The Coronavirus Anxiety in the Elderly: The Role of Coping Styles with Stress and Meta-Worry
Bibliographic record
Abstract
Coronavirus symptoms have more severe physical and psychological clinical manifestations in the elderly. Accordingly, the elderly seem to be one of the main groups at risk for Coronavirus disease. The aim of this study was to predict Coronavirus anxiety based on coping styles with stress and meta-worry. The research design was correlational. The statistical population included all the elderly living in Ahvaz, among whom 300 were selected as the study sample using online convenience sampling method. The research instruments included Alizadeh et al.'s Corona Anxiety, Lazarus and Falkman's Coping Styles, and Wells's meta-worry Inventory. Used to analyze the data was a multiple regression method. The results indicated that problem-oriented coping style (r-=0.401) had a negative and significant relationship with corona anxiety in the elderly and emotion-centered coping style (r=0.281) and meta-worry (r=0.429) have a positive and significant relationship with corona anxiety (p < 0.01). Besides, the variables of problem-oriented coping style, emotion-centered coping style and meta-worry were able to predict 31.5% of the changes in corona anxiety in the elderly, which the share of meta-worry was more than other variables (p < 0.01). Considering the capability of coping style and meta-worry in predicting Coronavirus anxiety in the elderly, training programs can be designed and represented through virtual workshops to increase problem-oriented coping style and to decrease emotion-centered coping style and meta-worry, in order to reduce Coronavirus anxiety. References Aldwin, C. M., Molitor, N. T., Avron, S., Levenson, M. R., Molitor, J., & Igarashi, H. (2011). Do stress trajectories predict mortality in older men? Longitudinal findings from the VA normative aging study. Journal of Aging Research, 11(1), Article 896109. Alipour, A., Ghadami, A., Alipour, Z., Abdollahzadeh, H. (2020). Preliminary validation of the Corona Disease Anxiety Scale (CDAS) in the Iranian sample. 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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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".