Digital Ecosystems, Children, and Adolescents: Technical Report

In the paper

“Possible mechanisms include more sedentary behavior250 and greater energy intake for children, teens, and young adults.251”

What the sources say

• Disputed

  Citation 250 is attached to the proposed mechanism of more sedentary behavior, not to the separate energy-intake claim. The Discussion (page unavailable) reports that, among the primary-school children studied, screen time did not correlate significantly with objectively measured sedentary time; it therefore does not support more sedentary behavior as a screen-time mechanism. (LLM, conf=0.82)

  Checked by a reasoning model — may be wrong.

  cites [250] Tanaka, 2017, Association between objectively evaluated physical activity and sedentary behavior and screen time in primary school children, BMC Res Notes. sourceExperimental — accuracy not yet measured
• Supported

  Citation 251 is attached to greater energy intake, not to the separate sedentary-behavior mechanism. The Results (Body composition, “Diet and energy intake”) report increased dietary intake with screentime, and the Methods table identifies an included review covering ages 5–24, encompassing children, teens, and young adults. (LLM, conf=0.91)

  cites [251] Stiglic, 2019, Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews, BMJ Open. source

In the paper

“Although some benefits are seen in sleep for preschoolers,231 school-aged children,231,232 and teens,230 others have found music to shorten sleep duration or delay sleep onset in teens.209,233”

What the sources say

• ?Not checked — no full text of the sourcecites [231] Field, 1999, Music Enhances Sleep in Preschool Children, Early Child Dev Care. source
• ?Not checked — no full text of the sourcecites [232] Tan, 2004, The effects of background music on quality of sleep in elementary school children, J Music Ther. source
• Disputed

  The citation is attached to the claim that music shortened sleep or delayed sleep onset in teens. In Results > Mechanisms of music therapy (page unavailable), the review reports that total sleep time fell across adolescent participants, but says rap music therapy had a modest positive effect on sleep duration; it does not attribute the decline to music or report delayed sleep onset in teens. (LLM, conf=0.84)

  Checked by a reasoning model — may be wrong.

  cites [230] Gou, 2025, Meta-narrative review: the impact of music therapy on sleep and future research directions, Front Neurol. sourceExperimental — accuracy not yet measured
• Partly supported

  The Abstract (p. 2) reports that bedtime music use was associated with trouble falling or staying asleep in early adolescents. The paper did not separately measure delayed sleep onset or show that music shortened sleep duration; its Introduction (p. 3) reports a prior study linking bedtime music with shorter sleep duration. The cited paper therefore supports a related association, but not the claim's more specific outcomes as its own findings. (LLM, conf=0.84)

  cites [209] Nagata, 2023, Bedtime screen use behaviors and sleep outcomes: Findings from the Adolescent Brain Cognitive Development (ABCD) Study, Sleep Health. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [233] Nosetti, 2021, Impact of pre-sleep habits on adolescent sleep: an Italian population-based study, Sleep Med. source

In the paper

“when children and families view or engage with digital media that provide privacy, safety, and meaningful experiences,12,13 families can set better boundaries around digital use and children can exercise their imagination, play, and social skills.14,15”

What the sources say

• ?Not checked — no full text of the sourcecites [12] Mares, 2013, Effects of Sesame Street: A meta-analysis of children’s learning in 15 countries, J Appl Dev Psychol. source
• Not checked yetcites [13] Huston, 2014
• Partly supported

  The Proximal factors section says parental limit-setting and guidance can buffer against problematic media use, and Current digital media use in early-middle childhood acknowledges positive outcomes from prosocial, age-appropriate media. Neither passage says that media offering privacy, safety, and meaningful experiences helps families set boundaries or children exercise imagination, play, and social skills. Page numbers are unavailable in our copy. (LLM, conf=0.84)

  cites [14] Domoff, 2020, Interactional theory of childhood problematic media use, Hum Behav Emerg Technol. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [15] Rasmussen, 2019, Promoting Preschoolers’ Emotional Competence Through Prosocial TV and Mobile App Use, Media Psychol. source

In the paper

“systems and structures are the invisible and visible rules and organizations that can facilitate opportunity for families32 and influence how the digital ecosystem is built.”

What the sources say

• Partly supported

  The “Horizontal Integration Across Sectors at the Community Level” section describes organizations and public policies working together to support families and remove barriers. It does not define systems and structures as “invisible and visible rules and organizations.” The citation follows “families,” so the subsequent claim about the digital ecosystem is not attributed to this source. (LLM, conf=0.78)

  cites [32] Garner, 2021, Preventing Childhood Toxic Stress: Partnering With Families and Communities to Promote Relational Health, Pediatrics. sourceExperimental — accuracy not yet measured

In the paper

“Digital media can be a critical source of support for families, and not all ways of using digital media are equivalent.52”

What the sources say

• Supported

  The paper’s main text (page not provided) identifies social support as a potentially positive use of parents’ phones. It distinguishes seeking support or parenting information from using a phone for “Virtual Escape,” supporting the claim that different uses are not equivalent. (LLM, conf=0.90)

  cites [52] Torres, 2021, Is it fair to simply tell parents to use their phones less? A qualitative analysis of parent phone use, Acta Paediatr. source

In the paper

“Compared with nondigital devices, joint media engagement was sometimes associated with reduced caregiver language overall and occasional negative interactions for young children (eg, pushing caregivers’ hands away or using tablets in more isolated ways).54”

What the sources say

• Supported

  Section 3.3.1 (Language; page unavailable) reports that some measures of parent language, including total verbalizations, were lower during shared e-book reading than print-book reading, while other measures showed no difference. Section 3.2.6 (Negative interactions; page unavailable) describes children pushing parents’ hands away, and section 3.2.1 (Limited interaction; page unavailable) describes some children using devices independently and rejecting parents’ attempts to participate. The review does not report how frequently the negative interactions occurred. (LLM, conf=0.88)

  cites [54] Ewin, 2021, The impact of joint media engagement on parent–child interactions: A systematic review, Hum Behav Emerg Technol. source

In the paper

“Online supports for caregivers are often critical to their information gathering and as a source of support (eg, breastfeeding, rare medical conditions).56-58”

What the sources say

• ?Not checked — no full text of the sourcecites [56] Robinson, 2019, It takes an e-village: Supporting African American mothers in sustaining breastfeeding through Facebook communities, J Hum Lact. source
• Supported

  The Introduction’s “Social media, social support and breastfeeding” section reports that mothers used social media to obtain important information and described Facebook as invaluable for breastfeeding support. This supports the breastfeeding example attributed to this source; the paper is not being cited here as evidence about rare medical conditions. (LLM, conf=0.90)

  cites [57] Robinson, 2019, Facebook support for breastfeeding mothers: A comparison to offline support and associations with breastfeeding outcomes, Digit Health. source
• ?Not checked — no full text of the sourcecites [58] Thoren, 2013, Online support for parents of preterm infants: a qualitative and content analysis of Facebook ‘preemie’ groups, Arch Dis Child Fetal Neonatal Ed. source

In the paper

“This review found that caregivers verbalize, teach, and scaffold children about the devices themselves and provide positive affective prompts during joint media engagement.54”

What the sources say

• Supported

  Section 3.3.1 (page not provided) reports that parents spoke to children about the media format itself. Sections 3.2.4 and 3.2.5 (pages not provided) describe instruction and technical scaffolding in device use, as well as supportive comments and verbal affective scaffolds during joint media engagement. (LLM, conf=0.92)

  cites [54] Ewin, 2021, The impact of joint media engagement on parent–child interactions: A systematic review, Hum Behav Emerg Technol. source

In the paper

“The inverse relationship is also true,47,48 creating a feedback cycle (Figure 2).45”

What the sources say

• Partly supported

  The Discussion reports that child behavioral difficulties predicted greater media use, while only TV viewing—not other forms of media use—predicted later externalizing behavior. The H2 results found no reverse association for overall media use. Thus the paper supports a possible feedback cycle involving TV viewing, but not the unqualified cycle implied by the sentence. (LLM, conf=0.88)

  cites [47] McDaniel, 2020, Longitudinal associations between early childhood externalizing behavior, parenting stress, and child media use, Cyberpsychol Behav Soc Netw. sourceExperimental — accuracy not yet measured
• Partly supported

