Effect of Technology and Digital Media Use on Adolescent Health and Development: Protocol for a Multimethod Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Technology and digital media (TDM) use is integral to modern adolescence; adolescents have been labeled as "digital natives," since they have had exposure to digital technology for their entire lives. Previous evidence has illustrated TDM's connections with adolescent risk behaviors such as increased alcohol use and social media exposure, as well as relationships with adolescent well-being such as improved socioemotional health and social media connections with peers. Although several recent review articles have described both the benefits and risks of technology use, most individual studies adopt a singular risk-centered approach. In addition, reviews suggest that little evidence exists on the potential mediating and moderating factors between TDM use and well-being and health outcomes, which limits our understanding of what influences the outcomes of interest. Therefore, there is an urgent need to fill these gaps. OBJECTIVE: This protocol addresses the need to understand how TDM exposure and use affect multiple developmental domains and health outcomes. We address the fragmented nature of previous research, the common focus on single behaviors or conditions, and the typical narrow lens on risks. Our approach further aligns with reviews that called for studies identifying and investigating the factors that moderate the relationships between social media and health behaviors and outcomes. METHODS: We will address our objective by longitudinally examining over a 2-year period a common set of adolescent participants (N=400, aged 13-15 years) across 3 studies that adopt a multimethodological approach. Study 1 will use TDM to understand the mechanisms behind adolescent health and risk behaviors. Study 2 will use functional magnetic resonance imaging to understand how positive and negative TDM experiences relate to mental and behavioral health in a subsample of 150 adolescents. Study 3 will use a mixed methods design to evaluate self- and other-generated TDM content as the predictors of socioemotional well-being in sexual and gender minority and non-sexual and gender minority adolescents. RESULTS: Recruitment is ongoing, and the initial results from the first wave of recruitment are expected in 2024. CONCLUSIONS: This integrated approach to longitudinal data collection from a shared adolescent participant pool will lead to novel analyses and findings, allowing for the examination of the health and well-being risks and benefits associated with TDM use and factors that moderate these relationships. The findings from this study will advance conceptual models and inform new interventions to improve adolescent health. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50984.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".