Using Social Media for Social Comparison and Feedback-Seeking: Gender and Popularity Moderate Associations with Depressive Symptoms
Open accessAbstract
This study examined specific technology-based behaviors (social comparison and interpersonal feedback-seeking) that may interact with offline individual characteristics to predict concurrent depressive symptoms among adolescents. A total of 619 students (57 % female; mean age 14.6) completed self-report questionnaires at 2 time points. Adolescents reported on levels of depressive symptoms at baseline, and 1 year later on depressive symptoms, frequency of technology use (cell phones, Facebook, and Instagram), excessive reassurance-seeking, and technology-based social comparison and feedback-seeking. Adolescents also completed sociometric nominations of popularity. Consistent with hypotheses, technology-based social comparison and feedback-seeking were associated with depressive symptoms. Popularity and gender served as moderators of this effect, such that the association was particularly strong among females and adolescents low in popularity. Associations were found above and beyond the effects of overall frequency of technology use, offline excessive reassurance-seeking, and prior depressive symptoms. Findings highlight the utility of examining the psychological implications of adolescents' technology use within the framework of existing interpersonal models of adolescent depression and suggest the importance of more nuanced approaches to the study of adolescents' media use.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
13 of 62 cited sources checked · 7 supported · 0 flagged · accuracy not yet measured
- Premisecitation
Youth with lower self-esteem and weaker offline friendships may be more prone to problematic online behaviors, including posting negative content and consuming content instead of communicating directly with peers.
“For example, research suggests that individuals with lower self-esteem and poorer offline friendship quality are more likely to engage in maladaptive behaviors using technology, such as posting negative or inappropriate content and using the Internet primarily for content consumption, rather than direct communication with peers (Mikami et al. 2010; Selfhout et al. 2009).”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Mikami et al. 2010 source
The Discussion reports that weaker face-to-face peer relationships predicted fewer online friends and fewer comments indicating connection, while adolescent delinquency and depressive symptoms predicted hostile profile text and inappropriate photos, respectively. This supports the claim’s broad link between offline difficulties and some negative online content, but the paper does not establish lower self-esteem or using the Internet primarily to consume content rather than communicate directly with peers. (LLM, conf=0.87)
Experimental — accuracy not yet measured - cites Selfhout et al. 2009 source
- Premisecitation
Situational continuity between offline and online contexts suggests that this effect is likely to occur online as well.
“Situational continuity between offline and online contexts (Mikami et al. 2010) suggest that this effect is likely to occur online, as well.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Mikami et al. 2010 source
- Findingown data
Gender moderated the link between technology-based SCFS and depressive symptoms, with a stronger association among females.
“Popularity and gender served as moderators of this effect, such that the association was particularly strong among females and adolescents low in popularity.”
Quote in the paperSubstantial claim - Findingown data
The link between technology-based SCFS and depressive symptoms remained after adjusting for overall technology use frequency, offline excessive reassurance-seeking, and baseline depressive symptoms.
“Associations were found above and beyond the effects of overall frequency of technology use, offline excessive reassurance-seeking, and prior depressive symptoms.”
Quote in the paperSubstantial claim - Findingown data
Popularity moderated the link between technology-based SCFS and depressive symptoms, with a stronger association among adolescents low in popularity.
“Popularity and gender served as moderators of this effect, such that the association was particularly strong among females and adolescents low in popularity.”
Quote in the paperSubstantial claim
- Findingown data
Frequency of technology use, technology-based social comparison and feedback-seeking, and offline excessive reassurance seeking were positively correlated.
“Significant positive associations were found between frequency of technology use, technology-based SCFS, and offline excessive reassurance-seeking.”
Quote in the paperNot a substantial claim - Findingown data
Technology-based social comparison and feedback-seeking had a significant positive main effect on depressive symptoms, controlling for overall technology use frequency, offline excessive reassurance seeking, and prior depressive symptoms.
“In support of the first hypothesis, results revealed a significant main effect of technology-based SCFS on depressive symptoms (B=0.21, p<0.001).”
- Also stated in: § Discussion · plain
“In support of the first hypothesis, technology-based SCFS was found to be associated with depressive symptoms, controlling for overall frequencies of technology use, offline ERS, and prior depressive symptoms.”
Quote in the paperSubstantial claim - Also stated in: § Discussion · plain
- Findingown data
Popularity was positively associated with frequency of technology use.
“Popularity was positively associated with frequency of technology use and technology-based SCFS; however, it was negatively associated with depressive symptoms.”
Quote in the paperNot a substantial claim - Findingown data
There was a significant technology-based social comparison and feedback-seeking by gender interaction effect on depressive symptoms, B = −0.08, p < 0.05.
“Additionally, in support of the second and third hypotheses, analyses revealed a significant technology-based SCFS × gender interaction effect (B=−0.08, p<0.05), as well as a significant technology-based SCFS × popularity effect (B=−0.11, p<0.01).”
Quote in the paperSubstantial claim - Findingown data
Popularity was negatively associated with depressive symptoms.
“Popularity was positively associated with frequency of technology use and technology-based SCFS; however, it was negatively associated with depressive symptoms.”
Quote in the paperNot a substantial claim - Findingown data
Female adolescents had higher average excessive reassurance seeking than male adolescents.
“Interestingly, females reported higher average values of most study variables, including depressive symptoms, technology-based SCFS, frequencies of technology use, and excessive reassurance seeking.”
Quote in the paperNot a substantial claim - Findingown data
Female adolescents had higher average frequency of technology use than male adolescents.
“Interestingly, females reported higher average values of most study variables, including depressive symptoms, technology-based SCFS, frequencies of technology use, and excessive reassurance seeking.”
Quote in the paperNot a substantial claim - Findingown data
Female adolescents had higher average technology-based social comparison and feedback-seeking than male adolescents.
“Interestingly, females reported higher average values of most study variables, including depressive symptoms, technology-based SCFS, frequencies of technology use, and excessive reassurance seeking.”
Quote in the paperNot a substantial claim - Findingown data
There was a significant technology-based social comparison and feedback-seeking by popularity interaction effect on depressive symptoms, B = −0.11, p < 0.01.
“Additionally, in support of the second and third hypotheses, analyses revealed a significant technology-based SCFS × gender interaction effect (B=−0.08, p<0.05), as well as a significant technology-based SCFS × popularity effect (B=−0.11, p<0.01).”
Quote in the paperSubstantial claim - Findingown data
The 53 students who reported not using technology had lower peer-reported popularity than technology users.
“However, the 53 students who indicated that they did not use technology were more likely to be male, t (698)=3.83, p<0.001; lower in depressive symptoms, t (698)=−2.86, p=0.004; lower in ERS, t (698)=−3.51, p<0.001; and lower in peer-reported popularity t (698)=−4.60, p<0.001.”
Quote in the paperNot a substantial claim - Findingown data
Among boys, greater technology-based social comparison and feedback-seeking was associated with greater depressive symptoms, b = 0.133, p < 0.001.
“Results revealed significant slopes for both girls, b (se)=0.239 (0.03); p<0.001, and boys, b (se)=0.133 (0.04); p<0.001, indicating that greater levels of technology-based SCFS were associated with greater levels of depressive symptoms for both genders.”
Quote in the paperSubstantial claim - Findingown data
Adolescents with lower socioeconomic status had lower levels of popularity.
“Individuals lower in SES reported higher frequencies of technology use and lower levels of popularity (see Table 1).”
Quote in the paperNot a substantial claim - Findingown data
The 53 students who reported not using technology had lower depressive symptoms than technology users.
“However, the 53 students who indicated that they did not use technology were more likely to be male, t (698)=3.83, p<0.001; lower in depressive symptoms, t (698)=−2.86, p=0.004; lower in ERS, t (698)=−3.51, p<0.001; and lower in peer-reported popularity t (698)=−4.60, p<0.001.”
Quote in the paperNot a substantial claim - Findingown data
Popularity was positively associated with technology-based social comparison and feedback-seeking.
“Popularity was positively associated with frequency of technology use and technology-based SCFS; however, it was negatively associated with depressive symptoms.”
Quote in the paperNot a substantial claim - Findingown data
The association between technology-based social comparison and feedback-seeking and depressive symptoms was stronger for girls than for boys.
“The slope for girls was significantly steeper than for boys, indicating that the effect of technology-based SCFS on depressive symptoms is stronger among females (see Fig. 1).”
- Also stated in: § Discussion · plain
“In support of the third hypothesis, gender was also found to moderate the association between technology-based SCFS and depressive symptoms, with the association stronger for females.”
Quote in the paperSubstantial claim - Also stated in: § Discussion · plain
- Findingown data
In the full regression model, frequency of technology use was not associated with depressive symptoms.
“Importantly, results did not identify any overall association between frequency of technology use and depressive symptoms.”
Quote in the paperSubstantial claim - Findingown data
Female adolescents had higher average depressive symptoms than male adolescents.
“Interestingly, females reported higher average values of most study variables, including depressive symptoms, technology-based SCFS, frequencies of technology use, and excessive reassurance seeking.”
Quote in the paperNot a substantial claim - Findingown data
There was no gender difference in popularity levels.
“No gender differences were found in levels of popularity.”
Quote in the paperNot a substantial claim - Findingown data
The 53 students who reported not using technology were more likely to be male than technology users.
“However, the 53 students who indicated that they did not use technology were more likely to be male, t (698)=3.83, p<0.001; lower in depressive symptoms, t (698)=−2.86, p=0.004; lower in ERS, t (698)=−3.51, p<0.001; and lower in peer-reported popularity t (698)=−4.60, p<0.001.”
Quote in the paperNot a substantial claim - Findingown data
The positive association between technology-based social comparison and feedback-seeking and depressive symptoms was stronger for adolescents low in popularity than for those high in popularity.
“Results suggested stronger associations between technology-based SCFS and depressive symptoms for individuals low in popularity, (−1 SD), b (se)=0.329 (0.04), p<0.001, than for individuals high in popularity (+SD), b (se)=0.181 (0.03), p<0.001 (see Fig. 2).”
- Also stated in: § Discussion · hedged
“In support of the second hypothesis, findings indicated that this association might be dependent on the offline characteristic popularity, with the strongest associations between technology-based SCFS and depressive symptoms found for adolescents lower in popularity.”
Quote in the paperSubstantial claim - Also stated in: § Discussion · hedged
- Findingown data
The full regression model explained a significant proportion of variance in depressive symptoms, with R2 = 0.470 and p < 0.001.
“The full regression model explained a significant proportion of the variance in depressive symptoms, R2=0.470, p< 0.001.”
Quote in the paperNot a substantial claim - Findingown data
Among girls, greater technology-based social comparison and feedback-seeking was associated with greater depressive symptoms, b = 0.239, p < 0.001.
“Results revealed significant slopes for both girls, b (se)=0.239 (0.03); p<0.001, and boys, b (se)=0.133 (0.04); p<0.001, indicating that greater levels of technology-based SCFS were associated with greater levels of depressive symptoms for both genders.”
Quote in the paperSubstantial claim - Findingown data
The pattern of significant and non-significant effects remained the same when ethnicity and socioeconomic status were added as covariates.
“This model was further analyzed with the addition of ethnicity and SES variables as covariates. The pattern of significant and non-significant effects remained the same; thus, to present a more parsimonious model, ethnicity and SES were not included in results.”
Quote in the paperNot a substantial claim - Findingown data
The 53 students who reported not using technology had lower excessive reassurance seeking than technology users.
“However, the 53 students who indicated that they did not use technology were more likely to be male, t (698)=3.83, p<0.001; lower in depressive symptoms, t (698)=−2.86, p=0.004; lower in ERS, t (698)=−3.51, p<0.001; and lower in peer-reported popularity t (698)=−4.60, p<0.001.”
Quote in the paperNot a substantial claim - Findingown data
The association between technology-based social comparison and feedback-seeking and depressive symptoms was significant at all centered popularity values below 2.08.
“Results suggested that the association was significant at all centered values of popularity less than 2.08 (approximately two standard deviations above the mean).”
Quote in the paperSubstantial claim - Premisecitation
Depressed or depression-prone individuals may engage in social comparison and feedback-seeking in maladaptive ways that are unique depressogenic-interpersonal behaviors.
“However, depressed or depression-prone individuals may engage in these social behaviors in maladaptive ways, such that they represent unique depressogenic-interpersonal behaviors (Hames et al. 2013).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hames et al. 2013 source
- Premisecitation
Technology-based media may facilitate technology-based social comparison and feedback-seeking.
