Symptom Inventory—BSI) and measured participant loneliness (using the revised UCLA Loneliness Scale—RULS). COVID-19 stress was a significant predictor of depression. The interaction between COVID-19 stress and SM use was also significant. The analysis revealed that the relationship between COVID-19 stress and depression was strongest among adolescents who reported the highest SM use after the pandemic as compared to adolescents with lower and average use ( p < 0.001).

Three studies assessed psychological distress, but under different terms, as mental distress [ 28 ], psychological distress [ 30 ] or MH imbalance [ 21 ].

Rens et al. [ 28 ] used GHQ-12 for the assessment of mental distress. Their results indicate experiencing mental distress were significantly higher among those with small or large increase in SM use. Chen et al. [ 30 ] investigated the changes in time spent on use of internet-related activities, changes in problematic use of internet-related activities and changes in psychological distress before and during the school suspension period due to the COVID-19 outbreak. Using 21 items embedded within three subscales of depression (seven items), anxiety (seven items) and stress (seven items), the DASS-21, they have assessed psychological distress. According to their results, increased and problematic SM use is significantly associated with psychological distress. Alam et al. [ 21 ] measured stress level using Perceived Stress Scale (PSS), but they also assessed depression (using PHQ-9) and anxiety (using GAD-7). They use the term MH imbalance, which was constructed and categorized in four categories, using cluster analysis combination among three MH scales (PSS, GAD-7 and PHQ-9). Students were categorized into four categories of MH imbalance, where 4.32% had mild, 72.7% had moderate, 12.57% had moderately severe and 10.41% suffered from severe MH imbalance. Since psychological distress refers to non-specific symptoms of stress, anxiety and depression [ 42 ], the term MH imbalance used in Alam et al.’s study [ 21 ] can be presented also as psychological distress. Their results showed that students spending more time on SM (22.60%) were more likely to be severely depressed, anxious and stressed, or as they stated “in severe MH imbalance”.

Depression Anxiety Stress Scale 21 (DASS-21) was also used by Wheaton et al. [ 27 ]. Their results indicate that hours per day of SM use weakly yet significantly related to concern about COVID-19 that are linked to stress and depression, but not anxiety and OCD. In this study terms psychological or mental distress were not used.

Murata et al. [ 31 ] assessed depression symptoms (using PHQ-9), anxiety symptoms (using GAD-7), PTSD symptoms (using PC-PTSD-5), perceived stress (using Perceived Stress Scale—PSS), lifetime suicidal ideation and behavior (using SITBI) and prolonged grief reactions (using ICG-RC). According to the findings of this study, adolescents were significantly more likely to report clinically significant depression, anxiety and PTSD symptoms, suicidal ideation or behavior, perceived stress and sleep problems compared to adults. Adolescents with more hours spent on SM were more likely to have moderate to severe depressive and anxiety symptoms.

This review found a link between increased SM use and depression [ 24 , 27 , 29 , 31 , 32 ], which is consistent with the findings in recent research where SM exposure [ 38 ] and excessive SM networking site usage [ 39 , 40 ] were associated with increased depression. Research has shown that the more time adolescents and students spend on SM, the more likely they are to experience negative effects on their MH [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ], that excessive use of SM can contribute to feelings of loneliness [ 39 ], anxiety [ 36 , 40 ] and depression [ 36 , 38 , 39 , 40 ]. This is particularly true for those who compare themselves to others on SM [ 44 ] and experience cyberbullying [ 45 , 46 ].

Results were similar when looking at anxiety. This review found that adolescents with more hours spent on SM were more likely to have moderate to severe anxiety symptoms [ 31 ]. Similarly, individuals with increasing anxiety symptoms during the pandemic usually conduct longer sessions when engaging with SM (YouTube) [ 32 ].

Recent research confirms this and finds that anxiety scores were higher in those who used the SM for more than 7 h per day, compared to those who used it for 0–2 or 3–4 h [ 36 ] and that excessive time spent on SM platform was associated with a greater likelihood of having anxiety symptoms [ 40 ].

Other research also shows that the COVID-19 pandemic has exacerbated existing MH problems among adolescents [ 47 ] and SM may exacerbate these problems [ 48 ]. For example, the constant stream of news and information about the pandemic on SM can lead to increased levels of stress and anxiety [ 49 ]. Additionally, the lack of in-person social support and the increased reliance on SM for social interaction may contribute to feelings of loneliness [ 34 ]. There is also some evidence to suggest that SM use may interfere with sleep quality and quantity among adolescents and students, which can negatively affect their overall MH and well-being [ 50 , 51 ].

Even though the majority of the studies in this review associate increased or problematic use of SM with a predominantly negative impact on the MH of adolescents and students during the early months of the COVID-19 pandemic, two studies, however, indicated some potentially positive influences of SM on MH, such as long periods of sleep [ 25 ] and support in coping through humoristic content and positive exchange in SM [ 26 ]. A similar beneficial effect of SM use was also observed by other studies, which found that SM can provide a sense of connection and support for those who are isolated or feeling isolated due to social distancing measures [ 43 ] or SM was observed to offer a helpful way of educating and reaching adolescents to promote mental well-being and cope with emotional burdens [ 52 , 53 ]. Additionally, other publications found SM useful in providing information about MH [ 43 , 53 ] and substituting live social contacts [ 54 ].

Contrarily, SM was used by some to seek support for suicidal thoughts and self-harm [ 36 ] and also contributed to poor MH through validation-seeking practices, fear of judgment, body comparison, addiction and cyberbullying [ 43 ]. A result from a longitudinal study conducted in Sweden, with a 2-year long follow-up, suggests that increased use of SM might be an indicator, rather than a risk factor for MH symptoms [ 55 ].

