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. 2025 May 10;4(1):15.
doi: 10.1038/s44184-025-00131-z.

Examining measurement discrepancies in adolescent screen media activity with insights from the ABCD study

Affiliations

Examining measurement discrepancies in adolescent screen media activity with insights from the ABCD study

Yihong Zhao et al. Npj Ment Health Res. .

Abstract

Concerns about the accuracy of self-reported screen time persist due to discrepancies with objective measures. This study compared passive smartphone tracking via the "Effortless Assessment of Risk States'' (EARS) app with self-reported screen time from 495 adolescents. Based on self-reports, 94.26% of social media use occurred on smartphones. EARS-recorded social media use was higher (1.64 ± 1.93 h) than past-year self-report (1.44 ± 1.97 h; p = 0.037) but similar to post-sensing self-report (1.63 ± 1.93 h; p = 0.835). Higher picture vocabulary scores were associated with lower odds of under-reporting social media use (OR = 0.96, 95% CI: 0.93-0.99). Both self-reported (β = 0.06, 95% CI: 0.01-0.11) and EARS (β = 0.07, 95% CI: 0.03-0.12) measures correlated with externalizing symptoms. They were also correlated with social media addiction (self-reported:β = 0.15, 95% CI: 0.10-0.20; EARS:β = 0.06, 95% CI: 0.01-0.11). However, past-year self-report uniquely correlated with internalizing symptoms (β = 0.05, 95% CI: 0.01-0.09) and video game addiction (β = 0.05, 95% CI: 0.01-0.10). These findings highlight the value of integrating self-report and objective measures in screen media use research.

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Conflict of interest statement

Competing interests: Dr. Potenza has consulted for Opiant Therapeutics, Game Day Data, the Addiction Policy Forum, AXA and Idorsia Pharmaceuticals; has been involved in a patent application with Yale University and Novartis; has received research support from Mohegan Sun Casino and the National Center for Responsible Gaming; has participated in surveys, mailings or telephone consultations related to drug addiction, impulse-control disorders or other health topics; has consulted for and/or advised gambling and legal entities on issues related to impulse-control/addictive disorders; has provided clinical care in a problem gambling services program; has performed grant reviews for research-funding agencies; has edited journals and journal sections; has given academic lectures in grand rounds, CME events and other clinical or scientific venues; and has generated books or book chapters for publishers of mental health texts. The other authors do not report disclosures.

Figures

Fig. 1
Fig. 1. Pairwise correlation among key SMA measures, including self-reported screen time, EARS-related measures, and addiction scores among all available data.
The number in each cell stands for the correlation coefficient between two variables. Significant correlations are highlighted with circles, where the size and color indicated the strength and direction of the association.
Fig. 2
Fig. 2. Scatterplot of absolute differences between objective and subjective social media usage against cognitive measurements.
Absolute time discrepancy in objective and subjective social media usage was significantly related to lower picture vocabulary score (A) but not picture sequencing memory score (B). Here,subjective social media usage was based on youth self-report over past 12 months.
Fig. 3
Fig. 3. Forest plot of behavior-SMA relationship across objective and subjective social media measures.
Here, SR(3-wks) stands for self-report screen time during post-sensing period and SR(12-mos) for self-report screen time in the past 12-months. EARS refers to the logged data collected by the effortless assessment of risk states app. Beta estimates were standardized. CI = confidence interval, CBCL = child behavior check list, SMAQ = social media addiction questionnaire, VGAQ = videogame addiction questionnaire.

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