“In fact, these media may facilitate certain technology-based behaviors, or behaviors that occur as a result of, or in conjunction with, technology use, such as technology-based social comparison and feedback-seeking (SCFS; Manago et al. 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Manago et al. 2008 source
- Premisecitation
Correspondence bias may lead adolescents to assume that others' photos and text reflect stable personality traits rather than situational factors when forming impressions of people they do not know well offline.
“Thus, in forming impressions of individuals that they do not know well offline, correspondence bias (Gilbert and Malone 1995) may lead adolescents to assume that others’ photos and text reflect stable personality traits, rather than situational factors.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Gilbert and Malone 1995 source
- Rests on an assumption: Many of an adolescent's online connections are only casual acquaintances in offline life.
- Study design and conductown data
Mean levels of depressive symptoms were very low in the current analyses.
“It should also be noted that, as is typical in school-based samples, mean levels of depressive symptoms were very low in the current analyses.”
Quote in the paperSubstantial claim - Premisecitation
Girls are more likely to prioritize and compare themselves on physical attractiveness online.
“Furthermore, girls are more likely to prioritize and compare themselves on dimensions of physical attractiveness online (Haferkamp and Krämer 2011; Jones 2001).”
Quote in the paperNot a substantial claim0 of 2 sources checked - Premisecitation
Established interpersonal theories of depression indicate that the link between interpersonal stressors and depressive symptoms may be particularly strong for girls.
“Furthermore, established interpersonal theories of depression show that the link between interpersonal stressors and depressive symptoms may be particularly strong for girls (Rudolph 2002); thus, insofar as technology-based SCFS present a source of interpersonal stress for girls, these behaviors are likely to be associated with depressive symptoms.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Rudolph 2002 source
- Interpretationreasoning
The tendency of depressed individuals to prefer comparisons with equal or less fortunate others may explain why depression and technology-based social comparison and feedback-seeking are associated.
“This may explain why depression and technology-based SCFS are significantly associated.”
Quote in the paperSubstantial claim- Rests on an assumption: Depressed people tend to prefer comparisons with others they see as equal or worse off.
- Interpretationcitation
Because online and offline networks overlap substantially, adolescents who are unpopular offline likely have fewer online friends.
“Additionally, given the substantial overlap between online and offline networks (Reich et al. 2012), it is likely that adolescents who are unpopular offline have fewer online friends.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Reich et al. 2012 source
- Interpretationreasoning
Downward comparisons may be especially difficult for adolescents low in popularity.
“Downward comparisons may be especially challenging for adolescent low in popularity.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Selective self-presentation online may increase the likelihood that adolescents encounter and recall distorted positive perceptions of peers' lives.
“The tendency for selective self-presentation online may increase the probability that adolescents encounter, and thus recall, distorted positive perceptions of their peers’ lives.”
Quote in the paperSubstantial claim - Study design and conductown data
The MEIS-SCFS subscale had high internal consistency (alpha = 0.92).
“The scale showed good internal consistency (Cronbach’s alpha 0.92).”
Quote in the paperNot a substantial claim - Study design and conductreasoning
The statistical controls in the model allowed examination of effects over and above prior depressive symptoms.
“Although statistical controls in the model allowed for examination of effects over and above those of prior depressive symptoms, further work is needed to rigorously assess temporal relationships between study variables, perhaps testing for the presence of transactional effects between depressive symptoms and technology-based behaviors (Valkenburg and Peter 2013).”
Quote in the paperNot a substantial claim - Study design and conductreasoning
The study could not fully assess differences in outcomes by ethnicity or socioeconomic status.
“A final limitation of the current study was the inability to fully assess differences in outcomes by ethnicity or SES.”
Quote in the paperNot a substantial claim - Interpretationown data
The results may not generalize to a clinical sample.
“Thus, although providing preliminary insight into these effects within a community setting, results may not generalize to a clinical sample.”
Quote in the paperSubstantial claim
- May combine two claims. 36
- Classified as probably not a substantial claim. 38
- The quote only partly states this claim. 1
May combine two claims.
PremisecitationSeveral studies report no link between how often technology is used and either general well-being or depressive symptoms.
“Importantly, a number of studies have found no association between frequency of technology use and general well being (Gross 2004), nor between frequency of technology use and depressive symptoms (Davila et al. 2012; Jelenchick et al. 2013), further highlighting the inconclusive nature of attempts to characterize overall associations between technology use and psychological outcomes.”
Quote in the paperSubstantial claim1 of 3 sources checkedClassified as probably not a substantial claim.
PremisecitationThe quality of peer interactions or behaviors occurring via SNS, rather than the quantity of SNS usage, may longitudinally influence depressive symptoms.
“In fact, it may not be the quantity of social networking site usage that longitudinally influences depressive symptoms, but rather the positive or negative quality of peer interactions or behaviors that occur via these technologies (Davila et al. 2012).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Davila et al. 2012 source
May combine two claims.
PremisecitationMaladaptive technology-based behaviors may be associated with negative online peer feedback, increased loneliness, and depressive symptoms, potentially influencing future technology use cyclically.
“Maladaptive technology-based behaviors, in turn, may be associated with negative online peer feedback, as well as increases in loneliness and depressive symptoms (Burke et al. 2010; Forest and Wood 2012; Selfhout et al. 2009), which may influence future technology use in a cyclical fashion.”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Burke et al. 2010 source
The Discussion (p. 4) links greater consumption of friends’ content with loneliness and leaves open whether loneliness leads to more clicking or vice versa. It does not establish a cyclical effect, and the paper does not link these behaviors to negative online peer feedback or increased depressive symptoms. (LLM, conf=0.87)
Experimental — accuracy not yet measured - cites Forest and Wood 2012 source
- cites Selfhout et al. 2009 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationFrequent SNS use may be associated with negative outcomes including depressive symptoms, short-term declines in subjective well-being, romantic jealousy, and the belief that others are happier.
“For example, frequent use of social networking sites may be associated with depressive symptoms (van den Eijnden et al. 2008), short-term declines in subjective well-being (Kross et al. 2013), romantic jealousy (Muise et al. 2009), and the belief that others are happier and living better lives than one’s self (Chou and Edge 2012).”
Quote in the paperNot a substantial claim1 of 3 sources checkedClassified as probably not a substantial claim.
InterpretationcitationOnline, girls may be drawn to comparisons that are more self-relevant and therefore more threatening to self-worth.
“Given the emphasis on photo sharing in today’s popular social networking tools (i.e., Facebook, Instagram), as well as the increased likelihood that girls will post photos compared to boys, it may be that online, girls are drawn to comparisons that are more self-relevant, and thus more threatening to self-worth (Stefanone et al. 2011).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Stefanone et al. 2011 source
The Discussion (page unavailable) reports that female participants shared more photos and identified more strongly with appearance-based self-worth; it also discusses appearance threats. The paper does not establish that girls are drawn to more self-relevant online comparisons or that such comparisons threaten their self-worth. That proposed link goes beyond the study's findings. (LLM, conf=0.85)
Experimental — accuracy not yet measured
- Rests on an assumption: Adolescent girls are more likely than boys to post photos online.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe SMFQ is psychometrically sound and commonly used to measure depressive symptoms in adolescents.
“The SMFQ has good psychometric properties (Sharp et al. 2006) and has been widely used to assess depressive symptoms in adolescent samples (e.g., Rothon et al. 2009).”
Quote in the paperNot a substantial claim1 of 2 sources checkedClassified as probably not a substantial claim. May combine two claims.
Study design and conductcitationA factor analysis of the MEIS produced one 10-item factor for technology-based social comparison and feedback-seeking, plus separate factors for general communication, social support seeking, and sexual health discussions.
“Factor analysis revealed a single 10-item factor indicating engagement in social comparison and feedback-seeking behaviors using technology, as well as other factors relating to the use of technology for general communication with romantic partners, social support seeking, and discussions about sexual health topics (Widman et al. 2014).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Widman et al. 2014 source
The Methods section describes questions about six sexual-health topics discussed with dating partners, and the Results report how often adolescents discussed them. Our copy does not report a MEIS factor analysis, a 10-item social-comparison and feedback-seeking factor, or factors for general communication and social support seeking (searched: MEIS, factor analysis, and the named factors). No page numbers were available in the indexed passages. (LLM, conf=0.76)
Experimental — accuracy not yet measured
Classified as probably not a substantial claim. May combine two claims.
PremisecitationThe link between reassurance-seeking and depressive symptoms may be especially strong for adolescent girls and may also appear in online settings.
“Furthermore, associations between reassurance-seeking behaviors and depressive symptoms may be particularly strong among adolescent girls, for whom rates of depression are higher in general (Starr and Davila 2008), and given known situational continuities between online and offline contexts (Mikami et al. 2010), this effect may occur online, as well.”
Quote in the paperSubstantial claim1 of 2 sources checkedMay combine two claims.
PremisecitationIndividuals lower in popularity and self-esteem receive less positive feedback on social networking profiles and post updates that are more negative and less positive.
“Prior research suggests that individuals lower in popularity and self-esteem receive less positive feedback on their social networking profiles (Mikami et al. 2010) and post updates that are higher in negativity and lower in positivity (Forest and Wood 2012).”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Mikami et al. 2010 source
The Results (Longitudinal Associations; page unavailable) report that higher peer sociometric status at ages 13–14 predicted more friends posting supportive comments on participants’ web pages, supporting the popularity portion of the clause attributed to Mikami et al. Our copy does not report the same finding for self-esteem. The claim about the positivity of participants’ own updates is cited to Forest and Wood, not Mikami et al., and is not part of this verdict. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites Forest and Wood 2012 source
Classified as probably not a substantial claim. May combine two claims.
PremisecitationAdolescents who are popular and have higher self-esteem may make fewer upward comparisons, feel less negative after comparisons, and receive more positive peer feedback.
“Popular adolescents, who are higher in self-esteem (Babad 2001), may engage in fewer upward comparisons, experience less negative affect as a result of these comparisons, and receive more positive feedback from peers (Mikami et al. 2010).”
Quote in the paperSubstantial claim1 of 2 sources checked- cites Babad 2001 source
- cites Mikami et al. 2010 source
The Results (Longitudinal Associations Between Early Adolescent Adjustment and Web Page Indicators; page unavailable) report that higher peer status at ages 13–14 predicted more friends posting supportive comments on participants’ social-networking pages at ages 20–22. This supports the positive-feedback portion in that specific setting, but the paper does not address upward comparisons or negative affect resulting from them. The self-esteem assertion is separately attributed to Babad (2001). (LLM, conf=0.87)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationGirls may more often compare their physical attractiveness using online photos, which could make those images more personally relevant and threatening to self-worth.
“In terms of gender, females may be more likely to compare themselves on dimensions of physical attractiveness based on online photos (Haferkamp and Krämer 2011), perhaps making such photos more self-relevant and threatening to self-worth (Stefanone et al. 2011).”
Quote in the paperNot a substantial claim1 of 2 sources checkedThe quote only partly states this claim.
Findingown dataAdolescents who engaged more in technology-based social comparison and feedback-seeking had higher levels of depressive symptoms.
“Consistent with hypotheses, technology-based social comparison and feedback-seeking were associated with depressive symptoms.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThere were no differences in depression levels between racial/ethnic groups.
“No differences were found in levels of depression between racial/ethnic groups.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataDepressive symptoms had a positive bivariate correlation with concurrent technology use frequency, but this association was not significant in the full regression model.
“Interestingly, although depressive symptoms were positively correlated with concurrent technology use frequency, this association was no longer significant after accounting for other variables in the full regression model, as discussed below.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataAdolescents with lower socioeconomic status reported higher frequencies of technology use.
“Individuals lower in SES reported higher frequencies of technology use and lower levels of popularity (see Table 1).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataTechnology users and non-users did not differ in socioeconomic status or ethnicity.
“No differences emerged between users and non-users of technology in terms of SES or ethnicity.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAdolescents typically increase social comparison and interpersonal feedback-seeking as they develop cohesive self-identities.
“For example, as adolescents move toward developing cohesive self-identities, they typically engage in greater levels of social comparison and interpersonal feedback-seeking (Harter 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Harter 2012
Probably not a substantial claim: may not pass S2 (checkable).
