The Impact of the COVID-19 Pandemic on Physical and Mental Health in China and Spain: Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Differences in physical and mental health impact across continents during the COVID-19 pandemic are unknown. OBJECTIVE: This study compared the levels of impact of COVID-19 on mental health among people from Spain and China and correlated mental health parameters with variables relating to symptoms similar to COVID-19, COVID-19 knowledge, and precautionary measures. METHODS: We collected information on demographic data, physical symptoms, contact history with persons with a confirmed COVID-19 diagnosis, COVID-19 knowledge, and precautionary measures. Participants completed the Impact of Event Scale-Revised (IES-R) and the Depression, Anxiety and Stress Scale-21 Items (DASS-21). To analyze the differences in the mental health parameters, the mean scores between Chinese and Spanish respondents were compared using the independent samples t test. The differences in categorical variables between the two samples were analyzed by the chi-square test. Linear regression was used to calculate the univariate associations between the independent variables and mental health parameters for both groups separately, with adjustments made for age, gender, and education. RESULTS: A total of 1528 participants (Spain: n=687; China: n=841) were recruited. The mean age of the Chinese respondents was 24.73 years (SD 7.60; range 18-65 years), and the mean age of the Spanish respondents was 43.06 years (SD 11.95; range 18-76 years). Spanish participants reported significantly more symptoms similar to COVID-19 infection (eg, fever, sore throat, and breathing difficulties), contact history with COVID-19, higher perceived risk of contracting COVID-19, frequent use of medical services, and less confidence in medical services compared with their Chinese counterparts (P<.001). Spanish participants reported significantly higher DASS-21 stress and depression scores, while Chinese participants reported significantly higher IES-R scores (P<.001). Chinese participants encountered more discrimination from other countries (P<.001). Significantly more Chinese participants reported using face masks than Spanish ones (P<.001). More exposure to health information was associated with adverse mental health in Spain (depression: P=.02; anxiety: P=.02; stress: P=.001). CONCLUSIONS: Our study found that Spanish respondents reported higher levels of stress and depression as well as more symptoms and use of medical services. In preparation for the next pandemic, Spain needs to establish a prompt policy to implement rapid response and enhance medical services to safeguard physical and mental health.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".