4.2. Limitations

There are several limitations to this review. The search for this literature review was performed in April 2021 using two databases, PubMed and Web of Science Core Collection. Future searches should be optimized by searching additional multi-disciplinary databases, such as Scopus, CINAHL or PsycINFO. The search for reference lists and citations would also be welcomed in the subsequent literature reviews. Only English language articles, presenting original research in a defined period were included; papers in other languages and outside the timeframe for inclusion may have identified additional relevant studies.

This review was conducted according to the guidelines for the preferred reporting items for systematic reviews and meta-analyses [ 17 , 18 , 20 ], with minor modifications. Even though there are recommendations from the JBI that COVID-19 related reviews should, besides the comprehensive literature of multiple bibliographic databases search (e.g., MEDLINE and WoS), include a search of the gray literature and/or scanning of the references [ 56 ]; we have not performed a search of the gray literature nor scanned the references of our final sample. Searching these sources is complex because of a lack of indexing and poor functionality of the search interfaces, thus we omitted it.

The data processed in the studies that were collected were obtained from November 2019 [ 30 ] until August 2020 [ 33 ] and generally related to the first year of the lockdown. Such data represents the short-term impacts of SM use on the MH of adolescents and students. The limitations imposed on the population due to the outbreak of the COVID-19 pandemic have, however, already lasted much longer than initially expected more than two years. Therefore, the findings of this review are relevant just for the relatively short period at the beginning of the pandemic, the first 16 months of the COVID pandemic, which limits their relevance. However, this period was significant since the most severe lockdown measures were introduced globally, allowing us to review studies from that period, from a specific perspective on the impact of SM use on MH within the most vulnerable populations (adolescents and students). At the same time, the long-term impacts of SM use on the MH of adolescents and students might significantly differ from the shorter-term impacts included in the reviewed papers.

All of the studies were observational and the majority [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 31 , 33 ] were cross-sectional and went no further than describing a prevalence of the specific MH condition. Another limitation was that just two longitudinal studies [ 30 , 32 ] investigating this review’s aims could be found—limiting the time component of reviewed studies. This is probably a consequence of the data collection period occurring relatively early after the pandemic outbreak, so there was a limited opportunity for multiple subsequent research waves on the relevant population samples to be performed.

This notion is also proven by the fact that the included studies used convenient sampling, recruiting participants predominantly via SM and Internet, using online questionnaires. Those methods were the most convenient, practical and feasible methods during the lockdown. Therefore, the results of this review are based on data from the studies, dominantly based on a convenient sample.

Regarding the risk of bias, and quality of the studies in this review’s final sample, only four studies, exactly stated their response rate [ 24 , 30 , 32 , 33 ], ranging from 53% to 100%. Even though the risk of bias vas very low in 11 of 13 studies, it is important that future studies report response rates more often to increase the studies’ quality.

The age of the participants spanning from childhood (elementary school students) to adulthood, makes the review population somewhat heterogeneous. However, the mean/average age of participants, ranging from 10.32 [ 30 ] to 22.92 [ 27 ] years, makes the data used in this study relevant for the population of adolescents and students.

COVID-19 pandemic mitigation efforts have lasted much longer than the period examined in this review. Impacts of SM use during pandemics on the MH of adolescents and students in such a prolonged period might significantly differ from those observed in reviewed papers. Therefore, findings from more recent studies investigating the long-term impact of SM on adolescents and students during the COVID-19 pandemic should also be examined to identify possible differences with outcomes observed in this review.

5. Conclusions

Based on the findings of reviewed studies, we conclude that increased or problematic use of SM predominantly negatively impacted the MH of adolescents and students during the first year of the COVID-19 pandemic. The majority of the included studies observed the negative impact of SM on MH, while just two studies recorded some potentially positive effects, such as support in coping and providing a sense of connection for those who were isolated due to social distancing measures. Among the negative consequences of increased or problematic SM use on MH of adolescents and students, most noticeably observed were anxiety, depression and stress. Since this review focuses on the early period of the pandemic, at this point, we can only speculate about the long-term impacts of SM on MH of adolescents and students during the COVID-19 pandemic.

Future studies, especially longitudinal and studies observing the influence of different types of SM behavior and activities, could provide valuable insights and directions for dealing with the influence of SM on the MH of adolescents and students during pandemics since we are clearly facing a new pandemic—an increase of MH disorders among our youngest generations. We should be prepared for how MH care should change due to the COVID-19 pandemic and adequately respond, especially concerning MH of adolescents and students.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph20043392/s1 , Table S1: Search strategy used in PubMed and Web of Science Core Collection.

Funding Statement

This research received no external funding.

Author Contributions

M.D. and T.V.R. led the initial idea, study design and development of the protocol. The search strategy was developed by T.V.R. and L.M.P.; L.M.P. performed the searches and extracted the data files. Title and abstract screening were performed by M.D. and T.V.R. Full text screening was conducted by M.D. and T.V.R.; M.D. led on data extraction for each full text article. M.D. and T.V.R. drafted the narrative overview with support from L.M.P. All authors contributed to the interpretation of the findings. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

This was a desk-based review of the literature therefore ethical approval was not required.

Informed Consent Statement

Not applicable.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

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• Open access
• Published: 20 June 2024

The twisted path to sacredness: a grounded theory study of irrational religious orientation and its psycho-sociological implications

• Ziang Wang 1 ,
• Yinglin Luo 1 ,
• Xuan Cao 2 &
• Jindong Jiang 1  

BMC Psychology volume  12 , Article number:  360 ( 2024 ) Cite this article

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This research delves into the nuances, origins, and societal effects of irrational religious orientations within China’s Generation Z, employing grounded theory methodology for a comprehensive analysis. The focus is on those born between 1995 and 2010, a demographic raised amidst rapid information technology growth and significantly influenced by digitalization and globalization. The study identifies three primary dimensions of irrational religious orientations in Generation Z: religious spiritual dependence, religious instrumental tendency, and religious uniqueness identity. These are shaped by factors such as the overwhelming influx of information via digital media, societal pressures and psychological dilemmas, conflicts in values and identity crises, as well as feelings of social isolation and the need for group belonging. To address these trends, the study suggests several interventions: enhancing multicultural and values education, implementing stricter online information regulation and literacy programs, boosting mental health awareness and support, and fostering engagement in social and cultural activities. These recommendations are essential for comprehensively understanding and effectively responding to the irrational religious orientations of Generation Z, ultimately contributing to their overall well-being and healthy development.

