Literature DB >> 30027248

Association of Digital Media Use With Subsequent Symptoms of Attention-Deficit/Hyperactivity Disorder Among Adolescents.

Chaelin K Ra1, Junhan Cho1, Matthew D Stone2, Julianne De La Cerda1, Nicholas I Goldenson1, Elizabeth Moroney3, Irene Tung3, Steve S Lee3, Adam M Leventhal1,4.   

Abstract

Importance: Modern digital platforms are easily accessible and intensely stimulating; it is unknown whether frequent use of digital media may be associated with symptoms of attention-deficit/hyperactivity disorder (ADHD). Objective: To determine whether the frequency of using digital media among 15- and 16-year-olds without significant ADHD symptoms is associated with subsequent occurrence of ADHD symptoms during a 24-month follow-up. Design, Setting, and Participants: Longitudinal cohort of students in 10 Los Angeles County, California, high schools recruited through convenience sampling. Baseline and 6-, 12-, 18-, and 24-month follow-up surveys were administered from September 2014 (10th grade) to December 2016 (12th grade). Of 4100 eligible students, 3051 10th-graders (74%) were surveyed at the baseline assessment. Exposures: Self-reported use of 14 different modern digital media activities at a high-frequency rate over the preceding week was defined as many times a day (yes/no) and was summed in a cumulative index (range, 0-14). Main Outcomes and Measures: Self-rated frequency of 18 ADHD symptoms (never/rare, sometimes, often, very often) in the 6 months preceding the survey. The total numbers of 9 inattentive symptoms (range, 0-9) and 9 hyperactive-impulsive symptoms (range, 0-9) that students rated as experiencing often or very often were calculated. Students who had reported experiencing often or very often 6 or more symptoms in either category were classified as being ADHD symptom-positive.
Results: Among the 2587 adolescents (63% eligible students; 54.4% girls; mean [SD] age 15.5 years [0.5 years]) who did not have significant symptoms of ADHD at baseline, the median follow-up was 22.6 months (interquartile range [IQR], 21.8-23.0, months). The mean (SD) number of baseline digital media activities used at a high-frequency rate was 3.62 (3.30); 1398 students (54.1%) indicated high frequency of checking social media (95% CI, 52.1%-56.0%), which was the most common media activity. High-frequency engagement in each additional digital media activity at baseline was associated with a significantly higher odds of having symptoms of ADHD across follow-ups (OR, 1.11; 95% CI, 1.06-1.16). This association persisted after covariate adjustment (OR, 1.10; 95% CI, 1.05-1.15). The 495 students who reported no high-frequency media use at baseline had a 4.6% mean rate of having ADHD symptoms across follow-ups vs 9.5% among the 114 who reported 7 high-frequency activities (difference; 4.9%; 95% CI, 2.5%-7.3%) and vs 10.5% among the 51 students who reported 14 high-frequency activities (difference, 5.9%; 95% CI, 2.6%-9.2%). Conclusions and Relevance: Among adolescents followed up over 2 years, there was a statistically significant but modest association between higher frequency of digital media use and subsequent symptoms of ADHD. Further research is needed to determine whether this association is causal.

Entities:  

Mesh:

Year:  2018        PMID: 30027248      PMCID: PMC6553065          DOI: 10.1001/jama.2018.8931

Source DB:  PubMed          Journal:  JAMA        ISSN: 0098-7484            Impact factor:   56.272


  29 in total

Review 1.  Smartphones, social media use and youth mental health.

Authors:  Elia Abi-Jaoude; Karline Treurnicht Naylor; Antonio Pignatiello
Journal:  CMAJ       Date:  2020-02-10       Impact factor: 8.262

2.  Digital media use and subsequent cannabis and tobacco product use initiation among adolescents.

Authors:  Annemarie R Kelleghan; Adam M Leventhal; Tess Boley Cruz; Mariel S Bello; Fei Liu; Jennifer B Unger; Kira Riehm; Junhan Cho; Matthew G Kirkpatrick; Rob S McConnell; Jessica L Barrington-Trimis
Journal:  Drug Alcohol Depend       Date:  2020-04-26       Impact factor: 4.492

Review 3.  The Many Channels of Screen Media Technology in ADHD: a Paradigm for Quantifying Distinct Risks and Potential Benefits.

Authors:  Matthew M Engelhard; Scott H Kollins
Journal:  Curr Psychiatry Rep       Date:  2019-08-13       Impact factor: 5.285

4.  Featured Article: Technology Use and Sleep in Adolescents With and Without Attention-Deficit/Hyperactivity Disorder.

Authors:  Elizaveta Bourchtein; Joshua M Langberg; Caroline N Cusick; Rosanna P Breaux; Zoe R Smith; Stephen P Becker
Journal:  J Pediatr Psychol       Date:  2019-06-01

5.  Preventing adverse health outcomes among children and adolescents by addressing screen media practices concomitant to sleep disturbance.

Authors:  Susan K Riesch; Jianghong Liu; Peter G Kaufmann; Willa M Doswell; Sally Cohen; Judith Vessey
Journal:  Nurs Outlook       Date:  2019 Jul - Aug       Impact factor: 3.250

6.  Screenomics: A New Approach for Observing and Studying Individuals' Digital Lives.

Authors:  Nilam Ram; Xiao Yang; Mu-Jung Cho; Miriam Brinberg; Fiona Muirhead; Byron Reeves; Thomas N Robinson
Journal:  J Adolesc Res       Date:  2019-11-01

7.  Prospective Association of Digital Media Use with Alcohol Use Initiation and Progression Among Adolescents.

Authors:  Kira E Riehm; Johannes Thrul; Jessica L Barrington-Trimis; Annemarie Kelleghan; Ramin Mojtabai; Adam M Leventhal
Journal:  Alcohol Clin Exp Res       Date:  2021-03-12       Impact factor: 3.455

8.  Risk and Protective Factors for Frequent Electronic Device Use of Online Technologies.

Authors:  Paul L Morgan; Yangyang Wang; Adrienne D Woods
Journal:  Child Dev       Date:  2021-01-11

9.  Increases in Serious Psychological Distress among Ontario Students between 2013 and 2017: Assessing the Impact of Time Spent on Social Media.

Authors:  Steven Cook; Hayley A Hamilton; Shirin Montazer; Luke Sloan; Christine M Wickens; Amy Cheung; Angela Boak; Nigel E Turner; Robert E Mann
Journal:  Can J Psychiatry       Date:  2021-01-28       Impact factor: 4.356

10.  Autistic traits in young adults who gamble.

Authors:  Jon E Grant; Samuel R Chamberlain
Journal:  CNS Spectr       Date:  2020-07-09       Impact factor: 3.790

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