  The Discussion reports an association between parenting stress and parents’ mobile gaming and perceived interference with family time. It raises increased phone use as a possible response to stress, but says the direction of the relationship remains unresolved; it does not establish that the inverse relationship is true. No page number is available in our copy. (LLM, conf=0.82)

  cites [48] McDaniel, 2024, Parent social media use and gaming on mobile phones, technoference in family time, and parenting stress, Psychology of Popular Media. sourceExperimental — accuracy not yet measured
• Supported

  The Abstract and Discussion (page numbers not provided) describe associations in both directions: child behavior problems predict greater parental technology interference through parenting stress, while technology interference predicts later behavior problems. The Discussion interprets these findings as a possible transactional cycle, consistent with the cited claim. (LLM, conf=0.90)

  cites [45] McDaniel, 2018, Technoference: longitudinal associations between parent technology use, parenting stress, and child behavior problems, Pediatr Res. sourceExperimental — accuracy not yet measured

In the paper

“Longitudinal correlations suggest that greater caregiver disruptions from mobile devices is associated with greater child externalizing symptoms (eg, aggression, hyperactivity)45,47 and greater challenges with caregiver-child relationships.30”

What the sources say

• Supported

  The Results report that technoference during parent-child interactions predicted greater child externalizing behavior at subsequent time points. The separate claim about caregiver-child relationship challenges is attached to citation 30, not to this source. (LLM, conf=0.93)

  cites [45] McDaniel, 2018, Technoference: longitudinal associations between parent technology use, parenting stress, and child behavior problems, Pediatr Res. source
• ?Could not verify

  The cited paper examines children’s media use, not disruptions caused by caregivers’ mobile devices. Its Discussion (page unavailable) reports that child behavioral difficulties predicted later media use and that, among media types, only TV viewing predicted later externalizing behavior. Neither finding tests the attributed association between caregiver device disruptions and child externalizing symptoms; the caregiver–child relationship clause has a separate citation. (LLM, conf=0.77)

  cites [47] McDaniel, 2020, Longitudinal associations between early childhood externalizing behavior, parenting stress, and child media use, Cyberpsychol Behav Soc Netw. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [30] Corkin, 2021, Associations between technoference, quality of parent-infant interactions, and infants’ vocabulary development, Infant Behav Dev. source

In the paper

“However, in one study following children annually from ages 3 to 7 years, digital games (ie, gaming consoles, apps) at age 4 years were associated with greater fluid intelligence (ie, problem solving, logical thinking) at age 5 years but not the reverse.87”

What the sources say

• Partly supported

  The Discussion reports that digital game play in Wave 2 predicted fluid intelligence in Wave 3, while the reverse, selection relationship was not supported. The Method says participants were already aged 3–7 at Wave 1, with waves one year apart. Thus the result applies to a mixed-age group, not specifically to gaming at age 4 and intelligence at age 5. (LLM, conf=0.89)

  cites [87] Fikkers, 2019, Child’s Play? Assessing the Bidirectional Longitudinal Relationship between Gaming and Intelligence in Early Childhood, J Commun. sourceExperimental — accuracy not yet measured

In the paper

“Specifically, digital media duration at age 2 and 3 was directionally associated with poorer achievement of developmental milestones at ages 3 and 5, respectively.90”

What the sources say

• Supported

  The Key Points state that higher screen time at 24 and 36 months was associated with poorer developmental-milestone screening performance at 36 and 60 months, respectively. The Abstract reports significant associations for both age-to-age comparisons. The citing sentence describes a directional association, not a causal effect. (LLM, conf=0.94)

  cites [90] Madigan, 2019, Association between screen time and children’s performance on a developmental screening test, JAMA Pediatr. source

In the paper

“However, one study found that higher digital media duration at age 1 was negatively associated with children’s communication scores at age 2, which in turn was negatively associated with more digital media duration at age 3, suggesting a reinforcing cycle.78”

What the sources say

• Partly supported

  The Discussion reports that greater screen time at age 1 was associated with poorer communication skills at age 2, and that lower communication scores at age 2 were associated with more screen time at age 3. This supports the suggested cycle, but the Methods (Measures; no page available) specify that screen time was measured only for TV/DVD viewing, not digital media generally. (LLM, conf=0.86)

  cites [78] Yamamoto, 2023, Screen Time and Developmental Performance Among Children at 1–3 Years of Age in the Japan Environment and Children’s Study, JAMA Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“Similarly, a meta-analysis on the effects of video game use and executive function85 found no evidence that video game use enhanced child and teen (age <18) working memory, though it did report a small beneficial effect on executive functioning skills.”

What the sources say

• Partly supported

  The Implications section (p. 17) reports no working-memory enhancement in video-game training experiments, but that analysis is not specific to people under 18. It describes a small executive-function effect in quasi-experimental comparisons of habitual gamers (p. 16), while training experiments showed negligible effects; the claim conflates those designs. (LLM, conf=0.87)

  cites [85] Powers, 2013, Effects of video-game play on information processing: a meta-analytic investigation, Psychon Bull Rev. sourceExperimental — accuracy not yet measured

In the paper

“However, brain development is a continuous process that unfolds through adolescence and into early adulthood, shaped by environmental experiences, including digital media use.72,73”

What the sources say

• ?Not checked — no full text of the sourcecites [72] Hutton, 2020, Associations between screen-based media use and brain white matter integrity in preschool-aged children, JAMA Pediatr. source
• Partly supported

  The Introduction says brain-structure changes continue into the mid-twenties, supporting development through adolescence into early adulthood. The Discussion considers social media use as a potential environmental influence, but says the observed differences were small, did not survive correction for multiple testing, and could reflect pre-existing traits. It therefore does not establish that digital media use shapes brain development. Page numbers were not provided in our copy. (LLM, conf=0.88)

  cites [73] Achterberg, 2022, Longitudinal associations between social media use, mental well-being and structural brain development across adolescence, Dev Cogn Neurosci. sourceExperimental — accuracy not yet measured

In the paper

“Many popular apps are of low educational quality and often contain in-app purchases and advertisements,5,92 which may bely this finding.”

What the sources say

• ?Not checked — no full text of the sourcecites [5] Meyer, 2019, Advertising in Young Children’s Apps: A Content Analysis, J Dev Behav Pediatr. source
• Partly supported

  The Results and Discussion (pages unavailable) report that most sampled popular educational apps scored in the lower quality range and that free apps had high levels of disruptive advertising. The Discussion says some free apps incorporate in-app purchases and advertisements, but does not establish that in-app purchases are common across popular apps. (LLM, conf=0.84)

  cites [92] Meyer, 2021, How educational are ‘educational’ apps for young children? App store content analysis using the Four Pillars of Learning framework, J Child Media. sourceExperimental — accuracy not yet measured

In the paper

“The structural condition of poverty is associated simultaneously with increased digital media exposure overall,115 less access to high-quality content,6 and increased barriers to early relational health and behaviors important for early relational health such as reading aloud and play.116”

What the sources say

• ?Could not verify

  Citation 116 is attached to the claim about poverty creating barriers to early relational health behaviors such as reading aloud and play; the media-exposure and content claims have separate citations. The Method and Results passages concern dual-earner couples, coparenting, and parenting adjustment. Searches for poverty, reading aloud, and play found no passage addressing the cited claim. Page numbers were not available in our copy. (LLM, conf=0.75)

  cites [115] Schoppe-Sullivan, 2016, Supportive coparenting relationships as a haven of psychological safety at the transition to parenthood, Res Hum Dev. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [6] Radesky, 2022, Video-Sharing Platform Viewing Among Preschool-Aged Children: Differences by Child Characteristics and Contextual Factors, Cyberpsychol Behav Soc Netw. source
• ?Not checked — no full text of the sourcecites [116] Mourgela, 2018, Children, extracurricular activities, and digital media: The process of displacement and school performance, J Educ Comput Res. source

In the paper

“Caregiver media use is associated with fewer words spoken to children, which may impact language development.112”

What the sources say

• Partly supported

  The Introduction reports that parents’ mobile-device use has been associated with fewer verbal communications with children, and the Discussion links a language-rich home environment to language development. But this study measured children’s screen exposure, not caregiver media use; its adult-word counts included words spoken near the child, whether directed to the child or not (Methods, Measures). (LLM, conf=0.88)

  cites [112] Brushe, 2024, Screen Time and Parent-Child Talk When Children Are Aged 12 to 36 Months, JAMA Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“Siblings can also co-view digital media, which might provide an added benefit for younger siblings.75”