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Introduction

Generation Z’s deep engagement with technology significantly influences their values, lifestyles, and worldviews, including their religious inclinations [ 1 – 2 ]. Studies by Davis and Venkatesh et al. underscore their dependency on technology, driven by its perceived usefulness and ease of use [ 3 , 4 , 5 ]. This dependence is shaped by how well technology meets their needs, the effort involved, and its fit with their social milieu [ 4 ]. Their digital habits, including the use of social media, not only shape their health behaviors but also their religious attitudes, steering them towards pragmatic rather than traditional religious practices [ 2 ]. Understanding these digital behaviors is crucial for appreciating how they affect Generation Z’s lifestyle choices and religious perspectives [ 1 – 2 , 4 − 5 ].

Regarding the “irrational religious orientation” in China’s Generation Z, it’s a multifaceted phenomenon influenced by various factors. Li Chen, Sheng Zeng, and Zaizhen Tian’s study challenges the notion of blind religious adherence among Generation Z, suggesting their religiosity is based on rational considerations of religious rewards [ 6 ]. Jurnal Pendidikan et al.‘s research implies that Generation Z’s openness to religion might indicate a moderate, flexible approach to beliefs [ 7 ]. This contradicts interpretations of their religious behavior as irrational. Demir’s study reveals Generation Z’s adoption of secular, transhumanist values like individuality and critical thinking, potentially influencing their religious orientations [ 8 ]. These findings highlight the need for future research to adopt a nuanced approach, considering the impacts of social change, globalization, and generational shifts on Generation Z’s religious orientations [ 6 , 7 , 8 ]. Such research could lead to strategies promoting balanced religious beliefs and practices in this demographic.

Literature review

The exploration of religious orientation as a key influencer of human behavior, interpersonal relationships, and mental health has revealed a complex duality in its impacts, as evidenced by a range of studies. G. Allport and J. M. Ross’s seminal work highlights how religious orientation can significantly contribute to prejudice, linking certain prejudiced behaviors to specific religious orientations, notably those with indiscriminate favoritism towards religion [ 9 ].

Further, the interaction between religious orientation and mental health is intricate. M. Janbozorgi and F. Aliakbari, Dawood Taqvaei, and Z. Pirani, delve into the potential therapeutic aspects of religious orientation, suggesting a beneficial connection with mental health [ 10 ].

Religious orientation’s influence extends to media engagement, as Ahmad Saifalddin Abu-Alhaija et al. demonstrate its impact on viewer loyalty and perceptions in satellite TV consumption [ 11 ]. Similarly, a study links religious orientation with consumer purchasing behavior influenced by social media advertising, indicating an economic behavioral impact [ 12 ].

The realm of pro-social behavior, particularly among young women, is also explored, focusing on how religious beliefs shape charitable actions and empathy [ 13 ]. Conversely, some studies reveal potential negative implications of religious orientation, such as ‘extrinsic religious orientation’ correlating negatively with well-being [ 14 ], or influencing job-related stress levels [ 15 ].

Noteworthy contributions also include research on religious orientation’s relation to death anxiety in the elderly [ 16 ], depression in college students [ 17 ], and reproductive behaviors in women [ 18 ]. These studies collectively reaffirm the broad and significant impact of religious orientation on diverse life aspects.

In summary, the synthesis of religious orientation literature encompasses a vast array of domains, ranging from media consumption and mental health to societal and economic behaviors. The effects are varied and heavily dependent on individual experiences with religion, highlighting a multifaceted relationship between religious orientation and its influence on human life. This literature review emphasizes the need for more comprehensive and nuanced research to better understand these dynamics [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ].

The existing literature on religious orientation predominantly focuses on Western contexts, underscoring a significant gap in research concerning non-Western societies, particularly China. Notably, the religious inclinations of Chinese youth, especially Generation Z, remain insufficiently explored. Chen, Zeng, and Tian found that religiosity among China’s Generation Z is notably higher than the national average, influenced by factors like practical benefits and religious socialization [ 20 ]. This underscores the importance of considering the unique cultural and social context in religious studies. Minkov and Kaasa’s study in Africa also highlights the often-neglected cultural differences in religion, sometimes misinterpreted as racial or ethnic disparities [ 21 ]. These insights call for a recontextualization of religious orientation research, particularly in non-Western settings, to enhance its relevance and accuracy.

In China, research on Generation Z’s religious inclinations predominantly focuses on rational factors that drive their religious choices [ 6 ], such as tangible benefits over supernatural elements. However, this perspective, aligning with theories from Stark and Finke, and Hartmut Rosa, largely omits the exploration of irrational or non-rational factors. This aligns with theories by Stark and Finke, and Hartmut Rosa [ 22 ], but largely ignores the role of irrational or non-rational factors [ 23 ]. Studies on religious moderation and the impact of Internet use on religious authority choices tend to focus on rational aspects [ 8 ]. In contrast, research on older populations reveals insights into irrational religious beliefs through acceptance and commitment therapy and the role of doubt in religious education, which could provide useful perspectives for studying Generation Z’s irrational beliefs [ 24 – 25 ].

In essence, while current literature provides critical insights, it largely overlooks the irrational elements of religious inclination in Generation Z. Exploring these aspects in future research could offer a more comprehensive understanding of this demographic’s religious dynamics.

Purpose of the study

The research purpose of the study is to delve into the nuances, origins, and societal effects of irrational religious orientations within China’s Generation Z using grounded theory methodology. The study aims to provide a comprehensive analysis of these orientations, shaped by factors such as the influx of information via digital media, societal pressures, and psychological dilemmas. Additionally, it suggests several interventions to address these trends, ultimately contributing to the overall well-being and healthy development of this demographic.

