There Is No Evidence That Associations Between Adolescents’ Digital Technology Engagement and Mental Health Problems Have Increased

Vuorre, Matti; Orben, Amy; Przybylski, Andrew K.

doi:10.1177/2167702621994549

Cited by 158Impact of Technology on AdolescentsChild Development and Digital TechnologyChild and Adolescent Psychosocial and Emotional Development

There Is No Evidence That Associations Between Adolescents’ Digital Technology Engagement and Mental Health Problems Have Increased

Open access

Vuorre, Matti, Orben, Amy, Przybylski, Andrew K.·2021·Clinical Psychological Science

DOI 10.1177/2167702621994549PMC PMC7614449

Published version of a preprint

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Abstract

Digital technology is ubiquitous in modern adolescence, and researchers are concerned that it has negative impacts on mental health that, furthermore, increase over time. To investigate whether technology is becoming more harmful, we examined changes in associations between technology engagement and mental health in three nationally representative samples. Results were mixed across types of technology and mental health outcomes: Technology engagement had become less strongly associated with depression in the past decade, but social-media use had become more strongly associated with emotional problems. We detected no changes in five other associations or differential associations by sex. There is therefore little evidence for increases in the associations between adolescents’ technology engagement and mental health. Information about new digital media has been collected for a relatively short time; drawing firm conclusions about changes in their associations with mental health may be premature. We urge transparent and credible collaborations between scientists and technology companies.

AI snapshot

Written from the paper’s full text.

TL;DR

Across three large nationally representative samples, the paper finds little evidence that associations between adolescents’ technology engagement and mental health problems have increased over time. Results were mixed by technology and outcome, with some associations decreasing and one increasing, but changes were very small.

Key findings

In 2017, technology–mental health associations were generally weak, ranging from zero to about 0.15 SD; in YRBS, males at average device use reported suicide planning with 9% probability versus 11% at 1 SD above the mean (difference 2%, 95% CI [1.6%, 2.7%]).
No consistent increase over time: social media use became more strongly associated with emotional problems, but depression’s association with social media and TV decreased; no credible changes were detected in five other associations, and no changes differed by gender.
Where credible changes occurred, they were smaller than 0.01 SD per year; GAMs explained less than 3% of variance and indicated only two nonlinear changes: social media–emotional problems and TV–depression.

Methods

Analyzed three nationally representative datasets—Monitoring the Future, Understanding Society, and Youth Risk Behavior Surveillance System—with a combined 430,561 participants, restricting to ages 10–15 where possible.
Outcomes included depression, conduct problems, emotional problems, and suicidal ideation/behaviour; predictors included TV viewing, social media use, and digital device use.
Estimated Bayesian models with year (centered at 2017), technology use, and their interaction, plus sex interactions; US models included random intercepts, YRBS used Bernoulli/probit models with random item parameters, and sensitivity analyses used generalized additive models.

Limitations

The paper states that between-person associations cannot support causal claims, that no covariates were included due to lack of strong theory and cross-dataset heterogeneity, and that self-report technology use is biased and noisy.
The paper states that newer technologies have a shorter observation window, making firm conclusions premature, and that the work may conflate between- and within-person associations or different levels of analysis.
Evident from the text: most analyses are cross-sectional except Understanding Society, and the study relies on self-reported mental health and technology use rather than objective usage data.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1177/2167702621994549

Cites

48 of 48 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 38 cited sources checked · 0 supported · 0 flagged

Findingown data
No credible changes were detected in the relationship between suicidal ideation and behaviour and either social media or television.
“Interestingly, no credible changes were detected in the relationship between suicidal ideation and behaviour and either social media or television.”
Quote in the paperSubstantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
Findingown data
Emotional problems were related to both TV and social media.
“Emotional problems were also related to both technologies, but suicidal ideation and behaviour was reliably associated only with social media.”
Quote in the paperNot a substantial claim
Findingown data
The relationship between social media and TV, and conduct problems remained stable, with parameters narrowly centered on zero.
“The relationship between social media and TV, and conduct problems had remained stable, as indicated by the estimated parameters narrowly centered on zero.”
Quote in the paperSubstantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
Findingown data
Most GAM models showed that the nonlinear technology-mental health relationships did not change over time.
“Critically, most models indicated that the (nonlinear) technology-mental health relationships had not changed over time as suggested by model comparison using AIC (Figure 3, bottom right)”
Quote in the paperSubstantial claim
Findingown data
The GAMs with year and technology use but no interaction explained under 3% of variance in the mental health outcomes.
“However, in line with the previous linear models, the GAMs that included year and technology use, but not their interaction, still only explained less than 3% of variance in the outcomes (Figure 3, bottom left).”
Quote in the paperNot a substantial claim

