Self-Perceived Health and Life Satisfaction During COVID-19 Pandemic
Bibliographic record
Abstract
Abstract The aim of the study was to assess both self-perceived health and life satisfaction during one of COVID-19 pandemic peaks and to reveal their correlates among the study characteristics. Materials and methods. An online survey was conducted at the end of 2020 among 930 participants recruited via Facebook. Results. A quarter of the participants (26.2%) rated their own health as very good, 47.1% – as good, for 22.8% it was satisfactory, 2.9% claimed it as bad and 0.9% as very bad. Life satisfaction was measured by a 10-point scale ranging from 1 “very unsatisfied” to 10 – “very satisfied“. The median level of satisfaction was 6 (IQR 3-8). With the decrease of self-perceived health a significant drop of life satisfaction was observed (Kendall’s tau = 0.172, p < 0.001). No significant difference was noticed in both self-perceived health and life satisfaction between patients who had suffered from COVID-19 and those who had not (p > 0.05). Self-perceived health was positively correlated with self-perceived living standard (Kendall’s tau = 0.118, p < 0.001) and negative with age (Kendall’s tau = -0.112, p < 0.001). Females’ health was significantly worse (p=0.006) and also single, divorced and widowed reported significantly worse health compared to married/in a steady relationship (p = 0.019). Life satisfaction was positively correlated with net monthly income (Kendall’s tau = 0.199, p < 0.001), self-perceived living standard (Kendall’s tau = 0.246, p < 0.001) and education (Kendall’s tau = 0.101, p < 0.001). Married or in a steady relationship reported significantly higher life satisfaction than single, divorced and widowed (p = 0.001). Conclusion. Better economic status and living with spouse or having a steady partner (instead of being single, divorced or widowed) helps individuals to maintain better health and subjective well-being during pandemics.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".