PremisecitationScholars recommend studying particular online behaviors and offline traits to clarify how frequent technology use relates to psychological adjustment.
“As such, researchers have suggested the need to examine specific technology-based behaviors, as well as individual, offline characteristics, that may help explain associations between psychological adjustment and frequent technology use (Bessière et al. 2008; Valkenburg and Peter 2013).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Bessière et al. 2008 source
- cites Valkenburg and Peter 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
PremisecitationAdolescents' use of SNS features allows them to receive constant peer feedback and to engage in online social comparison.
“Thus, adolescents use the features of SNS to both create and consume online content, including profiles, photos, and posts. This allows adolescents to receive constant feedback from their peers and to engage in social comparison processes with them online (Manago et al. 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Manago et al. 2008 source
May combine two claims.
PremisecitationAdolescents' selective self-presentation online heightens self-focus, increasing feedback-seeking and social comparison, perhaps especially upward comparisons.
“As adolescents use selective self-presentation strategies to portray themselves online in an ideal manner (Chou and Edge 2012; Gonzales and Hancock 2011), self-focus is heightened, increasing feedback-seeking and social comparison (Manago et al. 2008), perhaps especially upward comparisons, or comparisons with those believed to be of higher status than the self.”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationUnfavorable comparisons on Facebook may relate to reduced life satisfaction, more rumination, and depressive symptoms.
“Furthermore, preliminary findings suggest that negative social comparison on Facebook may be associated with lower life satisfaction (Krasnova et al. 2013), as well as increased rumination and depressive symptoms (Feinstein et al. 2013).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationDigital media have shifted many social interactions from private settings into public view, fostering online commentary and performance.
“Modern technologies have transferred many social relations from the private to public sphere (Subrahmanyam and Greenfield 2008), creating an atmosphere of public commentary and performance online.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Subrahmanyam and Greenfield 2008 source
Classified as probably not a substantial claim.
PremisecitationInterpersonal models of adolescent depression emphasize cyclical links among social experiences, depressogenic interpersonal behaviors, and depressive symptoms.
“Interpersonal models of depression in adolescents emphasize the cyclical associations among social experiences, depressogenic interpersonal behaviors, and depressive symptoms (Hames et al. 2013).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hames et al. 2013 source
May combine two claims.
PremisecitationModern technologies may enable social comparison and feedback-seeking, behaviors often viewed as depressogenic interpersonal patterns.
“Interpersonal feedback-seeking and social comparison, which have often been conceptualized as depressogenic interpersonal behaviors (e.g., Borelli and Prinstein 2006), may actually be facilitated by modern technologies.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Borelli and Prinstein 2006 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationA recent narrative review indicates that online technologies are associated with both positive outcomes (self-esteem, social support, self-disclosure) and negative outcomes (social isolation, depression, cyber-bullying).
“A recent narrative review reflects these mixed results, indicating associations between online technologies and positive outcomes such as self-esteem, social support, and self-disclosure, as well as negative outcomes, such as social isolation, depression, and cyber-bullying (Best et al. 2014).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Best et al. 2014 source
Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing).
PremisecitationMore frequent technology use may relate to better adjustment, such as greater self-disclosure and friendship quality.
“Other studies have indicated the opposite: that frequent technology use may be associated with positive adjustment, including increases in self-disclosure and friendship quality (Valkenburg and Peter 2009).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Valkenburg and Peter 2009 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationSocial comparison and feedback-seeking are important to adolescent identity construction, as adolescents seek normative standards and engage in reflected appraisal.
“These behaviors are important to adolescent identity construction processes, as adolescents seek to ascertain normative standards of behavior and engage in reflected appraisal (i.e. evaluation of the self based on perceived opinions of others; Harter et al. 1996).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Harter et al. 1996
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationA criticism of the original RSS is that it has only four items and is not developmentally sensitive.
“One critique of the original RSS is that it is very brief (four items), and that it lacks developmental sensitivity (Starr and Davila 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Starr and Davila 2008 source
May combine two claims.
PremisecitationPositive feedback on social networking sites enhances adolescents' self-esteem, while negative feedback decreases it.
“While positive feedback on SNS has been found to enhance adolescents’ self-esteem, negative feedback has been found to decrease self-esteem (Valkenburg et al. 2006).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Valkenburg et al. 2006 source
May combine two claims.
InterpretationcitationUnpopular adolescents may be more likely both to post or send negative content and to receive negative feedback.
“Thus, it may be that unpopular adolescents are not only more likely to post or send negative content, but also to receive negative feedback.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataResults were similar whether outliers were removed or Winsorised.
“The pattern of results was consistent in both treatments of outliers; thus, results for the analysis in which outliers were deleted are reported here.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductnone givenThe study relied on self-report measures, which are subject to recall and other biases.
“Another limitation of this study is its reliance on self-report measures, which are subject to recall and other biases.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataSample socioeconomic status averaged the same as the town's average household income.
“The mean SES for this sample was identical to the average household income for the town in which the data were collected, according to census data.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataIn this sample, the SMFQ showed high internal consistency (alpha = 0.94).
“The current sample yielded good internal consistency (Cronbach’s alpha 0.94).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPeer nomination methods are widely regarded as the most reliable and valid way to measure adolescent popularity.
“Sociometric nomination procedures are largely considered the most reliable and valid indices of adolescents’ popularity among peers (Coie et al. 1983).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Coie et al. 1983 source
May combine two claims.
InterpretationcitationAdolescents may be especially likely to engage in technology-based social comparison and feedback-seeking and may be vulnerable to negative comparisons with peers.
“Given that young people spend the majority of their time on SNS looking at peers’ profiles and photos, rather than posting or updating their own profiles (Pempek et al. 2009), adolescents may be especially likely to engage in technology-based SCFS and may be vulnerable to negative comparisons with their peers.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Pempek et al. 2009 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataNinety percent of the original 868 students took part in the follow-up (n = 779).
“Of the original sample of 868, 90% of students participated (n=779).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationFrequent technology users may use heuristics that lead them to believe life is unfair and that others are happier and live better lives.
“Chou and Edge (2012) suggest that frequent users of technology employ certain heuristics that lead them to believe that “life is not fair” and “others are happier and living better lives.””
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Chou and Edge (2012) source
May combine two claims.
PremisecitationThe original RSS has demonstrated sound psychometric properties and prior use in adolescent depression research.
“The original RSS has been shown to have good psychometric properties (Joiner and Metalsky 2001) and has been used to assess depressive symptoms in adolescent samples (e.g., Prinstein et al. 2005).”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe online environment may facilitate higher levels of social comparison and feedback-seeking.
“First, it may be that the online environment facilitates higher levels of SCFS.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationAdolescents who engage in technology-based social comparison and feedback-seeking may develop distorted perceptions of peers, leading to harmful upward comparisons, doubt about positive feedback, and decreases in mood or self-esteem.
“Second, adolescents engaging in technology-based SCFS may form distorted perceptions of their peers, leading them to engage in harmful upward comparisons, or to doubt the sincerity of positive feedback that is sought online, and experience decreases in mood or self-esteem.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationcitationDepressive symptoms may precede and predict technology-based social comparison and feedback-seeking.
“Third, it may be that depressive symptoms precede and predict technology-based SCFS.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationInterpersonal theories of depression suggest that depressed and depression-prone individuals engage in higher levels of social comparison and feedback-seeking in offline social worlds.
“Interpersonal theories of depression similarly suggest that within offline social worlds, depressed and depression-prone individuals are more likely to engage in overall higher levels of social comparison (Gibbons and Buunk 1999) and feedback-seeking behaviors (Hames et al. 2013).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
InterpretationreasoningIn an online hyperpersonal environment where peers selectively show positive aspects of their lives, depressed individuals may be unable to make downward comparisons and may experience worsening symptoms in light of others' perceived happiness.
“Unfortunately, within a computer-mediated, hyperpersonal environment in which peers selectively portray the most positive aspects of their lives, however, these downward comparisons may not be possible. In an online world where users portray themselves in an ideal manner, depressed individuals may be stymied in their efforts to seek out negative information about others, potentially experiencing a”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningWhen seeking feedback from peers, unpopular adolescents may obtain self-relevant information that harms self-esteem and is related to increases in depressive symptoms.
“In seeking out feedback from peers, unpopular adolescents may actually be garnering self-relevant information that is harmful to their self-esteem and related to increases in depressive symptoms.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationDepressed and dysthymic individuals may be motivated to seek negative information about others.
“Some research suggests that depressed and dysthymic individuals may be motivated to seek out negative information about others (Wenzlaff and Beevers 1998).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Wenzlaff and Beevers 1998 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAdolescent girls are more likely than boys to experience depressive symptoms as a result of offline reassurance-seeking behaviors.
“Prior work has indicated important differences between adolescent girls and boys that may be relevant to an online context, with girls more likely experience depressive symptoms as the result of reassurance-seeking behaviors offline (Prinstein et al. 2005).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Prinstein et al. 2005 source
May combine two claims.
Interpretationown dataTechnology-based social comparison and feedback-seeking may be associated with depressive symptoms for most adolescents, with stronger associations for those lower in popularity.
“This indicates that technology-based SCFS may be associated with depressive symptoms for the majority of individuals, but with stronger associations for those lower in popularity.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe demographic profile of the sample was very similar to that of the school district where recruitment occurred.
“This sample closely matched the demographic makeup of the district from which participants were recruited.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningLower-status adolescents may perceive smaller audiences for their posted content when seeking feedback online, leading to decreased peer support and life satisfaction.
“Thus, it may be that, when seeking feedback online, lower status adolescents perceive smaller audience sizes for their posted content, resulting in feelings of decreased peer support and overall life satisfaction.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAccording to the availability heuristic, young people who frequently use technology may more easily recall online information when forming impressions of others.
“For example, according to the availability heuristic (Tversky and Kahneman 1973), young people who frequently engage with technology may more easily recall information encountered online when forming impressions of others.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Tversky and Kahneman 1973 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningFor half the participants chosen at random, the roster's alphabetical order was reversed to prevent order effects.
“Alphabetization of the roster was reversed for a random half of the participants in order to control for order effects in participants’ selection of names.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataStudents excluded from analysis were disproportionately male and African American, according to attrition tests.
“Attrition analyses indicated that excluded students were, on average, more likely to be male, t (775)=3.13, p=0.002, and African American, χ2(3)=24.77, p<0.001.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationThe online context encourages idealized self-presentations, and people are likely to form positive assumptions about others after viewing online content.
“In other words, the online context fosters idealized self-presentations and individuals are likely to make positive assumptions about others subsequent to viewing online content.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationLarger online networks and perceived audiences predict life satisfaction and perceived social support.
“Manago et al. (2012) posit that larger online networks and perceived audiences predict life satisfaction and perceived social support.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Manago et al. (2012) source
May combine two claims.
Study design and conductown dataIn this sample, the Revised ERS scale had high internal consistency and a unifactorial structure (alpha = 0.90).
“The Revised ERS scale showed good internal consistency as a unifactorial scale in this sample (Cronbach’s alpha 0.90).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationAdolescents' reports of technology use frequency were consistent with nationally representative statistics from over 2000 students collected by the Kaiser Family Foundation.
“Adolescents’ reports of technology use frequency in the study are consistent with nationally representative statistics of over 2000 students, collected by the Kaiser Family Foundation (Rideout et al. 2010).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Rideout et al. 2010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe hyperpersonal model of computer-mediated communication holds that some features of technology-based interaction intensify identity construction by increasing feedback and decision-making.
“The hyperpersonal model of computer-mediated communication (CMC; Walther et al. 2011) suggests that certain components of technology-based interaction serve to intensify the process of identity construction through increased feedback and decision-making within these environments.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Walther et al. 2011 source
Classified as probably not a substantial claim. May combine two claims.
InterpretationcitationIf technology-based social comparison and feedback-seeking is a source of interpersonal stress for girls, then these behaviors are likely associated with depressive symptoms.
“Furthermore, established interpersonal theories of depression show that the link between interpersonal stressors and depressive symptoms may be particularly strong for girls (Rudolph 2002); thus, insofar as technology-based SCFS present a source of interpersonal stress for girls, these behaviors are likely to be associated with depressive symptoms.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe use of census tract data provides only a rough estimate of families' true socioeconomic status.
“Additionally, the use of census tract data provides only a rough estimate of families’ true SES; more sensitive measures of SES should be used in future studies.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningCell sizes may have been too small to examine potential interaction effects by ethnicity.