What the sources say

• Partly supported

  The Co-Viewing section reports a positive association between co-viewing and child language skills, and the Discussion describes potential benefits of caregiver co-viewing. Neither passage addresses siblings co-viewing or an added benefit specifically for younger siblings; the Conclusions instead qualify the apparent benefit as applying to older children. Page numbers were not available in our copy. (LLM, conf=0.85)

  cites [75] Madigan, 2020, Associations between screen use and child language skills: A systematic review and meta-analysis, JAMA Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“Studies on social media and mental health have shown mixed results, with positive, negative, and null associations, all having small effect sizes102 or weak correlations.121,122”

What the sources say

• ?Not checked — no full text of the sourcecites [102] Vannucci, 2020, Social media use and risky behaviors in adolescents: A meta-analysis, J Adolesc. source
• Supported

  In “Pros and cons > What do the data show?”, the paper reports positive, negative and null findings for correlations between mental health and digital-technology use, all with minuscule effect sizes. This supports the mixed-results and small-effect-sizes point attributed to this citation. (LLM, conf=0.92)

  cites [121] Odgers, 2018, Smartphones are bad for some teens, not all, Nature. source
• Partly supported

  The Confirmatory analyses (pp. 8–9) report positive, flat, and negative associations between adolescents’ screen time and mental well-being, with a small average effect size for use above the identified thresholds (Cohen’s d = -0.18). The study examines several forms of digital-screen use, not social media specifically, and the reported effect size describes the negative association rather than establishing that all three kinds of association have small effect sizes. (LLM, conf=0.84)

  cites [122] Przybylski, 2017, A large-scale test of the goldilocks hypothesis: quantifying the relations between digital-screen use and the mental well-being of adolescents, Psychol Sci. sourceExperimental — accuracy not yet measured

In the paper

“Another study found that most 11- to 17-year-olds “sometimes” or “often” use their phones to escape from negative emotions,125 and many are using digital media to calm down before bed.”

What the sources say

• Supported

  Section 7 reports that over two-thirds of the 203 participants aged 11–17 sometimes or often used technology to escape sorrow or get relief from negative feelings. The Abstract reports that over half used phones on school nights, often to listen to music to wind down or fall asleep; the Takeaways also describe nighttime phone use as a way to unwind. These findings support the claim as a description of the study participants. (LLM, conf=0.91)

  cites [125] Radesky, 2023 source

In the paper

“One randomized control trial aimed at reducing social media duration for children and teens finds improvements in internalizing symptoms and greater prosocial behavior for children and teens in the intervention group.145”

What the sources say

• Partly supported

  The Results report improved internalizing symptoms and prosocial behavior in the intervention group. However, the Methods and Conclusions specify that the trial targeted leisure-time screen media use across devices, not social media duration specifically. (LLM, conf=0.90)

  cites [145] Schmidt-Persson, 2024, Screen Media Use and Mental Health of Children and Adolescents: A Secondary Analysis of a Randomized Clinical Trial, JAMA Netw Open. sourceExperimental — accuracy not yet measured

In the paper

“There are conflicting findings regarding the association between duration of digital media use and teen depressive symptoms, with some studies finding weak associations and others finding null associations,141-143 likely reflecting heterogeneity between different teens.”

What the sources say

• Partly supported

  Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [141] Kreski, 2021, Social Media Use and Depressive Symptoms Among United States Adolescents, J Adolesc Health. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [142] Twenge, 2018, Decreases in psychological well-being among American adolescents after 2012 and links to screen time during the rise of smartphone technology, Emotion. source
• Partly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [143] Li, 2022, Screen time and depression risk: A meta-analysis of cohort studies, Front Psychiatry. sourceExperimental — accuracy not yet measured

In the paper

“Teens’ developmental stages is another area of differential susceptibility, with younger teens experiencing less life satisfaction and higher depression symptoms when they use more social media, as compared with older teens.137,144”

What the sources say

• Partly supported

  The Discussion (page not provided) reports that, among participants aged 9 to 12, increases in social media use were associated with subsequent depressive symptoms. The paper does not report life satisfaction or show that the association is stronger for younger teens than for older teens. (LLM, conf=0.88)

  cites [137] Nagata, 2025, Social Media Use and Depressive Symptoms During Early Adolescence, JAMA Netw Open. sourceExperimental — accuracy not yet measured
• Partly supported

  The Results and discussion (page unavailable) report different social-media-use–life-satisfaction patterns for younger (10–15) and older (16–21) adolescents, with a more linear negative pattern among younger adolescents. The paper does not establish the claimed younger-versus-older comparison for depression symptoms; its Methods say additional mental-health questionnaires were completed only by younger adolescents. These are associations, not evidence that social media use causes either outcome. (LLM, conf=0.86)

  cites [144] Orben, 2022, Windows of developmental sensitivity to social media, Nat Commun. sourceExperimental — accuracy not yet measured

In the paper

“Earlier age of device ownership for girls is correlated with worse behavioral adjustment, but this association is null for boys among an Irish cohort, although this evidence is correlational.156”

What the sources say

• Supported

  The Abstract reports that girls who received phones earlier had worse behavioural adjustment scores at age 13, while no robust associations were found for boys. The gender-specific results for Table 3 likewise report stronger negative associations for girls. The paper describes these as associations and calls for further research into causal mechanisms. (LLM, conf=0.94)

  cites [156] Dempsey, 2020, Early mobile phone ownership: influencing the wellbeing of girls and boys in Ireland?, J Child Media. source

In the paper

“Previous work also has found that teens with low subjective well-being,133 fear of missing out,134 or loneliness135 may also experience greater challenges with digital media.”

What the sources say

• Supported

  Citation 133 is attached to low subjective well-being, not fear of missing out or loneliness. The Discussion reports a negative association between subjective well-being and problematic internet use, and the Results > Moderator Analyses table shows the same association specifically for secondary-school students. The finding is correlational, consistent with the claim’s cautious wording. (LLM, conf=0.92)

  cites [133] Cai, 2023, Associations Between Problematic Internet Use and Mental Health Outcomes of Students: A Meta-analytic Review, Adolesc Res Rev. source
• ?Not checked — no full text of the sourcecites [134] Oberst, 2017, Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out, J Adolesc. source
• ?Not checked — no full text of the sourcecites [135] Tóth-Király, 2021, Longitudinal trajectories, social and individual antecedents, and outcomes of problematic internet use among late adolescents, Child Dev. source

In the paper

“Furthermore, the relationship between mental well-being and digital media is likely bidirectional,103 where media can shape mental health, which can in turn shape digital media use.”

What the sources say

• Partly supported

  The Cross-lagged parameter estimates report that, among preschool children, internalizing behaviors predicted later screen time and screen time predicted later internalizing behaviors. The Discussion says this bidirectional association was not observed later in childhood. The claim generalizes these associations to mental well-being and digital media broadly and implies influence in both directions, whereas the paper studied associations between children's screen time and specific behavioral outcomes. (LLM, conf=0.88)

  cites [103] Neville, 2021, Bidirectional associations between screen time and children’s externalizing and internalizing behaviors, J Child Psychol Psychiatry. sourceExperimental — accuracy not yet measured

In the paper

“Teens who struggle with emotion regulation, such as those experiencing problematic internet use, anxiety, or depression, are particularly vulnerable to adverse digital media effects and using digital media to cope.126”

What the sources say

• ?Could not verify

  Section 2.1 discusses harmful online content, including material that may trigger trauma or promote self-harm, and Section 5.1.2 describes emotional harm from viewing content. Neither passage addresses whether teens with emotion-regulation difficulties, problematic internet use, anxiety, or depression are particularly vulnerable to digital media effects or use digital media to cope. Searches for those terms and related phrasing found no supporting passage in our copy; page numbers were not available. (LLM, conf=0.73)

  cites [126] Scheuerman, 2021, A framework of severity for harmful content online, Proceedings of the ACM on Human-Computer Interaction. sourceExperimental — accuracy not yet measured

In the paper

“Prolonged TV viewing,88 video game playing,88 and mobile device use140 are associated with lower academic scores.”

