Longitudinal associations between lifestyle changes during the COVID-19 pandemic and distress among children and adolescents in Montréal
Bibliographic record
Abstract
Background: COVID-19 mitigation measures disrupted many youths’ lives. The burden that pandemic changes induced on children and adolescent’s mental health requires further research.Objective: This study explores the associations between lifestyle changes during the COVID-19 pandemic and distress and/or social impairment (herein abbreviated as “distress”) among children and adolescents in Montréal, Canada.Methods: Data were collected as part of a longitudinal survey and serology study of two to 20-year-olds at five different time points between October 2020 and June 2023. The outcome, distress, was the dichotomised score on the Strengths and Difficulties Questionnaire impact supplement. Lifestyle changes included changes in sleep, eating, and physical activity, among others. Adjusted risk ratios (RR) measuring associations between lifestyle changes and distress were estimated using regression models.Results: The 2 183 participants contributed 5 359 observations across the five waves of data collection. The crude prevalence of distress was 14.4% (95% CI 13.2, 15.7). In the adjusted analyses, distress was associated with spending both less and more time sleeping (e.g., less: RR = 2.28; 95% CI: 1.98, 2.98), less time engaged in physical activity (RR = 2.14; 95% CI: 1.78, 2.57), and with social media use of greater than three hours per day versus none (RR = 2.22, 95% CI: 1.69, 2.92).Conclusion: This study found that certain lifestyle changes occurring during the COVID-19 pandemic were associated with distress and social impairment among children and adolescents.
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 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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".