“Although the study’s large and diverse sample provided the opportunity to examine effects across different ethnicities, it is possible that cell sizes were too small to examine potential interaction effects.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
The literature has limited knowledge about adolescents' social experiences via technological media.
“Although much research has investigated the interactions among these social behaviors, depressive symptoms, and in-person peer interactions in this age group, relatively little is known regarding social experiences that occur through technological media, including Social Networking Sites (SNS, e.g., Facebook) and text messages.”
The paper relies on this without support.
For some adolescents, greater technology use may go along with more social comparison and feedback-seeking.
“However, high levels of technology use may be associated with increased levels of these behaviors among some adolescents.”
The paper relies on this without support.
Whether gender and popularity differences appear in online settings has not been rigorously tested.
“However, the possibility that gender and popularity differences may occur within online contexts has not yet been rigorously examined.”
The paper relies on this without support.
The original ERS scale is not detailed; it only measures how often people seek reassurance that others like and care about them.
“Another criticism of the original ERS scale is that it lacks detail, simply assessing how often individuals request assurance that others like and care for them.”
The paper relies on this without support.
SNS features produce an online social environment that differs fundamentally from offline social life.
“These features create an online social world that is fundamentally different than its offline counterpart.”
The paper relies on this without support.
Self-report measures are commonly used in prior research on technology-use frequency.
“Self-report measures have been widely used in previous studies assessing frequency of technology use.”
The paper relies on this without support.
Many of an adolescent's online connections are only casual acquaintances in offline life.
“Furthermore, given the very large size of a typical adolescent’s online social network, it is likely that many online connections are mere acquaintances offline.”
The paper relies on this without support.
Adolescent girls are more likely than boys to post photos online.
“as well as the increased likelihood that girls will post photos compared to boys”
The paper relies on this without support.
Depressed people tend to prefer comparisons with others they see as equal or worse off.
“In doing so, depressed individuals may prefer to compare themselves to others perceived to be equal to or less fortunate than them.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Almost a third of all social media users are adolescents and young adults, while 93-97% of all teenagers aged 13 to 17 use at least one form of social media.
“Studies have shown that almost a third of all social media users are adolescents and young adults, while 93-97% of all teenagers aged 13 to 17 years use at least one form of social media [2,3].”
From Social Media Algorithms and Teen Addiction: Neurophysiological Impact and Ethical Considerations (2025) · cites this paper as [3]
In “Adolescents’ Online Social World” (page unavailable), the paper says over 93% of American teenagers aged 12–17 are connected to the Internet, but estimates that 73% belong to at least one social networking site. The claim appears to treat the Internet figure as a social-media-use figure; the paper also gives no estimate that adolescents and young adults make up almost a third of social media users. (LLM, conf=0.82)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredMany teens tie their self-worth to the number of likes, comments, and followers they receive.
“Many teens, both boys and girls, tie their self-worth to the number of likes, comments, and followers they receive [45].”
From The Impact of Social Media & Technology on Child and Adolescent Mental Health (2025) · cites this paper as [45]
The Discussion (Effects of Popularity; page not provided) links online feedback to adolescents’ self-esteem, and the Methods (Technology-Based Social Comparison and Feedback-Seeking; page not provided) measures seeking others’ opinions online. The paper does not establish that many teens of both genders tie their self-worth specifically to counts of likes, comments, and followers. (LLM, conf=0.86)
Experimental — accuracy not yet measuredFemale-identifying individuals, especially adolescent females, are at increased risk of experiencing detrimental mental health outcomes associated with PSMU.
“Importantly, female-identifying individuals, especially adolescent fe males, are at an increased risk of experiencing detrimental mental health outcomes associated with PSMU (Ahmed et al., 2024; Nesi & Prinstein, 2015).”
From Problematic social media use and inhibitory control among post-secondary students (2025) · cites this paper as Nesi & Prinstein, 2015
The Abstract and Discussion > Effects of Gender report that the association between technology-based social comparison and feedback-seeking and depressive symptoms was particularly strong among adolescent females. The study does not establish increased risk for female-identifying individuals generally, for mental health outcomes beyond depressive symptoms, or for problematic social media use broadly; the Discussion also reports no overall association between frequency of technology use and depressive symptoms. (LLM, conf=0.86)
Experimental — accuracy not yet measuredResearch has highlighted differences between males and females in the links between social media use and well-being in adolescence in a small subset of the analyzed data or other datasets.
“Research has highlighted differences between males and females in the links between social media use and well-being in adolescence in a small subset of the analyzed data28, or other datasets10,29–33.”
From Windows of developmental sensitivity to social media (2022) · cites this paper as [30]
It is not the quantity of social networking site usage per se that is associated with depressive symptoms, but rather the negative quality of peer interactions such as social comparison and feedback-seeking.
“it was not the quantity of social networking site usage per se that was associated with depressive symptoms, but rather the negative quality of peer interactions such as social comparison and feedback-seeking (Nesi and Prinstein, 2015).”
From Social functioning in major depressive disorder (2016) · cites this paper as Nesi and Prinstein, 2015
Use of social media for the purpose of social comparison and feedback seeking, and passive rather than active use of social media, have been shown to be associated with higher subsequent depressive symptoms among adolescents.
“Furthermore, the use of social media for the purpose of social comparison and feedback seeking (Nesi & Prinstein, 2015), and passive, rather than active use of social media (Frison & Eggermont, 2016;Thorisdottir, Sigurvinsdottir, Asgeirsdottir, Allegrante, & Sigfusdottir, 2019) have been shown to be associated with higher subsequent depressive symptoms among adolescents.”
From The relationship between screen time and mental health in young people: A systematic review of longitudinal studies (2021) · cites this paper as Nesi & Prinstein, 2015
Statistics recomputed
Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.
- Consistentt(775) = 3.13reported p = .002 · recomputed p = .002
“t (775)=3.13, p = .002”
- Consistentχ²(3) = 24.77reported p < .001 · recomputed p < .001
“χ2(3)=24.77, p < .001”
- Consistentt(698) = 3.83reported p < .001 · recomputed p < .001
“t (698)=3.83, p < .001”
- Consistentt(698) = -2.86reported p = .004 · recomputed p = .004
“t (698)=−2.86, p = .004”
- Consistentt(698) = -3.51reported p < .001 · recomputed p < .001
“t (698)=−3.51, p < .001”
- Consistentt(698) = -4.6reported p < .001 · recomputed p < .001
“t (698)=−4.60, p < .001”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Not every measure was self-reported
MinorThe methods describe all measures as self-reported, but popularity was measured through other students' nominations rather than each participant's report about themselves.
“All measures were self-reported and administered to students in classrooms during the school day using computer-assisted self-interviews (CASI).”
“Sociometric nomination procedures were used to measure peer-reported popularity (Coie et al. 1983).”
Cites
Multiple regression: testing and interpreting interactions
(1992) · Choice Reviews Online · doi:10.5860/choice.29-3352 · Cited by 36,644 · see citing works
Multiple Regression: Testing and Interpreting Interactions
Aiken, L., West, S. G., & Reno, R. R. (1991) · Oxford University Press eBooks · doi:10.1037/10520-147 · Cited by 24,912 · see citing works
Availability: A heuristic for judging frequency and probability
Tversky, A., & Kahneman, D. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90033-9 · Cited by 9,984 · cited 1× · see citing works
“^ For example, according to the availability heuristic (Tversky and Kahneman 1973), young people who frequently engage with technology may more easily recall information encountered online when forming impressions of others.”
(1991) · Cited by 7,187 · see citing works
Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986031004437 · Cited by 5,044 · cited 1× · see citing works
“Interactions were probed following procedures outlined by Aiken andWest (1991) and using interaction utilities provided by Preacher et al. (2006).”
Dimensions and types of social status: A cross-age perspective.
Coie, J. D., Dodge, K. A., & Coppotelli, H. (1982) · Developmental Psychology · doi:10.1037/0012-1649.18.4.557 · Cited by 2,452 · cited 2× · see citing works
“Sociometric nomination procedures are largely considered the most reliable and valid indices of adolescents’ popularity among peers (Coie et al. 1983).”
Kraut, R. E., Kiesler, S. B., Boneva, B. S., Cummings, J. N., Helgeson, V. S., & Crawford, A. M. (2002) · Journal of Social Issues · doi:10.1111/1540-4560.00248 · Cited by 2,254 · cited 1× · see citing works
“Researchers have called for a more nuanced understanding of the specific online behaviors and pre-existing individual characteristics that may influence these associations (Bessière et al. 2008; Davila et al. 2012; Kraut et al. 2002; Valkenburg and Peter 2013).”
Generation M2: Media in the Lives of 8- to 18-Year-Olds
Foehr, U. G., Rideout, V. J., & Roberts, D. F. (2010) · Cited by 2,197 · see citing works
College students' social networking experiences on Facebook
Pempek, T. A., Yermolayeva, Y. A., & Calvert, S. L. (2009) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2008.12.010 · Cited by 2,081 · cited 1× · see citing works
“…that young people spend the majority of their time on SNS looking at peers’ profiles and photos, rather than posting or updating their own profiles (Pempek et al. 2009), adolescents may be especially likely to engage in technology-based SCFS and may be vulnerable to negative comparisons with…”
Gilbert, D. T., & Malone, P. S. (1995) · Psychological Bulletin · doi:10.1037/0033-2909.117.1.21 · Cited by 1,897 · cited 1× · see citing works
“Thus, in forming impressions of individuals that they do not know well offline, correspondence bias (Gilbert and Malone 1995) may lead adolescents to assume that others’ photos and text reflect stable personality traits, rather than situational factors.”
(1995) · International Journal of Methods in Psychiatric Research · Cited by 1,847 · see citing works
Holmbeck, G. N. (2002) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/27.1.87 · Cited by 1,819 · cited 1× · see citing works
“First, models were reduced by removing covariates and non-significant interaction terms (Holmbeck 2002).”
Gibbons, F. X., & Buunk, B. P. (1999) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.76.1.129 · Cited by 1,813 · cited 2× · see citing works
“Interpersonal theories of depression similarly suggest that within offline social worlds, depressed and depression-prone individuals are more likely to engage in overall higher levels of social comparison (Gibbons and Buunk 1999) and feedback-seeking behaviors (Hames et al. 2013).”
Facebook Use Predicts Declines in Subjective Well-Being in Young Adults
Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., Shablack, H., Jonides, J., & Ybarra, O. (2013) · PLoS ONE · doi:10.1371/journal.pone.0069841 · Cited by 1,596 · cited 2× · see citing works
“…of social networking sites may be associated with depressive symptoms (van den Eijnden et al. 2008), short-term declines in subjective well-being (Kross et al. 2013), romantic jealousy (Muise et al. 2009), and the belief that others are happier and living better lives than one’s self (Chou and…”
Friend networking sites and their relationship to adolescents’ well-being and social self-esteem
Valkenburg, P. M., Peter, J., & Schouten, A. P. (2006) · CyberPsychology & Behavior · doi:10.1089/cpb.2006.9.584 · Cited by 1,531 · cited 1× · see citing works
“While positive feedback on SNS has been found to enhance adolescents’ self-esteem, negative feedback has been found to decrease self-esteem (Valkenburg et al. 2006).”
Probing interactions in fixed and multilevel regression: Inferential and graphical techniques
Bauer, D. J., & Curran, P. J. (2005) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr4003_5 · Cited by 1,506 · cited 1× · see citing works
“To further explore this effect, the Johnson-Neyman (J-N) technique was used to identify the region of significance (Bauer and Curran 2005), that is, the values of popularity for which technology-based SCFS had a significant effect on depressive symptoms.”
International Journal of Methods in Psychiatric Research
Bhugra, D., Bhui, K. S., Desai, M., Singh, J., & Baldwin, D. (2006) · International Journal of Methods in Psychiatric Research · doi:10.1002/(issn)1557-0657 · Cited by 1,492 · see citing works
Journal of Research on Adolescence
(2010) · Journal of Research on Adolescence · doi:10.1111/(issn)1532-7795 · Cited by 1,274 · see citing works
Handbook of Developmental Psychopathology
Lewis, M., & Rudolph, K. D. (2014) · Springer eBooks · doi:10.1007/978-1-4614-9608-3 · Cited by 1,259 · see citing works
Chou, H.-T. G., & Edge, N. (2012) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2011.0324 · Cited by 1,166 · cited 3× · see citing works
“…networking sites may be associated with depressive symptoms (van den Eijnden et al. 2008), short-term declines in subjective well-being (Kross et al. 2013), romantic jealousy (Muise et al. 2009), and the belief that others are happier and living better lives than one’s self (Chou and Edge 2012).”