What the sources say

• Supported

  The Conclusions state that television viewing and video game playing were the activities most negatively associated with academic performance, particularly among adolescents. Those are the two activities attached to this source’s citation (88); mobile device use is attached to a different citation (140) and is not judged here. (LLM, conf=0.92)

  cites [88] Adelantado-Renau, 2019, Association between screen media use and academic performance among children and adolescents: a systematic review and meta-analysis, JAMA Pediatr. source
• ?Not checked — no full text of the sourcecites [140] Liu, 2020, Prolonged Mobile Phone Use Is Associated with Poor Academic Performance in Adolescents, Cyberpsychol Behav Soc Netw. source

In the paper

“Furthermore, there are many other ways of using social media, with opportunities offered for social, identity-formation, cognitive (learning information), and emotional needs (feeling empathy), which might help understand social media’s benefits and downsides for each teen.146”

What the sources say

• Supported

  Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [146] Moreno, 2019, Applying an affordances approach and a developmental lens to approach adolescent social media use, Digit Health. source

In the paper

“The more a user interacts with harmful social media content, such as violent, abusive, discriminatory, or misleading material; posts promoting self-harm or disordered eating; or content that fosters negative social comparisons; the more social media algorithms display such content, making further exposure to harmful content hard to avoid if should youth attempt to control social media feeds.126,”

What the sources say

• Partly supported

  The Introduction and §2.1 describe several of the cited kinds of harmful content, including violent imagery, hate speech, misinformation, and material promoting self-harm or anorexia. They do not establish that interacting with such content causes algorithms to show more of it, or that youth consequently cannot avoid it by controlling their feeds. A search for recommendation algorithms, engagement feedback, and youth feed control found no supporting passage; the study recruited general-population participants aged 18 or older. (LLM, conf=0.86)

  cites [126] Scheuerman, 2021, A framework of severity for harmful content online, Proceedings of the ACM on Human-Computer Interaction. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [181] Harness, 2022, Youth insight about social media effects on well/ill-being and self-modulating efforts, J Adolesc Health. source

In the paper

“One peer-reviewed study from Spain169 found associations between school phone bans and less bullying and greater academic scores.”

What the sources say

• Supported

  The Abstract (p. 1) reports reduced bullying in both Spanish regions with school phone bans and higher PISA maths and science scores in Galicia. The Results (pp. 13, 16) likewise report improved scores in Galicia and reduced bullying among students aged 12–17 in both regions. The claim's wording, “associations,” does not overstate these findings. (LLM, conf=0.93)

  cites [169] Beneito, 2022, Banning mobile phones in schools: evidence from regional-level policies in Spain, Applied Economic Analysis. source

In the paper

“Minoritized populations often face increased exposure to harmful content, such as racist comments or discriminatory practices, which could significantly impact mental health177 and further exacerbate mental health issues among minoritized populations.178”

What the sources say

• Partly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [177] Tynes, 2024, Online racial discrimination, suicidal ideation, and traumatic stress in a national sample of Black adolescents, JAMA Psychiatry. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [178] Kleinberg, 2018, Discrimination in the Age of Algorithms, J Legal Anal. source

In the paper

“When schools enact phone bans or policies, the responsibility falls on individual teachers to enforce the rules, resulting in some variability even within schools.125”

What the sources say

• Supported

  The “School policies and smartphones” section reports inconsistency between teachers’ classroom expectations, including class-specific rules. It also says school phone use varies with teacher and staff enforcement, supporting the claim that enforcement can differ within a school. The paper does not describe enforcement as teachers’ responsibility alone. (LLM, conf=0.88)

  cites [125] Radesky, 2023 source

In the paper

“Teens believe exposure to mental health content can increase awareness and decrease stigma.184”

What the sources say

• Partly supported

  The Results section (“Connection: Mental Health Content on TikTok Makes Youth Feel Seen”; page unavailable) says participants felt TikTok content increased awareness of less-discussed mental health experiences and helped destigmatize conversations. The claim narrows the participants to teens, but the study included youth aged 13–24 and does not distinguish teenagers’ views from those of older participants. (LLM, conf=0.80)

  cites [184] Turuba, 2024, Exploring How Youth Use TikTok for Mental Health Information in British Columbia: Semistructured Interview Study With Youth, JMIR Infodemiology. sourceExperimental — accuracy not yet measured

In the paper

“Sleep in teens is vital for physical health, mental health including mood and emotional processing, and school performance, supporting learning, memory, and attention.195,197”

What the sources say

• ?Not checked — no full text of the sourcecites [195] Agostini, 2021, Normal Sleep in Children and Adolescence, Child Adolesc Psychiatr Clin N Am. source
• Partly supported

  The Conclusion (page unavailable) links adolescent sleep to cognitive function, mental well-being and better grades; Sleep-dependent Emotion Regulation links sleep loss to mood and emotional regulation in adolescents. The paper also discusses adolescent learning and memory, and Insufficient Sleep and Behavioral Problems in Teens reports physical-health risks including obesity. However, the explicit evidence for sleep's effects on attention in Sleep and Learning and Memory concerns adults, so the teen-specific attention claim is not established by this copy. (LLM, conf=0.82)

  cites [197] Tarokh, 2016, Sleep in adolescence: Physiology, cognition and mental health, Neurosci Biobehav Rev. sourceExperimental — accuracy not yet measured

In the paper

“Sleep disturbances may also arise because of cognitive arousal and alertness related to device content or engagement205 as well as nighttime sleep disturbances from devices such as vibrations and notification sounds.202”

What the sources say

• ?Not checked — no full text of the sourcecites [205] Higuchi, 2014, Influence of light at night on melatonin suppression in children, J Clin Endocrinol Metab. source
• Partly supported

  Citation 202 is attached to the nighttime-device-disturbance clause, not the preceding cognitive-arousal clause. The Results section (Mobile Devices and Sleep; page unavailable) reports that having a phone in the bedroom was associated with adverse sleep outcomes, but our copy does not identify vibrations or notification sounds as the cause of those disturbances. (LLM, conf=0.78)

  cites [202] Hale, 2015, Screen time and sleep among school-aged children and adolescents: a systematic literature review, Sleep Med Rev. sourceExperimental — accuracy not yet measured

In the paper

“Incoming alerts, ringers, and notifications can occur at any stage of sleep, with the potential to disrupt natural sleep progression and REM cycles.208”

What the sources say

• Partly supported

  The Introduction (page unavailable) says devices may interrupt sleep, and the Discussion’s summary of findings (page unavailable) associates bedroom device presence with poor sleep outcomes. The paper does not identify alerts, ringers, or notifications as the cause of interruptions, or discuss interruptions at any sleep stage or effects on REM cycles. (LLM, conf=0.84)

  cites [208] Carter, 2016, Association Between Portable Screen-Based Media Device Access or Use and Sleep Outcomes: A Systematic Review and Meta-analysis, JAMA Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“In school-aged children and teens, poor sleep is associated with lower cognitive function, poorer school performance, and socioemotional difficulties like depressed mood.193,197”

What the sources say

• ?Not checked — no full text of the sourcecites [193] Hirshkowitz, 2015, National Sleep Foundation’s updated sleep duration recommendations: final report, Sleep Health. source
• Supported

  The Conclusion (page not provided) says sleep supports cognitive function and mental well-being in adolescence, and links longer sleep after later school starts with better grades. “Insufficient Sleep and Behavioral Problems in Teens” associates less sleep with more depressive symptoms; “Sleep-dependent Emotion Regulation” also reports impaired learning and memory in adolescents with sleep-disrupting apnea. (LLM, conf=0.88)

  cites [197] Tarokh, 2016, Sleep in adolescence: Physiology, cognition and mental health, Neurosci Biobehav Rev. source

In the paper

“Teens and young adults who use screens at bedtime experience: delayed bedtime, less sleep, poorer sleep quality, and more daytime tiredness.219”

What the sources say

• Supported

  The Practice points state that bedtime and nighttime digital media use may result in later bedtime, shorter sleep time, poorer sleep quality, and daytime tiredness. The Summary of results also reports these associations among young people. (LLM, conf=0.94)

  cites [219] Brautsch, 2023, Digital media use and sleep in late adolescence and young adulthood: A systematic review, Sleep Med Rev. source

In the paper

“Sleep plays an integral role in the developing brain in teens as sleep patterns and physiology undergo significant changes.197”

What the sources say

• Supported

  The Summary: Sleep Matters section says research supports an important role for sleep in adolescent brain function and behavior. The Abstract reviews changes in sleep behavior and physiology during adolescence, and Sleep Physiology in Adolescence describes marked maturational changes in the sleep EEG. Page numbers are not provided in our copy. (LLM, conf=0.92)

  cites [197] Tarokh, 2016, Sleep in adolescence: Physiology, cognition and mental health, Neurosci Biobehav Rev. source

In the paper

“Listening to music may be beneficial for sleep across ages, with strong data in studies of preterm and term infants, in particular for music therapy in neonatal intensive care units.229,230”

