Digital Ecosystems, Children, and Adolescents: Technical Report

In the paper

“Children with higher impulsivity are also more prone to greater digital media use duration compared with children with lower sensory-seeking behaviors.68,69”

What the sources say

• Partly supported

  The Discussion (page not available in our copy) reports that higher sensation-seeking traits were associated with more frequent R-rated movie watching in early adolescents. The study measured sensation-seeking using an impulsive-behavior scale, but it does not establish that higher impulsivity predicts longer digital media use overall or compare impulsivity with lower sensation-seeking behavior. (LLM, conf=0.86)

  cites [68] Zhang, 2025, Prospective associations between sleep, sensation-seeking, and mature screen usage in early adolescents: findings from the Adolescent Brain Cognitive Development study, Sleep. sourceExperimental — accuracy not yet measured
• Disputed

  The Materials and methods section defines surgency as including impulsivity and enjoyment of high-stimulus situations. In the Results table (page unavailable), surgency was not associated with screen time after adjustment (p = 0.88). The paper instead found that higher effortful control was associated with less screen time; it does not report the claimed comparison with children with lower sensory-seeking behavior. (LLM, conf=0.86)

  Checked by a reasoning model — may be wrong.

  cites [69] Leppänen, 2020, Association of screen time with long-term stress and temperament in preschoolers: results from the DAGIS study, Eur J Pediatr. sourceExperimental — accuracy not yet measured

In the paper

“For young children, use of mobile devices for emotion regulation is associated with lower emotion regulation over time.47,67”

What the sources say

• Disputed

  The Discussion reports that only TV viewing, not mobile-device use, predicted later externalizing behavior across six months; the Introduction identifies externalizing behavior as a marker of emotion-regulation problems. The paper instead found that earlier behavioral difficulties predicted greater later media use. It did not separately measure mobile-device use for emotion regulation. (LLM, conf=0.87)

  Checked by a reasoning model — may be wrong.

  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 [67] Radesky, 2023, Longitudinal Associations Between Use of Mobile Devices for Calming and Emotional Reactivity and Executive Functioning in Children Aged 3 to 5 Years, JAMA Pediatr. source

In the paper

“One large population-based study finds that greater duration of social media use is associated with lower physical activity behaviors among Canadian teens.249”

What the sources say

• Disputed

  The Discussion says the study did not find that overuse of social media was associated with lower physical activity among Canadian adolescents. Instead, intense use was associated with greater odds of meeting physical activity recommendations, while non-active use was associated with lower odds. The Measures section assesses frequency of online contact, not social-media-use duration. (LLM, conf=0.90)

  Checked by a reasoning model — may be wrong.

  cites [249] Morningstar, 2023, The association between social media use and physical activity among Canadian adolescents: a Health Behaviour in School-aged Children (HBSC) study, Can J Public Health. sourceExperimental — accuracy not yet measured

In the paper

“This engagement-based digital ecosystem may take the form of AI algorithms inferring teens’ interest in harmful content,2-4”

What the sources say

• ?Not checked — no full text of the sourcecites [2] Wolak, 2018, Sextortion of Minors: Characteristics and Dynamics, J Adolesc Health. source
• ?Could not verify

  The Discussion says thinspiration and bonespiration are easy to find and that users can evade content-blocking algorithms. The Method describes searching hashtags, but neither section addresses AI algorithms inferring teens’ interests from engagement (searched: interest inference, recommendation algorithms, engagement). (LLM, conf=0.75)

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

  The Content Filters and Parental Controls section reports that teens encounter harmful stereotypes and violent sexual content through pornography, and the Self-Reported Accidental Pornography Exposure Experiences section identifies social media as one route of exposure. Neither section attributes that exposure to AI algorithms inferring teens’ interests or to an engagement-based recommendation system. (LLM, conf=0.82)

  cites [4] Robb, 2023 sourceExperimental — accuracy not yet measured

In the paper

“endless scrolls and autoplay that prolong digital engagement at the expense of other offline child opportunities.6-9”

What the sources say

• ?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
• Partly supported

  The Discussion (page unavailable) says thumbnail designs aim to capture and sustain attention, supporting the general point about engagement. The Methods say autoplay was disabled during data collection, and the paper does not establish that endless scrolling or autoplay prolongs use at the expense of children’s offline opportunities. (LLM, conf=0.85)

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

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [8] Kidron, 2021
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [9] Kidron, 2023

In the paper

“Children’s caregivers (eg, parents) are the relational cornerstone in which children explore, learn, and play.28-31”

What the sources say

• Partly supported

  The paper discusses parent–child play, interaction, and caregivers’ responsiveness to children (section labeled Abstract; page unavailable). That supports the importance of caregiver relationships to play, but our copy does not state that caregivers are the relational foundation for children’s exploration and learning. (LLM, conf=0.78)

  cites [28] McDaniel, 2018, Technoference: Parent distraction with technology and associations with child behavior problems, Child Dev. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [29] Stockdale, 2020, Infants’ response to a mobile phone modified still-face paradigm: Links to maternal behaviors and beliefs regarding technoference, Infancy. source
• ?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
• ?Not checked — no full text of the sourcecites [31] Holmgren, 2024, Patterns of Parent Media Use: The influence of parent media use profiles on parental mediation, technoference, and problematic media use, Comput Human Behav. source

In the paper

“Autonomy-supportive (providing choices and consistency) and open-ended discussions with children about digital media are associated with reduced likelihood of problematic internet use for children.60”

What the sources say

• Partly supported

  The Discussion (page not available in our copy) reports that adolescents whose parents used more autonomy-supportive mediation were more likely to belong to a higher-digital-flourishing group. It does not report a reduced likelihood of problematic internet use, which is a different outcome. (LLM, conf=0.86)

  cites [60] Rosič, 2024, Trajectories of digital flourishing in adolescence: The predictive roles of developmental changes and digital divide factors, Child Dev. sourceExperimental — accuracy not yet measured

In the paper

“One systematic review of parent-child joint media engagement suggested mixed findings, likely depending on the nature of the digital media task, age of child, and comparison condition (eg, toys, books, TV).54”

What the sources say

• Supported

  The Abstract reports inconsistent effects of joint media engagement on several parent–child interactions. The discussion (Additional information; page unavailable) says task differences may explain contrasting findings and identifies children’s age as a possible influence. The Data extraction section lists different comparison activities, including books, toys and television. (LLM, conf=0.91)

  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

“In one international systematic review, children and teens reported preferring that caregivers ask for their assent before sharing information, photos, or videos of them online.59”

What the sources say

• Supported

  The review’s “Children’s agency, privacy, and risks” section states that children and adolescents prefer parents to seek permission before sharing any content on social media. This supports the claim’s paraphrase about asking for assent before posting information, photos, or videos. No page number is provided in our copy. (LLM, conf=0.94)

  cites [59] Tosuntaş, 2024, Sharenting: A systematic review of the empirical literature, J Fam Theory Rev. source

In the paper

“Greater parenting stress also predicts greater caregiver disruptions from mobile devices, particularly for children who have externalizing behaviors.48”

What the sources say

• Partly supported

  The Results (page unavailable) report that parents with greater perceived parenting stress were more likely to say social media use and mobile gaming cut into family time. The paper does not report that this association is particularly strong for children with externalizing behaviors; it measures perceived interference, not observed disruptions. (LLM, conf=0.88)

  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

In the paper

“When mobile device apps and content are designed to absorb caregiver attention, it can be challenging for caregivers to attend and respond to cues from infants,24,46 children,47 and teens.41”

What the sources say

• ?Not checked — no full text of the sourcecites [24] McDaniel, 2016, Technology interference in the parenting of young children: Implications for mothers’ perceptions of coparenting, Soc Sci J. source
• ?Not checked — no full text of the sourcecites [46] Linder, 2021, The impact of parent and child media use on early parent-infant attachment, Infancy. source
• Partly supported

  The Introduction (page unavailable) says mobile media may displace parent–child interaction and that gamified design can absorb children’s attention, making interaction around devices harder. It does not say that apps absorb caregivers’ attention or make caregivers less able to notice and respond to children’s cues. This citation is attached to the claim about children, not the separate references for infants or teens. (LLM, conf=0.84)

  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 [41] Lauricella, 2020, Parental Influence on Youth Media Use, J Child Fam Stud. source

In the paper

“when social systems constrain families’ access to these opportunities, caregivers may need to rely on mobile devices for entertainment or stress relief.52”

