Older Adults’ Attitudes Regarding COVID-19 and Associated Infection Control Measures in Shanghai and Impact on Well-Being
Bibliographic record
Abstract
This cross-sectional study investigated health management, well-being, and pandemic-related perspectives in Shanghainese adults ≥50 years at the early stages of COVID-19 using a self-report survey in March−April, 2020. Items from the SSS, PHQ-9 and GAD-7 were administered. A total of 1181 primarily married, retired females participated. Many participants had hypertension (44.1%), coronary artery disease (CAD; 17.8%), and diabetes (14.5%). While most (n = 868, 73.5%) were strictly following control measures and perceived they could tolerate >6 months (n = 555, 47.0%) and were optimistic (n = 969, 82.0%). A total of 52 (8.2%) of those with any condition and 19 (3.5%) of those without a condition reported that the pandemic was impacting their health. Somatic symptoms were high (29.4 ± 7.1/36), with sleep/cognitive symptoms highest. Totals of 20.2% and 17.0% of respondents had elevated depressive and anxious symptoms, respectively; greater distress was associated with lower income (p = 0.018), having hypertension (p = 0.001) and CAD (p < 0.001), negative perceptions of global COVID-19 control (p = 0.004), COVID-19 spread (p < 0.001), impact on life/health (p < 0.001), compliance with control measures (p < 0.001), and the toleration of shorter time control measures (p < 0.001) in adjusted analyses. In conclusion, during the initial COVID-19 outbreak, most older adults were optimistic/resilient regarding the epidemic and control measures. However, the distress of older adults was not trivial, particularly in those with health issues.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".