Social network activity and social well-being
Burke, M., Marlow, C., & Lento, T. (2010) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1753326.1753613 · Cited by 1,109 · cited 2× · see citing works
“…decision can be found at danah.org. behaviors, in turn, may be associated with negative online peer feedback, as well as increases in loneliness and depressive symptoms (Burke et al. 2010; Forest and Wood 2012; Selfhout et al. 2009), which may influence future technology use in a cyclical fashion.”
Online communication, social media and adolescent wellbeing: A systematic narrative review
Best, P., Manktelow, R., & Taylor, B. (2014) · Children and Youth Services Review · doi:10.1016/j.childyouth.2014.03.001 · Cited by 1,067 · cited 1× · see citing works
“A recent narrative review reflects these mixed results, indicating associations between online technologies and positive outcomes such as self-esteem, social support, and self-disclosure, as well as negative outcomes, such as social isolation, depression, and cyber-bullying (Best et al. 2014).”
Mirror, Mirror on my Facebook Wall: Effects of Exposure to Facebook on Self-Esteem
Gonzales, A. L., & Hancock, J. T. (2011) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2009.0411 · Cited by 946 · cited 2× · see citing works
“As adolescents use selective selfpresentation strategies to portray themselves online in an ideal manner (Chou and Edge 2012; Gonzales and Hancock 2011), self-focus is heightened, increasing feedback-seeking and social comparison (Manago et al. 2008), perhaps especially upward comparisons, or…”
Adolescent Internet use: What we expect, what teens report
Gross, E. F. (2004) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2004.09.005 · Cited by 866 · cited 2× · see citing works
“Importantly, a number of studies have found no association between frequency of technology use and general well being (Gross 2004), nor between frequency of technology use and depressive symptoms (Davila et al.”
Online Communication and Adolescent Relationships
Subrahmanyam, K., & Greenfield, P. (2008) · The Future of Children · doi:10.1353/foc.0.0006 · Cited by 818 · cited 1× · see citing works
“Modern technologies have transferred many social relations from the private to public sphere (Subrahmanyam and Greenfield 2008), creating an atmosphere of public commentary and performance online.”
Gender differences in emotional responses to interpersonal stress during adolescence
Rudolph, K. D. (2002) · Journal of Adolescent Health · doi:10.1016/s1054-139x(01)00383-4 · Cited by 785 · cited 2× · see citing works
“Furthermore, established interpersonal theories of depression show that the link between interpersonal stressors and depressive symptoms may be particularly strong for girls (Rudolph 2002); thus, insofar as technology-based SCFS present a source of interpersonal stress for girls, these behaviors are likely to be assoc…”
The construction of the self: developmental and sociocultural foundations
(2012) · Choice Reviews Online · doi:10.5860/choice.50-1160 · Cited by 751 · cited 1× · see citing works
“For example, as adolescents move toward developing cohesive self-identities, they typically engage in greater levels of social comparison and interpersonal feedback-seeking (Harter 2012).”
Self-presentation and gender on MySpace
Manago, A. M., Graham, M. B., Greenfield, P. M., & Salimkhan, G. (2008) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2008.07.001 · Cited by 724 · cited 3× · see citing works
“This allows adolescents to receive constant feedback from their peers and to engage in social comparison processes with them online (Manago et al. 2008).”
Influential(2013) · mediaTUM (Technical University of Munich) · Cited by 701 · see citing works
Manago, A. M., Taylor, T., & Greenfield, P. M. (2012) · Developmental Psychology · doi:10.1037/a0026338 · Cited by 657 · cited 3× · see citing works
“…maintains a network of about 300 online friends (Madden et al. 2013a), meaning that behaviors on social networking sites are performed in the presence of an audience; every photo, comment, and new online friend provides details about the user to his or her public network (Manago et al. 2012).”
InfluentialForms and Functions of Adolescent Peer Aggression Associated With High Levels of Peer Status
Prinstein, M. J., & Cillessen, A. H. N. (2003) · Merrill-palmer Quarterly · doi:10.1353/mpq.2003.0015 · Cited by 594 · cited 2× · see citing works
“These differences scores were then re-standardized to create a measure of popularity, where higher scores indicated higher levels of popularity (Prinstein and Cillessen 2003).”
Self-citationMore information than you ever wanted: Does Facebook bring out the green-eyed monster of jealousy?
Muise, A., Christofides, E., & Desmarais, S. (2009) · CyberPsychology & Behavior · doi:10.1089/cpb.2008.0263 · Cited by 573 · cited 2× · see citing works
“…networking sites may be associated with depressive symptoms (van den Eijnden et al. 2008), short-term declines in subjective well-being (Kross et al. 2013), romantic jealousy (Muise et al. 2009), and the belief that others are happier and living better lives than one’s self (Chou and Edge 2012).”
van den Eijnden, R. J. J. M., Meerkerk, G.-J., Vermulst, A. A., Spijkerman, R., & Engels, R. C. M. E. (2008) · Developmental Psychology · doi:10.1037/0012-1649.44.3.655 · Cited by 562 · cited 1× · see citing works
“For example, frequent use of social networking sites may be associated with depressive symptoms (van den Eijnden et al. 2008), short-term declines in subjective well-being (Kross et al. 2013), romantic jealousy (Muise et al. 2009), and the belief that others are happier and living better lives than…”
Forest, A. L., & Wood, J. V. (2012) · Psychological Science · doi:10.1177/0956797611429709 · Cited by 547 · cited 4× · see citing works
“…decision can be found at danah.org. behaviors, in turn, may be associated with negative online peer feedback, as well as increases in loneliness and depressive symptoms (Burke et al. 2010; Forest and Wood 2012; Selfhout et al. 2009), which may influence future technology use in a cyclical fashion.”
InfluentialNegative social comparison on Facebook and depressive symptoms: Rumination as a mechanism.
Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013) · Psychology of Popular Media Culture · doi:10.1037/a0033111 · Cited by 500 · cited 2× · see citing works
“2013), as well as increased rumination and depressive symptoms (Feinstein et al. 2013).”
Interpersonal Processes in Depression
Hames, J. L., Hagan, C. R., & Joiner, T. E. (2013) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-050212-185553 · Cited by 499 · cited 4× · see citing works
“Interpersonal theories of depression similarly suggest that within offline social worlds, depressed and depression-prone individuals are more likely to engage in overall higher levels of social comparison (Gibbons and Buunk 1999) and feedback-seeking behaviors (Hames et al. 2013).”
InfluentialJones, D. C. (2001) · Sex Roles · doi:10.1023/a:1014815725852 · Cited by 467 · cited 1× · see citing works
“Furthermore, girls are more likely to prioritize and compare themselves on dimensions of physical attractiveness online (Haferkamp and Krämer 2011; Jones 2001).”
Social Comparison 2.0: Examining the Effects of Online Profiles on Social-Networking Sites
Haferkamp, N., & Krämer, N. C. (2011) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2010.0120 · Cited by 457 · cited 3× · see citing works
“Furthermore, girls are more likely to prioritize and compare themselves on dimensions of physical attractiveness online (Haferkamp and Krämer 2011; Jones 2001).”
(2012) · Guilford Press eBooks · Cited by 450 · see citing works
“Facebook Depression?” Social Networking Site Use and Depression in Older Adolescents
Jelenchick, L. A., Eickhoff, J. C., & Moreno, M. A. (2013) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2012.05.008 · Cited by 445 · cited 2× · see citing works
“Importantly, a number of studies have found no association between frequency of technology use and general well being (Gross 2004), nor between frequency of technology use and depressive symptoms (Davila et al. 2012; Jelenchick et al. 2013), further highlighting the inconclusive nature of attempts to characterize over…”
Reich, S. M., Subrahmanyam, K., & Espinoza, G. (2012) · Developmental Psychology · doi:10.1037/a0026980 · Cited by 411 · cited 1× · see citing works
“Additionally, given the substantial overlap between online and offline networks (Reich et al. 2012), it is likely that adolescents who are unpopular offline have fewer online friends.”
Jones, S., & Fox, S. (2009) · Cited by 381 · see citing works
Selfhout, M. H. W., Branje, S. J. T., Delsing, M., ter Bogt, T. F. M., & Meeus, W. H. J. (2009) · Journal of Adolescence · doi:10.1016/j.adolescence.2008.10.011 · Cited by 375 · cited 4× · see citing works
“…decision can be found at danah.org. behaviors, in turn, may be associated with negative online peer feedback, as well as increases in loneliness and depressive symptoms (Burke et al. 2010; Forest and Wood 2012; Selfhout et al. 2009), which may influence future technology use in a cyclical fashion.”
InfluentialSharp, C., Goodyer, I. M., & Croudace, T. J. (2006) · Journal of Abnormal Child Psychology · doi:10.1007/s10802-006-9027-x · Cited by 358 · cited 2× · see citing works
“The SMFQ has good psychometric properties (Sharp et al. 2006) and has been widely used to assess depressive symptoms in adolescent samples (e.g., Rothon et al. 2009).”
Joiner, T. E., & Metalsky, G. I. (1995) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.69.4.778 · Cited by 322 · see citing works
Effects of Internet use and social resources on changes in depression
Bessière, K., Kiesler, S., Kraut, R., & Boneva, B. S. (2008) · Information, Communication & Society · doi:10.1080/13691180701858851 · Cited by 316 · cited 2× · see citing works
“Researchers have called for a more nuanced understanding of the specific online behaviors and pre-existing individual characteristics that may influence these associations (Bessière et al. 2008; Davila et al. 2012; Kraut et al. 2002; Valkenburg and Peter 2013).”
Envy on Facebook: a hidden threat to users' life satisfaction?
Krasnova, H., Wenninger, H., Widjaja, T., & Buxmann, P. (2013) · University of Bern · doi:10.7892/boris.47080 · Cited by 290 · cited 2× · see citing works
“Furthermore, preliminary findings suggest that negative social comparison on Facebook may be associated with lower life satisfaction (Krasnova et al. 2013), as well as increased rumination and depressive symptoms (Feinstein et al.”
Valkenburg, P. M., & Peter, J. (2009) · Journal of Communication · doi:10.1111/j.1460-2466.2008.01405.x · Cited by 286 · cited 1× · see citing works
“Other studies have indicated the opposite: that frequent technology use may be associated with positive adjustment, including increases in self-disclosure and friendship quality (Valkenburg and Peter 2009).”
Joiner, T. E., & Metalsky, G. I. (2001) · Psychological Science · doi:10.1111/1467-9280.00369 · Cited by 272 · cited 2× · see citing works
“The original RSS has been shown to have good psychometric properties (Joiner and Metalsky 2001) and has been used to assess depressive symptoms in adolescent samples (e.g., Prinstein et al. 2005).”
Prinstein, M. J., Borelli, J. L., Cheah, C. S. L., Simon, V. A., & Aikins, J. W. (2005) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.114.4.676 · Cited by 266 · cited 3× · see citing works
“The original RSS has been shown to have good psychometric properties (Joiner and Metalsky 2001) and has been used to assess depressive symptoms in adolescent samples (e.g., Prinstein et al. 2005).”
Self-citationExcessive reassurance seeking, depression, and interpersonal rejection: A meta-analytic review.
Starr, L. R., & Davila, J. (2008) · Journal of Abnormal Psychology · doi:10.1037/a0013866 · Cited by 251 · cited 3× · see citing works
“Furthermore, associations between reassurance-seeking behaviors and depressive symptoms may be particularly strong among adolescent girls, for whom rates of depression are higher in general (Starr and Davila 2008), and given known situational continuities between online and offline contexts (Mikami et al.”
InfluentialDavila, J., Hershenberg, R., Feinstein, B. A., Gorman, K., Bhatia, V., & Starr, L. R. (2012) · Psychology of Popular Media Culture · doi:10.1037/a0027512 · Cited by 237 · cited 5× · see citing works
“Researchers have called for a more nuanced understanding of the specific online behaviors and pre-existing individual characteristics that may influence these associations (Bessière et al. 2008; Davila et al. 2012; Kraut et al. 2002; Valkenburg and Peter 2013).”