What the sources say

• Partly supported

  The paper’s table of parent responses describes caregivers using phones for distraction, games and relief during stressful parenting moments. Its discussion also describes phone use as a temporary escape from negative feelings. The paper does not establish that social systems constrain families’ access to other opportunities or that such constraints make caregivers rely on devices. (LLM, conf=0.84)

  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. sourceExperimental — accuracy not yet measured

In the paper

“Many caregivers also indicate that they post photos or images of their children online, known as sharenting, in order to connect with community.59”

What the sources say

• Supported

  The Introduction defines sharenting as parents sharing information and images of their children on social media and describes connecting with family and friends as a motivation. The “Characteristics of sharenting” section also reports that parents shared photos and other posts about their children and said the practice helped them stay in touch with family and friends. The copy provides no page numbers for these passages. (LLM, conf=0.91)

  cites [59] Tosuntaş, 2024, Sharenting: A systematic review of the empirical literature, J Fam Theory Rev. source

In the paper

“Caregivers have the power to shape their children’s digital experiences.23,54”

What the sources say

• ?Not checked — no full text of the sourcecites [23] Padilla-Walker, 2020, Parent-child joint media engagement in infancy, Infancy. source
• Supported

  Section 1.2 describes caregivers helping children understand digital content, use devices, and explore program features. Section 3.2.4 also reports parents providing technical guidance during app use. These passages support the broad claim that caregivers can shape children’s digital experiences. (LLM, conf=0.90)

  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

“some caregivers indicate that during moments of frustration with their children, they use their mobile devices to seek parenting advice.52”

What the sources say

• Supported

  The study asked parents to describe a recent time they used a mobile device because parenting felt stressful. Its table of phone-use motivations identifies parents who searched for parenting tips in the moment, including advice about handling a child’s crying or communication difficulties. This supports the claim about some caregivers seeking advice during difficult moments with their children. (LLM, conf=0.93)

  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. sourceExperimental — accuracy not yet measured

In the paper

“When digital media are designed to be persuasive, encourage prolonged use, and capture users’ attention, disengagement can be difficult.14,61,62”

What the sources say

• Supported

  The Distal factors section says digital products are designed to prolong use and that young children may find engagement-promoting features difficult to resist. It also reports difficulty transitioning away from autoplay video and getting children’s attention during tablet play. The paper discusses these effects in children; page numbers were not supplied. (LLM, conf=0.90)

  cites [14] Domoff, 2020, Interactional theory of childhood problematic media use, Hum Behav Emerg Technol. source
• Partly supported

  The Interactional Theory of Childhood Problematic Media Use section says some digital environments are designed to sustain engagement and that faster-paced content may make it harder for young children to disengage. This supports the claim's central idea, but the paper discusses children and particular media features, not difficulty disengaging for users generally. (LLM, conf=0.82)

  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
• Partly supported

  The Abstract (page not provided) describes problematic media use in young children as including difficulty transitioning away from media and fixating on screens. It does not say that persuasive design, prolonged-use features, or attention-capturing design causes that difficulty. (LLM, conf=0.82)

  cites [62] Coyne, 2024, The growth of problematic media use over early childhood: Associations with long-term social and emotional outcomes, Comput Human Behav. sourceExperimental — accuracy not yet measured

In the paper

“In turn, greater mobile device use may then be associated with more disrupted parent-child interactions.24,45,47,53”

What the sources say

• ?Not checked — no full text of the sourcecites [24] McDaniel, 2016, Technology interference in the parenting of young children: Implications for mothers’ perceptions of coparenting, Soc Sci J. source
• Supported

  The Introduction reports observations linking parent mobile-device use with fewer parent-child interactions and lower responsiveness to children’s bids for attention. The Conclusion likewise says digital technology may displace opportunities for parent-child connection, supporting the citing sentence’s hedged association. (LLM, conf=0.92)

  cites [45] McDaniel, 2018, Technoference: longitudinal associations between parent technology use, parenting stress, and child behavior problems, Pediatr Res. source
• Supported

  The Introduction says mobile devices can be used throughout daily routines and may displace opportunities for parent-child interaction. It also describes mobile device use as potentially interrupting those interactions. The citing sentence preserves that tentative wording; the paper does not claim to have measured interaction disruption directly. (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. source
• Supported

  Section 1.2 reports fewer and delayed responses to children when parents use their phones. The Discussion also states that parenting quality was worse among parents with greater device-related distraction scores, supporting the claim’s hedged association. (LLM, conf=0.88)

  cites [53] McDaniel, 2021, The DISRUPT: A measure of parent distraction with phones and mobile devices and associations with depression, stress, and parenting quality, Hum Behav Emerg Technol. source

In the paper

“These findings are likely related to modeled behaviors, genetic factors, and structural forces that shape the families’ behaviors.42”

What the sources say

• Partly supported

  The Discussion (page unavailable) suggests that parents may serve as role models for children's screen use and that low income or single-parent households may shape parental screen use. These passages support modeled behavior and some family-resource influences, but our copy does not attribute the findings to genetic factors. (LLM, conf=0.86)

  cites [42] Cost, 2023, Patterns of parent screen use, child screen time, and child socio-emotional problems at 5 years, J Neuroendocrinol. sourceExperimental — accuracy not yet measured

In the paper

“Indeed, greater notifications per day that require caregiver engagement are associated with stress, especially when notifications pertain to work.63”

What the sources say

• Partly supported

  The Discussion reports greater parent stress when notifications prompted more device pickups, supporting the caregiver-engagement part of the claim. It also reports no association between notifications from different apps and parent stress, so the claim that work-related notifications are especially linked to stress is not supported by this study. The Introduction mentions negative emotions from productivity notifications, but attributes that finding to prior work. (LLM, conf=0.88)

  cites [63] Munzer, 2024, Greater mobile device-prompted phone pickups are associated with daily parent stress, Acta Paediatr. sourceExperimental — accuracy not yet measured

In the paper

“High-quality child care, after-school activities, and safe outdoor play are often contingent on the structural resources that support families.16,51”

What the sources say

• ?Not checked — no full text of the sourcecites [16] McArthur, 2022, Screen Time as a Mechanism Through Which Cumulative Risk is Related to Child Socioemotional and Developmental Outcomes in Early Childhood, Res Child Adolesc Psychopathol. source
• Partly supported

  The 'Implications of Smart Beginnings' section describes inequality of resources and opportunity for families, and 'Preventing Poverty-Related Disparities through Supporting Early Relational Health' discusses barriers to obtaining resources for children’s development. These passages support the general connection between family resources and children’s opportunities, but the paper does not specifically address access to high-quality child care, after-school activities, or safe outdoor play. Page numbers are unavailable in our copy. (LLM, conf=0.79)

  cites [51] Shaw, 2021, Reducing Poverty-Related Disparities in Child Development and School Readiness: The Smart Beginnings Tiered Prevention Strategy that Combines Pediatric Primary Care with Home Visiting, Clin Child Fam Psychol Rev. sourceExperimental — accuracy not yet measured

In the paper

“In addition to quantity and quality, research has also focused on the interplay between digital media and caregiver-child relationships and behaviors (“early relational health”).32,65,66”

What the sources say

• Partly supported

  The Emerging Science of Relational Health section defines relational health through supportive caregiver–child relationships and responsive interactions. The Links Between Relational Health and Resilience section also notes concern that excessive screen time may limit opportunities to develop skills. Neither passage says that research has examined the interplay between digital media and caregiver–child relationships or behaviors, so that part of the attributed claim is unsupported. (LLM, conf=0.82)

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

  The Statement of Need (page unavailable) contrasts electronic media with interactive, nurturing shared reading. The Recommendations for Pediatricians (page unavailable) state that digital books do not foster equivalent parent-child interactions and advise reciprocal interaction during digital activities. The paper also defines foundational caregiver-child relationships as early relational health. (LLM, conf=0.88)

  cites [65] Klass, 2024, Literacy Promotion: An Essential Component of Primary Care Pediatric Practice: Policy Statement, Pediatrics. source
• Supported

  The “Encouraging Books Rather Than Screens” section reports research linking screen exposure and e-books to changes in positive parent-child interactions, including shared reading and engagement. The “Early Relational Health” section defines that term in part through positive parenting practices and nurturing, responsive parent-child relationships. Page numbers were not available in our copy. (LLM, conf=0.91)

  cites [66] Klass, 2024, Literacy Promotion: An Essential Component of Primary Care Pediatric Practice: Technical Report, Pediatrics. source

In the paper

“In terms of longitudinal studies testing bidirectional effects, one study found associations between quantity of digital media duration and children’s achievement of developmental milestones at ages 2, 3, and 5 years.90”