Methodology

The researcher’s analysis utilizes grounded theory, a methodology developed by Glaser and Strauss, which focuses on deriving theories from data rather than adhering to a pre-existing framework [ 26 , 27 , 28 ]. This approach is particularly effective in social science research, as demonstrated in the study of irrational religious orientations among Daoist and Buddhist believers. Grounded theory enables the development of theories that genuinely reflect respondents’ experiences, fostering a deeper understanding of the subject.

In this study, the researcher employed various grounded theory coding strategies, starting with open coding to extract key concepts, followed by principal axis coding to understand their interrelationships, and concluding with selective coding to build a comprehensive theoretical framework [ 27 , 28 , 29 , 30 ]. Semi-structured interviews, complemented by literature analysis, were pivotal in exploring the conceptual nuances of irrational religious orientations, enhancing the depth and applicability of the findings.

Overall, the researcher’s grounded theory approach, supported by relevant literature, illustrates its effectiveness in social sciences for examining complex phenomena like irrational religious orientations, confirming its vital role in current scholarly discourse. The research utilized a mix of online and offline interviews, guided by an outline of open-ended questions (see Table  1 ), ensuring comprehensive coverage of the research topic.

This study aims to define irrational religious orientations, setting a foundation for future research. A diverse and inclusive sample was crucial, with 29 participants from varied backgrounds in terms of gender, age, occupation, and religious affiliation, ensuring broad representativeness (details in Table  2 ). The sample included a balance of genders (8 males, 21 females) and a wide age range (19–55 years), encompassing various professions like clerical staff, freelancers, and entrepreneurs, enriching the study with diverse professional insights.

The participants’ religious beliefs included only three beliefs, Taoism, Buddhism, and no religious beliefs, which comprehensively reflected their religious orientation. The study utilized a dual-mode interview method, i.e., offline interviews using a KDDI SR502 recorder in a quiet environment and online interviews via Tencent conferencing software to ensure effective communication and data collection. Each interview lasted between 30 and 50 min and was adjusted according to the comfort level of the participants to optimize data quality.

Ethically, the study upheld privacy and confidentiality standards, with voluntary participation emphasized, showcasing a commitment to ethical research practices.

This research, grounded in qualitative methodology, emphasizes the open coding process in analyzing interview transcripts, underscoring the crucial role of qualitative data analysis software like NVivo14 in categorizing data and conceptualizing themes [ 31 – 32 ]. Open coding involves a detailed dissection of data, here interview transcripts, to extract categories, properties, and hypotheses, demanding an in-depth understanding and identification of recurring patterns or themes [ 33 ]. This creative yet disciplined process requires an analytical mind capable of connecting disparate qualitative data.

NVivo14 is instrumental in breaking down data into manageable units, organizing and analyzing content to identify key themes and patterns [ 32 ]. This software minimizes category overlap, clarifying and distinguishing each theme, thereby enhancing the analysis’s accuracy and quality. The incorporation of digital tools like NVivo14 in research workflows not only speeds up the process but also ensures a thorough, nuanced examination of qualitative data. The specifics of open coding are presented in Table  3 .

In grounded theory methodology, spindle coding follows open coding as a pivotal process [ 26 ]. Its primary role is to establish connections and relationships between pre-existing codes. This stage synthesizes initial codes into broader themes, revealing causal links, conditions, and contexts [ 34 ]. For instance, researchers might group codes into themes like “belief avoidance” or “belief dependence,” exploring their interplay within the studied phenomenon.

Selective coding, the final step in grounded theory [ 26 , 35 – 36 ], integrates categories from spindle coding around a central or “core category“ [ 37 ]. This is done to form a cohesive theory around the core categories that effectively summarizes the major phenomena observed in the study [ 26 , 34 , 38 ]. This forms a unified theory reflecting the study’s main observations. For example, if “religious spiritual dependence” emerges as a core category, selective coding aligns all related categories to depict its representation in the data. This process culminates in a structured, coherent theoretical framework, as outlined in Table  4 .

Dimension construction process

The results of the semi-structured interviews on irrational religious orientations revealed three main dimensions of irrational religious orientations: B01 Religious Spiritual Dependence; B02 Religious Instrumental Tendency; and B03 Religious Uniqueness Identity.

Religious spiritual dependence

The three main dimensions are A01 Faith Escape, A02 Faith Dependence, and A03 Faith Dissemination, and the five subdimensions are C10 Reality Escape, C11 Responsibility Escape, C14 Negative Coping, C18 Emotional Dependence, and C19 Persuasion.

Religious-spiritual dependence reflects an individual’s excessive reliance on religious beliefs, which usually manifests itself in the form of avoidance of real-life difficulties and responsibilities, as well as the search for psychological comfort and a sense of social belonging [ 39 ]. In gaining a deeper understanding of the nature of this dependence, its multiple dimensions can be revealed by analyzing the three main categories - Faithful Evasion, Faithful Dependence, and Faithful Dissemination - and their related subcategories.

Faithful Evasion encompasses the subcategories of " C10 Reality Escape " and " C11 Responsibility Escape “. This concept describes the use of religious beliefs by individuals to escape real-life dilemmas and personal responsibilities, reflecting religious spirituality as a mechanism to avoid real-life challenges.

Seeking Solace in Faith is a fusion of the subcategories of “C14 Negative Coping” and “C18 Emotional Dependence”. It expresses the tendency of individuals to seek religion for emotional comfort and psychological support in the face of life’s challenges, rather than actively solving problems, and shows individuals’ reliance on the spirit of religion for psychological comfort and emotional support in the face of adversity.

Faith Dissemination, derived from the subcategory of “C19 Persuasion”, describes individuals who actively persuade others to accept their religious beliefs due to the need for spiritual dependence. This behavior may be due to the fact that the individual seeks to gain self-affirmation and psychological support by getting others to accept his or her beliefs.