Findingown data
In 2017, associations differed notably across mental health outcomes and technologies.
“There were notable differences in associations across the different mental health outcomes and technologies (Figure 2, top panel).”
Quote in the paperNot a substantial claim
Findingown data
The association between emotional problems and TV remained stable over time.
“The association between emotional problems and social media had increased, but their association with TV had remained stable.”
Quote in the paperSubstantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
Findingown data
Conduct problems were positively related to both TV and social media.
“Conduct problems were positively related to both TV and social media, whereas depression’s relation to both was practically zero.”
Quote in the paperNot a substantial claim
Findingown data
Suicidal ideation and behaviour was reliably associated only with social media.
“Emotional problems were also related to both technologies, but suicidal ideation and behaviour was reliably associated only with social media.”
Quote in the paperNot a substantial claim
Findingown data
Depression's association with social media and TV decreased over time.
“Depression’s association with social media and TV had decreased over time.”
Quote in the paperSubstantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
Findingown data
Depression's relation to both TV and social media was practically zero.
“Conduct problems were positively related to both TV and social media, whereas depression’s relation to both was practically zero.”
Quote in the paperNot a substantial claim
Findingown data
Even the largest interaction parameters did not exceed 0.01 standard deviation change per year.
“Notably, even the greatest magnitudes of these parameters did not exceed 0.01 change in standard deviation units, suggesting that changes, if any, were very small.”
Quote in the paperSubstantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
Findingown data
The study partly reproduced earlier results that greater technology use goes with more reported mental health problems.
“We partially replicated previous findings whereby individuals who use more technology are likely to report higher mental health problems”
Quote in the paperNot a substantial claim
Findingown data
The decline in the depression association occurred for both television and social media.
“However, this decline was found for both television and social media”
Quote in the paperSubstantial claim
Findingown data
Links involving conduct problems and suicidality remained fairly stable across time.
“Technology associations with conduct problems and suicidality were relatively stable over time.”
Quote in the paperSubstantial claim
Findingown data
Social media's relations with emotional problems slightly increased over time.
“Social media’s relations with emotional problems had slightly increased”
Quote in the paperNot a substantial claim
Findingown data
Where uncertainty intervals excluded zero, the three relations were below 0.01 SD units per year.
“In all three cases where parameters’ uncertainty intervals excluded zero, the relations were smaller than 0.01 standard deviation units per year”
Quote in the paperSubstantial claim
Findingown data
In 2017, technology uses were weakly associated with higher levels of most mental health problems except depression.
“we first studied the technology associations specific to 2017, and found that technology uses were weakly associated with higher levels of most mental health problems, apart from depression.”
Quote in the paperNot a substantial claim
Findingown data
The social media use-emotional problems association became somewhat more linear over time.
“whereas the association between social media use and emotional problems had become a slightly more linear trend over time (Figure 3, top panel).”
Quote in the paperNot a substantial claim
Findingown data
Across eight models, depression was the one clinically relevant self-reported mental health outcome whose links with technology use became consistently less negative over time.
“From these eight models, we found one clinically relevant self-reported mental health outcome, depression, for which the links to technology use had become consistently less negative over time.”
Quote in the paperSubstantial claim
Findingown data
Technology's links with mental health did not show a consistent temporal trend.
“Most importantly to the present investigation, there was no consistent change over time in technology’s relations with mental health.”
Quote in the paperSubstantial claim
Findingown data
Television's relations with emotional problems did not increase over time.
“but television’s had not.”
Quote in the paperSubstantial claim
Findingown data
Only one case was found in which social media's relation with mental health became more negative over time.
“Further, we only found one case whereby social media’s relation with mental health had become more negative over time”
Quote in the paperSubstantial claim
Findingown data
TV's link with mental health initially stayed relatively unchanged for a long stretch.
“As is observed in Figure 1, there was an initial long period of relative invariance in TV’s relation to mental health”
Quote in the paperSubstantial claim
Findingown data
No sex differences appeared in the temporal patterns.
“Finally, we did not find any differences in the time courses between girls and boys.”
Quote in the paperNot a substantial claim
Findingown data
The TV viewing-depression association became somewhat more inverted U-shaped over time.
“The association between TV viewing and depression had generally become slightly more prominently an inverted U-shaped function over time”
Quote in the paperNot a substantial claim
Findingown data
Only two associations changed in potentially nonlinear ways according to GAM model comparisons: social media use with emotional problems, and television viewing with depression.
“There were only two associations, between social media use and emotional problems, and between television viewing and depression, that had changed in potentially nonlinear ways according to the GAM model comparisons (Figure 3, bottom right).”
Quote in the paperNot a substantial claim
Findingown data
Among males, average device use corresponded to a 9% probability of planning suicide, and one standard deviation above mean device use to an 11% probability, a 2% difference (95% CI [1.6%, 2.7%]).
“For example, males using an average amount of digital devices reported planning for suicide with a 9% probability, and males who were 1 standard deviation above the mean on device use endorsed the item with a 11% probability, leading to a small difference (2%, 95%CI [1.6%, 2.7%]).”
Quote in the paperSubstantial claim
Premisecitation
Public anxiety about digital technologies tends to rise and fall as new entertainment and social technologies appear and are taken up by youth.
“concerns about digital technologies are best understood to follow a pattern of societal apprehension that waxes and wanes as novel forms of entertainment and social technologies are invented and gradually adopted by young people (Orben, 2020).”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites Orben, 2020
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Interpretationreasoning
Consequently, it is unknown how the effects of existing technologies change when new technologies appear and are adopted by youth.
“Therefore, we have not learned how existing technologies’ effects change as new technologies emerge and are adopted by young people.”
Quote in the paperSubstantial claim
Premisecitation
The body of evidence that technology use reduces adolescent mental health is weak.
“there is little good evidence that technology use causes decreases in mental health (Dickson et al., 2019).”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites Dickson et al., 2019
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Premisecitation
In secondary analyses, inconsistent standards threaten the validity and robustness of reported associations because analytic choices can produce unrepresentative estimates.
“In secondary data analyses, these problems are compounded by a general lack of adherence to consistent standards (Weston et al., 2019), which threatens the validity and robustness of reported associations, as the many choices leading to a reported analysis can engender misrepresentative estimates (Orben & Przybylski, 2019a).”
Quote in the paperNot a substantial claim0 of 2 sources checked
- cites Weston et al., 2019
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- cites Orben & Przybylski, 2019a
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Premisecitation
When a new technology raises concern, worries about older technologies are dropped without agreement or good evidence about whether those older technologies were harmful.
“when fears emerge about a new technology, worries about previous technologies are largely abandoned without an agreement on—or good data indicating—whether, why or how the previous technologies were or were not harmful (Grimes et al., 2008; Orben, 2020).”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites Grimes et al., 2008
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- cites Orben, 2020
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Premisereasoning
Few or no studies have tested whether older technologies' effects, such as television's, rose or fell as attention moved to newer technologies.
“there are few or no tests of whether the effects of previous technologies, such as those of watching television, actually increased or decreased as society’s attention shifted to the possible harms associated with more recent technologies, e.g. playing video games.”
Quote in the paperSubstantial claim
Premisecitation
Technologies and their uses are not static; the contexts and ways digital technologies are used change, with platforms gaining and losing popularity within adolescent social groups.
“However, technologies, and their uses, are not static. The contexts and ways in which digital technologies are used are themselves in flux, with different platforms and technologies gaining and losing popularity within an adolescent’s social group (Boyd, 2014).”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites Boyd, 2014
  Not checked in the free run.
Interpretationreasoning
It is inaccurate to frame shifts in technology-mental health links as technology simply improving or worsening.
“our results suggest that just as the ways in which young people use technology is changing, so too may its relations with mental health change, but this change is not well characterized as technology becoming either better or worse.”
Quote in the paperSubstantial claim
Premisecitation
Earlier research indicates that adding covariates usually shrinks related associations.
“Nevertheless, previous studies have found that covariates tend to render related associations smaller (Orben & Przybylski, 2019b)”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites Orben & Przybylski, 2019b
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Interpretationown data
Even after allowing nonlinearity in both the technology-mental health relations and their changes over time, there was little evidence of drastic change in the associations over time.
“In sum, even after relaxing assumptions about linearity—in both the relations between technology use and mental health, and how they have changed over time—there was little evidence to suggest that there has been drastic change in the associations over time.”
Quote in the paperSubstantial claim
Premisecitation
Prior research indicates that for subjective well-being scales, effects around half a standard deviation are needed for people to subjectively experience change.
“Previous studies have shown that, in the case of subjective well-being scales, effects of about a half standard deviation are required for people to subjectively experience change (Anvari & Lakens, 2019).”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites Anvari & Lakens, 2019
  Not checked in the free run.
Interpretationcitation
The reported effect sizes likely exceed the true associations.
“suggesting that the magnitudes we report are overestimates of the true associations.”
Quote in the paperSubstantial claim
Interpretationown data
The claim that rapid changes to social media platforms and devices made them more harmful to adolescent mental health in the past decade is not strongly supported by the current data.
“The argument that fast-paced changes to social media platforms and devices have made them more harmful for adolescent mental health in the past decade is, therefore, not strongly supported by current data either.”
Quote in the paperSubstantial claim
Interpretationreasoning
These findings cannot directly establish that technology use causes mental health variation, as within-person longitudinal data could.
“but unlike longitudinal within-person data, these findings do not directly afford a causal claim that technology use is responsible for variation in mental health.”
Quote in the paperSubstantial claim
Interpretationown data
On the whole, the data offered little or no indication that technology's link with mental health is growing more negative across time.
“we studied changes in adolescent technology use’s relation to mental health, and found that, overall, there was little to no evidence showing that technology is becoming more negatively associated with mental health over time.”
Quote in the paperSubstantial claim
Interpretationreasoning
With 2017 associations between zero and 0.15, an annual linear change of 0.01 probably does not yield meaningful real-world changes.
“In the context of technology use-mental health associations that ranged between zero and 0.15 in 2017, a yearly linear change of 0.01 is unlikely to translate to meaningful changes in associations outside the statistical model.”
Quote in the paperSubstantial claim
Interpretationreasoning
The observed effect sizes probably do not accurately capture any causal links between technology use and mental health, should such links exist.
“In light of this, the exact magnitudes of the relations observed here are unlikely to provide accurate estimates of any underlying causal relations between technology use and mental health, if any exist.”
Quote in the paperSubstantial claim
- Rests on an assumption: No suitable theory specifying causal relations between variables currently exists.
Interpretationreasoning
The study's parameter estimates, ranging from zero to about 0.15, are unlikely to represent practically meaningful associations with mental health.
“In those terms, our parameter estimates that ranged from zero to about 0.15, are not likely to indicate practically meaningful associations with mental health.”
Quote in the paperSubstantial claim
- Rests on an assumption: Large samples probably cause even tiny associations to have confidence intervals that exclude zero.
Study design and conductcitation
Using self-report data introduces distinctive difficulties.
“In addition to the complexities in determining causal relations, the self-report nature of the current data presents unique problems.”
Quote in the paperNot a substantial claim
Study design and conductown data
The analysis used between-person associations linking technology use and mental health.
“First, we studied the between-person relationships between technology use and mental health.”
Quote in the paperSubstantial claim
Interpretationown data
The study did not find strong evidence that the television-negative mental health relation was uniquely waning over long periods.
“so we did not obtain strong evidence that the relation between television watching and negative mental health outcomes was unique in waning over long periods of time.”
Quote in the paperSubstantial claim

May combine two claims. 24
Classified as probably not a substantial claim. 20
The quote only partly states this claim. 1