Influential(2013) · Cited by 224 · see citing works
Contingencies of Self-Worth and Social-Networking-Site Behavior
Stefanone, M. A., Lackaff, D., & Rosen, D. (2011) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2010.0049 · Cited by 202 · cited 4× · see citing works
“In terms of gender, females may be more likely to compare themselves on dimensions of physical attractiveness based on online photos (Haferkamp and Krämer 2011), perhaps making such photos more self-relevant and threatening to self-worth (Stefanone et al. 2011).”
InfluentialMikami, A. Y., Szwedo, D. E., Allen, J. P., Evans, M. A., & Hare, A. L. (2010) · Developmental Psychology · doi:10.1037/a0017420 · Cited by 172 · cited 7× · see citing works
“Furthermore, associations between reassurance-seeking behaviors and depressive symptoms may be particularly strong among adolescent girls, for whom rates of depression are higher in general (Starr and Davila 2008), and given known situational continuities between online and offline contexts (Mikami et al. 2010), this…”
InfluentialThe Effect of Feedback on Identity Shift in Computer-Mediated Communication
Walther, J. B., Liang, Y. J., DeAndrea, D. C., Tong, S. T., Carr, C. T., Spottswood, E. L., & Amichai-Hamburger, Y. (2011) · Media Psychology · doi:10.1080/15213269.2010.547832 · Cited by 159 · cited 2× · see citing works
“The hyperpersonal model of computer-mediated communication (CMC; Walther et al. 2011) suggests that certain components of technology-based interaction serve to intensify the process of identity construction through increased feedback and decision-making within these environments.”
Harter, S. (1996) · Journal of Research on Adolescence · Cited by 155 · see citing works
(2012) · Cited by 139 · see citing works
(2013) · UvA-DARE (University of Amsterdam) · Cited by 132 · see citing works
Borelli, J. L., & Prinstein, M. J. (2006) · Journal of Abnormal Child Psychology · doi:10.1007/s10802-005-9010-y · Cited by 119 · cited 1× · see citing works
“Interpersonal feedback-seeking and social comparison, which have often been conceptualized as depressogenic interpersonal behaviors (e.g., Borelli and Prinstein 2006), may actually be facilitated by modern technologies.”
Self-citationThe BlackBerry project: Capturing the content of adolescents' text messaging.
Underwood, M. K., Rosén, L., More, D., Ehrenreich, S. E., & Gentsch, J. K. (2011) · Developmental Psychology · doi:10.1037/a0025914 · Cited by 117 · cited 1× · see citing works
“Initial studies using direct observation of adolescent media content (e.g. Underwood et al. 2012) have shown promising results.”
Rothon, C., Head, J., Clark, C., Klineberg, E., Cattell, V., & Stansfeld, S. (2009) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-008-0452-8 · Cited by 104 · cited 1× · see citing works
“The SMFQ has good psychometric properties (Sharp et al. 2006) and has been widely used to assess depressive symptoms in adolescent samples (e.g., Rothon et al. 2009).”
A Test of Interpersonal Theory of Depression in Youth Psychiatric Inpatients
Joiner, T. E. (1999) · Research on Child and Adolescent Psychopathology · doi:10.1023/a:1022666424731 · Cited by 88 · see citing works
On the conception and measurement of popularity: more facts and some straight conclusions
Babad, E. (2001) · Social Psychology of Education · doi:10.1023/a:1012780232587 · Cited by 72 · cited 2× · see citing works
“Popular adolescents, who are higher in self-esteem (Babad 2001), may engage in fewer upward comparisons, experience less negative affect as a result of these comparisons, and receive more positive feedback from peers (Mikami et al.”
Peer Relationships and the Development of Psychopathology
Choukas‐Bradley, S., & Prinstein, M. J. (2014) · Springer eBooks · doi:10.1007/978-1-4614-9608-3_10 · Cited by 58 · cited 2× · see citing works
“, more frequent, complex, and unsupervised peer contact) may complicate this process (Choukas-Bradley and Prinstein 2014), particularly as”
Self-citationSafe Sext: Adolescents' Use of Technology to Communicate About Sexual Health With Dating Partners
Widman, L., Nesi, J., Choukas-Bradley, S., & Prinstein, M. J. (2014) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2013.12.009 · Cited by 36 · cited 2× · see citing works
“Factor analysis revealed a single 10-item factor indicating engagement in social comparison and feedback-seeking behaviors using technology, as well as other factors relating to the use of technology for general communication with romantic partners, social support seeking, and discussions about sexual health topics (W…”
Self-citationWenzlaff, R. M., & Beevers, C. G. (1998) · Personality and Social Psychology Bulletin · doi:10.1177/0146167298244005 · Cited by 10 · cited 1× · see citing works
“Some research suggests that depressed and dysthymic individuals may be motivated to seek out negative information about others (Wenzlaff and Beevers 1998).”
Internet and Other Interactive Media
Uhls, Y. T., Espinoza, G., Greenfield, P. M., Subrahmanyam, K., & Šmahel, D. (2011) · Elsevier eBooks · doi:10.1016/b978-0-12-373951-3.00065-x · Cited by 8 · cited 2× · see citing works
“This may serve to intensify the issues of identity development and interpersonal connectedness, challenging adolescents to confront them with greater constancy and urgency (Uhls et al. 2011).”
Flagged first, then by citations
7 of the 75 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- boyd, d. (2007). Social networking sites: public, private, or what? Knowledge Tree, 13, 28.
- Rudolph, K. D. (2009). Adolescent depression. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of Depression: Second Edition (444–467).
Cited by
Sorted by citations
Nesi, J., Choukas-Bradley, S., & Prinstein, M. J. (2018) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-018-0261-x · Cited by 712 · see citing works
“Finally, a study with adolescents found that engagement in social comparison and feedback-seeking behaviors on social media was positively associated with depressive symptoms, over and above levels of excessive reassurance-seeking (Nesi and Prinstein 2015).”
Self-citationSocial functioning in major depressive disorder
Kupferberg, A., Bicks, L., & Hasler, G. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.07.002 · Cited by 663 · see citing works
Social media use and anxiety in emerging adults
Vannucci, A., Flannery, K. M., & Ohannessian, C. M. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.08.040 · Cited by 623 · see citing works
The interplay between Facebook use, social comparison, envy, and depression
Appel, H., Gerlach, A. L., & Crusius, J. (2016) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2015.10.006 · Cited by 605 · see citing works
“Current Opinion in Psychology 2016, 9:44–49 in opposite directions [25 ,32].”
BackgroundTwenge, J. M., & Martin, G. N. (2020) · Journal of Adolescence · doi:10.1016/j.adolescence.2019.12.018 · Cited by 582 · see citing works
Talwar, S., Dhir, A., Kaur, P., Zafar, N., & Alrasheedy, M. (2019) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2019.05.026 · Cited by 577 · see citing works
Rapee, R. M., Oar, E. L., Johnco, C. J., Forbes, M. K., Fardouly, J., Magson, N. R., & Richardson, C. E. (2019) · Behaviour Research and Therapy · doi:10.1016/j.brat.2019.103501 · Cited by 533 · see citing works
Islam, A. K. M. N., Laato, S., Talukder, S., & Sutinen, E. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120201 · Cited by 538 · see citing works
Love me Tinder: Untangling emerging adults’ motivations for using the dating application Tinder
Sumter, S. R., Vandenbosch, L., & Ligtenberg, L. (2016) · Telematics and Informatics · doi:10.1016/j.tele.2016.04.009 · Cited by 509 · see citing works
“In addition, individuals use social media platforms to satisfy psychosocial needs related to selfworth, such as validating the sexual attractiveness of one’s own appearance and feeling better about oneself in general (Nesi & Prinstein, 2015; Yurchisin, Watchravesringkan, & McCabe, 2005).”
Media use and brain development during adolescence
Crone, E. A., & Konijn, E. A. (2018) · Nature Communications · doi:10.1038/s41467-018-03126-x · Cited by 464 · see citing works
Media Use Is Linked to Lower Psychological Well-Being: Evidence from Three Datasets
Twenge, J. M., & Campbell, W. K. (2019) · Psychiatric Quarterly · doi:10.1007/s11126-019-09630-7 · Cited by 429 · see citing works
Social media use and risky behaviors in adolescents: A meta-analysis
Vannucci, A., Simpson, E. G., Gagnon, S., & Ohannessian, C. M. (2020) · Journal of Adolescence · doi:10.1016/j.adolescence.2020.01.014 · Cited by 410 · see citing works
Windows of developmental sensitivity to social media
Orben, A., Przybylski, A. K., Blakemore, S.-J., & Kievit, R. A. (2022) · Nature Communications · doi:10.1038/s41467-022-29296-3 · Cited by 387 · see citing works
Sherlock, M., & Wagstaff, D. L. (2019) · Psychology of Popular Media Culture · doi:10.1037/ppm0000182 · Cited by 324 · see citing works
Boer, M., Stevens, G. W. J. M., Finkenauer, C., de Looze, M. E., & van den Eijnden, R. J. J. M. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106645 · Cited by 335 · see citing works
Social Media and Depressive Symptoms in Childhood and Adolescence: A Systematic Review
McCrae, N., Gettings, S., & Purssell, E. (2017) · Adolescent Research Review · doi:10.1007/s40894-017-0053-4 · Cited by 304 · see citing works
“In the study of social comparison and feedback-seeking and depressive symptoms by Nesi and Prinstein (2015), a statistically significant relationship was found between these online behaviors at baseline and depression 12 months later.”
BackgroundInfluentialThe Conceptual and Methodological Mayhem of “Screen Time”
K. Kaye, L., Orben, A., A. Ellis, D., C. Hunter, S., & Houghton, S. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17103661 · Cited by 304 · see citing works
Tang, S., Werner-Seidler, A., Torok, M., Mackinnon, A. J., & Christensen, H. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2021.102021 · Cited by 284 · see citing works
Heffer, T., Good, M., Daly, O., MacDonell, E., & Willoughby, T. (2019) · Clinical Psychological Science · doi:10.1177/2167702618812727 · Cited by 278 · see citing works
“Research on the link between depressive symptoms and social-media use in particular has been primarily cross-sectional, or involving studies with multiple time points that did not allow for an assessment of change over time (e.g., Booker, Kelly, & Sacker, 2018; Nesi & Prinstein, 2015).”
ResultNesi, J., Choukas-Bradley, S., & Prinstein, M. J. (2018) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-018-0262-9 · Cited by 266 · see citing works
“The publicness and availability of social media provide adolescents with unprecedented access to information about popular peers, perhaps heightening “upward” social comparison processes, particularly among low-status adolescents (Nesi and Prinstein 2015).”
Self-citationNot all screen time is created equal: associations with mental health vary by activity and gender
Twenge, J. M., & Farley, E. (2021) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-020-01906-9 · Cited by 252 · see citing works
Keyes, K. M., & Platt, J. M. (2024) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13864 · Cited by 253 · see citing works
Social media use and depression in adolescents: a scoping review
Vidal, C., Lhaksampa, T., Miller, L., & Platt, R. (2020) · International Review of Psychiatry · doi:10.1080/09540261.2020.1720623 · Cited by 259 · see citing works
“Nesi and Prinstein (2015) found that technology-based social comparison and feedback-seeking were associated with depressive symptoms, even when controlling for the effects of overall frequency of technology use, offline excessive reassurance-seeking, and prior depressive symptoms.”
BackgroundJensen, M., George, M. J., Russell, M. R., & Odgers, C. L. (2019) · Clinical Psychological Science · doi:10.1177/2167702619859336 · Cited by 242 · see citing works
“This finding is consistent with a number of other longitudinal studies that have failed to replicate cross-sectional associations between digital technology use and mental health (Nesi, Miller, & Prinstein, 2017; Nesi & Prinstein, 2015; Ohannessian, 2009; Selfhout et al., 2009).”
ResultThe Impact of Social Media on the Mental Health of Adolescents and Young Adults: A Systematic Review
Khalaf, A. M., Alubied, A. A., Khalaf, A. M., & Rifaey, A. A. (2023) · Cureus · doi:10.7759/cureus.42990 · Cited by 252 · see citing works
“The research was conducted on young people who were referred to mental hospitals because they constituted a risk to others or themselves [24].”
