Risk and protective factors associated with change in well-being and mental health during the COVID-19 pandemic in South Africa
Bibliographic record
Abstract
OBJECTIVE: The COVID-19 pandemic and associated restrictive measures affected the mental health and well-being of individuals globally. We assessed non-modifiable and modifiable factors associated with the change in well-being and mental health from before to during the COVID-19 pandemic in South Africa. METHODS: -tests were conducted to assess change in well-being (measured on The World Health Organization-Five Well-Being Index (WHO-5)) and mental health (a validated composite psychopathology p-score). Sociodemographic, environmental, clinical, and behavioural factors associated with change in outcomes were examined. RESULTS: < 0.001) from before to during the pandemic. Having a prior mental health condition was associated with a worsening well-being score, while being female was associated with a worsening p-score. Being of Black African descent was associated with improved p-score and higher socio-economic status (SES) was associated with improved well-being. Factors associated with worsening of both well-being and the p-score included adulthood adversity, financial loss since COVID-19, and placing greater importance on direct contact/interactions and substance use as coping strategies. Higher education level and endorsing studying/learning something new as a very important coping strategy were associated with improved well-being and p-score. CONCLUSION: Findings inform the need for targeted interventions to reduce and prevent adverse well-being and mental health outcomes during a pandemic, especially among vulnerable groups.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".