Adolescent mental well‐being in time of crises: The role of social and residential contexts
Bibliographic record
Abstract
BACKGROUND: The extent of the impact and the interconnections among factors within social and residential contexts during the COVID-19 lockdowns on mental well-being remain to be elucidated. We identified latent classes of each of social and residential context during the lockdown and examined their associations with mental well-being among adolescents in France 1-year after the first lockdown. METHODS: We used data collected in 2021 in a cross-sectional school-based pilot study for EXIST, from 387 participants ages 12-15 years. Participants reported retrospectively on characteristics of their social and residential contexts during the lockdown, and their current mental well-being in self-report questionnaires. We used latent class analysis to identify latent classes of social and residential contexts, and linear regression models to examine the associations between these contexts and mental well-being. RESULTS: Four social context classes were identified: class 1 "Low opportunity for social contact at home," class 2 "Moderate opportunity for social contact at home," class 3 "High opportunity for social contact at home," and class 4 "Very high opportunity for social contact at home." Relative to class 4, lower levels of mental well-being were observed among adolescents in class 1 (b = -4.08, 95% CI [-8.06; -0.10]) 1 year after the lockdown. We identified four residential context classes based on proximity to nature, type of residence (e.g., apartment, house), and level of neighborhood deprivation. No association was detected between residential context during the lockdown and adolescent mental well-being one-year later. CONCLUSION: A limited social context may negatively impact adolescent mental well-being during crises.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".