May combine two claims.
Findingown data
Changes in technology-mental health relations were not moderated by sex; none of the estimates credibly differed from zero.
“We also investigated whether changes in technology’s relations with mental health described in the bottom panel of Figure 2 were moderated by sex, but none of the estimates were credibly different from zero, suggesting that any changes—or lack thereof—over time were not different between boys and girls.”
Quote in the paperNot a substantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data
The association between emotional problems and social media increased over time.
“The association between emotional problems and social media had increased, but their association with TV had remained stable.”
Quote in the paperNot a substantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
May combine two claims.
Findingown data
Cross-sectional correlations suggested that changes in the technology-mental health relationship over time were plausible but likely differed by outcome and technology.
“These cross-sectional between-person relationships are shown in Figure 1, which suggested that changes in the relationship over time were plausible, but likely to differ between outcomes and technologies.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
Structural equation models replicated the main results, except that the 2017 TV-suicide association's 95% CI just excluded zero ([0.001, 0.026]).
“Those analyses replicated the above results, with the only exception that the 2017 TV – suicide association’s 95% CI just excluded zero ([0.001, 0.026]; see online analysis supplement).”
Quote in the paperNot a substantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
- The authors state this as an assumption: Relations between technology use and mental health were linear, and any changes in those relations were linear.
May combine two claims.
Findingown data
The relationships between technology use and mental health in the GAM analysis were complex and mostly curvilinear.
“As can be seen in Figure 3 (top panel), the technology use-mental health relations were complex and generally curvilinear.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
Depression links declined for both social media and television.
“Unexpectedly, both social media’s and television’s associations with depression, on the other hand, had decreased.”
Quote in the paperNot a substantial claim
May combine two claims.
Findingown data
The study's observed patterns conflicted with one another and lacked conceptual replication in related outcomes.
“because the observed patterns in the current study were contradictory to each other, and not conceptually replicated across the other related outcomes”
Quote in the paperSubstantial claim
May combine two claims.
Premisecitation
Observed associations usually come from between-person correlations, which make causal direction hard to determine and are vulnerable to confounding.
“the observed associations are typically based on between-persons correlations, which make determining causality and directionality difficult, and are susceptible to the influence of confounding observed or unobserved variables (Ophir et al., 2020).”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites Ophir et al., 2020
  Not checked in the free run.
May combine two claims.
Premisecitation
The literature on a negative link between digital technology engagement and mental health is mixed and rests on weak methods and data.
“Currently, the literature suggesting a negative link between digital technology engagement and mental health is decidedly mixed and grounded on suboptimal methodologies and data (Dickson et al., 2019; Odgers & Jensen, 2020).”
Quote in the paperSubstantial claim0 of 2 sources checked
- cites Dickson et al., 2019
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- cites Odgers & Jensen, 2020
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Premisecitation
Studies using more systematic methods have found that well-being-technology relations depend on gender, arbitrary analytic choices, and the exact variables included.
“Studies that have adopted more systematic approaches to estimating associations between well-being and technology engagement have shown that the resulting relations depend on gender, arbitrary analytic choices, and the exact variables included in the analyses (Bjerre-Nielsen et al., 2020; Jensen et al., 2019; Kreski et al., 2020; Orben et al., 2019).”
Quote in the paperSubstantial claim0 of 3 sources checked
- cites Bjerre-Nielsen et al., 2020
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- cites Jensen et al., 2019
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- cites Kreski et al., 2020
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Premisereasoning
Researchers have treated technology effects as fixed, so at least two time-dependent changes have not been systematically tested.
“because researchers have assumed that technology effects are fixed, at least two time-dependent changes have evaded systematic testing.”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
Premisenone given
Little research attention has been given to how a technology's effects may change as its affordances expand or as business models alter how adolescents use it.
“Yet little attention is paid to how a given technology’s effects might shift over time, as affordances expand, or the underlying business models drive designers to change how adolescents use them.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation
The claim that video games created a generation of violent criminals has been refuted.
“but this argument has since been refuted (Drummond et al., 2020; Ferguson et al., 2020).”
Quote in the paperNot a substantial claim0 of 2 sources checked
- cites Drummond et al., 2020
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- cites Ferguson et al., 2020
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Premisecitation
Comic books and television were blamed for predisposing adolescents to maladjustment and antisocial behaviour.
“the visually stimulating characteristics of comic books and television were implicated as factors predisposing adolescents to maladjustment and antisocial behaviour (Wertham, 1954).”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites Wertham, 1954
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Classified as probably not a substantial claim. May combine two claims.
Premisecitation
Reviews by academic, medical, and policy groups have pointed to low-quality evidence and the need for longitudinal research.
“Literature reviews by academic, medical, and policy collaborations have highlighted both the low-quality evidence in this space and the need for a longitudinal perspective (Appel et al., 2020; Hawkes, 2019; Viner et al., 2019).”
Quote in the paperSubstantial claim0 of 3 sources checked
- cites Appel et al., 2020
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- cites Hawkes, 2019
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- cites Viner et al., 2019
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Premisecitation
Most of this literature relies on self-reported technology use, which is biased and noisy and leads to inaccurate estimates of health and well-being relations.
“most of this literature is limited by its use of self-reports of technology use, which are known to be biased and noisy indicators of true amounts of engagement, and lead to inaccurate estimated relations between health and well-being (Johannes et al., 2020; Parry et al., 2020; Scharkow, 2016; Shaw et al., 2020).”
Quote in the paperNot a substantial claim0 of 3 sources checked
- cites Johannes et al., 2020
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- cites Parry et al., 2020
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- cites Scharkow, 2016
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Premisecitation
In the early 1900s, dime novels were accused of causing mania and risk-taking.
“the early twentieth century saw dime novels blamed for eliciting mania and risk taking (Furedi, 2015).”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites Furedi, 2015
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Premisecitation
Radio dramas were believed to make young listeners susceptible to poor health, sleep loss, and anxiety.
“the immersive nature of radio dramas was thought to make young listeners vulnerable to ill health, sleep loss, and anxiety (Preston, 1941).”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites Preston, 1941
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May combine two claims.
Premisecitation
Technologies are often treated as unitary causes of social change through technological determinism, and academics seldom treat them as dynamic when studying effects on young people.
“Technologies are often considered as unitary causes of change in society, through a process called technological determinism, and academics therefore rarely treat them as dynamic when trying to understand their effects on young and vulnerable people (Grimes et al., 2008; Orben, 2020).”
Quote in the paperNot a substantial claim0 of 2 sources checked
- cites Grimes et al., 2008
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- cites Orben, 2020
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Study design and conductown data
The US conduct and emotional problems subscales had moderate reliabilities (alphas .62 and .69).
“19,190 (con-duct) and 19,184 (emotional problems) 10 to 15-year olds rated their agreement on a three-point scale from “Not true” to “Certainly true” to at least one of these items, which indicated moderate reliabilities (alphas .62 and .69, respectively).”
Quote in the paperNot a substantial claim
May combine two claims.
Interpretationown data
The magnitudes of these relations were within the ranges of previous findings and are generally considered very small.
“The magnitudes of these relations were within the ranges of previous findings (that have mainly ignored differences between years), and are generally considered to be very small.”
Quote in the paperNot a substantial claim
Classified as probably not a substantial claim. May combine two claims.
Premisecitation
Recent analyses and reviews show that people who report more technology engagement also tend to report more mental health problems, but the reasons for these cross-sectional links are poorly understood.
“recent analyses and reviews have shown a trend whereby individuals who report greater technology engagement tend to also report higher levels of mental health problems, but the factors underlying these cross-sectional relationships still remain poorly understood (Appel et al., 2020).”
Quote in the paperSubstantial claim0 of 1 sources checked
- cites Appel et al., 2020
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Classified as probably not a substantial claim.
Interpretationreasoning
Because information about new digital media has been collected for only a relatively short time, firm conclusions about changes in their mental health associations may be premature.
“Information about new digital media has been collected for a relatively short time; drawing firm conclusions about changes in their associations with mental health may be premature.”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown data
MTF and US outcomes had low item-level missingness (complete responses: MTF = 95%, US = 96%).
“Outcomes in the MTF and US datasets showed low item-level missingness (complete responses: MTF = 95%, US = 96%); missing item values were ignored in computing the scale means.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data
Rows with missing sex were excluded (MTF: 4%, US: 0.02%, YRBS: 0.3%).
“Rows of data where the sex variable was missing were excluded (MTF: 4%, US: 0.02%, YRBS: 0.3%) to allow using sex as a moderator in our analyses below.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Interpretationreasoning
These shifts can shape changes over time in user motivations and in technology-mental health associations, and may cause some technologies' effects to rise or fall over long periods.
“These shifts have the potential to shape differences over time in user motivations and the associations between technology engagement and mental health, and could therefore cause certain technologies’ effects on mental health to increase or decrease over long periods of time.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data
The MTF depression scale had good reliability (alpha = .85).
“380,924 8th and 10th graders responded to at least one item on the scale, whose items provided good reliability (alpha = .85).”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
Premisecitation
Dark patterns and attention-demanding features could amplify social media's negative effects, while tools that empower or connect users could improve health and well-being.
“the addition of so called dark patterns—features that are designed to manipulate users to e.g. purchase items (Singer, 2016)—and attention demanding features that undermine users’ psychological autonomy could serve to magnify negative impacts of social media, whereas tools that empower or connect users in new ways could do the opposite and promote health and well-being (Lewis, 2017; Solon, 2017;”
Quote in the paperNot a substantial claim0 of 3 sources checked
- cites Lewis, 2017
  Not checked in the free run.
- cites Solon, 2017
  Not checked in the free run.
- cites Verduyn et al., 2017
  Not checked in the free run.
May combine two claims.
Interpretationown data
Overall, there was very little evidence that negative associations between technology and mental health increased over time, and some evidence pointed the other way.
“Overall, there was very little evidence for an increase in the negative associations between technology and mental health over time, and some evidence to the contrary.”
Quote in the paperSubstantial claim
- The authors state this as an assumption: Any change over time in the technology–mental health association was linear over the study period.
- The authors state this as an assumption: Relations between technology use and mental health were linear, and any changes in those relations were linear.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationreasoning
Material changes in how technologies affect people and societies may not appear as an obvious stepwise shift between successive technologies; subtle advances within one technological environment may produce large changes.
“material changes in how technologies affect individuals and societies may therefore not be marked by an obvious stepwise shift between two successive forms of technology, say from radio to television. Instead, more subtle advances within a single technological milieu might drive profound changes.”
Quote in the paperNot a substantial claim
May combine two claims.
Study design and conductown data
The study used three large nationally representative datasets from the US and UK, with a combined 430,561 participants.
“We focused on three large nationally representative datasets, from the United States and United Kingdom, with pertinent variables on adolescent mental health and technology engagement, and a combined total of 430,561 participants.”
Quote in the paperSubstantial claim
Classified as probably not a substantial claim.
Study design and conductreasoning
The study's models did not include covariates.
“We also did not include covariates in our models for two reasons.”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Study design and conductreasoning
The study, as with earlier literature, may blur distinctions between between-person and within-person associations and causal mechanisms.
“In addition, it is important to note that this work, along with previous literature on this topic, to some extent risks conflating between- and within-person associations and causal mechanisms.”
Quote in the paperNot a substantial claim
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Interpretationown data
The observed shifts-more social media-emotional problems and less technology-depression-suggest emerging technologies' roles are changing and justify a more dynamic view of these links.
“Nevertheless, the observed patterns of change — the increased association between social media use and emotional problems, and decreased association between technology engagement and depression — hint at the changing roles of emerging technologies in young people’s lives and underlines the scientific value of considering a more dynamic picture of their associations with mental health.”
Quote in the paperNot a substantial claim
The quote only partly states this claim.
Interpretationown data
Any temporal change in effects is better seen as gradual drift, not a rapid shift.
“showing that if effects are changing over time, this change is better characterized as a slow drift rather than a rapid shift.”
Quote in the paperSubstantial claim
May combine two claims.
Premisecitation
Longitudinal work has sometimes shown mental health problems predicting smartphone use instead of the reverse, or bidirectional links.
“some longitudinal studies have found the opposite, whereby mental health problems predict smartphone use, rather than phone use predicting mental health problems (Bado et al., 2020), or found bidirectional relationships (Orben et al., 2019).”
Quote in the paperNot a substantial claim0 of 2 sources checked
- cites Bado et al., 2020
  Not checked in the free run.
- cites Orben et al., 2019
  Not checked in the free run.
May combine two claims.
Premisecitation
Research on this topic shows self-reported technology use is systematically biased and weakly related to objective measures.
“In studies of this topic, self-report measures of technology use are consistently biased and are not highly correlated with objective use (Johannes et al., 2020; Parry et al., 2020; Scharkow, 2016).”
Quote in the paperSubstantial claim0 of 3 sources checked
- cites Johannes et al., 2020
  Not checked in the free run.
- cites Parry et al., 2020
  Not checked in the free run.
- cites Scharkow, 2016
  Not checked in the free run.
May combine two claims.
Interpretationown data
The data did not support either the notion that older, less-worried-about technologies are becoming less harmful or that currently worrisome technologies are becoming more harmful.
“Overall, the ideas that technologies we no longer worry about are becoming less harmful or that technologies we worry the most about now are becoming more harmful were not supported in the data we analysed.”
Quote in the paperSubstantial claim
Probably not a substantial claim: may not pass S2 (checkable).
Premisecitation
Choosing covariates ought to follow a strong theory that lays out causal links among variables.
“First, the selection of covariates should be guided by a strong theory that specifies the causal relations between variables (Rohrer, 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked
- cites Rohrer, 2018
  Not checked in the free run.

