Exploring the trajectories of problematic smartphone use in adolescence: Insights from a longitudinal study
Bibliographic record
Abstract
Abstract The goal of the present study was to investigate the trajectories of problematic smartphone use among adolescents and its predictors, including self‐regulation, fear of missing out (FoMO), depression, and anxiety among Canadian adolescents. A total of 2549 participants (1025 girls; M age = 14.10 years, SD = 0.96 years) from grades 8 to 12 in Southern British Columbia, Canada, took part in the study. Self‐reported problematic smartphone use was collected annually over 4 years. At Time 1, adolescents provided self‐reports on self‐regulation, depression, anxiety, and FoMO. Growth mixture modelling was used to examine the trajectories of problematic smartphone use. The results revealed three distinct trajectories: low‐increasing‐decreasing (35.5%), moderate‐increasing (60.9%), and high‐stable (3.6%). Multinomial logistic regression revealed that higher FoMO and depression were significant predictors of membership in the high‐stable problematic smartphone use group, while better self‐regulation predicted lower problematic smartphone use. These findings highlight the dynamic nature of problematic smartphone use and the importance of self‐regulation and mental health in understanding problematic smartphone use trajectories among Canadian adolescents.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".