Considering the relationship between these primary and secondary categories together, the complexity of religious spiritual dependence can be seen. Individuals may seek to cope with life’s stresses and challenges through faith escape, find emotional solace and psychological support through faith dependence, and enhance their own faith experience and increase their sense of social belonging through faith transmission. Together, these patterns of behavior constitute the structure of religious-spiritual dependence, reflecting how individuals respond to various psychological and social needs in their personal lives through religious belief.

Religious instrumental tendency

The 4 main categories are A04 Extravagant Display, A05 Profit-driven, A06 Stubbornness and Narrow-mindedness, and A07 Social Avoidance. the 8 subcategories are C04 Wastefulness, C08 Flaunting, C06 Profit-making tendency, C09 Investing tendency, C02 Obsessive, C20 Paranoia, C13 Dogmatic rigidity, C17 Social isolation.

Religious instrumental tendency is a state of mind that uses religious beliefs as a means to achieve personal ends, and this tendency shows diversity and complexity among different individuals. By analyzing in depth the four main categories - Ostentatious Display, Profit-Driven, Stubborn Narrow-mindedness, and Social Avoidance - and the sub-categories associated with them, we can understand the nature and manifestations of this tendency more fully.

The concept of “A04 Extravagant display”, formed by combining the subcategories of “C08 Flaunting” and “C04 Wastefulness”, describes the excessive and unnecessary consumption behaviors that individuals engage in in order to display their social status and wealth. Such behavior is not only intended to attract the attention and admiration of others, but also reflects a strong desire for social recognition and status in the context of religious instrumentalism.

“A05 Profit-driven” is a blend of “C06 Profit-making tendency” and “C06 Profit-making tendency”, and is characterized by the individual’s intense pursuit of monetary rewards. This mindset may drive individuals to seek profit in various investments and business activities, sometimes without regard for risk or ethics.

“A07 Social avoidance”, derived directly from the subcategory of “C17 Social isolation”, describes an individual’s tendency to avoid social interactions due to fear of interpersonal complexity or distrust of others. This avoidance behavior may be a defense mechanism, but in the long run it may lead to a deterioration of social skills and impoverishment of interpersonal relationships.

“A06 Stubbornness and narrow-mindedness” combines the subcategories of " C02 Obsessive,” " C20 Paranoia,” and " C13 Dogmatic rigidity,” highlighting a lack of openness and flexibility in an individual’s thinking and behavior. A lack of openness and flexibility in individual thought and behavior. Such attitudes are often associated with resistance to dissent and new information, and reflect an overly insistent and narrow perspective on religious ideas.

Considering these categories together, religious instrumental tendencies constitute a complex web of individual behaviors and mindsets. Through extravagant displays, individuals may seek social recognition and status; through the profit motive, they pursue material gain; through social avoidance, they avoid confronting the complexity of relationships; and through stubborn narrow-mindedness, they defend their beliefs and perspectives. Together, these patterns of behavior exemplify how individuals use religious beliefs to achieve personal ends, including the pursuit of material gain, social status, and avoidance of social interactions.

Religious unique attribute identity

The four main categories are A08 Critically Deficient Conformity, A09 Psychological Compensatory Beliefs, A10 Authoritative Dependence, and A11 Identity Judgemental Discrimination Blind Conformity. the seven subcategories are C01 Blind Conformity, C05 Blind Rendering, C15 Authoritative Dependence, C07 Compensation, C03 Coercion, C12 Obedience to the Word, and C16 Double Standards.

Religious uniqueness identity refers to specific mental attitudes and behavioral patterns exhibited by individuals in their religious practices and beliefs. These patterns typically include blind obedience to authority, compensation for psychological needs, and discrimination and prejudice in identity judgments. By analyzing the four main categories: critically deficient conformity, psychologically compensatory beliefs, authority attachment, and identity-judging discrimination, as well as the related subcategories, we can gain insight into the nature of religiously exclusive identity.

Uncritical Conformity combines the subcategories of Blind Conformity, Blind Rendering, and Authority Dependence to describe the nature of individuals’ religious practices. It describes an individual’s blind acceptance of authoritative opinions and collective beliefs in religious practice without individual critical thinking. This reflects the individual’s unconditional obedience to religious authority and collective views.

Psychological Compensation Faith retains the independence of the Compensation subcategory and emphasizes the use of religious practices to satisfy internal psychological needs, such as comfort, self-affirmation, or escape from stressful situations.

Compliance Pressure combines the subcategories of Compulsion and Obedience to emphasize the unconditional obedience of individuals to authority in religious contexts and the coercion of beliefs on others. It expresses the individual’s submissiveness and dependence on religious authority.

Identity Judgment Bias maintains the independence of the subcategory of “double standards”, which relates to the impartiality of judgments, and manifests itself in discrimination and prejudice against different identities or groups in religious beliefs and practices.

The relationship between these primary and secondary categories reveals the multiple dimensions of religious identity. Individuals may exhibit blind obedience to religious authority and collective viewpoints through critically deficient subordination; through psychologically compensatory beliefs that utilize religion to satisfy internal psychological needs; through authoritative dependence, which manifests as obedience to authority and coercion of beliefs about others; and through identity judgmental discrimination, whereby individuals may exhibit discrimination and prejudice against different identities or groups in their religious beliefs and practices. Together, these behavioral and attitudinal patterns constitute the complex structure of religious uniqueness identity, reflecting how individuals develop specific psychological attitudes and behavioral patterns in their religious beliefs and practices.

Theoretical modeling of irrational religious orientations

In constructing a theoretical model of irrational religious dispositions, a variety of complex psychological, social, and cultural factors are considered and how they interact to shape an individual’s religious behaviors and attitudes (as shown in Fig.  1 ). The model refines the key factors that shape irrational religious dispositions, explores their profound impact on individual mindsets and behaviors, and proposes a range of strategies aimed at mitigating or preventing these dispositions. In this framework, we can see how religious beliefs can mutate from a healthy spiritual support to an irrational form that can bring about psychological distress and social division. Next, we will explore in detail the factors that shape irrational religious orientations as well as specific measures to counter these tendencies.