39 of 39

The authors state this as an assumption.
Any change over time in the technology–mental health association was linear over the study period.
“We adopted the simplifying assumption that any change to that relationship had been linear over the time frame studied.”
The authors state this as an assumption.
Relations between technology use and mental health were linear, and any changes in those relations were linear.
“In our focal analyses we assumed linear relations between technology use and mental health and assumed that any changes to those relations would be linear.”
The authors state this as an assumption.
Social media and similar digital technologies could have increasingly negative mental health effects over time because of their dynamic nature.
“Therefore, it remains a reasonable, yet untested, assumption that their possible negative influence on mental health could be magnified over time by virtue of their dynamic nature.”
The paper relies on this without support.
No suitable theory specifying causal relations between variables currently exists.
“Currently, no good candidates for such a theory exist, and it was not our purpose here to offer one.”
The paper relies on this without support.
Large samples probably cause even tiny associations to have confidence intervals that exclude zero.
“because the large sample sizes are likely to make even small relations’ confidence intervals exclude zero”
The paper relies on this without support.
Understanding of social media and digital devices is constrained by how recently they appeared.
“In the context of older technologies, such as TV, our knowledge of social media and digital device use is necessarily limited by their comparatively brief existence.”

6 of 6

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?

Few existing studies feature longitudinal time frames and account for additional demographic factors, particularly race/ethnicity and sex.
“For instance, few existing studies feature longitudinal time frames and account for additional demographic factors, particularly race/ethnicity and sex [12, 75, 76].”
From Screen time and mental health: a prospective analysis of the Adolescent Brain Cognitive Development (ABCD) Study (2024) · cites this paper as [76]

lavaan : An R Package for Structural Equation Modeling
Rosseel, Y. (2012) · Journal of Statistical Software · doi:10.18637/jss.v048.i02 · Cited by 27,955 · cited 1× · see citing works
“We further investigated the robustness of our results with respect to analysis strategy by estimating analogous structural equation models in which each mental health outcome was treated as a latent variable indicated by the items discussed above (Rosseel, 2012).”
Method
Generalized Additive Models: An Introduction with R
Wood, S. N. (2017) · doi:10.1201/9781315370279 · Cited by 13,852 · see citing works
Data Analysis Using Regression and Multilevel/Hierarchical Models
Gelman, A., & Hill, J. (2006) · doi:10.1017/cbo9780511790942 · Cited by 13,597 · see citing works
brms : An R Package for Bayesian Multilevel Models Using Stan
Bürkner, P.-C. (2017) · Journal of Statistical Software · doi:10.18637/jss.v080.i01 · Cited by 9,476 · cited 1× · see citing works
“All models were estimated within the Bayesian framework using minimally informative priors (see online analysis supplement); we report posterior means and quantiles as parameters’ point estimates and credibility intervals (CrIs; Bürkner, 2017; Carpenter et al., 2017).”
Method
Stan : A Probabilistic Programming Language
Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., & Riddell, A. (2017) · Journal of Statistical Software · doi:10.18637/jss.v076.i01 · Cited by 7,754 · cited 1× · see citing works
“All models were estimated within the Bayesian framework using minimally informative priors (see online analysis supplement); we report posterior means and quantiles as parameters’ point estimates and credibility intervals (CrIs; Bürkner, 2017; Carpenter et al., 2017).”
Method
Youth risk behavior surveillance-United States, 2017
Kann, L., McManus, T., Harris, W. A., Shanklin, S. L., Flint, K. H., Queen, B., Lowry, R., Chyen, D., Whittle, L., Thornton, J., et al. (2018) · MMWR. Surveillance Summaries · doi:10.15585/mmwr.ss6708a1 · Cited by 2,502 · cited 2× · see citing works
“YRBS is a biennial survey of ninth to 12th graders in the United States and has been conducted since 1991 by the U.S. Centers for Disease Control and Prevention (Kann, 2018).”
Method
Using the strengths and difficulties questionnaire (SDQ) to screen for child psychiatric disorders in a community sample
Goodman, R., Ford, T., Simmons, H., Gatward, R., & Meltzer, H. (2000) · British Journal of Psychiatry · doi:10.1192/bjp.177.6.534 · Cited by 1,818 · see citing works
Monitoring the Future national survey results on drug use, 1975-2017: Volume I, secondary school students
Miech, R., Johnston, L. A., O'Malley, P., Bachman, J., Schulenberg, J., & Patrick, M. E. (2005) · doi:10.3998/2027.42/146530 · Cited by 1,771 · see citing works
Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time
Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018) · Clinical Psychological Science · doi:10.1177/2167702617723376 · Cited by 1,705 · cited 1× · see citing works
“Depression was measured in the MTF data set with six items that have been used in previous research (Miech et al., 2020; Newcomb et al., 1981; Twenge et al., 2018), although not always in a consistent manner (Orben & Przybylski, 2019a, see especially Supplementary Table 6).”
Method
It's complicated: the social lives of networked teens
(2014) · Choice Reviews Online · doi:10.5860/choice.51-7042 · Cited by 1,607 · see citing works
The association between adolescent well-being and digital technology use
Orben, A., & Przybylski, A. K. (2019) · Nature Human Behaviour · doi:10.1038/s41562-018-0506-1 · Cited by 1,500 · cited 4× · see citing works
“Depression was measured in the MTF data set with six items that have been used in previous research (Miech et al., 2020; Newcomb et al., 1981; Twenge et al., 2018), although not always in a consistent manner (Orben & Przybylski, 2019a, see especially Supplementary Table 6).”
BackgroundMethodResultInfluentialSelf-citation
Do social network sites enhance or undermine subjective well-being? A critical review
Verduyn, P., Ybarra, O., Résibois, M., Jonides, J., & Kross, E. (2017) · Social Issues and Policy Review · doi:10.1111/sipr.12033 · Cited by 1,209 · see citing works
Annual Research Review: Adolescent mental health in the digital age: facts, fears, and future directions.
Odgers, C. L., & Jensen, M. R. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13190 · Cited by 1,189 · cited 1× · see citing works
“Currently, the literature suggesting a negative link between digital technology engagement and mental health is decidedly mixed and grounded on suboptimal methodologies and data (Dickson et al., 2019; Odgers & Jensen, 2020).”
Background
Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data
Rohrer, J. M. (2018) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245917745629 · Cited by 1,002 · cited 1× · see citing works
“First, the selection of covariates should be guided by a strong theory that specifies the causal relations between variables (Rohrer, 2018).”
Background
A Large-Scale Test of the Goldilocks Hypothesis: Quantifying the Relations Between Digital-Screen Use and the Mental Well-Being of Adolescents
Przybylski, A. K., & Weinstein, N. (2017) · Psychological Science · doi:10.1177/0956797616678438 · Cited by 890 · cited 1× · see citing works
“Specifically, the former assumption might be inaccurate because relations between technology use and mental health are sometimes better described by a quadratic function (Przybylski & Weinstein, 2017).”
BackgroundSelf-citation
A systematic review and meta-analysis of discrepancies between logged and self-reported digital media use
Parry, D. A., Davidson, B. I., Sewall, C. J. R., Fisher, J. T., Mieczkowski, H., & Quintana, D. S. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01117-5 · Cited by 793 · see citing works
Social media use and adolescent mental health: Findings from the UK Millennium Cohort Study
Kelly, Y., Zilanawala, A., Booker, C., & Sacker, A. (2018) · EClinicalMedicine · doi:10.1016/j.eclinm.2018.12.005 · Cited by 740 · cited 1× · see citing works
“Because previous literature has highlighted important differences between boys and girls in novel technolo-gies’ associations with adolescent mental health (Kelly et al., 2018; Kreski et al., 2021), we also investigated the moderating role of sex as a supplementary analysis.”
Background
Untitled work
(2019) · Cited by 633 · see citing works
Violent Video Games and Hostile Expectations: A Test of the General Aggression Model
Bushman, B. J., & Anderson, C. A. (2002) · Personality and Social Psychology Bulletin · doi:10.1177/014616702237649 · Cited by 615 · cited 1× · see citing works
“Most recently, video games were suggested to have produced a generation of violent criminals (Bushman & Anderson, 2002), but this argument has since been refuted (Drummond et al., 2020; Ferguson et al., 2020).”
Background
Social media’s enduring effect on adolescent life satisfaction
Orben, A., Dienlin, T., & Przybylski, A. K. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1902058116 · Cited by 485 · cited 2× · see citing works
“In fact, some longitudinal studies have found the opposite, whereby mental health problems predict smartphone use rather than phone use predicting mental health problems (Bado et al., 2020), or found bidirectional relationships (Orben et al., 2019).”
BackgroundSelf-citation
Screens, Teens, and Psychological Well-Being: Evidence From Three Time-Use-Diary Studies
Orben, A., & Przybylski, A. K. (2019) · Psychological Science · doi:10.1177/0956797619830329 · Cited by 414 · cited 4× · see citing works
“Depression was measured in the MTF data set with six items that have been used in previous research (Miech et al., 2020; Newcomb et al., 1981; Twenge et al., 2018), although not always in a consistent manner (Orben & Przybylski, 2019a, see especially Supplementary Table 6).”
BackgroundMethodResultInfluentialSelf-citation
The Accuracy of Self-Reported Internet Use—A Validation Study Using Client Log Data