What the sources say

• Supported

  The Abstract reports that screen time and developmental outcomes were assessed at 24, 36, and 60 months in a longitudinal cohort. The Discussion reports that greater screen time at 24 and 36 months was associated with poorer developmental screening performance at 36 and 60 months, respectively; the reverse association was not observed. (LLM, conf=0.93)

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

In the paper

“However, preschoolers tend to be more capable of language learning through educational media because of greater brain maturation and memory flexibility.81”

What the sources say

• Partly supported

  Section 2.1 (Content) says preschoolers can learn words from well-designed educational media and reports a hypothesis that their developmental readiness reflects improved memory flexibility and greater understanding of media’s symbolic nature. It does not identify greater brain maturation as the mechanism, and it presents the developmental explanation as a hypothesis rather than an established cause. (LLM, conf=0.85)

  cites [81] Dore, 2024 sourceExperimental — accuracy not yet measured

In the paper

“For example, one meta-analysis found that the quantity of digital media use (television and gaming) in children ages 4 to 18 years is associated with poorer academic performance scores, language, and mathematics.88”

What the sources say

• Partly supported

  The Search Strategy and Inclusion Criteria section includes children and adolescents aged 4–18. The Meta-analysis and Discussion sections report inverse associations for television viewing with composite scores, language, and mathematics, but for gaming only with composite scores; the Discussion also reports no association for overall screen-media time. The claim overgeneralizes the findings across media types and outcomes. Page numbers were not provided in our copy. (LLM, conf=0.90)

  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. sourceExperimental — accuracy not yet measured

In the paper

“For example, in one meta-analysis,75 the quantity of digital media is associated with poorer language skills.”

What the sources say

• Supported

  The Discussion reports that the paper’s meta-analyses associated greater quantity of screen use with lower child language skills. The Conclusions reiterate the finding, and the claim preserves its correlational framing. (LLM, conf=0.94)

  cites [75] Madigan, 2020, Associations between screen use and child language skills: A systematic review and meta-analysis, JAMA Pediatr. source

In the paper

“First, even high-quality programing and co-viewing digital media do not provide children with the same level of benefit as direct, device-free interactions with sensitive and attuned caregivers.79”

What the sources say

• Partly supported

  The Discussion (page unavailable) reports that sensitive, attuned caregiver interactions are associated with stronger child language skills. It does not compare those interactions with high-quality programming or co-viewing, or establish that device-free interaction provides greater benefits. The Limitations section also cautions that the findings do not establish causality. (LLM, conf=0.87)

  cites [79] Madigan, 2019, Parenting Behavior and Child Language: A Meta-analysis, Pediatrics. sourceExperimental — accuracy not yet measured

In the paper

“Meta-analytic studies are mixed.82”

What the sources say

• Supported

  The Education Outcomes section reports mixed meta-analytic findings for youths: general screen use, television and video games were negatively associated with learning, while narrated e-books and educational screen interventions were positively associated with it. It also reports that the association between screen use and literacy changed direction with co-viewing or educational content. No page number is available in our copy. (LLM, conf=0.92)

  cites [82] Sanders, 2024, An umbrella review of the benefits and risks associated with youths’ interactions with electronic screens, Nat Hum Behav. source

In the paper

“In one meta-analysis, among children ages 0 to 12, the quantity of digital media use was associated with both internalizing and externalizing problems.100”

What the sources say

• Supported

  The Introduction says the meta-analysis focused on children 12 years or younger and examined both types of behavior problems. The Results report small but significant correlations between longer screen time and both externalizing and internalizing problems. (LLM, conf=0.94)

  cites [100] Eirich, 2022, Association of screen time with internalizing and externalizing behavior problems in children 12 years or younger: a systematic review and meta-analysis, JAMA Psychiatry. sourceExperimental — accuracy not yet measured

In the paper

“In longitudinal studies testing bidirectional effects, one study found that greater internalizing and externalizing behaviors in children at age 3 are directionally associated with increased duration of digital media use at age 5.103”

What the sources say

• Supported

  The Abstract reports that greater externalizing and internalizing behaviors at age 3 were directionally associated with increased screen time at age 5. The Cross-lagged parameter estimates section separately reports the same age-3-to-age-5 association for each behavior type. The study measured screen time in hours per day, consistent with the claim’s reference to duration of digital media use. (LLM, conf=0.95)

  cites [103] Neville, 2021, Bidirectional associations between screen time and children’s externalizing and internalizing behaviors, J Child Psychol Psychiatry. source

In the paper

“Kidfluencers, defined as children who are influencers themselves, likely reflect the digital ecosystems that incentivize user-generated content that leverage parasocial relationships to sell commercial products and capture children’s attention.113”

What the sources say

• Partly supported

  The Introduction (page unavailable) describes parasocial relationships as part of social-media influencers’ persuasive power, which supports that element of the claim. It does not discuss kidfluencers, digital ecosystems that incentivize user-generated content, or using such content to sell products and capture children’s attention; the study concerns followers of food influencers. (LLM, conf=0.82)

  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. sourceExperimental — accuracy not yet measured

In the paper

“Design features, such as auto-play, infinite scrolling, and personalized algorithmic recommendations on social media platforms are digitally engineered to both prolong device use and make disengagement from devices more difficult,19 particularly for children, who may be developing their ability to control impulses.”

What the sources say

• ?Could not verify

  The Problematic Media Use section discusses excessive use and children’s self-regulation, but not platform design features. Searches for auto-play, infinite scrolling, algorithmic recommendations, and engineered difficulty disengaging found no passage addressing the claim. Page numbers were not available in our copy. (LLM, conf=0.76)

  cites [19] Coyne, 2021, Tantrums, toddlers and technology: Temperament, media emotion regulation, and problematic media use in early childhood, Comput Human Behav. sourceExperimental — accuracy not yet measured

In the paper

“Children with attention-deficit/hyperactivity (ADHD) symptoms (ie, inattention and hyperactivity) at age 6 were more likely to engage in violent video gaming 1 year later.87”

What the sources say

• ?Could not verify

  The Method section (page unavailable) describes annual measurements of children's digital game use and cognitive tasks, but does not report ADHD symptoms or violent-game use as outcomes. Searches for age-six ADHD symptoms predicting violent gaming one year later found no passage addressing that relationship; the Discussion's mention of violent gaming concerns a different study of adults. (LLM, conf=0.76)

  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

“However, the reverse was not true—playing more violent video games did not heighten children’s ADHD symptoms.87”

What the sources say

• ?Could not verify

  The Discussion addresses gaming and intelligence, not whether violent video games affect children’s ADHD symptoms. Searches for ADHD and violent game play found only a related title in the References and a Discussion example about aggression; neither reports the claimed finding. Page numbers were not available in our copy. (LLM, conf=0.76)

  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

“and also that social media use was likely to heighten later depression symptoms.106”

What the sources say

• ?Could not verify

  The Discussion (page unavailable) describes social media as a possible way for adolescents to stay connected during lockdown, while the Results discuss depressive symptoms without linking them to social media use. Searches for later depression symptoms and social media as a predictor found no passage addressing the claimed relationship. (LLM, conf=0.74)

  cites [106] Houghton, 2022, Longitudinal trajectories of mental health and loneliness for Australian adolescents with-or-without neurodevelopmental disorders: the impact of COVID-19 school lockdowns, J Child Psychol Psychiatry. sourceExperimental — accuracy not yet measured

In the paper

“Moreover, greater digital media duration at ages 3 and 5 was also directionally associated with increased internalizing behaviors at ages 5 and 7, respectively.103”

What the sources say

• Supported

  The Abstract states that greater screen time at ages 3 and 5 was directionally associated with increased internalizing behaviors at ages 5 and 7, respectively. The Cross-lagged parameter estimates section reports both age-to-age associations. The source measures screen time, which the claim paraphrases as digital media duration. (LLM, conf=0.94)

  cites [103] Neville, 2021, Bidirectional associations between screen time and children’s externalizing and internalizing behaviors, J Child Psychol Psychiatry. source

In the paper

“Additionally, as mentioned earlier, there are also associations between greater digital media use and higher well-being that are often overlooked.120”

What the sources say

• Supported

  In “Recommendation 1: don’t collapse across well- and ill-being outcomes” (page unavailable), the paper reports a positive meta-analytic association between time spent on social media and happiness. It argues that combining well-being and ill-being measures obscures findings such as this, supporting the claim that positive associations can be overlooked. The evidence concerns social media use specifically, rather than every form of digital media use. (LLM, conf=0.90)

  cites [120] Valkenburg, 2022, Social media use and well-being: What we know and what we need to know, Curr Opin Psychol. source