What the sources say

• Partly supported

  The Introduction (page unavailable) says passive music listening has shown improvements in infant sleep and that lullabies promote sleep in premature and healthy infants. The review studies term and preterm newborns, but does not provide evidence for benefits across ages. It also notes inconsistent NICU outcomes and no clear consensus on the efficacy of music therapy and music medicine, so the claim of strong data particularly for NICU music therapy overstates its findings. (LLM, conf=0.85)

  cites [229] Papatzikis, 2024, Music medicine and music therapy in neonatal care: a scoping review of passive music listening research applications and findings on infant development and medical practice, BMC Pediatr. sourceExperimental — accuracy not yet measured
• Partly supported

  The Results (Mechanisms of music therapy, page not provided) report improved quiet sleep in preterm infants receiving live or recorded music in a neonatal intensive care unit. The review also discusses possible sleep benefits at other ages, but it does not report evidence for term infants; its Discussion (Gaps in the methodology, page not provided) says studies in younger age groups are limited. Thus it does not support the claim of strong data for both preterm and term infants. (LLM, conf=0.86)

  cites [230] Gou, 2025, Meta-narrative review: the impact of music therapy on sleep and future research directions, Front Neurol. sourceExperimental — accuracy not yet measured

In the paper

“For instance, the competition for users’ attention has created an digital environment where content is more arousing or elicits strong emotions7 and may make it more difficult to relax for sleep.200,202”

What the sources say

• Partly supported

  The Results (Attention-Capture Designs; page unavailable) describe recommended video thumbnails using shocking messages and extreme facial expressions to attract clicks. The Discussion (page unavailable) says creators use such features to encourage views. The paper does not establish that competition has made digital content more arousing over time, and its evidence concerns thumbnails on a video-sharing platform used by children rather than the digital environment generally. The sleep clause has separate citations and is not attributed to this source. (LLM, conf=0.84)

  cites [7] Radesky, 2024, Algorithmic Content Recommendations on a Video-Sharing Platform Used by Children, JAMA Netw Open. sourceExperimental — accuracy not yet measured
• Supported

  The citation to this source is attached to the suggestion that arousing content may make it harder to relax for sleep; the preceding claim about competition for attention carries a different citation. In “Psychological stimulation from media content disrupting sleep” (page not provided), the paper says arousal likely mediates some effects of screen use on sleep and reports slightly delayed sleep onset after an exciting video game. (LLM, conf=0.88)

  cites [200] Hale, 2018, Youth Screen Media Habits and Sleep: Sleep-Friendly Screen Behavior Recommendations for Clinicians, Educators, and Parents, Child Adolesc Psychiatr Clin N Am. source
• Supported

  The Introduction states that psychological and physical arousal due to media content may interfere with falling and staying asleep. That supports the sleep-related clause to which this source is cited; the separate claim about competition for users’ attention has a different citation. (LLM, conf=0.90)

  cites [202] Hale, 2015, Screen time and sleep among school-aged children and adolescents: a systematic literature review, Sleep Med Rev. source

In the paper

“Specific content such as apps, social media, internet use, and gaming lead to shorter sleep duration and poorer sleep quality compared with other content.214,216,219”

What the sources say

• Partly supported

  Section 7.1 (page unavailable) reports that social media use in adolescence was associated with shorter sleep duration and lower sleep quality at a later time point. It does not establish that these activities cause poorer sleep than other content; it says the social-media association was weaker than the association for traditional media. The cited passages also do not establish the claimed sleep outcomes for apps, internet use, and gaming as a group; section 6.3.1 reports a study in which videogame use was not associated with sleep duration. (LLM, conf=0.86)

  cites [214] Pagano, 2023, “Using digital media or sleeping … that is the question”. A meta-analysis on digital media use and unhealthy sleep in adolescence, Comput Human Behav. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [216] Hisler, 2020, Associations between screen time and short sleep duration among adolescents varies by media type: evidence from a cohort study, Sleep Med. source
• Partly supported

  The Summary of results (§3.10; page not specified) says studies suggested associations between gaming, internet use and social media use and shorter sleep duration and poor sleep quality. It does not establish that these activities cause those outcomes, identify apps as a category with that finding, or show that their effects are worse than those of other content. (LLM, conf=0.87)

  cites [219] Brautsch, 2023, Digital media use and sleep in late adolescence and young adulthood: A systematic review, Sleep Med Rev. sourceExperimental — accuracy not yet measured

In the paper

“Interventional work among adults finds that removing mobile devices from bedrooms is linked with greater quality of life, happiness, and quality of sleep, suggesting this approach may have promise for caregivers’ well-being,243 but this association has not yet been examined among teens.”

What the sources say

• Partly supported

  Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [243] Hughes, 2018, Sleeping with the frenemy: How restricting ‘bedroom use’ of smartphones impacts happiness and wellbeing, Comput Human Behav. sourceExperimental — accuracy not yet measured

In the paper

“Commercial meditation apps are reported by caregivers to be helpful with sleep, stress, depression, and anxiety as well as overall health.228”

What the sources say

• Partly supported

  The Results report that parents said their children began using Calm for sleep, stress, depression or anxiety, and overall health. Parents also perceived its components as helpful for sleep, but the paper does not report that they found it helpful for the other listed concerns. The study concerns children using one app, not commercial meditation apps generally. (LLM, conf=0.89)

  cites [228] Puzia, 2020, Parents’ Perceptions of Their Children’s Engagement in a Consumer-Based Meditation Mobile App: Cross-Sectional Survey Study, JMIR Pediatr Parent. sourceExperimental — accuracy not yet measured

In the paper

“Brambilla et al find that 25% of 1- to 3-year-olds and nearly 75% of children and teens have devices in the bedroom and/or use them prior to bedtime.220”

What the sources say

• Partly supported

  The Results table (page unavailable) reports that 25.0% of 1–3-year-olds had a TV in the bedroom, while 39.6% used a display device before sleep. It reports pre-sleep device use of 75.8% and 79.5% in the two oldest age groups, not nearly 75% of children and teens overall. The claim blends different measures and age groups. (LLM, conf=0.88)

  cites [220] Brambilla, 2017, Sleep habits and pattern in 1–14 years old children and relationship with video devices use and evening and night child activities, Ital J Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“Although families with fewer socioeconomic barriers have more available devices at home, media devices are more frequently in bedrooms in families who face more socioeconomic barriers.221”

What the sources say

• Supported

  The Results report that device ownership was more common among higher-SES children, while bedroom devices were more prevalent among lower- and medium-SES children. The Discussion states the same home-versus-bedroom pattern for high- and low-SES families. The claim paraphrases this finding. (LLM, conf=0.95)

  cites [221] Rodrigues, 2021, Home vs. bedroom media devices: socioeconomic disparities and association with childhood screen- and sleep-time, Sleep Med. source

In the paper

“Conversely, problematic digital media use has associations with later sleep onset, shorter duration of sleep, and poorer quality sleep, creating a feedback loop.214”

What the sources say

• Supported

  Section 3 links smartphone addiction to insufficient sleep quantity and quality and describes media use delaying sleep onset. Section 6.3.1 reports an association between problematic social media use and later bedtime, while section 7.2 describes a bidirectional relationship between dysfunctional media use and sleep health as a possible vicious cycle. The paper’s evidence concerns adolescents. (LLM, conf=0.87)

  cites [214] Pagano, 2023, “Using digital media or sleeping … that is the question”. A meta-analysis on digital media use and unhealthy sleep in adolescence, Comput Human Behav. source

In the paper

“There is a large collection of sleep apps that exists for use in children and teens, however, few apps include evidence-based behavioral strategies.226”

What the sources say

• Partly supported

  The Results (Behavioral Strategies; page unavailable) found that 18 of 83 children’s sleep app descriptions (21.6%) contained an evidence-based behavioral strategy, supporting the claim that few did. The Strengths and Limitations section says apps aimed specifically at adolescents need future analysis, so the finding does not establish the claim for teens. The study assessed app descriptions, not all content within the apps. (LLM, conf=0.88)

  cites [226] Simon, 2022, Evidence-Based Behavioral Strategies in Smartphone Apps for Children’s Sleep: Content Analysis, JMIR Pediatr Parent. sourceExperimental — accuracy not yet measured

In the paper

“Lack of adequate housing and space may contribute to room sharing and make it difficult to constrain exposures to digital media at night.238”

