Well-Being During Times of Heightened Social Isolation: A Panel Study Examination of the Protective Effects of Social Support Availability
Bibliographic record
Abstract
The COVID-19 lockdowns had negative impacts on psychological well-being and amplified certain stressors (e.g., social isolation), especially in at-risk populations.My thesis examined social support availability as a coping strategy.Single people living alone (N=220) were recruited during the initial 2020 lockdown and followed over a period of six weeks.Each week, participants reported their perceived social support availability, social isolation, and life satisfaction.I hypothesized that greater perceptions of social support availability, both on the within-and between-person levels, would buffer the negative effects of social isolation on psychological well-being.Multi-level modeling results showed that stress-buffering occurred on the between-person level.Associations were analyzed longitudinally, revealing that lagged social isolation did not predict life satisfaction the week after.An interaction was observed between lagged social isolation and lagged social support availability, such that lagged social isolation predicted less life satisfaction when social support was unavailable the week before.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".