In the paper

“Indeed, greater social support for families facing socioeconomic barriers is associated with more digital device boundaries, which speaks to the benefits of support provision.117”

What the sources say

• Supported

  The Discussion reports that, among low-income families, greater parent social support was associated with high restriction of child screen time in multivariate analyses. This supports the cited association between social support and screen-time boundaries; the sentence’s suggestion about providing support is an inference, not a tested intervention effect. (LLM, conf=0.92)

  cites [117] Lampard, 2013, The family context of low-income parents who restrict child screen time, Child Obes. source

In the paper

“Longitudinal studies testing bidirectional associations in teens found that depressive symptoms were likely to heighten social media use across adolescence105,106”

What the sources say

• Partly supported

  The Discussion reports that depressive symptoms predicted slight increases in active social media use within individuals across adolescence. The Conclusions qualify this as a very small, statistically weak effect that was somewhat inconsistent over time; saying symptoms were likely to heighten social media use omits those limits and extends the finding beyond active use. (LLM, conf=0.84)

  cites [105] Puukko, 2020, Social Media Use and Depressive Symptoms-A Longitudinal Study from Early to Late Adolescence, Int J Environ Res Public Health. sourceExperimental — accuracy not yet measured
• ?Could not verify

  The Methods > Measures section shows that depressive symptoms were assessed, while the Discussion mentions social media use during COVID-19 lockdowns. Neither section reports a test of bidirectional associations or a finding that depressive symptoms predicted increased social media use across adolescence; searches for those relationships found no such passage. Page numbers were not available in our copy. (LLM, conf=0.76)

  cites [106] Houghton, 2022, Longitudinal trajectories of mental health and loneliness for Australian adolescents with-or-without neurodevelopmental disorders: the impact of COVID-19 school lockdowns, J Child Psychol Psychiatry. sourceExperimental — accuracy not yet measured

In the paper

“Furthermore, many online videos and apps in the app store are low-quality, despite having educational claims otherwise.5,92”

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 report that 72 of 124 educational apps (58%) were classified as lower-quality, and the Discussion concludes that not all apps marketed as educational are equally educational. The paper does not establish that many online videos are low-quality; its assessment concerns apps. (LLM, conf=0.88)

  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

“and worsened sleep.139”

What the sources say

• Partly supported

  The Results and Discussion report that more frequent electronic media use in bed before sleep was associated with shorter sleep and more sleep difficulties in adolescents. The Measures section shows that this bedtime-use measure assessed frequency, not duration; the paper does not establish the claimed association specifically for greater duration of digital media use. (LLM, conf=0.82)

  cites [139] Lemola, 2015, Adolescents’ electronic media use at night, sleep disturbance, and depressive symptoms in the smartphone age, J Youth Adolesc. sourceExperimental — accuracy not yet measured

In the paper

“Those who report “none” to “very limited” social media use and those who report “very heavy” social media use tend to experience worse mental well-being compared with those with a middling “sweet spot” of use.122”

What the sources say

• Partly supported

  The Confirmatory analyses (pp. 7–8) support a ‘sweet spot’ pattern for adolescents’ digital-screen time: well-being was generally flat or improved below the observed thresholds and declined above them. But the activities analyzed were films and TV, games, computer use, and smartphone use—not social media use specifically—so the claim’s social-media-specific comparison is not established by this paper. (LLM, conf=0.88)

  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

“The ubiquity of access to digital media allows it to become an easy distraction during times of emotional distress, providing emotional relief and subsequently reinforcing digital media engagement.19”

What the sources say

• Partly supported

  The Media Emotion Regulation section describes parents using phones to soothe distressed infants and toddlers, and the Problematic Media Use section proposes that this may foster reliance on media for coping. The Discussion reports an association with concurrent problematic media use, but the paper does not establish that ubiquitous access causes emotional relief and reinforces engagement across digital-media users generally. (LLM, conf=0.87)

  cites [19] Coyne, 2021, Tantrums, toddlers and technology: Temperament, media emotion regulation, and problematic media use in early childhood, Comput Human Behav. sourceExperimental — accuracy not yet measured

In the paper

“Teens who experience challenges with emotion regulation,129 executive function and impulsivity (eg, ADHD),61,130,131 or social interactions (autism spectrum disorder)132 may experience more adverse effects from digital media.”

What the sources say

• Partly supported

  Citation 129 is attached to the emotion-regulation part of the sentence. The Introduction (page not provided) describes developing emotion-regulation circuits as one reason youth may be vulnerable to negative outcomes from social media. It does not establish that teens who specifically experience emotion-regulation challenges have more adverse effects than other teens. (LLM, conf=0.82)

  cites [129] Shannon, 2022, Problematic Social Media Use in Adolescents and Young Adults: Systematic Review and Meta-analysis, JMIR Ment Health. sourceExperimental — accuracy not yet measured
• Partly supported

  The Discussion (page not provided) says executive functioning and self-regulation might protect against problematic media-use symptoms, and notes that regulation strategies appear protective at later ages. The paper studies young children, however, and does not establish that teens with ADHD or impulsivity experience more adverse effects from digital media. (LLM, conf=0.82)

  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 [130] Magis-Weinberg, 2021, Problematic Media Use and Symptoms of Anxiety and Depression During the Pandemic: An Investigation among Peruvian Adolescents in low-and middle-income Settings, PsyArXiv. source
• Partly supported

  The Abstract says adolescents with co-occurring mental health concerns or other vulnerabilities may experience problems related to social media use. It does not specifically address autism spectrum disorder or establish that challenges with social interactions increase adverse effects. Citation 132 is attached to that autism-specific part of the sentence. (LLM, conf=0.78)

  cites [131] Borgen, 2022, Developing Healthy Social Media Practices: An Outpatient Caregiver-Adolescent Group Intervention, J Contemp Psychother. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [132] Normand, 2021, A systematic review of problematic internet use in children, adolescents, and adults with autism spectrum disorder, J Autism Dev Disord. source

In the paper

“However, more recent data suggested this patterning of findings is more heterogeneous.148”

What the sources say

• Supported

  The Discussion (p. 19) reports that the effects of all three types of social media use differed from adolescent to adolescent, with positive, negative, and negligible effects. This supports the claim that the findings show more heterogeneous patterns, specifically across adolescents. (LLM, conf=0.91)

  cites [148] Beyens, 2024, Social Media Use and Adolescents’ Well-Being, Developing a Typology of Person-Specific Effect Patterns. source

In the paper

“Early adolescence may be a period of relative susceptibility to negative effects.137”

What the sources say

• Supported

  The Introduction describes adolescence as a critical period of vulnerability to social-media effects on mental health. The Discussion adds that developmental factors, including age, may make some adolescents more susceptible to negative media effects; the study focuses on early adolescence. (LLM, conf=0.87)

  cites [137] Nagata, 2025, Social Media Use and Depressive Symptoms During Early Adolescence, JAMA Netw Open. source

In the paper

“In one systematic review, problematic internet use was associated with greater depressive, anxiety symptoms, and psychological distress symptoms with moderate effect estimates.127”

What the sources say

• Partly supported

  The Discussion reports moderate positive correlations between problematic Instagram use and depression and anxiety, and a moderate-to-large association with other psychological distress. The claim instead says problematic internet use, a broader category the review did not assess; its abbreviation PIU refers to problematic Instagram use. (LLM, conf=0.88)

  cites [127] Sepas, 2024, The Association between Problematic Instagram Use, Psychological Distress, and Well-Being: A Systematic Review and Meta-Analysis, Cyberpsychol Behav Soc Netw. sourceExperimental — accuracy not yet measured

In the paper

“Previous work among teens has supported a “goldilocks” effect or U-shaped relationship between the duration of time spent using social media and mental well-being for teens.122”

What the sources say

• Partly supported

  The Confirmatory analyses (p. 7) and Discussion (p. 9) support a Goldilocks-shaped relationship between digital-screen time and mental well-being among adolescents. But the measured activities were films and TV, games, computer use, and smartphone use—not time spent using social media specifically—so the citation does not establish the claim at that level of specificity. (LLM, conf=0.88)

  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

“Difficulties with emotion regulation are associated with anxiety, depression, ADHD, conduct problems, and problematic internet use.124”