What the sources say

• Partly supported

  The Discussion (page unavailable) identifies limitations in household space as a possible reason for parent-child room sharing. It does not say that inadequate space makes nighttime digital-media exposure difficult to constrain; the Discussion says screen use was not included in this study. (LLM, conf=0.87)

  cites [238] Hoyniak, 2022, The physical home environment and sleep: What matters most for sleep in early childhood sourceExperimental — accuracy not yet measured

In the paper

“Algorithms that personalize content recommendations prolong use of a device, as does auto play and dark patterns in which a user must return to an app on a schedule determined by the app.237”

What the sources say

• Supported

  In ‘Opportunities for Platform Developers,’ the paper says engagement-optimized features, including tailored feeds and autoplay, are designed to keep children connected. The same passage identifies interaction-by-demand as a dark pattern that requires users to return on a schedule dictated by the app. (LLM, conf=0.91)

  cites [237] Radesky, 2022, From Moral Panic to Systemic Change: Making Child-Centered Design the Default, Int J Child Comput Interact. source

In the paper

“Randomized clinical trials focusing on behavioral change document that decreasing digital media before bedtime is feasible and shows some beneficial effects on sleep, with the added benefit of improved attention in toddlers, preschoolers, and school-aged children.240,241”

What the sources say

• Partly supported

  The Conclusions and Discussion report that removing screens before toddler bedtime was feasible and showed modest, preliminary benefits for sleep. But the Results (Attention) and Discussion report no clear improvement in toddler attention. This trial studied toddlers, not preschoolers or school-aged children; the Introduction describes findings in older children from earlier programs. (LLM, conf=0.92)

  cites [240] Pickard, 2024, Toddler Screen Use Before Bed and Its Effect on Sleep and Attention: A Randomized Clinical Trial, JAMA Pediatr. sourceExperimental — accuracy not yet measured
• Partly supported

  The Results (Study characteristics; page not provided) describe randomized trials that reduced screen time in preschool-aged children, and the Discussion (Screen time reduction; page not provided) reports reductions of 25–39 minutes per day in promising studies. The paper does not report interventions specifically reducing media before bedtime, benefits for sleep or attention, or findings in school-aged children. (LLM, conf=0.88)

  cites [241] Lewis, 2021, What behavior change techniques are associated with effective interventions to reduce screen time in 0–5 year olds? A narrative systematic review, Prev Med Rep. sourceExperimental — accuracy not yet measured

In the paper

“The co-location of media devices in bedrooms is associated with greater screen time and shorter sleep duration.221”

What the sources say

• Supported

  The Discussion (section 4) explicitly states that media devices in children’s bedrooms are associated with increased screen-time and decreased sleep-time. The Results (section 3) report device-specific associations consistent with that summary. (LLM, conf=0.94)

  cites [221] Rodrigues, 2021, Home vs. bedroom media devices: socioeconomic disparities and association with childhood screen- and sleep-time, Sleep Med. source

In the paper

“Recent systematic reviews highlight the mixed evidence regarding suicide and self-harm risk and social media use and the potential for vulnerable subgroups.282,283”

What the sources say

• ?Not checked — no full text of the sourcecites [282] Jaycox, 2024, Social Media and Suicide Risk in Youth, JAMA Netw Open. source
• Supported

  The Discussion’s “Risk and protective factors” section describes possible links between heavy social media use and suicidal risk but cautions that the evidence is limited. “Vulnerable Subgroups” reports limited research on groups that may experience either positive or negative effects. Page numbers are not provided in our copy. (LLM, conf=0.90)

  cites [283] Biernesser, 2020, Social Media Use and Deliberate Self-Harm Among Youth: A Systematized Narrative Review, Child Youth Serv Rev. source

In the paper

“With regard to sexting, “non-consensual and pressured sexting are positively related to depressive symptoms and non-suicidal self-harm, whereas consensual sexting is unrelated to these outcomes.”284”

What the sources say

• Supported

  The Results (§3.2) report positive associations of non-consensual and pressured sexting with both depressive symptoms and non-suicidal self-harm. Consensual sexting was not significantly related to either outcome. (LLM, conf=0.95)

  cites [284] Wachs, 2021, How Are Consensual, Non-Consensual, and Pressured Sexting Linked to Depression and Self-Harm? The Moderating Effects of Demographic Variables, Int J Environ Res Public Health. source

In the paper

“These behaviors include sexting, cyberbullying, and problematic internet use.284”

What the sources say

• Partly supported

  The Introduction (§1.1; page unavailable) discusses sexting and names cyberbullying as another online risk. Problematic internet use appears only in the title of a cited work in the References; the paper does not itself discuss it as one of these behaviors. (LLM, conf=0.86)

  cites [284] Wachs, 2021, How Are Consensual, Non-Consensual, and Pressured Sexting Linked to Depression and Self-Harm? The Moderating Effects of Demographic Variables, Int J Environ Res Public Health. sourceExperimental — accuracy not yet measured

In the paper

“Exposure to food marketing, displacement of physical activity, and food consumption during digital media use may underly these findings.254”

What the sources say

• Partly supported

  The Results (§3.3; page not provided) report that food advertising during a television programme increased children's snacking, and that food-marketing games increased consumption of unhealthy food. These passages support food-marketing exposure and some consumption during media use, but the paper does not address displacement of physical activity as an explanation. (LLM, conf=0.86)

  cites [254] Smith, 2019, Food marketing influences children’s attitudes, preferences and consumption: a systematic critical review, Nutrients. sourceExperimental — accuracy not yet measured

In the paper

“Exposures to branded and ultraprocessed foods in videos is associated with children’s positive food attitudes and preferences for such foods and greater overall consumption of the marketed food immediately following viewing.254”

What the sources say

• Partly supported

  Section 3.3 reports that television and movie marketing of unhealthy foods was associated with more positive attitudes, more frequent choices, and greater consumption of advertised food. Section 3.5 notes that studies often used well-known brands. The copy does not establish that the foods were ultraprocessed, and its example measured snacking during the programme rather than immediately after viewing. (LLM, conf=0.85)

  cites [254] Smith, 2019, Food marketing influences children’s attitudes, preferences and consumption: a systematic critical review, Nutrients. sourceExperimental — accuracy not yet measured

In the paper

“Access to positive social influences online, access to help-giving resources, and reduced isolation can be protective and encourage recovery.281”

What the sources say

• Supported

  The Social connection section reports that online peer support can help people feel less isolated, offer help, and mitigate urges to self-harm. The Potentially protective impacts section describes images and comments promoting recovery narratives and encouraging help-seeking. The review frames these as possible protective effects, consistent with the claim’s cautious wording. (LLM, conf=0.87)

  cites [281] Susi, 2023, Research Review: Viewing self-harm images on the internet and social media platforms: systematic review of the impact and associated psychological mechanisms, J Child Psychol Psychiatry. source

In the paper

“The digital ecosystem also includes branded and ultraprocessed food marketing toward children, which is common in influencer videos viewed by children.261,262”

What the sources say

• ?Not checked — no full text of the sourcecites [261] Tsai, 2022, Food and Beverage Product Appearances in Educational, Child-Targeted YouTube Videos, Child Obes. source
• Partly supported

  The Abstract and Discussion report that food and drink appeared in 179 of 418 sampled kid-influencer videos and that most featured products were unhealthy branded items. The Methods classify products by nutritional quality, not degree of processing, so the paper does not establish how common ultraprocessed food marketing was. (LLM, conf=0.87)

  cites [262] Alruwaily, 2020, Child Social Media Influencers and Unhealthy Food Product Placement, Pediatrics. sourceExperimental — accuracy not yet measured

In the paper

“Other work finds links between daily screen media duration and higher cardiometabolic risk,252 which could also be explained by sleep deficits.253”

What the sources say

• ?Not checked — no full text of the sourcecites [252] Jahangiry, 2022, Screen time and the risk of metabolic syndrome among children and adolescents: A systematic review and dose-response meta-analysis, Nutr Metab Cardiovasc Dis. source
• Supported

  The citation to this source follows the proposed sleep-deficit explanation, rather than the preceding claim about daily screen duration. Section 7 (p. 6) says screen exposure is linked to shorter, poorer sleep and that sleep disruption contributes to the pathway connecting digital media exposure with increased adiposity and metabolic dysfunction in youth. (LLM, conf=0.92)

  cites [253] Samara, 2025, Sleep Patterns and Obesity Risk in Children, Sch J App Med Sci. source

