Determinants of psychological and social well-being among youth in Canada: investigating associations with sociodemographic factors, psychosocial context and substance use
Bibliographic record
Abstract
INTRODUCTION: Positive mental health is an essential part of youth's healthy development. For instance, positive mental health is associated with greater self-reported physical health, closer relationships and fewer conduct problems in youth. As positive mental health promotion is a public health priority, examining its potential determinants is important. METHODS: We analyzed data from students in Grades 7-12 (secondary I-V in Quebec), from nine Canadian provinces, who participated in the 2016/2017 Canadian Student Tobacco, Alcohol and Drugs Survey. Psychological and social well-being (PSWB) was assessed using the Children's Intrinsic Needs Satisfaction Scale (CINSS). We conducted linear regression analyses to determine associations of sociodemographic, psychosocial and substance use variables with overall CINSS scores (n = 37 897). RESULTS: In general, youth in Canada reported fairly high PSWB. After adjusting for all included variables, being in a higher grade, being bullied, bullying others, reporting more behavioural problems and using cigarettes, e-cigarettes or cannabis at least once in the past 30 days were associated with lower overall CINSS scores for both male and female students. Reporting more prosocial behaviours was associated with higher overall scores for both sexes. CONCLUSION: A number of sociodemographic, psychosocial and substance use factors are associated with PSWB among youth in Canada. Prospective longitudinal and intervention studies could examine whether changes in these potential risk/protective factors are accompanied by changes in positive mental health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".