Scharkow, M. (2016) · Communication Methods and Measures · doi:10.1080/19312458.2015.1118446 · Cited by 408 · cited 2× · see citing works
“…validity, they might be poor representations of the actual state of affairs (Shaw et al., 2020): In studies of this topic, self-report measures of technology use are consistently biased and are not highly correlated with objective use (Johannes et al., 2020; Parry et al., 2020; Scharkow, 2016).”
Background
A multidimensional assessment of stressful life events among adolescents: Derivation and correlates
Newcomb, M. D., Huba, G. J., & Bentler, P. M. (1981) · Journal of Health and Social Behavior · doi:10.2307/2136681 · Cited by 359 · cited 1× · see citing works
“Depression was measured in the MTF data set with six items that have been used in previous research (Miech et al., 2020; Newcomb et al., 1981; Twenge et al., 2018), although not always in a consistent manner (Orben & Przybylski, 2019a, see especially Supplementary Table 6).”
Method
Video game play is positively correlated with well-being
Johannes, N., Vuorre, M., & Przybylski, A. K. (2021) · Royal Society Open Science · doi:10.1098/rsos.202049 · Cited by 330 · cited 2× · see citing works
“…validity, they might be poor representations of the actual state of affairs (Shaw et al., 2020): In studies of this topic, self-report measures of technology use are consistently biased and are not highly correlated with objective use (Johannes et al., 2020; Parry et al., 2020; Scharkow, 2016).”
BackgroundSelf-citation
The Sisyphean Cycle of Technology Panics
Orben, A. (2020) · Perspectives on Psychological Science · doi:10.1177/1745691620919372 · Cited by 316 · cited 5× · see citing works
“First, when fears emerge about a new technology, worries about previous technologies are largely abandoned without an agreement on—or good data indicating—whether, why, or how the previous technologies were or were not harmful (Grimes et al., 2008; Orben, 2020).”
BackgroundMethodInfluentialSelf-citation
Cyberbullying and children and young people’s mental health: A systematic map of systematic reviews
Kwan, I., Dickson, K., Richardson, M., MacDowall, W., Burchett, H., Stansfield, C., Brunton, G., Sutcliffe, K., & Thomas, J. (2020) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2019.0370 · Cited by 291 · see citing works
Are Social Media Ruining Our Lives? A Review of Meta-Analytic Evidence
Appel, M., Marker, C., & Gnambs, T. (2020) · Review of General Psychology · doi:10.1177/1089268019880891 · Cited by 290 · cited 2× · see citing works
“Literature reviews by academic, medical, and policy collaborations have highlighted both the low-quality evidence in this space and the need for a longitudinal perspective (Appel et al., 2020; Hawkes, 2019; Viner et al., 2019).”
Background
Young Adolescents’ Digital Technology Use and Mental Health Symptoms: Little Evidence of Longitudinal or Daily Linkages
Jensen, M., George, M. J., Russell, M. R., & Odgers, C. L. (2019) · Clinical Psychological Science · doi:10.1177/2167702619859336 · Cited by 242 · cited 1× · see citing works
“…to estimating associations between well-being and technology engagement have shown that the resulting relations depend on sex, arbitrary analytic choices, and the exact variables included in the analyses (Bjerre-Nielsen et al., 2020; Jensen et al., 2019; Kreski et al., 2021; Orben et al., 2019).”
Background
Recommendations for Increasing the Transparency of Analysis of Preexisting Data Sets
Weston, S. J., Ritchie, S. J., Rohrer, J. M., & Przybylski, A. K. (2019) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245919848684 · Cited by 206 · cited 1× · see citing works
“In secondary data analyses, these problems are compounded by a general lack of adherence to consistent standards (Weston et al., 2019), which threat-ens the validity and robustness of reported associations because the many choices leading to a reported analysis can engender misrepresentative…”
BackgroundSelf-citation
Do longitudinal studies support long-term relationships between aggressive game play and youth aggressive behaviour? A meta-analytic examination
Drummond, A., Sauer, J. D., & Ferguson, C. J. (2020) · Royal Society Open Science · doi:10.1098/rsos.200373 · Cited by 106 · cited 1× · see citing works
“Most recently, video games were suggested to have produced a generation of violent criminals (Bushman & Anderson, 2002), but this argument has since been refuted (Drummond et al., 2020; Ferguson et al., 2020).”
Background
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 · cited 3× · see citing works
“Because previous literature has highlighted important differences between boys and girls in novel technolo-gies’ associations with adolescent mental health (Kelly et al., 2018; Kreski et al., 2021), we also investigated the moderating role of sex as a supplementary analysis.”
Background
Media Violence and Aggression: Science and Ideology
Grimes, T., Anderson, J. A., & Bergen, L. (2007) · Cited by 95 · see citing works
Reexamining the Findings of the American Psychological Association’s 2015 Task Force on Violent Media: A Meta-Analysis
Ferguson, C. J., Copenhaver, A., & Markey, P. M. (2020) · Perspectives on Psychological Science · doi:10.1177/1745691620927666 · Cited by 95 · cited 1× · see citing works
“Most recently, video games were suggested to have produced a generation of violent criminals (Bushman & Anderson, 2002), but this argument has since been refuted (Drummond et al., 2020; Ferguson et al., 2020).”
Background
Monitoring the Future national survey results on drug use, 1975-2018: Volume I, Secondary school students
Miech, R., Johnston, L., O'Malley, P., Bachman, J., Schulenberg, J., & Patrick, M. (2019) · doi:10.3998/2027.42/150622 · Cited by 90
Contextualising the link between adolescents’ use of digital technology and their mental health: a multi‐country study of time spent online and life satisfaction
Kardefelt‐Winther, D., Rees, G., & Livingstone, S. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13280 · Cited by 67 · see citing works
A Systematic Review and Meta-Analysis of Discrepancies Between Logged and Self- Reported Digital Media UsePreprint
Parry, D. A., Davidson, B. I., Sewall, C. J. R., et al. (2020) · doi:10.31234/osf.io/f6xvz · Cited by 64 · see citing works
Prospective Investigation of Video Game Use in Children and Subsequent Conduct Disorder and Depression Using Data from the Avon Longitudinal Study of Parents and Children
Etchells, P. J., Gage, S. H., Rutherford, A. D., & Munafo, M. R. (2016) · PLoS ONE · doi:10.1371/journal.pone.0147732 · Cited by 61 · see citing works
Quantifying smartphone ‘use’: Choice of measurement impacts relationships between ‘usage’ and health
Shaw, H., Ellis, D. A., Geyer, K., Davidson, B. I., Ziegler, F. V., & Smith, A. (2020) · doi:10.31234/osf.io/mpxra · Cited by 59 · see citing works
Using Anchor-Based Methods to Determine the Smallest Effect Size of InterestPreprint
Anvari, F., & Lakens, D. (2019) · doi:10.31234/osf.io/syp5a · Cited by 51 · cited 1× · see citing works
“Previous studies have shown that in the case of subjective well-being scales, effects of about a half standard deviation are required for people to subjectively experience change (Anvari & Lakens, 2019).”
Background
Video game play is positively correlated with well-being
(2020) · doi:10.31234/osf.io/qrjza · Cited by 49 · see citing works
Self-citation
The Negative Effect of Smartphone Use on Academic Performance May Be Overestimated: Evidence From a 2-Year Panel Study
Bjerre-Nielsen, A., Andersen, A., Minor, K., & Lassen, D. D. (2020) · Psychological Science · doi:10.1177/0956797620956613 · Cited by 40 · see citing works
New-Media Screen Time Is Not (Necessarily) Linked to Depression: Comments on Twenge, Joiner, Rogers, and Martin (2018)
Ophir, Y., Lipshits‐Braziler, Y., & Rosenberg, H. (2019) · Clinical Psychological Science · doi:10.1177/2167702619849412 · Cited by 36 · cited 1× · see citing works
“That is, the observed associations are typically based on between-persons correlations, which make determining causality and directionality difficult and are susceptible to the influence of confounding observed or unobserved variables (Ophir et al., 2020).”
Background
Children's reactions to movie horrors and radiocrime
Preston, M. I. (1941) · The Journal of Pediatrics · doi:10.1016/s0022-3476(41)80059-6 · Cited by 35 · cited 1× · see citing works
“young listeners vulnerable to ill health, sleep loss, and anxiety (Preston, 1941).”
Background
Understanding Society: Waves 1-9, 2009-2018 and Harmonised BHPS: Waves 1-18, 1991-2009
University Of Essex, I. F. S. (2020) · UK Data Archive · doi:10.5255/ukda-sn-6614-13 · Cited by 27 · see citing works
CMO report is unable to shed light on impact of screen time and social media on children’s health
Hawkes, N. (2019) · BMJ · doi:10.1136/bmj.l643 · Cited by 13 · cited 1× · see citing works
“Literature reviews by academic, medical, and policy collaborations have highlighted both the low-quality evidence in this space and the need for a longitudinal perspective (Appel et al., 2020; Hawkes, 2019; Viner et al., 2019).”
Background
Links between screen use and depressive symptoms in adolescents over 16 years: Is there evidence for increased harm?
Ferguson, C. J. (2021) · Developmental Science · doi:10.1111/desc.13008 · Cited by 13 · cited 1× · see citing works
“…static would have substantial implications for regulation, and this potential is often discussed in public conversation, the idea has garnered only limited attention in empirical studies, which have typically treated the relation as invariant over time (but see Ferguson, 2021; Kreski et al., 2021).”
Background
Screen time and psychopathology: investigating directionality using cross-lagged panel models
Bado, P., Schäfer, J., Simioni, A., Bressan, R. A., Gadelha, A., Pan, P. M., Miguel, E. C., Rohde, L. A., & Salum, G. A. (2020) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-020-01675-5 · Cited by 9 · see citing works
Screen time and psychopathology: investigating directionality using cross-lagged panel modelsPreprint
Bado, P., Schäfer, J., Simioni, A., Bressan, R. A., Gadelha, A., Pan, P. M., Miguel, E. C., Rohde, L. A., & Salum, G. A. (2020) · doi:10.31234/osf.io/q8tur · Cited by 3 · see citing works