BackgroundInfluentialSteele, R. G., Hall, J. A., & Christofferson, J. L. (2019) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-019-00300-5 · Cited by 242 · see citing works
“, pre-existing psychosocial functioning, personality traits) appear to significantly moderate the impact of social media use on measured outcomes (Nesi and Prinstein 2015; Twenge et al. 2018).”
BackgroundDigital Media, Anxiety, and Depression in Children
Hoge, E., Bickham, D., & Cantor, J. (2017) · Pediatrics · doi:10.1542/peds.2016-1758g · Cited by 237 · see citing works
Christina, S., Magson, N. R., Kakar, V., & Rapee, R. M. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2021.101979 · Cited by 251 · see citing works
Mechanisms linking social media use to adolescent mental health vulnerability
Orben, A., Meier, A., Dalgleish, T., & Blakemore, S.-J. (2024) · Nature Reviews Psychology · doi:10.1038/s44159-024-00307-y · Cited by 220 · see citing works
“Engaging in comparisons on social media has been associated with depression in correlational studies 159 .”
Wang, P., Wang, X., Wu, Y., Xie, X., Wang, X., Zhao, F., Ouyang, M., & Lei, L. (2018) · Personality and Individual Differences · doi:10.1016/j.paid.2018.02.008 · Cited by 221 · see citing works
Social Media Use Subgroups Differentially Predict Psychosocial Well-Being During Early Adolescence
Vannucci, A., & Ohannessian, C. M. (2019) · Journal of Youth and Adolescence · doi:10.1007/s10964-019-01060-9 · Cited by 205 · see citing works
“…strategies among adolescents with these intensified identity and peer acceptance concerns that contribute to negative self-evaluations and worsening negative mood, including excessive interpersonal feedback seeking, upward social comparisons, rumination, and co-rumination (Nesi and Prinstein 2015).”
BackgroundInfluentialSuicide and Suicide Risk in Adolescents
Hua, L. L., Lee, J., Rahmandar, M. H., Sigel, E. J., COMMITTEE ON ADOLESCENCE, & COUNCIL ON INJURY, V. (2024) · Pediatrics · doi:10.1542/peds.2023-064800 · Cited by 205 · see citing works
Problematic Social Media Use and Its Relationship with Depression or Anxiety: A Systematic Review
Lopes, L. S., Valentini, J. P., Monteiro, T. H., Costacurta, M. C. D. F., Soares, L. O. N., Telfar-Barnard, L., & Nunes, P. V. (2022) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2021.0300 · Cited by 197 · see citing works
“37,40,51,53,66 In other studies, 67,95,108,109,112,115,116 higher social media use had a relationship with gaming.”
InfluentialSocial media usage and development of psychiatric disorders in childhood and adolescence: a review
Cataldo, I., Lepri, B., Neoh, M. J. Y., & Esposito, G. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.508595 · Cited by 186 · see citing works
“As a consequence, people showing downward social comparisons are more likely to seek offline feedback for reassurance (66).”
BackgroundResultSocial Media Use and Self-Injurious Thoughts and Behaviors: A Systematic Review and Meta-Analysis
Nesi, J., Burke, T. A., Bettis, A. H., Kudinova, A. Y., Thompson, E. C., MacPherson, H. A., Fox, K. A., Lawrence, H. R., Thomas, S. A., Wolff, J. C., et al. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2021.102038 · Cited by 186 · see citing works
Self-citationHawes, T., Zimmer-Gembeck, M. J., & Campbell, S. M. (2020) · Body Image · doi:10.1016/j.bodyim.2020.02.010 · Cited by 186 · see citing works
Kupferberg, A., & Hasler, G. (2023) · Journal of Affective Disorders Reports · doi:10.1016/j.jadr.2023.100631 · Cited by 195 · see citing works
McComb, C. A., Vanman, E. J., & Tobin, S. J. (2023) · Media Psychology · doi:10.1080/15213269.2023.2180647 · Cited by 167 · see citing works
Burnell, K., George, M. J., Vollet, J. W., Ehrenreich, S. E., & Underwood, M. K. (2019) · Cyberpsychology Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2019-3-5 · Cited by 175 · see citing works
“The ten-item Comparison and Feedback-Seeking scale (Nesi, 2014; Nesi & Prinstein, 2015) was used to measure participants’ engagement of technology-based social comparisons and feedback-seeking behaviors.”
MethodThe Appearance-Related Social Media Consciousness Scale: Development and validation with adolescents
Choukas-Bradley, S., Nesi, J., Widman, L., & Galla, B. M. (2020) · Body Image · doi:10.1016/j.bodyim.2020.02.017 · Cited by 160 · see citing works
Self-citationGutman, L. M., & Mcmaster, N. C. (2020) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-020-00623-w · Cited by 162 · see citing works
“Specific technology-based behaviours, such as social comparison and feedback seeking, have also been shown to be associated with depressive symptoms, suggesting a more nuanced approach to the study of adolescents’ media use (Nesi and Prinstein 2015).”
BackgroundPlaisime, M. V., Robertson-James, C., Mejia, L., Núñez, A. E., Wolf, J., & Reels, S. (2020) · Social Media + Society · doi:10.1177/2056305119886025 · Cited by 148 · see citing works
“Over 93% of American teenagers (ages: 12–17 years) are now connected to the Internet, more than any other age group, with an estimated 73% belonging to at least one social network site (SNS) (Lenhart, Purcell, Smith, & Zickuhr, 2010; Nesi & Prinstein, 2015).”
BackgroundUnderwood, M. K., & Ehrenreich, S. E. (2017) · American Psychologist · doi:10.1037/a0040429 · Cited by 144 · see citing works
“For U.S. adolescents, using social media for social comparison and feedback seeking predicted depressive symptoms over 1 year’s time, but this relation was stronger for adolescents lower in popularity, and for girls (Nesi & Prinstein, 2015).”
The big picture on Instagram research: Insights from a bibliometric analysis
Rejeb, A., Rejeb, K., Abdollahi, A., & Treiblmaier, H. (2022) · Telematics and Informatics · doi:10.1016/j.tele.2022.101876 · Cited by 160 · see citing works
Coyne, S. M., McDaniel, B. T., & Stockdale, L. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.12.081 · Cited by 143 · see citing works
Escobar-Viera, C. G., Whitfield, D. L., Wessel, C. B., Shensa, A. S., Sidani, J. E., Brown, A. L., Chandler, C. J., Hoffman, B. L., Marshal, M. P., & Primack, B. A. (2018) · JMIR Mental Health · doi:10.2196/10496 · Cited by 135 · see citing works
“Moreover, several studies have looked at either the moderating or mediating role of upward social comparison [25-30], social connectedness [31], envy [32], and intensity of use [33].”
BackgroundLiu, Q., Zhou, Z., Yang, X., Niu, G., Tian, Y., & Fan, C. (2017) · Personality and Individual Differences · doi:10.1016/j.paid.2017.03.037 · Cited by 139 · see citing works
“Research showed that upward social comparison on SNSs was positively associated with depressive symptoms (Nesi & Prinstein, 2015), and envy on SNSs positively predicted symptoms of depression (Tandoc et al., 2015).”
BackgroundThe serially mediated relationship between emerging adults’ social media use and mental well-being
Rasmussen, E. E., Punyanunt-Carter, N. M., LaFreniere, J. R., Norman, M. S., & Kimball, T. G. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.08.019 · Cited by 136 · see citing works
Self-reflection and interpersonal connection: Making the most of self-presentation on social media.
Vogel, E., & Rose, J. P. (2016) · Translational Issues in Psychological Science · doi:10.1037/tps0000076 · Cited by 117 · see citing works
Rosenthal-von der Pütten, A. M., Hastall, M. R., Köcher, S., Meske, C., Heinrich, T., Labrenz, F., & Ocklenburg, S. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.10.017 · Cited by 126 · see citing works
“Recent studies suggest that such overexploitation can significantly alter subjective well-being and perceived life satisfaction (Kross et al., 2013; Verduyn et al., 2015), possibly leading to addiction (Turel, He, Xue, Xiao, & Bechara, 2014) and depression (Nesi & Prinstein, 2015).”
BackgroundInfluentialJiang, Y. N. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.612007 · Cited by 141 · see citing works
Upward social comparison and depression in social network settings
Li, Y. (2018) · Internet Research · doi:10.1108/intr-09-2017-0358 · Cited by 126 · see citing works
Lee, H. Y., Jamieson, J. P., Reis, H. T., Beevers, C. G., Josephs, R. A., Mullarkey, M. C., O’Brien, J. M., & Yeager, D. S. (2020) · Child Development · doi:10.1111/cdev.13422 · Cited by 122 · see citing works
“As in past research (Hankin & Abramson, 2001; Nesi & Prinstein, 2015), girls exhibited more negative internalizing responses overall: Feelings of rejection (Mboys = 2.83, SDboys = 1.78; Mgirls = 3.37, SDgirls = 1.89, t(589) = 3.47, p < .001), negative affect (Mboys = 1.70, SDboys = 0.91; Mgirls =…”
BackgroundResultInfluentialSelf-Esteem, Social Comparison, and Facebook Use
Bergagna, E., & Tartaglia, S. (2018) · Europe's Journal of Psychology · doi:10.5964/ejop.v14i4.1592 · Cited by 110 · see citing works
“Women are more prone to prioritize and compare themselves on the dimension of physical attractiveness based on online photos (Nesi & Prinstein, 2015; Stefanone et al., 2011).”
BackgroundMethodResultInfluentialWirtz, D., Tucker, A., Briggs, C., & Schoemann, A. M. (2020) · Journal of Happiness Studies · doi:10.1007/s10902-020-00291-z · Cited by 121 · see citing works
“While these findings focus on Facebook, other social network sites afford the opportunity for upward social comparison; for example, greater use of Instagram has also been associated with comparing oneself to others and to increased depressive symptoms (Nesi and Prinstein 2015; Lup et al. 2015).”
BackgroundInfluentialZink, J., Belcher, B. R., Imm, K., & Leventhal, A. M. (2020) · BMC Public Health · doi:10.1186/s12889-020-08572-1 · Cited by 105 · see citing works
Van Bavel, J. J., Robertson, C. E., del Rosario, K., Rasmussen, J., & Rathje, S. (2024) · Annual Review of Psychology · doi:10.1146/annurev-psych-022123-110258 · Cited by 121 · see citing works
The contribution of social media addiction to adolescent LIFE: Social appearance anxiety
Caner, N., Efe, Y. S., & Başdaş, Ö. (2022) · Current Psychology · doi:10.1007/s12144-022-03280-y · Cited by 128 · see citing works
Camera-ready: Young women’s appearance-related social media consciousness.
Choukas-Bradley, S., Nesi, J., Widman, L., & Higgins, M. K. (2019) · Psychology of Popular Media Culture · doi:10.1037/ppm0000196 · Cited by 105 · see citing works
Self-citationMcLean, S. A., Jarman, H. K., & Rodgers, R. F. (2019) · Psychology Research and Behavior Management · doi:10.2147/prbm.s177834 · Cited by 105 · see citing works
The use of social media by Australian preadolescents and its links with mental health.
Fardouly, J., Magson, N. R., Rapee, R. M., Johnco, C. J., & Oar, E. L. (2020) · Journal of Clinical Psychology · doi:10.1002/jclp.22936 · Cited by 102 · see citing works
Rousseau, A., Eggermont, S., & Frison, E. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.03.056 · Cited by 104 · see citing works
Social Media Use and Depressive Symptoms Among United States Adolescents
Kreski, N., Platt, J., Rutherford, C., Olfson, M., Odgers, C., Schulenberg, J., & Keyes, K. M. (2021) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2020.07.006 · Cited by 97 · see citing works
“These negative effects of social media affect girls more than boys [10], plausibly explaining why trends in mental health problems have been more prominent among girls and underscoring the need to examine potential gender-specific effects.”
BackgroundJeri-Yabar, A., Sanchez-Carbonel, A., Tito, K., Ramirez-delCastillo, J., Torres-Alcantara, A., Denegri, D., & Carreazo, Y. (2019) · International Journal of Social Psychiatry · doi:10.1177/0020764018814270 · Cited by 98 · see citing works
Prinstein, M. J., Nesi, J. L., & Telzer, E. H. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13219 · Cited by 107 · see citing works
“…rather specifically for © 2020 Association for Child and Adolescent Mental Health social comparison and feedback seeking, may be associated with depressive symptoms, perhaps even more strongly than adolescents’ engagement in offline excessive reassurance-seeking behavior (Nesi & Prinstein, 2015).”
