Contribution of Emotion Dynamics to Adolescent Psychosocial Well-Being: Protocol for a Longitudinal Study (Preprint)
Bibliographic record
Abstract
BACKGROUND As a critical period in psychosocial development, adolescence is marked by heightened emotion regulation demands as well as increased risk for, and vulnerability to, stress. OBJECTIVE This longitudinal study investigates how dynamic patterns (ie, mean intensity, variability, instability, inertia, and reactivity to stress) in positive and negative affect relate to, and predict change in, broad domains of adolescent psychosocial well-being (ie, mental health, social well-being, and academic motivation). Using a daily diary procedure to capture adolescents’ daily naturalistic affective experiences, this study will provide novel insights into how affective processes predict psychosocial well-being over time beyond traditional, static assessment. METHODS At baseline, adolescents aged 14-17 years from Southwestern Ontario reported on their academic motivation (eg, extrinsic motivation), social well-being (eg, social support and loneliness), and mental health (eg, anxiety syndrome severity) before completing a 35-day smartphone-based daily diary protocol wherein participants reported twice daily in the morning (ie, 7-10 AM) and evening (ie, 8-11 PM) on positive and negative affect, stress, and internalizing symptom severity. Participants then repeat the surveys of academic motivation, social well-being, and mental health 6, 12, and 18 months following baseline assessment to assess change in each domain of psychosocial well-being over time. RESULTS Adolescents (N=149) were enrolled into this longitudinal study between April 2023 and November 2024, such that all participants will complete the scheduled 18 months of longitudinal follow-up assessments by May 2026. Primary study analyses will use multilevel modeling, structural equation modeling, multilevel structural equation modeling, and dynamic structural equation modeling to examine how dynamic patterns in positive and negative affect (eg, instability, inertia) concurrently correlate with, and prospectively predict change in, psychopathology and well-being. CONCLUSIONS This study protocol paper outlines the overarching study objectives and methodology to promote transparency and reproducibility. Through the integration of daily diary methodology within a longitudinal design, this study aims to clarify the potential implications of dynamic affective processing (eg, affective reactivity to daily stress) for both adolescent psychopathology and well-being beyond clinical syndromes. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/76333
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.077 | 0.017 |
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 source (direct Gemma or distilled Codex), 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".