Flagged first, then by citations

1 of the 49 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

Furedi F., 2015, History Today, 65, 46
Viner R., 2019, The health impacts of screen time: A guide for clinicians and parents
Wertham F., 1954, Seduction of the innocent

Sorted by citations

Problematic Social Media Use in Adolescents and Young Adults: Systematic Review and Meta-analysis.
Shannon, H., Bush, K., Villeneuve, P. J., Hellemans, K. G., & Guimond, S. (2022) · JMIR Mental Health · doi:10.2196/33450 · Cited by 593 · see citing works
“In order to thoroughly understand the direct implications of problematic social media use, longitudinal studies could aid in providing more causational conclusions, as cross-sectional methodology is limited in its ability to draw conclusions beyond correlation [62].”
Background
Annual Research Review: Sex, gender, and internalizing conditions among adolescents in the 21st century – trends, causes, consequences
Keyes, K. M., & Platt, J. M. (2024) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13864 · Cited by 253 · see citing works
Understanding Social Media Literacy: A Systematic Review of the Concept and Its Competences
Polanco-Levicán, K., & Salvo-Garrido, S. I. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19148807 · Cited by 131 · see citing works
“It is important to note that the use of social media is not negative in itself as it can increase social capital, foster friendships and reduce feelings of loneliness; however, it depends on the user’s characteristics and how the different platforms are used [28,29].”
Background
Screen time and mental health: a prospective analysis of the Adolescent Brain Cognitive Development (ABCD) Study
Nagata, J. M., Al-Shoaibi, A. A. A., Leong, A. W., Zamora, G., Testa, A., Ganson, K. T., & Baker, F. C. (2024) · BMC Public Health · doi:10.1186/s12889-024-20102-x · Cited by 103 · see citing works
“Additionally, investigating these potential moderators may improve the identification of at-risk populations and aid in the development of more targeted interventions [51, 76].”
Background
From “online brains” to “online lives”: understanding the individualized impacts of Internet use across psychological, cognitive and social dimensions
Firth, J., Torous, J. B., López‐Gil, J. F., Linardon, J., Milton, A. C., Lambert, J. D., Smith, L., Jarić, I., Fabian, H., Vancampfort, D., et al. (2024) · World Psychiatry · doi:10.1002/wps.21188 · Cited by 99 · see citing works
“…a large-scale epidemiological research 12 synthesized data from reviews, meta-analyses and cohort studies to assess digital technology’s correlation with depression and anxiety, and a robust analysis of these relationships in adolescents was conducted across multiple national datasets 13 .”
Background
Social media mindsets: a new approach to understanding social media use and psychological well-being
Lee, A. Y., & Hancock, J. T. (2023) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmad048 · Cited by 82 · see citing works
Developing digital resilience: An educational intervention improves elementary students’ response to digital challenges
Lee, A. Y., & Hancock, J. T. (2023) · Computers and Education Open · doi:10.1016/j.caeo.2023.100144 · Cited by 70 · see citing works
Structure and trends of externalizing and internalizing psychiatric symptoms and gender differences among adolescents in the US from 1991 to 2018
Askari, M. S., Rutherford, C. G., Mauro, P. M., Kreski, N. T., & Keyes, K. M. (2021) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-021-02189-4 · Cited by 68 · see citing works
Time spent on social media among the least influential factors in adolescent mental health: preliminary results from a panel network analysis
Panayiotou, M., Black, L., Carmichael-Murphy, P., Qualter, P., & Humphrey, N. (2023) · Nature Mental Health · doi:10.1038/s44220-023-00063-7 · Cited by 62 · see citing works
Objective, subjective, and accurate reporting of social media use: No evidence that daily social media use correlates with personality traits, motivational states, or well-being.
Johannes, N., Nguyen, T.-V. T., Weinstein, N., & Przybylski, A. K. (2021) · Technology Mind and Behavior · doi:10.1037/tmb0000035 · Cited by 53 · see citing works
Self-citation
Toy story or children story? Putting children and their rights at the forefront of the artificial intelligence revolution
Fosch-Villaronga, E., van der Hof, S., Lutz, C., & Tamò-Larrieux, A. (2023) · AI & SOCIETY · doi:10.1007/s00146-021-01295-w · Cited by 54 · see citing works
Smartphone screen time reduction improves mental health: a randomized controlled trial
Pieh, C., Humer, E. C., Hoenigl, A., Schwab, J., Mayerhofer, D., Dale, R., & Haider, K. (2025) · BMC Medicine · doi:10.1186/s12916-025-03944-z · Cited by 64 · see citing works
“These results fit with the results of a study, showing that a five-day abstinence from Face-book led to lower cortisol levels [54].”
No effect of different types of media on well-being
Johannes, N., Dienlin, T., Bakhshi, H., & Przybylski, A. K. (2022) · Scientific Reports · doi:10.1038/s41598-021-03218-7 · Cited by 42 · see citing works
Self-citation
Stress and Mood Associations With Smartphone Use in University Students: A 12-Week Longitudinal Study
Bradley, A. H. M., & Howard, A. L. (2023) · Clinical Psychological Science · doi:10.1177/21677026221116889 · Cited by 49 · see citing works
“Of the studies making such claims, the vast majority rely on self-report measures to quantify types of screen use—now shown to be highly variable, biased, and unreliable (David et al., 2018; Parry et al., 2021; Vuorre et al., 2021).”
Background
Screen media activity in youth: A critical review of mental health and neuroscience findings
Paulus, M. P., Zhao, Y., Potenza, M. N., Aupperle, R. L., Bagot, K. S., & Tapert, S. F. (2023) · Journal of Mood and Anxiety Disorders · doi:10.1016/j.xjmad.2023.100018 · Cited by 44 · see citing works
“Some researchers argue that impacts on affective well-being are generally small and mostly based on use versus non-use, rather than time spent with a medium [18,38].”
Screen time and suicidal behaviors among U.S. children 9–11 years old: A prospective cohort study
Chu, J., Ganson, K. T., Baker, F. C., Testa, A. M., Jackson, D. B., Murray, S. B., & Nagata, J. M. (2023) · Preventive Medicine · doi:10.1016/j.ypmed.2023.107452 · Cited by 42 · see citing works
Relations between academic boredom, academic achievement, ICT use, and teacher enthusiasm among adolescents
Borgonovi, F., Pokropek, M., & Pokropek, A. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104807 · Cited by 54 · see citing works
“…effects of ICT use on key outcomes for adolescence such as academic achievement, psychological well-being and social connectedness, the increasing use of ICT among children has spurred growing anxieties among educators, politicians, and parents (Orben, 2020; Vuorre, Orben, & Przybylski, 2021).”
Background
From social media to artificial intelligence: improving research on digital harms in youth
Mansfield, K. L., Ghai, S., Hakman, T., Ballou, N., Vuorre, M., & Przybylski, A. K. (2025) · The Lancet Child & Adolescent Health · doi:10.1016/s2352-4642(24)00332-8 · Cited by 46 · see citing works
Self-citation
Disconnection More Problematic for Adolescent Self-Esteem than Heavy Social Media Use: Evidence from Access Inequalities and Restrictive Media Parenting in Rural America
Hampton, K. N., & Shin, I. (2022) · Social Science Computer Review · doi:10.1177/08944393221117466 · Cited by 35 · see citing works
“There is little evidence that this relationship has increased over time (Vuorre et al., 2021).”
Background
Adolescents' mental health in the social‐media era: The role of offline and online need‐based experiences
de Casteele, M. V., Flamant, N., Ponnet, K. S., Soenens, B., Hees, V. V., & Vansteenkiste, M. (2023) · Journal of Adolescence · doi:10.1002/jad.12286 · Cited by 41 · see citing works
Estimating the association between Facebook adoption and well-being in 72 countries
Vuorre, M., & Przybylski, A. K. (2023) · Royal Society Open Science · doi:10.1098/rsos.221451 · Cited by 34 · see citing works
Self-citation
A Systematic Review of Structural and Functional MRI Studies Investigating Social Networking Site Use
Wadsley, M. G., & Ihssen, N. (2023) · Brain Sciences · doi:10.3390/brainsci13050787 · Cited by 34 · see citing works
“Of concern is that SNS use has been linked to reduced well-being and an increase in mental health disorders, particularly in younger populations [4–6], although such findings are the subject of debate [7,8].”
Background
Association between smartphone usage and health outcomes of adolescents: A propensity analysis using the Korea youth risk behavior survey
Cha, J. H., Choi, Y., Ryu, S., & Moon, J. (2023) · PLoS ONE · doi:10.1371/journal.pone.0294553 · Cited by 34 · see citing works
Psychological and Emotional Effects of Digital Technology on Digitods (14–18 Years): A Systematic Review
Limone, P., & Toto, G. A. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.938965 · Cited by 33 · see citing works
Twitter (X) use predicts substantial changes in well-being, polarization, sense of belonging, and outrage
de Mello, V. O., Cheung, F., & Inzlicht, M. (2022) · doi:10.31234/osf.io/4x5em · Cited by 25 · see citing works
The light, the dark, and everything else: making sense of young people's digital gaming
Meriläinen, M., & Ruotsalainen, M. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1164992 · Cited by 25 · see citing works
“…of young people’s agency in relation to diﬀerent media have long been a core topic in discussions of media literacy (e.g., Buckingham, 1998; Hobbs, 2011) and are central to the contemporary debate on the role of digital media in young people’s lives (e.g., Granic et al., 2020; Vuorre et al., 2021).”
Social Media and Adolescent Mental Health
Yue, Z., & Rich, M. (2023) · Current Pediatrics Reports · doi:10.1007/s40124-023-00298-z · Cited by 30 · see citing works
“) [32] and Kreski et al. (2020) [33].”
Excessive smartphone use and addiction: When harms start outweighing benefits
Larsen, H., Wiers, R. W. H. J., Su, S., & Cousijn, J. (2022) · Addiction · doi:10.1111/add.16060 · Cited by 26 · see citing works
Twitter (X) use predicts substantial changes in well-being, polarization, sense of belonging, and outrage
de Mello, V. O., Cheung, F., & Inzlicht, M. (2024) · Communications Psychology · doi:10.1038/s44271-024-00062-z · Cited by 35 · see citing works
“To address the limitations of prior social media studies (e.g., cross-sectional methods and retrospective self-reports) 24,44 ), we conduct an experience sampling study.”
A taxonomy of social media for learning