Conceptual Model of Irrational religious orientations

Factors shaping generation Z’s Irrational religious orientations

Information explosion and online communication.

In the digital age, Generation Z is significantly impacted by the vast availability of online information, particularly in shaping their religious beliefs. This information overload often leads to cognitive stress and confusion, as they struggle to process and assimilate extensive religious content [ 40 ]. Consequently, decision-making becomes more challenging, and there’s a tendency towards superficial information processing [ 41 ]. The diversity of information, while offering broad perspectives, also poses risks. Extreme or irrational religious views online can mislead youth, impacting their value formation. Additionally, social media algorithms may reinforce existing beliefs, creating an ‘Echo Chamber Effect’ and hindering critical thinking [ 42 – 43 ].

Therefore, the information era presents both opportunities and challenges for Generation Z in forming religious concepts. The key concern is aiding them in effectively filtering and processing information to develop rational beliefs [ 44 ].

Social pressures and psychological difficulties

In the current social context, Generation Z faces considerable stressors, including academic, career, and social pressures, contributing to mental health issues like anxiety and depression [ 45 ]. To cope, many turn to religious beliefs for solace, sometimes adopting irrational religious ideas that offer simple solutions [ 45 ].

This reliance on irrational religious concepts can lead to avoidance behaviors, impacting long-term development and mental health [ 46 ]. Such avoidance may manifest as denial of real-life problems and a lack of constructive coping strategies.

This reliance on irrational religious concepts can lead to avoidance behaviors, impacting long-term development and mental health [ 47 ]. This avoidance behavior may manifest itself in ignoring or denying real-life problems, as well as a lack of positive coping attitudes in the face of difficulties.

Furthermore, excessive reliance on these beliefs in decision-making can impair rational thinking, leading to potentially harmful choices in education, career, health, and relationships [ 48 – 49 ].This can also result in a disconnect from family, friends, and society, potentially leading to social isolation and increased psychological distress [ 41 , 50 ].

In summary, Generation Z’s turn to irrational religious beliefs as a response to societal and psychological pressures not only affects their mental health and development but also influences their social relationships and life choices. Understanding and addressing these tendencies is vital for their overall well-being.

Value conflict and identity crisis

In the context of globalization and the digital era, Generation Z navigates complex challenges in shaping their identity and values [ 51 ]. This generation actively seeks to establish unique identities, often blending various cultures, values, and lifestyles beyond traditional or ethnic boundaries. Balancing cultural conflicts and integration, they grapple with tradition versus modernity and local versus global influences.

Many in Generation Z question traditional religions and cultural values, gravitating towards non-mainstream or emerging religious beliefs as a form of spiritual solace and a means to express individuality and dissent [ 52 – 53 ]. This exploration is also driven by their need for a sense of community and belonging. They often turn to virtual communities, which offer a platform for aligning with specific religious concepts or lifestyles, providing a new avenue for identity formation and belonging [ 54 – 55 ].

Overall, Generation Z’s journey in forming personal identities and values is influenced by a mix of cultural diversity, individualization, and community belonging. This journey often includes an attraction to non-mainstream religious beliefs, highlighting the complexity of their search for identity and belonging.

Social loneliness and sense of group belonging

The rise of social networks has had a profound dual impact on Generation Z’s social habits and religious perspectives [ 56 ]. Social media, while facilitating connectivity, often lacks depth and authenticity, leading to decreased real-life socialization and potential social isolation [ 57 – 58 ]. The culture of online comparison can undermine self-worth, exacerbating feelings of loneliness and dissatisfaction. Additionally, overreliance on virtual communication may impair real-life social skills, hindering the formation of meaningful relationships [ 59 ].

In response, religious groups are becoming increasingly appealing to Generation Z for offering community and a sense of belonging [ 50 , 60 ]. The shared beliefs and community activities within these groups can mitigate feelings of isolation and promote social engagement. However, in their search for belonging and meaning, Gen Z may also be drawn to irrational religious beliefs that provide simple answers to complex life questions.

In summary, social media’s influence and the resulting social isolation may prompt Gen Z to seek belonging in religious communities, while simultaneously increasing their susceptibility to irrational religious orientations. This underscores the complexities of Gen Z’s pursuit of social connection, psychological solace, and identity formation.

Response to Generation Z’s Irrational religious orientations

Strengthening internet information regulation and literacy education.

Enhancing internet information regulation and literacy education is vital in assisting Generation Z to discern and resist irrational religious orientations, fostering the development of sound religious concepts and values.

Effective online information regulation involves scrutinizing and filtering religious content to prevent the spread of misinformation and extreme ideas [ 61 – 62 ]. This includes restricting misleading content and ensuring online platforms are transparent and accountable, flagging or removing content promoting harmful religious ideologies [ 63 ].

Literacy education should focus on equipping Gen Z with skills to critically analyze internet content, particularly religious information. This involves teaching them to identify credible sources, understand the intentions behind information, and evaluate online content from various perspectives [ 64 – 65 ].Media literacy education, crucial for safe and responsible use of social media and online platforms, should be integrated into school curricula and broader societal education [ 66 ]. A comprehensive approach requires multifaceted education and guidance, extending beyond formal school settings to families, communities, and online platforms. Promoting content that disseminates healthy religious concepts and recognizing individual differences in information processing and critical thinking are also key. Personalized support should be offered based on individual needs [ 63 , 64 , 65 , 66 ]. These strategies will help Generation Z to develop healthy and rational beliefs and values.

Mental health and counseling

Mental health education and counseling are pivotal for assisting Generation Z in managing psychological stress and diminishing their reliance on irrational religious beliefs. Firstly, enhancing mental health awareness is crucial. It involves educating young people about recognizing and understanding common psychological issues, like anxiety and depression, which are fundamental for mental well-being [ 67 ].