BackgroundSelf-citationSocial Media Use and Depressive Symptoms-A Longitudinal Study from Early to Late Adolescence
Puukko, K., Hietajärvi, L., Maksniemi, E., Alho, K., & Salmela-Aro, K. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17165921 · Cited by 99 · see citing works
“Other studies have highlighted the mediating role of social comparisons and perceived social support in online interactions [70,71].”
BackgroundYankouskaya, A., Liebherr, M., & Ali, R. (2025) · Human-Centric Intelligent Systems · doi:10.1007/s44230-025-00090-w · Cited by 100 · see citing works
“This aligns with research on the problematic use of social media driven by the need for social validation and reassurance [103] and leading to fear of missing out [104] and procrastination [105].”
Toward improved methods in social media research.
Griffioen, N., van Rooij, M. M. J. W., Lichtwarck‐Aschoff, A., & Granic, I. (2020) · Technology Mind and Behavior · doi:10.1037/tmb0000005 · Cited by 94 · see citing works
“Indeed, the social salience of social media has been previously acknowledged: Social media are infamous for their role in eliciting social comparison (Appel et al., 2015; Chow & Wan, 2017; Fardouly et al., 2015; Haferkamp & Krämer, 2011; Jang, Park, & Song, 2016; Nesi & Prinstein, 2015).”
BackgroundLink between excessive social media use and psychiatric disorders
Zubair, U., Khan, M. K., & Albashari, M. S. G. (2023) · Annals of Medicine and Surgery · doi:10.1097/ms9.0000000000000112 · Cited by 95 · see citing works
“negatively impact self-esteem and self-image through unwanted feedback, not receiving enough social validation, or unhealthy competition and comparisons([13]).”
BackgroundWeinstein, E. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.07.038 · Cited by 92 · see citing works
Biagianti, B., Quraishi, S. H., & Schlosser, D. A. (2018) · Psychiatric Services · doi:10.1176/appi.ps.201700283 · Cited by 90 · see citing works
Vahedi, Z., & Zannella, L. (2021) · Current Psychology · doi:10.1007/s12144-019-0150-6 · Cited by 86 · see citing works
“Despite these motivations, however, the use of SNS’s has been associated with various detrimental consequences, including depressive symptoms (e.g., Frison and Eggermont 2016; Lee 2014; Nesi and Prinstein 2015).”
BackgroundDing, Q., Zhang, Y.-X., Wei, H., Huang, F., & Zhou, Z. (2017) · Personality and Individual Differences · doi:10.1016/j.paid.2017.03.027 · Cited by 90 · see citing works
“Empirically, one study found that gender moderated the relationship between using social media for social comparison and depressive symptoms, with the association being particularly strong for females compared to males (Nesi & Prinstein, 2015).”
BackgroundYin, X.-Q., de Vries, D. A., Gentile, D. A., & Wang, J.-L. (2019) · Social Science Computer Review · doi:10.1177/0894439318784908 · Cited by 82 · see citing works
“Our result was consistent with many prior findings (Lin & Lu, 2011; Nesi & Prinstein, 2015).”
BackgroundResultNesi, J., Rothenberg, W. A., Bettis, A. H., Massing-Schaffer, M., Fox, K. A., Telzer, E. H., Lindquist, K. A., & Prinstein, M. J. (2022) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2021.1955370 · Cited by 82 · see citing works
“This heightened emotional investment in social experiences may extend to the online context (Nesi & Prinstein, 2015; Nesi & Prinstein, 2019; Zimmer-Gembeck et al., 2021).”
BackgroundSelf-citationTaking a Short Break from Instagram: The Effects on Subjective Well-Being
Fioravanti, G., Prostamo, A., & Casale, S. (2019) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2019.0400 · Cited by 87 · see citing works
“32,33 For these reasons gender needs to be considered when studying the association between Ig use and well-being.”
Context, Development, and Digital Media: Implications for Very Young Adolescents in LMICs
Magis‐Weinberg, L., Suleiman, A. B., & Dahl, R. E. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.632713 · Cited by 87 · see citing works
“digital drama (Anderson and Jiang, 2018), social comparison and feedback seeking (Nesi and Prinstein, 2015), and risky behaviors (Vannucci et al.”
BackgroundBandwagon vs snob luxuries: Targeting consumers based on uniqueness dominance
Das, M., Habib, M., Saha, V., & Jebarajakirthy, C. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102582 · Cited by 65 · see citing works
Adolescent Development in the Digital Media Context
Nesi, J. L., Telzer, E. H., & Prinstein, M. J. (2020) · Psychological Inquiry · doi:10.1080/1047840x.2020.1820219 · Cited by 91 · see citing works
“…social status plays an important role, with youth who are less popular among their peers exhibiting fewer ‘status-seeking’ online behaviors (Nesi & Prinstein, 2019), and also showing stronger associations between online social comparison behaviors and depressive symptoms (Nesi & Prinstein, 2015).”
BackgroundSelf-citationReviewing the Impact of Social Media on the Mental Health of Adolescents and Young Adults
Gupta, C., Jogdand, S., & Kumar, M. (2022) · Cureus · doi:10.7759/cureus.30143 · Cited by 123 · see citing works
“8% of young people referred to mental hospitals because they posed a risk to others or themselves had accessed online resources that promoted suicide in the two weeks leading up to their admission [19].”
BackgroundNesi, J., Miller, A. B., & Prinstein, M. J. (2017) · Journal of Applied Developmental Psychology · doi:10.1016/j.appdev.2017.02.002 · Cited by 76 · see citing works
“…behavior, which may be conceptually distinct from similar offline behaviors, is technology-based social comparison and feedback seeking (SCFS; Nesi & Prinstein, 2015), or the use of social media to seek out information regarding one's appearance, behaviors, and social status, relative to…”
Self-citationMcCrory, A., Best, P., & Maddock, A. (2020) · Children and Youth Services Review · doi:10.1016/j.childyouth.2020.105053 · Cited by 70 · see citing works
Suicide Risk in Emerging Adulthood: Associations with Screen Time over 10 years
Coyne, S. M., Hurst, J. L., Dyer, W. J., Hunt, Q. A., Schvanaveldt, E., Brown, S., & Jones, G. C. (2021) · Journal of Youth and Adolescence · doi:10.1007/s10964-020-01389-6 · Cited by 81 · see citing works
Social media use in adolescents with and without mental health conditions
Fassi, L., Ferguson, A. M., Przybylski, A. K., Ford, T. J., & Orben, A. C. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02134-4 · Cited by 102 · see citing works
“1c), while also monitoring 54,55 (H1.”
Life Challenges and Barriers to Help Seeking: Adolescents’ and Young Adults’ Voices of Mental Health
Hellström, L., & Beckman, L. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182413101 · Cited by 77 · see citing works
“Further, social media may function as a source of stress or reinforce negative self-evaluations through social comparisons, and heavier Facebook users are more likely to believe others are happier and have better lives [22,23].”
BackgroundKingsbury, M. K., Reme, B., Skogen, J. C., Sivertsen, B., Øverland, S. N., Cantor, N., Hysing, M., Petrie, K. J., & Colman, I. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106614 · Cited by 69 · see citing works
Kırcaburun, K., Griffiths, M. D., & Billieux, J. (2019) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-019-0054-6 · Cited by 76 · see citing works
“It is also consistent with empirical evidence showing that females are more prone to be adversely affected by peer and media influence than males (Brown and Tiggemann 2016; Nesi and Prinstein 2015).”
ResultPeng, C.-T., Wu, T.-Y., Chen, Y., & Atkin, D. J. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.05.011 · Cited by 69 · see citing works
“Evidence shows that social comparison is triggered by a variety of SNS content, such as user profiles (Vogel, Rose, Roberts, & Eckles, 2014), status updates (Nesi & Prinstein, 2015), and “likes” as”
BackgroundLian, S.-L., Sun, X.-J., Zhou, Z.-K., Fan, C.-Y., Niu, G.-F., & Liu, Q.-Q. (2018) · PLOS ONE · doi:10.1371/journal.pone.0208162 · Cited by 68 · see citing works
Online media consumption and depression in young people: A systematic review and meta-analysis
Shin, M., Juventin, M., Chu, J. T. W., Manor, Y. D., & Kemps, E. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107129 · Cited by 65 · see citing works
Young, R., Len-Ríos, M. E., & Young, H. N. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.04.021 · Cited by 71 · see citing works
A Neurocognitive Model of Self-Concept Development in Adolescence
Crone, E. A., Green, K. H., van de Groep, I. H., & van der Cruijsen, R. (2022) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-120920-023842 · Cited by 74 · see citing works
Hilty, D. M., Stubbe, D. E., McKean, A. J. S., Hoffman, P. E., Zalpuri, I., Myint, M. T., Joshi, S. V., Pakyürek, M., & Li, S. T. (2023) · BJPsych Open · doi:10.1192/bjo.2023.523 · Cited by 80 · see citing works
Shin, E., & Lee, J. E. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.04.022 · Cited by 66 · see citing works
Zhang, W., & Ram, S. (2020) · MIS Quarterly · doi:10.25300/misq/2020/15106 · Cited by 64 · see citing works
Sexting Among Adolescents: The Emotional Impact and Influence of the Need for Popularity
Rey, R. D., Ojeda, M., Casas, J. A., Mora-Merchán, J. A., & Elipe, P. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01828 · Cited by 70 · see citing works
Mann, R. B., & Blumberg, F. C. (2022) · Acta Psychologica · doi:10.1016/j.actpsy.2022.103629 · Cited by 80 · see citing works
Mathew, G. M., Hale, L. E., & Chang, A. (2019) · Journal of Biological Rhythms · doi:10.1177/0748730419828102 · Cited by 62 · see citing works
“Indeed, having an electronic device (such as a mobile phone) in the bedroom or internet use in the hour before bedtime predicts greater social jetlag, and these behaviors are more prevalent in female adolescents (Nesi and Prinstein, 2015; Spilková et al., 2017).”
Reciprocal associations between screen time and emotional disorder symptoms during adolescence
Zink, J., Belcher, B. R., Kechter, A., Stone, M. D., & Leventhal, A. M. (2019) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2019.01.014 · Cited by 62 · see citing works
“(e.g., passive social media use) may become socially isolated or may engage in upward social comparison, whereby feelings of inferiority and envy reduce emotional well-being (Frison and Eggermont, 2016; Verduyn et al., 2015; Verduyn et al., 2017; Nesi and Prinstein, 2015).”
BackgroundCo-Rumination Exacerbates Stress Generation among Adolescents with Depressive Symptoms
Rose, A. J., Glick, G. C., Smith, R. L., Schwartz‐Mette, R. A., & Borowski, S. K. (2016) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-016-0205-1 · Cited by 64 · see citing works
“Moreover, these pathways may be activated especially strongly for girls (as compared to boys) because the mean levels of co-rumination (e.g., Rose 2002) and some risky coginitions and behaviors (e.g., Jose et al. 2012; Nesi and Prinstein 2015) are higher among girls than boys.”
- Authors
- Nesi, J., & Prinstein, M. J.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Nesi, Jacqueline
- Prinstein, Mitchell J.
- Venue
- Journal of Abnormal Child Psychology
- Published
- 2015-04-23
- Volume
- 43
- Issue
- 8
- Pages
- 1427-1438
- ISSN
- 0091-0627 (ISSN-L)
- 1573-2835
- PMC
- PMC5985443
- OpenAlex
- W2012064690
- Cited by
- 758
- References
- 75
- Citations by year
- 2026: 104 · 2025: 132 · 2024: 99 · 2023: 81 · 2022: 82 · 2021: 80 · 2020: 67 · 2019: 40 · 2018: 31 · 2017: 28 · 2016: 8 · 2015: 4
- FWCI
- 78.31
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Research on Child and Adolescent Psychopathology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Foundation
- National Institutes of Health
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD055342)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Clinical Psychology › Child and Adolescent Psychosocial and Emotional Development
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Keywords
- social media use, social comparison, feedback seeking, depressive symptoms, adolescents, gender differences, popularity, sociometric nominations, reassurance seeking, Facebook, Instagram, mobile phone use
- MeSH terms
- Adolescent, Adolescent Behavior, Depression, Female, Humans, Interpersonal Relations, Male, Social Desirability, Feedback, Psychological, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read under definition version 3 (extract-v3) on 2026-09-28.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