Demir, M. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105091 · Cited by 35 · see citing works
Exploring the relationship between personality, decision-making styles, and problematic smartphone use
Urieta, P., Sorrel, M., Aluja, A., Balada, F., Lacomba, E., & García, L. F. (2022) · Current Psychology · doi:10.1007/s12144-022-02731-w · Cited by 16 · see citing works
Associations of active and passive smartphone use with measures of youth mental health during the COVID-19 pandemic
Marin-Dragu, S., Forbes, A., Sheikh, S., Iyer, R. S., dos Santos, D. P., Alda, M., Hájek, T., Uher, R., Wozney, L., Paulovich, F. V., et al. (2023) · Psychiatry Research · doi:10.1016/j.psychres.2023.115298 · Cited by 21 · see citing works
General Versus Vocational Education in High School: Cross‐Sectional Associations with Student's Health
Coledam, D. H. C., Frotta, B. M., & Ré, A. H. N. (2022) · Journal of School Health · doi:10.1111/josh.13165 · Cited by 18 · see citing works
The Impact of YouTube on Loneliness and Mental Health
Balcombe, L., & Leo, D. D. (2023) · Informatics · doi:10.3390/informatics10020039 · Cited by 24 · see citing works
“However, there is no evidence to suggest an association between adolescents’ digital technology use and an increase in mental health problems [74].”
Background
Social Media as Source of Information, Stress Symptoms, and Burden Caused by Coronavirus (COVID-19)
Brailovskaia, J., Margraf, J., & Schneider, S. (2021) · European Psychologist · doi:10.1027/1016-9040/a000452 · Cited by 13 · see citing works
“Furthermore, it has been emphasized that overall the effects of digital technology use are assessed for an only relatively short time interval, and therefore, conclusions on its potential negative effects and its associations with well-being might be premature (Vuorre et al., 2021).”
Background
Social Media and Subjective Well-Being: The Moderating Role of Personality Traits
Alphenaar, L. E. V., Shiner, R. L., Arana, C. C., & Prinzie, P. (2025) · Journal of Happiness Studies · doi:10.1007/s10902-025-00898-0 · Cited by 18 · see citing works
“…), and life satisfaction (Valenzuela et al., 2009 ), whereas others highlight negative outcomes, such as mental health difficulties (McGorry et al., 2024 ; Rasmussen et al., 2020 ; Vuorre et al., 2021 ) and lower subjective well-being (Brooks, 2015 ; Marttila et al., 2021 ; Wirtz et al., 2020 ).”
What’s the problem with “screen time”? A content analysis of dominant voices and worries in three years of national print media
Størup, J. O., & Lieberoth, A. (2022) · Convergence The International Journal of Research into New Media Technologies · doi:10.1177/13548565211065299 · Cited by 17 · see citing works
“…due to new technologies historically raise questions, especially among parents and caregivers (Downes, 1999; Drotner, 1999; Leick, 2019; Vuorre et al., 2021; Willett, 2015) because “the notion of the ‘child’ acts both as a nostalgic and futuristic device through which societal changes…”
Background
Parental monitoring of adolescent social media use: relations with adolescent mental health and self-perception
Barry, C. T., & Kim, H. (2023) · Current Psychology · doi:10.1007/s12144-023-04434-2 · Cited by 17 · see citing works
“instance, although social media use predicted depressive symptoms in a cross-sectional study (Twenge et al., 2018), this relation has not consistently been evident in longitudinal studies (Coyne et al., 2020 ; Heffer et al., 2019; Vuorre et al., 2021).”
How does mobile social media use associate with adolescents’ depression? The mediating role of psychological security and its gender difference
Kong, F., Deng, H., Meng, S., & Ge, Y. (2022) · Current Psychology · doi:10.1007/s12144-022-03880-8 · Cited by 20 · see citing works
A scoping review of current research on social media use among children and adolescents
Jungselius, B. (2024) · Discover Psychology · doi:10.1007/s44202-024-00226-2 · Cited by 16 · see citing works
Enterprise Human Resource Management Model by Artificial Intelligence Digital Technology
Jiaping, Y. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/6186811 · Cited by 15 · see citing works
“Tese functions include the formulation of corporate human resource strategies, employee recruitment and selection, training and development, performance management, employee relationship management, and employee safety and health management [2].”
Background
Retracted
Moderating Effects of Digital Citizenship on Problematic Digital Media Use and Children's Happiness: A Cross‐Sectional Study
Si, E., & Lee, G. (2022) · Journal of School Health · doi:10.1111/josh.13275 · Cited by 13 · see citing works
Usage of digital technology in improving the mental health of workers on construction sites
Nelumdeniya, A. U., Perera, B. A. K. S., & Gimhani, K. D. M. (2023) · Construction Innovation · doi:10.1108/ci-08-2022-0214 · Cited by 13 · see citing works
Examining the Impact of Digital Detox Interventions on Anxiety and Depression Levels Among Young Adults
Alanzi, T. M., Arif, W. M., Aqeeli, R., Alnafisi, A., Qumosani, T., Alreshidi, A., Alhawsawi, S., Alnakli, R., Alotaibi, A., AlOthman, M., et al. (2024) · Cureus · doi:10.7759/cureus.75625 · Cited by 20 · see citing works
Ciber-rumor y síntomas internalizantes en la adolescencia: efecto mediador de la resiliencia
Bravo, A., Alcaide, F. C., Ruiz, R. O., & Romera, E. M. (2022) · Psychology Society & Education · doi:10.21071/psye.v14i1.14168 · Cited by 12 · see citing works
“…negativo del uso de las tecnologías en el bienestar adolescente, sino que el tipo de impacto que la ciberconducta tiene entre sus usuarios puede implicar ciertos riesgos aún no conocidos y presenta un carácter dinámico y variable (Valkenburg et al., 2022; Vuorre et al., 2021; Weinstein, 2018).”
Background
Time spent on social media use and BMI z‐score: A cross‐sectional explanatory pathway analysis of 10798 14‐year‐old boys and girls
Foubister, C., Jago, R., Sharp, S. J., & van Sluijs, E. M. F. (2023) · Pediatric Obesity · doi:10.1111/ijpo.13017 · Cited by 12 · see citing works
“Previous evidence has suggested links between social media use and sleep,(45) depressive symptoms, and well-being, although the magnitude and importance of these links have been contested.(26,34,46) Given the lack of strong evidence, additional research which uses high quality and longitudinal measures across geograph…”
Background
An integrative literature review of birth cohort and time period trends in adolescent depression in the United States
Askari, M. S., Belsky, D. W., Olfson, M., Breslau, J. A., Mojtabai, R., Kajeepeta, S., Bruzelius, E., & Keyes, K. M. (2023) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-023-02527-8 · Cited by 12 · see citing works
“Many of these mechanisms, particularly social media [33–36], have been empirically explored.”
Less social media use – more satisfied, work-engaged and mentally healthy employees: an experimental intervention study
Brailovskaia, J., Becherer, I., Wicker, V., Schillack, H., & Margraf, J. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2286529 · Cited by 11 · see citing works
“Some research did not ﬁ nd a signi ﬁ cant link between SMU and mood modi ﬁ cation (Banjanin et al. 2015; Berryman, Ferguson, and Negy 2018; Vuorre, Orben, and Przybylski 2021).”
The anti‐consumption journey: Unplugging for improved well‐being
Anderson, K. C., Wallach, K. A., & Grimes, M. (2024) · Journal of Consumer Behaviour · doi:10.1002/cb.2390 · Cited by 12 · see citing works
It’s not what you do, it’s the way that you do it: An experimental task delineates among passive, reactive and interactive styles of behaviour on social networking sites
Shaw, D. J., Kaye, L. K., Ngombe, N., Kessler, K., & Pennington, C. R. (2022) · PLoS ONE · doi:10.1371/journal.pone.0276765 · Cited by 11 · see citing works
Social Media Use May Not Be As Bad As Some Suggest: Implication for Older Adults
Cotten, S. R., Anaraky, R. G., & Schuster, A. M. (2023) · Innovation in Aging · doi:10.1093/geroni/igad022 · Cited by 12 · see citing works
“However, these findings do not support the limited prior research that suggests causal relationships between SMU and depression (Fu & Xie, 2021; Kouvonen et al., 2021; Lewin et al., 2022; Vuorre et al., 2021).”
Gamers’ subjective Well-Being: the role of Peripheral and Core elements of eSporst Videogame Addiction
Abbasi, A. Z., Khan, M. K., Naeem, F., Albashrawi, M. A., Ting, D. H., & Kumar, S. (2023) · Current Psychology · doi:10.1007/s12144-022-04222-4 · Cited by 10 · see citing works
“Recently, Vuorre et al. (2021) found no evidence between digital technology engagement (e.g. eSports) and mental health problems.”
Background
From entertainment to extortion: Tunisian children's online experiences
Martin, A. P., Keskes, H., Heni, W., et al. (2023) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2023.106405 · Cited by 9 · see citing works
The limits of learning engagement and academic leadership within the higher education digitalization process ‐ analysis by using PLS SEM
Guțu, I., Medeleanu, C., & Asiminei, R. (2024) · PLoS ONE · doi:10.1371/journal.pone.0306079 · Cited by 10 · see citing works
Deviation from Design: A Meta-Analytic Review on the Link Between Social Media Use and Less Connection Between the Self and Others
Bunker, C. J., & Kwan, V. S. Y. (2023) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2022.0372 · Cited by 8 · see citing works
Neurobiological sensitivity to popular peers moderates daily links between social media use and affect
Maza, M. T., Kwon, S., Jorgensen, N. A., Capella, J., Prinstein, M. J., Lindquist, K. A., & Telzer, E. H. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101335 · Cited by 10 · see citing works
“Greater social media use in adolescence coincides with an increased risk for the onset of depression and anxiety (Vuorre et al., 2021) which has sparked growing concerns among the public regarding how social media may be affecting adolescents ’ emotional well-being (Barry, 2023; Gordon and Brown,…”
Digital measures of activity and motivation impact depression and anxiety in the real world
Beltrán, J., Jacob, Y., Mehta, M., Hossain, T., Adams, A., Fontaine, S., Torous, J. B., McDonough, C., Johnson, M., Delgado, A. D., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01669-0 · Cited by 7 · see citing works
“Although this dichotomous view has been recently challenged 63 , motivations behind use, and a range of other variables, can all in ﬂ uence the effect of screentime betweenusersandwithinusersovertime 29,64,65 .”
Exploring the Impact of Female Student’s Digital Intelligence on Sustainable Learning and Digital Mental Well-Being: A Case Study of Saudi Arabia
