Trends in Psychological Symptoms among Canadian Adolescents from 2002 to 2014: Gender and Socioeconomic Differences
Bibliographic record
Abstract
OBJECTIVE: To describe trends in psychological health symptoms in Canadian youth from 2002 to 2014 and examine gender and socioeconomic differences in these trends. METHOD: We used data from the Canadian Health Behaviour in School-aged Children (HBSC) study. We assessed psychological symptoms from a validated symptom checklist and calculated a symptom score (range, 0-16). We stratified our analyses by gender and affluence tertile based on an index of material assets. We then plotted trends in symptom score and calculated the probability of experiencing specific symptoms over time. RESULTS: Between 2002 and 2014, psychological symptom score increased by 1.01 (95% confidence interval [CI], 0.73 to 1.41), 1.08 (95% CI, 0.79 to 1.37), and 0.84 (95% CI, 0.55 to 1.13) points in girls in the low-, middle-, and high-affluence tertiles, respectively. In boys, psychological symptoms decreased by -0.39 (95% CI, -0.66 to -0.12) and -0.12 (95% CI, -0.43 to 0.19) points in the high- and middle-affluence tertiles, respectively, and increased by 0.30 (95% CI, -0.04 to 0.63) points in the low-affluence tertile. The probability of feeling anxious and having sleep problems at least once a week notably increased in girls from all affluence groups, while the probability of feeling depressed and irritable decreased among boys from the high-affluence tertile. CONCLUSION: Psychological symptoms increased in Canadian adolescent girls across all affluence groups while they remained stable in boys from low and middle affluence and decreased in boys from high affluence. Specific psychological symptoms followed distinct trends. Further research is needed to uncover the mechanisms driving these trends.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".