Sociodemographic, Lifestyle, and Psychological Factors Associated With Flourishing Mental Health in Young Adults: Facteurs sociodémographiques, liés au mode de vie et psychologiques, associés à une bonne santé mentale chez les jeunes adultes
Bibliographic record
Abstract
OBJECTIVE: To identify sociodemographic, lifestyle, and psychological correlates of flourishing mental health (i.e., feeling good and functioning well) in a population-based sample of young adults. METHOD: Data for this cross-sectional study were drawn from the ongoing Nicotine Dependance in Teens study, Québec, Canada. Of 799 participants in cycle 23, 792 (mean (SD) age = 30.6 (1.0) years) provided data on positive mental health using the Mental Health Continuum - Short Form (MHC-SF) and were retained for analysis. Each potential correlate was studied in an unadjusted model, a model adjusted for age and sex, and a model adjusted for age, sex and other covariates related to the specific correlate of interest. RESULTS: Of 792 participants retained for analysis, 39.4% (39.9% of females; 38.8% of males) reported flourishing mental health. Variables associated with higher odds of flourishing included attended university (OR: 1.44 [1.05, 1.99]), being in a relationship (OR: 1.64 [1.22, 2.21], being employed (OR: 1.97 [1.27, 3.11]), high sleep quality (OR: 3.45 [2.53, 4.73]), meeting leisure screen time guidelines (OR: 2.12 [1.59, 2.85]), and relatively high levels of coping ability (OR: 3.11 [2.58, 3.80]). Variables associated with lower odds of flourishing included living alone (OR: 0.58 [0.38, 0.86]), relatively low household income (OR: 0.37 [0.20, 0.64]), and high depressive (OR: 0.05 [0.01, 0.15]) and anxiety (0.17 [0.09, 0.29]) symptoms. CONCLUSIONS: Sociodemographic (education, relationship status, employment status, and income), lifestyle (sleep, screen time), and psychological (coping ability, depressive and anxiety symptoms) factors are correlates of flourishing mental health in this population-based sample of young adults. Results provide a foundation for future research to inform the development of effective programs targeting specific subgroups to promote positive mental health in young adults.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".