Social Connectedness, Adolescent Mental Health and Well-Being at the Later Stages of the COVID-19 Pandemic: A Mixed Methods Exploration
Bibliographic record
Abstract
COVID-19 posed novel challenges by limiting in-person interactions and shifting interactions online. Effects of online and offline social connectedness on adolescent mental health and well-being, and the moderating role of the social determinants of health (SDoH) were explored. Canadian adolescents (n=1,586; Mage=15.3, range 13 to 18 years; surveyed summer 2022) reported their social connectedness, psychological distress, and mental well-being. An ordinal logistic regression was performed to examine the association between social connectedness (online and offline) and dual-factor mental health. Responses to two open-ended survey questions were analyzed. Social disconnection was associated with higher odds of being in a poorer mental state, with a stronger association for offline than online social connectedness. The SDoH may moderate this relationship. Participants described negative and positive pandemic-related changes to relationships, mental health and well-being. Although online and offline social connectedness both contribute to adolescent mental health and well-being, offline social connectedness appears more impactful.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".