What the sources say

• ?Could not verify

  The research-agenda table lists depression, emotional reactivity, and dysregulation of ICT use as separate constructs; it does not link difficulties with emotion regulation to any of the claimed conditions. Searches for anxiety, ADHD, conduct problems, and problematic internet use found no passage establishing those associations. (LLM, conf=0.76)

  cites [124] de la Fuente, 2022, Advances on self-regulation models: A new research agenda through the SR vs ER behavior theory in different psychology contexts, Front Psychol. sourceExperimental — accuracy not yet measured

In the paper

“Greater duration of digital media use is associated with greater ADHD symptoms138”

What the sources say

• Partly supported

  The Primary Analysis and Secondary Analyses report that greater high-frequency digital media use was associated with subsequent ADHD symptoms among adolescents. But the study measured how often activities were used, not the duration of use, so it does not establish the claim as phrased. (LLM, conf=0.88)

  cites [138] Ra, 2018, Association of digital media use with subsequent symptoms of attention-deficit/hyperactivity disorder among adolescents, JAMA. sourceExperimental — accuracy not yet measured

In the paper

“Use of social media before age 11 is related to greater problematic digital media behaviors153”

What the sources say

• Supported

  The Abstract defines childhood initiation as starting Instagram or Snapchat at age 10 or younger and reports an association with more problematic digital behaviors than later initiation. The Results section, “Age of Initiation and Digital Behaviors,” reports more frequent social-media checking and higher problematic digital technology use among childhood initiators. (LLM, conf=0.94)

  cites [153] Charmaraman, 2022, Associations of early social media initiation on digital behaviors and the moderating role of limiting use, Comput Human Behav. source

In the paper

“Overall, population-level and meta-analytic studies suggest there are small associations between duration of time spent on digital media use and teen well-being.122,136”

What the sources say

• Supported

  The Abstract (p. 3) describes a representative sample of 120,115 English adolescents, supporting the population-level part of the sentence. Confirmatory analyses (p. 9) report that higher screen time accounted for 1.0% or less of the observed variation in mental well-being, supporting the characterization of the association as small. This paper is not a meta-analysis; the sentence cites two sources for the two types of study. (LLM, conf=0.91)

  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. source
• Supported

  The Conclusion (page unavailable) reports a small negative correlation between digital technology use and adolescent well-being across the research reviewed. The ‘Small negative associations’ section (page unavailable) specifically describes small associations in meta-analyses. The paper cautions that the evidence is conflicting and does not establish causation, consistent with the claim’s wording as an association. (LLM, conf=0.91)

  cites [136] Orben A, 2020, Teenagers, screens and social media: a narrative review of reviews and key studies, Soc Psychiatry Psychiatr Epidemiol. source

In the paper

“In general, early adolescence (10-15 years) 152 may represent a time of relatively greater susceptibility to the effects of social media (eg, lower life satisfaction).144”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [152] McCabe, 2023
• Supported

  The Results and discussion identify younger adolescents as ages 10–15 and report a more negative association between social media use and life satisfaction in adolescence than in most other age groups. The paper also reports age-specific windows in which higher social media use predicted lower life satisfaction one year later—ages 11–13 for females and 14–15 for males—supporting the claim’s cautious wording. (LLM, conf=0.92)

  cites [144] Orben, 2022, Windows of developmental sensitivity to social media, Nat Commun. source

In the paper

“For instance, some teens with more passive social media use actually experience more positive effects on well-being compared with those with more active social media use.149”

What the sources say

• Partly supported

  The Abstract reports that some adolescents felt better after browsing, and the Conclusion says browsing may have positive, negative, or no effects on well-being. But this study does not show that teens with more passive use had more positive effects than teens with more active use; its active-versus-passive discussion reports findings from another study, not that comparison. (LLM, conf=0.87)

  cites [149] Valkenburg, 2021, Social Media Browsing and Adolescent Well-Being: Challenging the “Passive Social Media Use Hypothesis”, J Comput Mediat Commun. sourceExperimental — accuracy not yet measured

In the paper

“and disruption of sleep duration and timing.154”

What the sources say

• Partly supported

  The Abstract Results report that starting social media at an early age was among factors associated with later bedtimes and fewer hours of sleep on school nights. Our copy does not establish a specific before-age-11 cutoff; the surveyed adolescents were aged 11–15, so the sleep outcomes were not measured before age 11. (LLM, conf=0.85)

  cites [154] Charmaraman, 2021, Quantity, Content, and Context Matter: Associations Among Social Technology Use and Sleep Habits in Early Adolescents, J Adolesc Health. sourceExperimental — accuracy not yet measured

In the paper

“The optimal age of mobile device ownership is variable and likely depends on many individual and psychosocial characteristics.155,156”

What the sources say

• Partly supported

  The Discussion (page unavailable) suggests that the effects of phone ownership may differ by sex and pubertal maturity, supporting the idea that individual characteristics matter. But these findings were exploratory, and the Results report no statistically significant associations for acquisition age after correction for multiple testing. The paper does not establish that an optimal ownership age varies with many individual and psychosocial characteristics. (LLM, conf=0.84)

  cites [155] Sun, 2023, Are mobile phone ownership and age of acquisition associated with child adjustment? A 5-year prospective study among low-income Latinx children, Child Dev. sourceExperimental — accuracy not yet measured
• Partly supported

  The Discussion reports no general association between early ownership and wellbeing, but finds differing associations by gender and psychosocial domain. That supports the idea that effects vary; the paper does not establish an optimal ownership age or show that it depends on many individual characteristics. The Limitations (p. 21) note that the study cannot determine precisely when children acquired phones between ages 9 and 13. (LLM, conf=0.82)

  cites [156] Dempsey, 2020, Early mobile phone ownership: influencing the wellbeing of girls and boys in Ireland?, J Child Media. sourceExperimental — accuracy not yet measured

In the paper

“When teens feel less in control of their bodies, emotions, and social life offline, these symptoms might also be mirrored in the online world.128”

What the sources say

• Partly supported

  The Mental disorders and Indices of impact of PIU sections report associations between problematic internet use, depressive disorders, and broader impairment in children and adolescents. The Discussion also links poor self-control with PIU in individuals with ADHD. The paper does not establish that feeling less in control of one's body, emotions, and offline social life is mirrored online; that interpretation goes beyond the reported associations. (LLM, conf=0.78)

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

In the paper

“These teens may be more likely to encounter harmful content, such as violence, cyberbullying, exposure to unwanted sexual images or videos, and racist comments or discriminatory practices.179”

What the sources say

• Partly supported

  The Introduction describes cyberbullying as a violent online act, and the Discussion reports higher cyberbullying victimization among girls and greater involvement in several online risks among older adolescents. The paper does not establish that these teens are more likely to encounter violent content, unwanted sexual images or videos, or racist comments and discriminatory practices; its discussion of sexual images concerns sexting and grooming instead. The excerpt also does not identify which teens “these teens” refers to. (LLM, conf=0.85)

  cites [179] Machimbarrena, 2018, Internet risks: An overview of victimization in cyberbullying, cyber dating abuse, sexting, online grooming and problematic internet use, Int J Environ Res Public Health. sourceExperimental — accuracy not yet measured

In the paper

“Another study finds no association between age of device ownership and well-being for both boys and girls among a Hispanic cohort.155”

What the sources say

• Supported

  The Discussion reports no statistically significant association between mobile-phone acquisition age and the measured child-adjustment outcomes among low-income Latinx children. The Results report no significant sex moderation of the acquisition-age associations; the exploratory sex difference concerned phone ownership, not age of acquisition. The study measured specific outcomes, including depressive symptoms, grades, and sleep, rather than well-being in general. (LLM, conf=0.88)

  cites [155] Sun, 2023, Are mobile phone ownership and age of acquisition associated with child adjustment? A 5-year prospective study among low-income Latinx children, Child Dev. source

In the paper

“and less time spent using social media.163”

What the sources say

• Supported

  The Conclusions and directions for future research section states that adolescents whose parents use mediation and monitoring, especially in an autonomy-supportive way, spend less time using social media. The parental mediation and monitoring section also reports this association specifically for autonomy-supportive restrictive mediation. (LLM, conf=0.92)

  cites [163] Beyens, 2022, Social media, parenting, and well-being, Curr Opin Psychol. source

In the paper

“Exposure to harmful content, particularly cyberbullying, is associated with greater emotional distress, anxiety, and depression.180”

What the sources say

• Partly supported

  The Results report that youth who said cyberbullying had increased or remained frequent showed the most anxiety and depression, but the difference only approached statistical significance (p < 0.084). The paper does not establish an association for exposure to harmful content generally or separately assess emotional distress. (LLM, conf=0.86)

  cites [180] Englander, 2021, Bullying, cyberbullying, anxiety, and depression in a sample of youth during the coronavirus pandemic, Pediatr Rep. sourceExperimental — accuracy not yet measured