In the paper

“Overall, interventional work that changes the physical built environment are likely to have a larger effect on digital media viewing habits and promote movement behaviors.258”

What the sources say

• Partly supported

  The Discussion reports that some playground and schoolyard changes increased children’s physical activity, although results were mixed. The review does not establish that built-environment interventions have a larger effect than other interventions, and the passages found do not address digital media viewing habits (searched: digital media viewing, screen time, television). (LLM, conf=0.87)

  cites [258] Schipperijn, 2024, The role of playgrounds in promoting children’s health - a scoping review, Int J Behav Nutr Phys Act. sourceExperimental — accuracy not yet measured

In the paper

“The built environment in Denmark may differ from that in the US, which may facilitate these nonsedentary activities.256,257”

What the sources say

• ?Not checked — no full text of the sourcecites [256] Pedersen, 2022, Effects of Limiting Recreational Screen Media Use on Physical Activity and Sleep in Families With Children: A Cluster Randomized Clinical Trial, JAMA Pediatr. source
• Partly supported

  Section 4.3 (p. 6) reports that nearly all Danish children had greenspace within walking or cycling distance and links nearby greenspaces to use, including cycling. Section 4.1 (p. 5) describes greenspace as a pathway to recreational physical activity. The paper does not compare Denmark’s built environment with that of the US, so that part of the attributed claim is unsupported. (LLM, conf=0.83)

  cites [257] Arvidsen, 2022, Demographic, social, and environmental factors predicting Danish children’s greenspace use, Urban For Urban Green. sourceExperimental — accuracy not yet measured

In the paper

“Although programs focusing only on body image internalization are not as effective as those also including media literacy,321 more benefit has been found with dissonance-based prevention programs.322”

What the sources say

• ?Not checked — no full text of the sourcecites [321] Stice, 2021, A meta-analytic review of trials that tested whether eating disorder prevention programs prevent eating disorder onset, Clin Psychol Rev. source
• Supported

  Citation 322 is attached to the claim that dissonance-based prevention programs show more benefit, not to the preceding media-literacy comparison. The Discussion (Summary of Average Effect Sizes; page not provided) reports significantly larger reductions in eating-disorder risk factors and symptoms than with minimal-intervention controls. It also notes that some trials did not find superiority over alternative programs. (LLM, conf=0.92)

  cites [322] Stice, 2019, Meta-analytic review of dissonance-based eating disorder prevention programs: Intervention, participant, and facilitator features that predict larger effects, Clin Psychol Rev. source

In the paper

“Specifically, these effects can either facilitate adaptive or contributive to maladaptive eating patterns.113”

What the sources say

• Supported

  The Conclusion says food influencers can facilitate adaptive or contribute to maladaptive eating routines and habits among their followers. The claim paraphrases this possibility in the context of parasocial effects; the paper does not present both outcomes as experimentally established. (LLM, conf=0.91)

  cites [113] Shabahang, 2024, Downloading appetite? Investigating the role of parasocial relationship with favorite social media food influencer in followers’ disordered eating behaviors, Eat Weight Disord. source

In the paper

“Online feeds and algorithms might contain overt sexual content,267,286 contributing to risky sexual behaviors.273,287”

What the sources say

• ?Not checked — no full text of the sourcecites [267] Collins, 2017, Sexual media and childhood well-being and health, Pediatrics. source
• ?Not checked — no full text of the sourcecites [286] Smith, 2016, Is sexual content in new media linked to sexual risk behaviour in young people? A systematic review and meta-analysis, Sex Health. source
• ?Not checked — no full text of the sourcecites [273] Mori, 2023, Exposure to sexual content and problematic sexual behaviors in children and adolescents: A systematic review and meta-analysis, Child Abuse Negl. source
• Partly supported

  The Discussion (Principal Findings; page not provided) reports an association between high-frequency SMS use and increased sexual risk behavior among adolescents, and suggests that social-media networks may create risk opportunities. It does not show that overt sexual content in online feeds or algorithms contributes to those behaviors; the mechanisms it discusses concern peers, partners, and perceived privacy. (LLM, conf=0.85)

  cites [287] Landry, 2017, Social media and sexual behavior among adolescents: is there a link?, JMIR Public Health Surveill. sourceExperimental — accuracy not yet measured

In the paper

“Developmentally, editing can offer positive options for benign creative expression and innovation but also enable perpetuation of unrealistic beauty standards.308”

What the sources say

• Supported

  The Background states that photo manipulation offers opportunities for creative expression and innovation while identifying the perpetuation of unrealistic beauty standards as its main risk. The Conclusion and call to action likewise says editing tools and filters may create unrealistic beauty standards. (LLM, conf=0.94)

  cites [308] Bozzola, 2024, Photo editing and the risk of anorexia nervosa among children and adolescents, Ital J Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“Websites containing “pro-Ana” (pro-anorexia) and “pro-Mia” (pro-bulimia) content promote restrictive eating and purging as lifestyle choices and minimize the medical consequences of disordered eating.3”

What the sources say

• Partly supported

  The Background (page not provided) says the pro-eating-disorder community has identified eating disorders as a lifestyle choice rather than an illness. It does not say that pro-Ana or pro-Mia websites promote restrictive eating or purging, or that they minimize the medical consequences of those behaviors. (LLM, conf=0.86)

  cites [3] Talbot, 2017, A content analysis of thinspiration, fitspiration, and bonespiration imagery on social media, J Eat Disord. sourceExperimental — accuracy not yet measured

In the paper

“Sextortion significantly impacts victims’ psychological, physical, social, and economic well-being, often resulting in heightened risks of depression, anxiety, suicidal thoughts, and in extreme cases, suicide.285”

What the sources say

• Supported

  The Introduction reports psychological harms including depression, anxiety, and suicidal ideation, as well as financial losses and disrupted relationships. The Impacts and Harms section reports suicide in some cases, and the Discussion notes other physical effects. (LLM, conf=0.93)

  cites [285] Ray, 2025, Sextortion: A Scoping Review, Trauma Violence Abuse. source

In the paper

“Girls are more likely to report sexting to be a result of pressure, whereas boys and teens who identify as LGBTQ+ report engaging in more consensual sexting.284”

What the sources say

• Partly supported

  The Results (§3.2) report that girls experienced more pressured sexting than boys and sexual-minority adolescents reported more consensual sexting than non-sexual-minority adolescents. They do not support the claim about boys engaging in more consensual sexting: boys reported more non-consensual sexting, and no other demographic differences in sexting were found. (LLM, conf=0.91)

  cites [284] Wachs, 2021, How Are Consensual, Non-Consensual, and Pressured Sexting Linked to Depression and Self-Harm? The Moderating Effects of Demographic Variables, Int J Environ Res Public Health. sourceExperimental — accuracy not yet measured

In the paper

“Digital media systems may also have lax privacy settings and recommendation algorithms that connect minors with strangers and put them at risk of exploitation.279,288”

What the sources say

• ?Not checked — no full text of the sourcecites [279] Patchin, 2020, Sextortion among adolescents: Results from a national survey of US youth, Sex Abuse. source
• Partly supported

  The Introduction (‘Online sexual abuse’) reports sexual approaches by unknown adults contacting children online, and the Discussion reports abuse by perpetrators adolescents had met online. Neither passage attributes those connections to lax privacy settings or recommendation algorithms; the paper does not support those proposed mechanisms. No page numbers are provided in our copy. (LLM, conf=0.87)

  cites [288] Jonsson, 2019, Online sexual abuse of adolescents by a perpetrator met online: a cross-sectional study, Child Adolesc Psychiatry Ment Health. sourceExperimental — accuracy not yet measured

In the paper

“Emerging work has identified symptoms of problematic internet use as early as toddlerhood, with moderately stable trajectories in the early childhood years and also in the teen years.61,135,327”

What the sources say

• Partly supported

  The Discussion reports early signs of problematic media use and moderate stability from age 2 to age 3. It does not report stable trajectories in the teen years. The study measures problematic media use broadly, rather than specifically problematic internet use. (LLM, conf=0.86)

  cites [61] Coyne, 2022, ABCs or Attack-Boom-Crash? A longitudinal analysis of associations between media content and the development of problematic media use in early childhood, Technol Mind Behav. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [135] Tóth-Király, 2021, Longitudinal trajectories, social and individual antecedents, and outcomes of problematic internet use among late adolescents, Child Dev. source
• ?Not checked — no full text of the sourcecites [327] Jolliff, 2020, #TechAddicted: Understanding Problematic Internet Use in Adolescents, Pediatr Rev. source