Alruwaili, N. M., Ali, Z., Siddiqui, M. S., Butt, A. H., Ahmad, H., Ali, R., & Alsalem, S. H. (2025) · Sustainability · doi:10.3390/su17146632 · Cited by 7 · see citing works
Does meaningful work mediate the relationship between empowering leadership and mental health? Evidence from Malaysian SME employees
Jalil, M. F., Tariq, B., & Ali, A. (2023) · Frontiers in Sociology · doi:10.3389/fsoc.2023.1138536 · Cited by 9 · see citing works
“In the last few decades, the number of people suffering from mental illnesses has increased (Vuorre et al., 2021).”
Background
Spatio-temporal differentiation on China’s green agricultural total factor productivity guided by digital technology and fuzzy systems
Wen, C., Hu, B., Sun, Y., & Xiao, Y. (2024) · Cogent Food & Agriculture · doi:10.1080/23311932.2024.2311962 · Cited by 8 · see citing works
“Digital technology has emerged as the predominant technological force, permeating every facet of human society (Vuorre et al., 2021). in the context of green agriculture development, digital technology assumes a pivotal role. as an illustrative example, precision agriculture technology employs…”
Child Online Safety Legislation (COSL) - A Primer
Marwick, A. E., Smith, J., Caplan, R., & Wadhawan, M. (2024) · doi:10.21428/bfcb0bff.de78f444 · Cited by 7 · see citing works
“Mature Enough to Handle it?”: Gendered Parental Interventions in and Adolescents’ Reactions to Technology Use During the Pandemic
Steinberg, H., Mollborn, S., & Pace, J. A. (2023) · Journal of Family Issues · doi:10.1177/0192513x221150979 · Cited by 8 · see citing works
“Evidence of a link between technology use and poor mental health has been mixed, and some research shows no difference by gender (Vuorre et al., 2021).”
Background
Relationships between depression, anxiety, and motivation in the real-world: Effects of physical activity and screentimePreprint
Beltrán, J., Jacob, Y., Mehta, M., Hossain, M. T., Adams, A., Fontaine, S., Torous, J. B., McDonough, C., Johnson, M., Delgado, A. D., et al. (2024) · medRxiv · doi:10.1101/2024.08.06.24311477 · Cited by 7 · see citing works
“Although this dichotomous view has been recently challenged (Valkenburg et al., 2022b) motivations behind use, and a range of other variables, can all influence the effect of screentime between users and within users over time (Orben et al., 2022; Valkenburg et al., 2022a; Vuorre et al., 2021).”
Background
Open Science at Clinical Psychological Science : Reflections on Progress, Lessons Learned, and Suggestions for Continued Improvement
Howard, A. L., Neal, T. M. S., Kirtley, O. J., Urry, H. L., & Tackett, J. L. (2024) · Clinical Psychological Science · doi:10.1177/21677026241255882 · Cited by 7 · see citing works
“…Report or a regular article, null results from high-quality studies that preregister study designs and analyses, share data, and transparently document the research workflow are valuable, and CPS encourages these contributions (e.g., Gallyer et al., 2023; Rogers et al., 2024; Vuorre et al., 2021).”
Exploring the digital detox journey among generation Y Instagram users
Scheppe, M. M., Seiffen, A. L., & Berndt, A. D. (2025) · Information Technology and People · doi:10.1108/itp-07-2023-0721 · Cited by 6 · see citing works
A survey study of Chinese adolescents’ mental and interpersonal quality: Evidence from COVID-19 pandemic
Huang, L., Zhu, Y., Kang, W., & Zhu, C. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1049077 · Cited by 6 · see citing works
“org smartphones and other digital technologies to prevent children from developing negative emotional and psychological problems due to excessive dependence on digital devices (Ravens-Sieberer et al., 2021; Vuorre et al., 2021).”
Background
A multiverse analysis of the associations between internet use and well-beingPreprint
Vuorre, M., & Przybylski, A. K. (2023) · doi:10.31234/osf.io/jp5nd · Cited by 6 · see citing works
Self-citation
Adolescent social media use and psychiatric outcomes: a longitudinal mediation analysis via interpersonal distrust, sleep, and self-image.
Tsomokos, D. I. (2026) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-025-02999-w · Cited by 5 · see citing works
Beyond Active and Passive Social Media Use: Habit Mechanisms Are Behind Frequent Posting and Scrolling on Twitter/XPreprint
Anderson, I. A. (2024) · doi:10.31234/osf.io/824nb · Cited by 4 · see citing works
The representation of adolescent social media use: a systematic review and content analysis of UK newspaper articles
Davies, J., Cadwallader, S., Black, L., Dunne, J. H., & Panayiotou, M. (2025) · BMC Public Health · doi:10.1186/s12889-025-23897-5 · Cited by 4 · see citing works
“This is despite evidence suggesting that social media use shows only weak, if any, correlations with self-reported mental health and wellbeing among adolescents [90, 124].”
Longitudinal Associations Between Social Media Use and Mental Health Outcomes in Sample of Irish Youth: A Brief Report
Ferguson, C. J. (2024) · Communication Reports · doi:10.1080/08934215.2023.2298948 · Cited by 4 · see citing works
Emotional Health of Immigrant Adolescents by a Cross-Lagged Panel Network Analysis: Self-Esteem and Depression
Sui, T., & Yeung, J. W. K. (2024) · Healthcare · doi:10.3390/healthcare12242563 · Cited by 4 · see citing works
“While modern technological changes are an important consideration, the core dynamics between self-esteem and depression, particularly in immigrant populations, may be consistent over time [91].”
Nighttime Texting on Social Media, Sleep Parameters, and Adolescent Sadness: A Mediation Analysis
Sancho-Domingo, C., Garmy, P., & Norell‐Clarke, A. (2024) · Behavioral Sleep Medicine · doi:10.1080/15402002.2024.2314281 · Cited by 5 · see citing works
“Although the strength of the curvilinear association was low (potential inverted U-shape association), previous works support this finding (Vuorre et al., 2021).”
BackgroundResult
VRZM: Exploring the Effect of Zen Meditation on EEG Patterns in Immersive Environments
Kumar, A., Sankhyan, S., Tripathi, K. M., Thakur, S., Bhavsar, A. V., & Dutt, V. (2024) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc54092.2024.10831479 · Cited by 3 · see citing works
Self-Directed Learning and Consensus Decision-Making in the Co-Creation of Virtual Worlds Promoting Student Mental Health Through Mobile Technology Use: A Scoping Review
Nash, C. (2025) · Virtual Worlds · doi:10.3390/virtualworlds4020026 · Cited by 4 · see citing works
“One systematic review concludes that there is no evidence that mental health problems have increased in association with cellphone use [104].”
Relationships between problematic binge-watching behavior with psychological and social states
Özkent, Y., & Akdoğan, Y. (2025) · BMC Public Health · doi:10.1186/s12889-025-23422-8 · Cited by 3 · see citing works
Incorporating Blockchain Technology for Integrity and Transparency in Human Resource Management Processes
Choubey, A., Choubey, S., Jaiswal, D., et al. (2025) · OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry (OTCON) · doi:10.1109/otcon65728.2025.11070457 · Cited by 3 · see citing works
“Immutability, independence, and openness make it a viable alternative for HRM process issues [2].”
Physical Activity for Youth Mental Health in the “Online Era”: Risks, Opportunities, and Implementation Priorities
Firth, J., Linardon, J., Sawyer, C. S., French, C., Stubbs, B., Firth, J. A., Solmi, M., Torous, J. B., Berhe, K., Hallal, P. C., et al. (2026) · Journal of Physical Activity and Health · doi:10.1123/jpah.2026-0550 · Cited by 3 · see citing works
Psychometric Properties of the Moral Disengagement through Technologies Questionnaire (MDTech-Q) in a Sample of Chilean University Students
Polanco-Levicán, K., & Salvo-Garrido, S. I. (2023) · Healthcare · doi:10.3390/healthcare11081097 · Cited by 3 · see citing works
Violent online game contact and academic procrastination: A moderated mediation model
Luo, Y., Ye, C., Zhao, Y., & Zhang, H. (2023) · Psychology in the Schools · doi:10.1002/pits.23103 · Cited by 3 · see citing works
Assessing the effect of Digital Detoxification on Psychological Burden among Adults in Pakistan
Jauhar, A. A., Ashraf, S., Mubashir, A., Sharif, M., Farooq, K., & Gardezi, A. A. (2025) · Bulletin of Business and Economics (BBE) · doi:10.61506/01.00574 · Cited by 3 · see citing works
Self-reported social media use by adolescents in Brazil: a school-based survey
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“Studies reporting that Generation Z experiences unprecedented anxiety and depression rates (Twenge et al., 2019a,b; Auxier and Anderson, 2021; Vuorre et al., 2021) may reflect measurement artifacts rather than genuine psychological differences.”
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“Yet, the evidence has been far from conclusive as studies have delivered mixed results (Odgers and Jensen, 2020; Vuorre et al., 2021).”
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Background
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ИСПОЛЬЗОВAНИЕ ПОТЕНЦИAЛA СОЦИAЛЬНЫХ ПAРТНЕРОВ В ПОДГОТОВКЕ БУДУЩИХ ПЕДAГОГОВ
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Authors: Vuorre, M., Orben, A., & Przybylski, A. K.
Affiliations: University of Oxford (GB)
MRC Cognition and Brain Sciences Unit (GB)
Corresponding author: Przybylski, Andrew K.
ORCID: Vuorre, Matti
Orben, Amy
Przybylski, Andrew K.
Venue: Clinical Psychological Science
Publisher: SAGE Publications
Published: 2021-05-03
Volume: 9
Issue: 5
Pages: 823-835
ISSN: 2167-7026 (ISSN-L)
2167-7034
DOI: 10.1177/2167702621994549
PMC: PMC7614449
OpenAlex: W3136028244
Semantic Scholar: aba7fff55e4a1ac69300cbe379f3dcc4c0a2f8ae
Cited by: 158
References: 49
Citations by year: 2026: 26 · 2025: 30 · 2024: 32 · 2023: 39 · 2022: 21 · 2021: 9 · 2020: 1
FWCI: 34.99
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: Clinical Psychological Science (publishedVersion, cc-by)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
PsyArXiv (OSF Preprints) (submittedVersion)
Apollo (University of Cambridge) (submittedVersion)
Apollo
Funders: Economic and Social Research Council (ES/T008709/1)
Hou Family Foundation
Topics: Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
Social Sciences › Education › Child Development and Digital Technology
Social Sciences › Psychology › Clinical Psychology › Child and Adolescent Psychosocial and Emotional Development
Keywords: adolescent mental health, social media use, depression, emotional problems, temporal trends, gender differences

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There Is No Evidence That Associations Between Adolescents’ Digital Technology Engagement and Mental Health Problems Have Increased

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