The relationship between maladaptive health beliefs, pandemic-related stress, and health anxiety during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: Research has demonstrated that people experience specific distress and anxiety regarding COVID-19. This distress may consist of interconnected symptom categories corresponding to a COVID stress syndrome. Susceptibility to COVID stress syndrome may be related to one's maladaptive health beliefs; however, no research has investigated the association between maladaptive health beliefs and COVID stress. The present study explored the impact of health beliefs on COVID stress, health anxiety, and associated psychological constructs. PARTICIPANTS AND PROCEDURE: = 2.28). Participants completed an online survey including demographic questionnaires and self-report measures of health beliefs, COVID stress, health anxiety, and related psychological constructs. RESULTS: < .001). Health beliefs (i.e., perceived likelihood of illness, medical service inadequacy, and difficulty coping) were associated with greater COVID stress, although health beliefs were not found to mediate the relationship between health anxiety and COVID stress. CONCLUSIONS: Health beliefs were associated with greater COVID stress, although health beliefs did not mediate the relationship between health anxiety and COVID stress. The relationship between health anxiety and COVID stress may be better explained by other COVID-related cognitions (e.g., vaccine efficacy, dangerousness of COVID-19). The findings highlight the importance of peoples' health beliefs during the pandemic. Given anxiety's influence on peoples' behavioural responses to the pandemic, further research should identify COVID-specific cognitions for prevention of COVID stress and health anxiety.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".