Older Adults’ Attitudes Regarding COVID-19 and Associated Infection Control Measures in Shanghai, and Impact on Well-Being
Bibliographic record
Abstract
Abstract This cross-sectional study investigated health management, well-being, and pandemic-related perspectives in Shanghainese adults ≥50 years during early and strict COVID-19 control measures. A self-report survey was administered via Wenjuanxing between March-April/2020. Items from the Somatic Symptom Scale, Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 were administered, as well as pandemic-specific questions. 1181 primarily married, retired females participated; Many had hypertension (n=521, 44.1%), coronary artery disease (CAD; n=201, 17.8%) and diabetes (n=171, 14.5%). While most respondents (n=868; 73.5%) were strictly following control measures (including limiting visits with children; n=390, 33.0%) and perceived they could tolerate that beyond 6 months (n=555;47.0%), they were optimistic about the future if control measures were continued (n=969;82.0%), and perceived impact would be temporary (n=646;64.7%). 52 of those with any condition (8.2%) and 19 of those without a condition (3.5%) reported the pandemic was impacting their health. Somatic symptoms were high (29.4±7.1/36), with Sleep & Cognitive symptoms highest. 24.4% and 18.9% 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), more negative perceptions of global COVID-19 control (p=0.004), COVID-19 spread (p≤0.001), impact on life and health (p<0.001), compliance with control measures (p<0.001), and shorter time control measures could be tolerated (p<0.001) in adjusted analyses. In the initial COVID-19 outbreak, most older adults were optimistic and resilient with regard to the epidemic and control measures. However, the distress of older adults is 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".