Internet Use, Depression, and Anxiety in a Healthy Adolescent Population: Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Psychiatric disorders, including conduct disturbances, substance abuse, and affective disorders, emerge in approximately 20% of adolescents. In parallel with the rise in internet use, the prevalence of depression among adolescents has increased. It remains unclear whether and how internet use impacts mental health in adolescents. OBJECTIVE: We assess the association between patterns of internet use and two mental health outcomes (depression and anxiety) in a healthy adolescent population. METHODS: A total of 126 adolescents between the ages of 12 and 15 years were recruited. Participants reported their typical computer and internet usage patterns. At baseline and one-year follow-up, they completed the Beck Depression Index for primary care (BDI-PC) and the Beck Anxiety Inventory for Primary Care (BAI-PC). Individual linear regressions were completed to determine the association between markers of internet use at baseline and mental health outcomes at one-year follow-up. All models controlled for age, gender, and ethnicity. RESULTS: There was an inverse correlation between minutes spent on a favorite website per visit and BAI-PC score. No association was found between internet use and BDI-PC score. CONCLUSIONS: There is no relationship between internet use patterns and depression in adolescents, whereas internet use may mitigate anxiety in adolescents with higher levels of baseline anxiety.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".