In the paper

“A supplementary category of “other specified feeding and eating disorder” (OSFED) captures approximately 60% of cases that do not meet criteria for a more specific clinical diagnosis.289”

What the sources say

• Partly supported

  The Introduction (Eating disorders in the 21st century; page unavailable) describes atypical eating disorders and reports overlooked cases of OSFED and binge eating disorder. It does not say that OSFED captures approximately 60% of cases, and its combined count for OSFED and binge eating disorder cannot establish that percentage for OSFED alone. (LLM, conf=0.82)

  cites [289] Dane, 2023, The social media diet: A scoping review to investigate the association between social media, body image and eating disorders amongst young people, PLOS Glob Public Health. sourceExperimental — accuracy not yet measured

In the paper

“Approximately 7% to 10% of children and teens are estimated to be affected by problematic internet use,324,325 but a range of estimates exist, with some as high as 28%.128,326”

What the sources say

• ?Not checked — no full text of the sourcecites [324] Pan, 2020, Systematic review and meta-analysis of epidemiology of internet addiction, Neurosci Biobehav Rev. source
• ?Not checked — no full text of the sourcecites [325] El Asam, 2019, Problematic internet use and mental health among British children and adolescents, Addict Behav. source
• Partly supported

  The Background reports that PIU prevalence estimates typically range from 1% to 10%, supporting the general magnitude but not the narrower 7%–10% estimate attributed to this source. The citing sentence attaches other citations to the separate 28% estimate, so that figure is not part of this verdict. (LLM, conf=0.87)

  cites [128] Restrepo, 2020, Problematic internet use in children and adolescents: associations with psychiatric disorders and impairment, BMC Psychiatry. sourceExperimental — accuracy not yet measured
• Partly supported

  The review reports adolescent estimates within the cited 7%–10% range, including 8.1% in Table 1 (p. 7), but does not give 7%–10% as an overall estimate for children and teens. Its Discussion (p. 20) emphasizes that prevalence varies widely across samples and measures; its high adolescent estimate is 26.7%, not 28%. (LLM, conf=0.83)

  cites [326] Kuss, 2014, Internet addiction: a systematic review of epidemiological research for the last decade, Curr Pharm Des. sourceExperimental — accuracy not yet measured

In the paper

“Although these online communities can also become a place of self-comparison, there can be more opportunities for this to be a beneficial and healing experience.301”

What the sources say

• Supported

  The Negative Influences section describes peer comparison on social media and its association with body-image concerns. The Positive Influences section says social media can build solidarity, reduce isolation, and support body acceptance and improved mood—benefits consistent with the citing sentence’s description of potentially beneficial experiences. (LLM, conf=0.88)

  cites [301] Clark, 2021, Weight Stigma and Social Media: Evidence and Public Health Solutions, Front Nutr. source

In the paper

“Previous work also supports that boys,337,338 teens with low subjective well-being,133 and teens who experience a fear of missing out134 or loneliness135 are also at greater likelihood of experiencing problematic internet use.”

What the sources say

• ?Not checked — no full text of the sourcecites [337] Lam, 2009, Factors associated with Internet addiction among adolescents, Cyberpsychol Behav. source
• ?Not checked — no full text of the sourcecites [338] Widyanto, 2006, ‘Internet Addiction’: A Critical Review, Int J Ment Health Addict. source
• Supported

  Citation 133 is attached to the low-subjective-well-being clause, not the claims about boys, fear of missing out, or loneliness. The Discussion (page not available) reports a negative correlation between problematic internet use and subjective well-being among students; the study includes secondary-school students. (LLM, conf=0.90)

  cites [133] Cai, 2023, Associations Between Problematic Internet Use and Mental Health Outcomes of Students: A Meta-analytic Review, Adolesc Res Rev. source
• ?Not checked — no full text of the sourcecites [134] Oberst, 2017, Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out, J Adolesc. source

In the paper

“Teens whose caregivers use more active mediation, defined as viewing together and discussing the content, spend less time using social media and report fewer problematic internet use symptoms.163,343”

What the sources say

• Partly supported

  The section on adolescents’ social media use reports less problematic social media use with active mediation, but it does not report less time on social media with active mediation; findings on time spent are mixed, and the reported reductions concern greater parental control or autonomy-supportive restrictive mediation. The parental mediation section says viewing together can become active mediation when it includes discussion, but distinguishes co-use from active mediation. The review addresses problematic social media use, not problematic internet use generally. (LLM, conf=0.88)

  cites [163] Beyens, 2022, Social media, parenting, and well-being, Curr Opin Psychol. sourceExperimental — accuracy not yet measured
• Partly supported

  The Discussion (§4.1) reports a significant inverse relationship between active parental mediation and problematic internet use among adolescents. The Introduction (§1.2) defines active mediation as explaining content and communicating views, but does not include viewing together; it distinguishes limits on media-use time as restrictive mediation. The paper does not report that teens with more active mediation spend less time on social media. (LLM, conf=0.90)

  cites [343] Liu, 2023, Active parental mediation and adolescent problematic internet use: The mediating role of parent–child relationships and hiding online behavior, Behav Sci (Basel). sourceExperimental — accuracy not yet measured

In the paper

“Overall, problematic internet use goes beyond the amount of time that is spent using digital media and also includes the quality of digital media use and impact on life functioning.14,323”

What the sources say

• Partly supported

  The ‘Problematic Media Use in Early-Middle Childhood’ section says screen-time hours alone should not determine problematic use and defines it by interference with a child’s functioning. The ‘Current Digital Media Use’ section also distinguishes benign, age-appropriate use from inappropriate use. The cited paper, however, addresses children’s screen-media use, not problematic internet use generally, so the citing sentence extends its scope. (LLM, conf=0.82)

  cites [14] Domoff, 2020, Interactional theory of childhood problematic media use, Hum Behav Emerg Technol. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [323] Moreno, 2013, Problematic internet use among older adolescents: A conceptual framework, Comput Human Behav. source

In the paper

“Online gambling has become increasingly popular and accessible, with about 5-15% of teens worldwide participating in online gambling.350,351”

What the sources say

• Supported

  The Introduction says online gambling is becoming increasingly popular among young people and reports that 5–15% of adolescents gamble online in international studies. It also describes online gambling as highly accessible. The Discussion notes substantial variation between countries, so the range is not a single worldwide prevalence estimate. (LLM, conf=0.93)

  cites [350] Montiel, 2021, Problematic online gambling among adolescents: A systematic review about prevalence and related measurement issues, J Behav Addict. source
• ?Not checked — no full text of the sourcecites [351] King, 2020, Adolescent land-based and internet gambling: Australian and international prevalence rates and measurement issues, Curr Addict Rep. source

In the paper

“These tools are validated, reliable questionnaires that assess the level of problematic media symptomatology among school-aged children and teens, respectively.”

What the sources say

• ?Not checked — no full text of the sourcecites [330] Domoff, 2020 source
• Partly supported

  The Discussion reports that the PMUM is a parent-report measure of problematic media use for children ages 4–11, and Study 1 Results support its reliability and validity. The paper does not evaluate the PRIUSS for teens; it lists the PRIUSS study in its References only. (LLM, conf=0.88)

  cites [332] Domoff, 2019, Development and validation of the Problematic Media Use Measure: A parent report measure of screen media “addiction” in children, Psychol Pop Media Cult. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [333] Jelenchick, 2015, Screening for Adolescent Problematic Internet Use: Validation of the Problematic and Risky Internet Use Screening Scale (PRIUSS), Acad Pediatr. source
• Partly supported

  The Methods > Measures section describes the PRIUSS-18 as a validated screening scale for problematic Internet use, and the Introduction says it was validated for adolescents and young adults. The paper does not address the PMUM or its use among school-aged children; it also does not establish that both questionnaires are reliable measures of broader problematic media symptoms. No page numbers are available in our copy. (LLM, conf=0.87)

  cites [334] Moreno, 2016, Development and Testing of a 3-Item Screening Tool for Problematic Internet Use, J Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“Such design reduces the friction to access digital technologies and prolongs the duration of digital play, because of the business model that supports many digital media companies.”

In the paper

“This rapidly changing technological landscape also converges with a period of increasing family stress.11”

What the sources say

• Not checked yetcites [11] Livingstone, 2019, Children’s data and privacy online: growing up in a digital age: an evidence review