In the paper

“Parenting approaches that are specific to teen digital media use also play a role in shaping digital media outcomes.60”

What the sources say

• Supported

  The Discussion reports that adolescents whose parents used particular mediation styles were more likely to belong to the higher digital-flourishing group. It also says that active and autonomy-supportive mediation styles were associated with more positive digital communication experiences and behaviors, supporting the broad claim about media-specific parenting approaches and outcomes. (LLM, conf=0.94)

  cites [60] Rosič, 2024, Trajectories of digital flourishing in adolescence: The predictive roles of developmental changes and digital divide factors, Child Dev. source

In the paper

“Digital discrimination is linked to various mental health problems, including anxiety, depression, and stress.176”

What the sources say

• Partly supported

  The Results report that individual online racial discrimination was associated with increases in depressive symptoms among Black U.S. adolescents, but vicarious online discrimination was not. The study did not report anxiety or stress as measured mental-health outcomes; the Discussion mentions stress reactions only as a possible explanation. (LLM, conf=0.88)

  cites [176] English, 2020, Daily multidimensional racial discrimination among Black U.S. American adolescents, J Appl Dev Psychol. sourceExperimental — accuracy not yet measured

In the paper

“Common apps that teens use during the school day include social media and YouTube.125”

What the sources say

• Supported

  The Talking Points section reports that social media and YouTube accounted for two of the largest shares of smartphone-use time during school hours among participants who used those app categories. This supports the claim that teens use them during the school day; the reported percentages describe time spent, not the proportion of teens using each app category. (LLM, conf=0.93)

  cites [125] Radesky, 2023 source

In the paper

“Research studies on adolescents a part of at least one minoritized community based on race, ethnicity, faith, disability, and/or sexuality found that they most commonly use the digital environment to facilitate positive connections.187,188”

What the sources say

• ?Not checked — no full text of the sourcecites [187] Lee, 2019, Social media use and well-being in people with physical disabilities: Influence of SNS and online community uses on social support, depression, and psychological disposition, Health Commun. source
• ?Could not verify

  The Results (§3.2; page unavailable) discuss ethnicity only as a possible adjustment variable. The Discussion (§4.8; page unavailable) mentions screen time and internet addiction as future research topics, not how adolescents from minoritized communities use digital environments. Searches for minoritized groups, online social connections, and positive digital use found no passage addressing the claim. (LLM, conf=0.76)

  cites [188] Vanaken, 2018, Impact of green space exposure on children’s and adolescents’ mental health: A systematic review, Int J Environ Res Public Health. sourceExperimental — accuracy not yet measured

In the paper

“Digital media platforms are a primary source for teens to gain information about mental health.182,183”

What the sources say

• Supported

  The Introduction describes social media as a platform for providing mental health information to children and young people and reports that social networking sites are their most important digital health resources. This supports the claim that digital platforms are a primary source of such information for teens. (LLM, conf=0.88)

  cites [182] McCashin, 2023, Using TikTok for public and youth mental health - A systematic review and content analysis, Clin Child Psychol Psychiatry. source
• Partly supported

  The 'Mental Health Support and Information' section says digital platforms provide young people with mental health information and peer support. It also reports that most respondents in a survey of 17- to 24-year-olds had used the internet for information or help with distressing feelings. It does not establish that digital media platforms are a primary source of mental health information specifically for teens; in that survey, information-based websites were more popular than social media sites. (LLM, conf=0.84)

  cites [183] Lupton, 2021, Young people’s use of digital health technologies in the global north: Narrative review, J Med Internet Res. sourceExperimental — accuracy not yet measured

In the paper

“In one study, teens used their mobile devices during school times (9 am-3 pm) for a median of about 43 minutes.125”

What the sources say

• Partly supported

  The TALKING POINTS report median smartphone use of about 43 minutes per school day, but define school hours as 8 a.m. to 3 p.m., not 9 a.m. to 3 p.m. The reported median therefore does not establish the claim for the narrower time window. (LLM, conf=0.88)

  cites [125] Radesky, 2023 sourceExperimental — accuracy not yet measured

In the paper

“Digital media, particularly with artificial intelligence (AI) and algorithmic decision-making, often rely on historical data that may contain biases, leading to the reinforcement of existing prejudices.172,173”

What the sources say

• ?Not checked — no full text of the sourcecites [172] Benjamin, 2019, Assessing risk, automating racism, Science. source
• Partly supported

  The paper says health-care prediction algorithms rely on past data (p. 2) and shows how a cost-based label produces racial bias (p. 2). It also discusses analogous risks in other sectors (Discussion, p. 8), but does not establish the claim specifically about digital media or how often this occurs there. (LLM, conf=0.85)

  cites [173] Obermeyer, 2019, Dissecting racial bias in an algorithm used to manage the health of populations, Science. sourceExperimental — accuracy not yet measured

In the paper

“Teen externalizing behaviors increase with caregiver digital media use.28”

What the sources say

• Partly supported

  The Results report that greater mobile-technoference in mother–child interactions was associated with greater child externalizing behavior. But the Method (Participants & Procedure; page unavailable) gives an index-child age range of 1 to 5.5 years, not teens. The Discussion also cautions that this cross-sectional analysis cannot establish whether caregiver technology use causes behavior to increase. (LLM, conf=0.90)

  cites [28] McDaniel, 2018, Technoference: Parent distraction with technology and associations with child behavior problems, Child Dev. sourceExperimental — accuracy not yet measured

In the paper

“Many teens search for social support regarding mental health on social media.159”

What the sources say

• Partly supported

  Results §3.5 reports that 36% of respondents had used social media for support with their own suicidal thoughts or self-harm, supporting the central point. But Methods §2.2 says the sample was aged 16–25, and the results do not report a separate rate for teens; the claim is more age-specific than the finding. (LLM, conf=0.82)

  cites [159] Bailey, 2022, The mental health and social media use of young Australians during the COVID-19 pandemic, Int J Environ Res Public Health. sourceExperimental — accuracy not yet measured

In the paper

“During the teen years, technoference has a significant correlation between caregiver mobile device use and teen symptoms of depression and anxiety.164,165”

What the sources say

• Supported

  The Results section (page not available) reports that four studies examined parental technoference and adolescent depression and/or anxiety, and all found that greater perceived parental technoference was related to increased symptoms. The review therefore supports the claimed association, although the quoted passage does not give a statistical significance value for every study. (LLM, conf=0.88)

  cites [164] Dixon, 2023, Parental technoference and adolescents’ mental health and violent behaviour: a scoping review, BMC Public Health. source
• Partly supported

  The Overall Association section says parental phubbing is associated with children's internalizing problems, including anxiety and depression; the results on p. 4274 report a significant positive correlation. The claim is narrower about teens, while the reported result pools children across ages. The paper also distinguishes phone-specific phubbing from the broader concept of technoference. (LLM, conf=0.84)

  cites [165] Zhang, 2023, Parental Phubbing and child social-emotional adjustment: A meta-analysis of studies conducted in China, Psychol Res Behav Manag. sourceExperimental — accuracy not yet measured

In the paper

“Cross-sectional studies show an association between greater green space exposure and greater mental well-being and cognitive development.188,189”

What the sources say

• Partly supported

  The Results (§3.2–3.3; pages not provided) identify cross-sectional studies and report positive associations between green-space exposure and children’s or adolescents’ well-being. The review also reports associations with cognitive development, but its Discussion (§4.1; page not provided) describes the attention and working-memory evidence as coming from longitudinal studies. It therefore does not support attributing both outcomes specifically to cross-sectional studies. (LLM, conf=0.84)

  cites [188] Vanaken, 2018, Impact of green space exposure on children’s and adolescents’ mental health: A systematic review, Int J Environ Res Public Health. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [189] McCormick, 2017, Does access to green space impact the mental well-being of children: A systematic review, J Pediatr Nurs. source

In the paper

“Teens and young adults self-report a preference for device ownership between 12 and 13 years of age in anticipation for the transition from middle school to high school.157”

What the sources say

• Partly supported

  The Abstract Results report that youths recommended a first phone between ages 12 and 13, and the Results give an average recommended age of 12.7. One respondent recommended late middle school to the start of high school, but the Discussion says that receiving a first phone generally coincided with starting middle school. The paper does not establish anticipation of the transition to high school as the general reason for the age preference. (LLM, conf=0.88)

  cites [157] Richter, 2022, Youth Perspectives on the Recommended Age of Mobile Phone Adoption: Survey Study, JMIR Pediatr Parent. sourceExperimental — accuracy not yet measured