Developing coping and emotional self-regulation skills is also essential. This approach teaches Generation Z effective strategies for handling life’s pressures and emotional challenges, enabling them to respond positively to mood swings and frustrations [ 68 ].

Professional psychological counseling plays a significant role, providing emotional support and specialized assistance, especially in addressing personal problems and stress. Tailored counseling services offer individualized support, helping young people discover personal coping strategies [ 69 – 70 ].

Implementing these strategies in schools and communities is equally important. Integrating mental health education into curriculums and providing accessible community resources, like hotlines and workshops, broadens support. Training parents and teachers enhances their ability to understand and meet the psychological needs of youth [ 71 ].

A comprehensive approach includes a multi-channel mental health support system, combining resources from educational institutions, families, communities, and professional organizations. This system should foster open discussions about mental health to dismantle taboos and offer specialized support for those with specific psychological needs [ 72 ].

Through these initiatives, Generation Z can more effectively manage psychological stress, enhancing their mental health and reducing dependency on irrational religious practices, thereby promoting their overall well-being and healthy development.

Multiculturalism and values education

Multiculturalism and values education are essential in addressing the irrational religious inclinations of Generation Z [ 73 ]. This form of education fosters an appreciation and respect for diverse cultural backgrounds, beliefs, and traditions, crucial for cultivating a broad-minded perspective among young people [ 74 ]. It enhances cultural awareness, sensitivity, and the ability to respect and value equality, while also sharpening critical thinking skills [ 75 ].

The role of public media is significant in promoting pluralistic and inclusive narratives. By offering varied perspectives, including those of minority and marginalized groups, media can contribute to a balanced understanding while steering clear of extreme or radical viewpoints.

Implementing systematic multicultural and values education programs involves integrating these themes into school curricula and leveraging the influence of public media. Encouraging active participation in social and cultural activities enables young people to engage with diverse groups, fostering practical experiences in multiculturalism and values. Opportunities for volunteerism, community involvement, and cultural experiences further reinforce these concepts [ 73 , 74 , 75 ].

These strategies are pivotal in helping Generation Z develop a rational worldview, mitigate the allure of irrational religious beliefs, and grow into open, tolerant, and understanding members of a multicultural society.

Religious education and dialogue

Religious education is key in enhancing young people’s comprehension and appreciation of various religions [ 76 ]. It delves into the history, core beliefs, and practices of different faiths, emphasizing the spectrum and intricacies of religious beliefs. This education is instrumental in helping Generation Z understand diverse religious perspectives, recognize similarities and differences among them, and discern between rational religious concepts and extremist ideas [ 77 – 78 ].

Public lectures and seminars featuring religious experts can foster dialogue and rational discussions, enabling students to articulate and respect diverse viewpoints [ 79 – 80 ]. Inter-religious exchange activities further promote mutual understanding and respect across different faiths.

Critical thinking is a cornerstone of religious education, equipping young people to analyze and critically evaluate religious information, identify prejudices, and base their understandings on facts and logic [ 81 – 82 ]. It encourages them to develop their own religious views, rather than conforming to others’ beliefs uncritically.

Effective strategies for promoting religious understanding include offering religious education and dialogue through schools, communities, religious institutions, and public media. Emphasizing inclusivity and respect for both believers and non-believers in all forms of religious education and dialogue is essential. These measures are designed to help Generation Z develop a well-rounded worldview, understand the role of religion in personal and societal contexts, and become more open, inclusive, and rational members of society [ 76 , 80 , 81 , 82 ].

Main findings

This research delves into the irrational religious orientations of Generation Z in China, uncovering their complexity and multidimensionality. The study identifies key aspects:

a. Religious Spiritual Dependence : This includes faith avoidance, dependence, and propagation, highlighting how individuals excessively rely on religious beliefs for psychological comfort and social belonging when facing real-life challenges.

b. Religious Instrumental Tendency : Some individuals use religion as a means to achieve personal goals, such as gaining social status or material benefits.

c. Religious Uniqueness Identity : This reflects specific attitudes and behaviors in religious practices among Generation Z, characterized by a lack of critical thinking and using religion to fulfill psychological needs.

The formation of these tendencies is influenced by factors such as information overload and Internet communication, leading to cognitive challenges and susceptibility to misinformation, particularly in developing religious ideas. Social pressures, academic and professional development challenges, value conflicts, identity crises, social isolation, and the need for group belonging also contribute significantly.

The study suggests multifaceted strategies to address these tendencies:

Promotion of Multiculturalism and Values Education : Through education and public media, fostering respect, equality, and critical thinking.

Strengthening Online Information Regulation and Literacy : Aiding Gen Z in discerning information and developing rational religious concepts.

Mental Health Awareness and Counseling : Supporting Gen Z in managing psychological stress and reducing dependence on irrational religious beliefs.

Encouragement of Social and Cultural Activities : Enhancing communication and understanding among diverse groups, promoting openness and inclusivity.

These findings and strategies provide valuable insights into Generation Z’s irrational religiosity and propose practical approaches for support and guidance. Implementing these strategies is key to understanding their psychological and behavioral patterns in religious beliefs, crucial for their well-being and healthy development.

Theoretical and practical implications

This study offers a comprehensive exploration of irrational religious orientations in China’s Generation Z, shedding light on their complex motivations and multidimensional nature. It examines how religious spiritual dependence, instrumental tendency, and exclusive identity interplay with personal behaviors, providing valuable theoretical insights into this complex phenomenon.

The research underscores the significance of cultural context in understanding religious orientations. Investigating these tendencies across various cultural and social environments can yield more nuanced understanding, highlighting the impact of cultural factors on the development and manifestation of these inclinations.