In the paper

“Digital mental health interventions have the potential to decrease barriers to mental health treatment.185”

What the sources say

• Supported

  The opening section identifies limited services and funding as barriers to mental health care, then describes digital health technologies as a feasible way to bridge the gap between treatment need and capacity. It also describes their potential to deliver accessible, affordable care. No page number is supplied in our copy. (LLM, conf=0.93)

  cites [185] Torous, 2021, The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality, World Psychiatry. source

In the paper

“Meanwhile, another study in Sweden found no associations between mobile phone bans and academic development.171”

What the sources say

• Supported

  The paper states in its Introduction (p. 5) that mobile phone bans had no impact on student performance in the Swedish setting. Its Results (p. 16) also report no impact on the mathematics-test outcome after a ban, supporting the citing sentence’s summary of academic outcomes. (LLM, conf=0.94)

  cites [171] Kessel, 2020, The impact of banning mobile phones in Swedish secondary schools, Econ Educ Rev. source

In the paper

“Autonomy-supportive parenting is also associated with digital flourishing for teens60”

What the sources say

• Supported

  The Discussion reports that adolescents whose parents used more autonomy-supportive active or restrictive mediation were more likely to belong to a class with relatively high digital flourishing than to a less-flourishing class. This supports the stated association for teens. (LLM, conf=0.93)

  cites [60] Rosič, 2024, Trajectories of digital flourishing in adolescence: The predictive roles of developmental changes and digital divide factors, Child Dev. source

In the paper

“Preschoolers, school-aged children, and teens who experience challenges with emotion regulation (social anxiety, mood conditions, stress), executive function, and impulsivity such as ADHD212 or social interactions (autism) are already more likely to have sleep disturbances compared with those with neurotypical development.”

What the sources say

• Supported

  The citation is attached specifically to ADHD, not to the sentence’s other examples. The Introduction reports a well-established association between ADHD and sleep disorders, supported by meta-analyses of sleep alterations in children with ADHD. The paper does not need to support the separate claims about anxiety or autism for this citation to fit. (LLM, conf=0.90)

  cites [212] Cortese, 2024, The management of sleep disturbances in children with attention-deficit/hyperactivity disorder (ADHD): an update of the literature, Expert Rev Neurother. source

In the paper

“as well as sleep disruption attributable to frequent presence of mobile devices in bedrooms.202”

What the sources say

• Partly supported

  The Results (Mobile Devices and Sleep) report significant associations between having a cell phone in the bedroom and adverse sleep outcomes. The Introduction describes screen time as a hypothesized cause of insufficient sleep, but the review does not establish that the presence of mobile devices itself causes sleep disruption. (LLM, conf=0.84)

  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

“AI chatbots may promise parasocial connection, using design affordances such as responsivity, attempting to meet an emotional need, and prolonging interactions,192”

What the sources say

• Partly supported

  The Introduction describes smart connected toys as reactive and socially receptive, and the “Individual level” section links their design to longer-term engagement and children’s emotional bonds. The paper addresses children’s interactions with smart toys, not AI chatbots generally, and does not say that they attempt to meet an emotional need. (LLM, conf=0.84)

  cites [192] Fosch-Villaronga, 2023, Toy story or children story? Putting children and their rights at the forefront of the artificial intelligence revolution, AI Soc. sourceExperimental — accuracy not yet measured

In the paper

“Children and teens with ADHD also are more likely to have digital media disrupt their sleep,213”

What the sources say

• Partly supported

  The Results (Study description; page unavailable) say that included studies examined digital media use and sleep, and the Results (Analyses; page unavailable) find that youth with ADHD spend more time on media than controls. The Background mentions lack of sleep as a plausible effect of excessive media use. None of these passages establishes that media disrupts sleep more often in children or teens with ADHD than in controls. (LLM, conf=0.80)

  cites [213] Werling, 2022, Problematic use of digital media in children and adolescents with a diagnosis of attention-deficit/hyperactivity disorder compared to controls. A meta-analysis, J Behav Addict. sourceExperimental — accuracy not yet measured

In the paper

“Strong evidence exists on the disruptive impact of digital media on child and teen sleep duration, onset, and quality.200-204”

• Also stated in: § Media Effects: Sleep · boosted

  “Strong evidence exists on the disruptive impact of digital technologies on child and teen sleep duration, onset, and quality.200-204,216,217”

What the sources say

• Supported

  The section on screen media and sleep time and quantity summarizes reviews and meta-analyses finding consistent associations in children and adolescents with shorter sleep, delayed bedtime, longer sleep-onset latency, and poorer sleep quality. The paper supports the broad claim, although much of the evidence it describes is associational rather than proof of causation. (LLM, conf=0.90)

  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. sourceExperimental — accuracy not yet measured
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [201] Robb, 2019
• Partly supported

  The Summary and Limitations section (page not available) reports that 90% of reviewed studies found an adverse association between screen time and at least one sleep outcome. The Results sections describe associations with shorter sleep, later sleep onset, and some measures of sleep quality, though quality findings vary by device. The claim’s wording implies a proven disruptive effect, whereas the Causality Difficult to Ascertain section says the studies do not establish causation. (LLM, conf=0.88)

  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
• Partly supported

  The Results (Total daily screen time) report unfavorable associations with sleep duration, latency and quality in children under five. But the Results (Quality of evidence) rate the screen-time evidence very low, and the paper does not study teenagers or establish that digital media causes sleep disruption. Page numbers were not available in our copy. (LLM, conf=0.90)

  cites [203] Janssen, 2020, Associations of screen time, sedentary time and physical activity with sleep in under 5s: A systematic review and meta-analysis, Sleep Med Rev. sourceExperimental — accuracy not yet measured
• Partly supported

  The Abstract notes that earlier research tested associations between children’s screen-media use and sleep problems. It does not establish strong evidence of a disruptive impact or address sleep duration, onset, and quality in both children and teens. The Discussion concerns measuring device use, including possible overnight use, rather than sleep outcomes. (LLM, conf=0.83)

  cites [204] Radesky, 2020, Young Children’s Use of Smartphones and Tablets, Pediatrics. 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 Conclusions report consistent evidence that electronic media use is associated with shorter sleep duration, especially among ages 6–15. The Abstract Results identify associations with delayed bedtime, difficulty falling asleep, and poor sleep quality in particular age groups, but describe evidence for these other outcomes as more inconclusive. The claim overstates both the strength of evidence across all three outcomes and the causal implication of “disruptive impact.” (LLM, conf=0.90)

  cites [217] Lund, 2021, Electronic media use and sleep in children and adolescents in western countries: a systematic review, BMC Public Health. sourceExperimental — accuracy not yet measured

In the paper

“In a randomized experimental study, 1 hour of light exposure before bedtime resulted in preschoolers having average delayed circadian phase of about 56 minutes.207”

What the sources say

• Supported

  The Discussion describes a randomized experimental study in which one hour of light exposure before bedtime produced an average circadian phase delay of 56 minutes in young children. The Introduction identifies the participants as preschool-aged children. (LLM, conf=0.95)

  cites [207] Hartstein, 2023, Evening Light Intensity and Phase Delay of the Circadian Clock in Early Childhood, J Biol Rhythms. source

In the paper

“Children who watch more television and have televisions in their bedrooms have shorter and worse sleep.218”

What the sources say

• Supported

  The Abstract (Results) directly reports significantly shorter sleep duration and worse sleep among children who watched more TV and had TVs in their bedrooms. The Discussion likewise associates greater viewing and bedroom TVs with shorter sleep and poorer sleep quality in the young children studied. (LLM, conf=0.95)

  cites [218] Helm, 2019, Television use and its effects on sleep in early childhood, Sleep Health. source

In the paper

“Once awake, children and teens may be inclined to further engage in screens, making it more difficult to fall back asleep.209”

What the sources say

• Partly supported

  The Results (p. 7) associate device use after waking overnight with greater trouble falling or staying asleep. The Discussion (p. 8) says adolescents may turn to devices when they wake, but cautions that the direction of the association is unknown; it does not establish that using screens makes it harder to fall back asleep. (LLM, conf=0.85)

  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

In the paper

“Indeed, even teens who kept their devices in their bedrooms but did not access them experienced inadequate or poor sleep quality and excessive daytime sleepiness.208”