For policymakers, the study’s findings offer crucial guidance. It suggests the need for educational policies, public communication strategies, and social interventions tailored to address irrational religious orientations among Generation Z. These strategies aim to foster social cohesion and support the healthy development of young people.

Educators and mental health professionals can leverage these insights to better assist Generation Z. Multicultural education, cyber literacy, and mental health counseling emerge as key tools for guiding young people towards healthier, more rational religious attitudes and helping them navigate the psychological and social challenges associated with these tendencies.

In summary, this study not only enriches the theoretical understanding of irrational religious orientations but also provides practical strategies for addressing these issues, particularly focusing on Generation Z in China. Its implications are vital for enhancing societal well-being and fostering healthy development.

There are still some limitations of this paper, which are as follows:

Sample diversity

The sample in this study may not be fully representative of the broader Generation Z population in different parts of China, which may affect the generalizability of the results. The sample is limited to participants from predominantly urban areas, which may not reflect the religious orientation of participants from rural areas.

Methodological limitations

While grounded theory provides reliable qualitative insights, the interpretation of the data may be subjective and influenced by the researcher’s viewpoint. This may affect the neutrality and replicability of the study.

Cross-sectional nature

The study design is cross-sectional, which limits the ability to capture changes in religious orientation over time or to infer causal relationships between observed factors and religious orientation.

Reliance on self-reported data

The study relies heavily on self-reported data obtained through interviews, which are susceptible to biases such as social desirability or recall bias. Participants may present themselves in ways that they find socially acceptable rather than reflecting their true religious orientation.

Digital influences

Given the study’s focus on the digital influences of Generation Z, the study may overemphasize the impact of digital media on religious orientation without sufficiently considering other important influences such as family, education, and personal experiences.

Recommendations for future research

To further enrich the understanding and theoretical framework of irrational religious orientations among China’s Generation Z, this study suggests employing innovative qualitative research methodologies such as Online Photovoice (OPV), Online Interpretative Phenomenological Analysis (OIPA), and Community-Based Participatory Research (CBPR) [ 83 ]. These methodologies are crucial for capturing the personal experiences and perceptions of individuals authentically and vividly, delving deeper into their thoughts, feelings, images, and behaviors.

Utilizing OPV and OIPA can provide valuable insights into the irrational religious orientations and their psycho-sociological implications. By applying OPV and CBPR, researchers can gain a deeper understanding of Generation Z’s approach to religious and spiritual concepts. Furthermore, examining religious and spiritual facilitators and barriers for Chinese people through the lens of OPV and OIPA, while collaborating with them from a CBPR perspective, is essential [ 84 ].

OPV, as one of the most recent and effective innovative qualitative research methods, offers a unique opportunity for participants to express their own experiences with minimal manipulation compared to traditional quantitative methods. Early adopters of OPV, such as Tanhan and Strack, have operationalized and explained it step by step, demonstrating its effectiveness in capturing authentic participant experiences [ 85 ].

Future researchers are encouraged to conduct qualitative or mixed-method studies to explore the potential of OPV. Educators and trainers can also use OPV for experiential activities to enhance group and organizational synergy. OPV and OIPA provide straightforward and comprehensive approaches to data analysis, resulting in meaningful and comprehensive insights [ 86 ].This approach is not only about expanding the understanding of irrational orientations but also about exploring the multi-dimensional aspects of religious spiritual dependence, instrumental tendency, and exclusive identity.

This comprehensive exploration provides critical insights into the interplay between religious beliefs and personal behaviors, offering new perspectives that contribute to a more nuanced understanding of this complex phenomenon. The study highlights the importance of conducting similar research in different cultural contexts, as cultural factors significantly influence the formation and manifestation of religious orientations. By analyzing these orientations in varied settings, researchers can obtain more comprehensive insights that enhance our understanding globally.

The findings from this study serve as important guidance for policymakers, suggesting the need for more effective educational policies, public communication strategies, and social interventions. These can be specifically targeted to address the challenges posed by irrational religious orientations and promote social cohesion and the healthy development of young people. Additionally, educators and mental health professionals can utilize these findings to better understand and support Generation Z. Through targeted interventions such as multicultural education, cyber literacy, and mental health counseling, professionals can guide young people to develop healthier and more rational religious attitudes, assisting them in navigating the psychological and social challenges associated with irrational religious orientations.

Overall, the integration of these innovative methodologies and the in-depth analysis provided by this study significantly contribute to the theoretical and practical understanding of irrational religious orientations. This is particularly significant in enhancing the well-being and promoting the healthy development of society, especially within the context of Generation Z in China.

Data availability

No datasets were generated or analysed during the current study.

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Acknowledgements

I am immensely grateful for the invaluable support and assistance I’ve received throughout this study. My profound thanks go to Hangzhou Qiuyue Xiyun Culture and Creativity Company, Hong Kong Ruyi Culture and Industry Company Limited, and Zhejiang Jinlan Law Firm for their generous financial backing, insightful guidance, and advice, which were instrumental in the study’s success. I would also like to express my heartfelt gratitude to all the volunteers and participants involved in this study. Their enthusiastic participation, sincere sharing, and invaluable advice provided critical data and profound insights that were invaluable to the depth and breadth of this study. My heartfelt appreciation extends to all the volunteers and participants for their enthusiastic involvement and meaningful contributions, offering essential data and perspectives that greatly enriched this research.

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Ziang Wang: Conceptualization, Methodology, Data Curation Software, Writing - Original Draft，Yinglin Luo: Writing Review & Editing, Visualization Xuan Cao: Investigation, Resources Jindong Jiang: Project administration, Resources.

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Correspondence to Jindong Jiang .

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Wang, Z., Luo, Y., Cao, X. et al. The twisted path to sacredness: a grounded theory study of irrational religious orientation and its psycho-sociological implications. BMC Psychol 12 , 360 (2024). https://doi.org/10.1186/s40359-024-01858-8

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Received : 23 December 2023

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DOI : https://doi.org/10.1186/s40359-024-01858-8

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