What the sources say

• Supported

  The Abstract (Results) reports that children with nighttime access to media devices who did not use them had higher odds of inadequate sleep quantity, poor sleep quality, and daytime sleepiness. The Discussion (Summary of findings) likewise describes an association between devices in the bedroom, even without use, and detrimental sleep outcomes. The paper reports an association, not that the devices caused those outcomes. (LLM, conf=0.92)

  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. source

In the paper

“Systemic challenges such as long work hours, lack of affordable child care, and loss of third spaces make it harder for families and teens to access rich, in-person social connections.38,191”

What the sources say

• ?Not checked — no full text of the sourcecites [38] Abbasi, 2023, Surgeon general sounds the alarm on social media use and youth mental health crisis, JAMA. source
• ?Could not verify

  The Discussion and Implications for Policy and Practice sections discuss how COVID-19 distancing curtailed young people’s social contact, but they do not address long work hours, unaffordable child care, or the loss of third spaces as barriers for families and teens. Searches for those factors and related terms found no passage supporting the attributed claim; page numbers were unavailable in our copy. (LLM, conf=0.76)

  cites [191] Loades, 2020, Rapid systematic review: the impact of social isolation and loneliness on the mental health of children and adolescents in the context of COVID-19, J Am Acad Child Adolesc Psych. sourceExperimental — accuracy not yet measured

In the paper

“Teens surveyed reported using media as a distraction from negative and unpleasant thoughts before bedtime.215”

What the sources say

• Supported

  The Results section reports that 62% of surveyed adolescents said they used technology in the evening to distract themselves from negative or distressing thoughts. The Qualitative analyses section places the question in the hour before bed, supporting the claim’s timing. (LLM, conf=0.94)

  cites [215] Daniels, 2022, Technology use as a sleep-onset aid: are adolescents using apps to distract themselves from negative thoughts?, Sleep Adv. source

In the paper

“and fussier infants may also be exposed to greater digital media for soothing.211”

What the sources say

• Partly supported

  In “Using Devices Separately Versus Coviewing” (page not available), the paper reports that caregivers sometimes gave toddlers devices apparently to control behavior when they became more active. This supports the possibility of using digital media to soothe or manage a child, but the paper does not establish that fussier infants receive greater exposure than less fussy infants. (LLM, conf=0.85)

  cites [211] Radesky, 2014, Patterns of mobile device use by caregivers and children during meals in fast food restaurants, Pediatrics. sourceExperimental — accuracy not yet measured

In the paper

“Insomnia and problems falling asleep may promote media use so as to relax.214”

What the sources say

• Supported

  Section 7.2 states that insomnia symptoms, including difficulty falling asleep, could prompt adolescents to use digital devices to relax. This directly supports the citing sentence’s hedged claim. (LLM, conf=0.95)

  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

“Healthier sleep hygiene is associated with healthier weight.198,199”

What the sources say

• Partly supported

  The Results and Discussion report that healthier sleep hygiene was associated with lower BMIz in children during the school year. The claim omits that setting-specific qualifier: the Results found no association between sleep hygiene behaviors and BMIz during summer. (LLM, conf=0.86)

  cites [198] Moreno, 2023, Examination of parent-reported differences in children’s daily screen use, sleep, and sleep hygiene behaviors during the school year and summer and their association with BMI, Sleep Health. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [199] Matricciani, 2019, Children’s sleep and health: A meta-review, Sleep Med Rev. source

In the paper

“In a study of over 10 000 US teens, those who left their phone ringer on overnight were significantly more likely to experience trouble falling asleep, staying asleep, and overall sleep disturbance compared with teens who turned their phones off at night.209”

What the sources say

• Supported

  The Results (p. 7) report a sample of 10,280 U.S. early adolescents. Compared with turning phones off, leaving the ringer on was associated with higher risks of trouble falling or staying asleep and overall sleep disturbance; both reported confidence intervals exclude 1. (LLM, conf=0.94)

  cites [209] Nagata, 2023, Bedtime screen use behaviors and sleep outcomes: Findings from the Adolescent Brain Cognitive Development (ABCD) Study, Sleep Health. source

In the paper

“One app studied, an automated app-based insomnia intervention utilizing cognitive behavioral therapy for insomnia (CBT-I), showed a greater reduction in insomnia symptoms for teens randomized to receive the intervention compared with those who did not.227”

What the sources say

• Supported

  The Methods describe adolescents aged 12–16 randomized to the Sleep Ninja CBT-I app or an active control group receiving weekly sleep-tip texts. The Discussion reports a greater reduction in insomnia symptoms in the Sleep Ninja group than in the control group. (LLM, conf=0.94)

  cites [227] Werner-Seidler, 2023, The effects of a sleep-focused smartphone application on insomnia and depressive symptoms: a randomised controlled trial and mediation analysis, J Child Psychol Psychiatry. source

In the paper

“Decades of observational research has demonstrated correlation between screen media duration and higher risk of adiposity and unhealthy weight among children and teens.247,248”

What the sources say

• Partly supported

  The Discussion reports that higher screen time was associated with greater odds of overweight or obesity, and the Methods specify that the review included observational studies. But the included participants were adolescents aged 10–19, so this source does not establish the association for younger children; the cited passages also do not establish the claim’s ‘decades’ timeframe. (LLM, conf=0.84)

  cites [247] Haghjoo, 2022, Screen time increases overweight and obesity risk among adolescents: a systematic review and dose-response meta-analysis, BMC Prim Care. sourceExperimental — accuracy not yet measured
• ?Could not verify

  The Background links screen-device use to sedentary behaviour and higher energy intake, while the Screen Time section reports duration distributions for children aged 6–9; neither reports a correlation with adiposity or unhealthy weight. Searches for screen time, BMI, weight status, obesity, and adiposity found no passage establishing the claimed association in children and teens or describing decades of observational research. (LLM, conf=0.72)

  cites [248] Whiting, 2021, Physical activity, screen time, and sleep duration of children aged 6–9 years in 25 countries: An analysis within the WHO European childhood obesity surveillance initiative (COSI) 2015–2017 sourceExperimental — accuracy not yet measured

In the paper

“Apps such as YouTube or video gaming consoles contribute to more sleep disturbances as compared with TV.215,222”

What the sources say

• Partly supported

  The Discussion (page unavailable) reports that YouTube use was a significant predictor of insufficient sleep. The Results describe gaming consoles as a way adolescents distracted themselves before bed, but do not link them to greater sleep disturbance. The Introduction mentions TV as a sleep aid; the paper does not compare its effects with YouTube or gaming consoles or establish the claimed causal effect. (LLM, conf=0.86)

  cites [215] Daniels, 2022, Technology use as a sleep-onset aid: are adolescents using apps to distract themselves from negative thoughts?, Sleep Adv. sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [222] Pillion, 2022, What’s “app”-ning to adolescent sleep? Links between device, app use, and sleep outcomes, Sleep Med. source

In the paper

“Digital media, particularly smartphones and computers, are associated with a greater risk for myopia as compared with television.”

What the sources say

• Supported

  The Results (section 3.1, Myopia) explicitly state that computers and smartphones were linked with an increased risk of myopia compared with television. The same section identifies computers and smartphones, but not television, as factors correlated with myopic refractive errors in childhood. (LLM, conf=0.94)

  cites [245] Bozzola, 2024, Media Device Use and Vision Disorders in the Pediatric Age: The State of the Art, Children (Basel). source

In the paper

“Less flexible, demanding, or shift work schedules may make it harder for caregivers to set boundaries around digital media use in the evenings.239”

What the sources say

• Partly supported

  The Abstract says inflexible or unpredictable maternal work schedules may interfere with establishing consistent bedtime routines, and the Results report lower perceived flexibility among mothers working long hours or nonstandard shifts. The paper does not address caregivers setting boundaries around evening digital media use; its bedtime measure concerns adherence to a regular bedtime. (LLM, conf=0.88)

  cites [239] Lee, 2019, Maternal perceived work schedule flexibility predicts child sleep mediated by bedtime routines, J Child Fam Stud. sourceExperimental — accuracy not yet measured

In the paper

“Digital media viewing duration and distance are associated with greater risk for myopia.245”

What the sources say

• Supported

  The Discussion states that media device viewing duration and close viewing distance relate to myopia risk. The Results (3.1, Myopia) also report that myopia risk is mainly time-related in children and adolescents. The citing sentence is a faithful paraphrase of this association. (LLM, conf=0.93)

  cites [245] Bozzola, 2024, Media Device Use and Vision Disorders in the Pediatric Age: The State of the Art, Children (Basel). source

In the paper

“Longer digital media use duration is associated with greater neck and shoulder pain frequency.246”