Social Cognitive Predictors of Health Promotion Self-Efficacy Among Older Adults During the COVID-19 Pandemic
Bibliographic record
Abstract
Purpose To examine the relative importance of social cognitive predictors (ie, performance accomplishment, vicarious learning, verbal persuasion, affective state) on health promotion self-efficacy among older adults during COVID-19. Design Cross-sectional. Setting Data collected online from participants in British Columbia (BC), Canada. Subjects Seventy-five adults (n = 75) aged ≥65 years. Measures Health promotion self-efficacy was measured using the Self-Rated Abilities for Health Practices Scale. Performance accomplishment was assessed using the health directed behavior subscale of the Health Education Impact Questionnaire; vicarious learning was measured using the positive social interaction subscale of the Medical Outcomes Survey - Social Support Scale (MOS-SSS); verbal persuasion was assessed using the informational support subscale from the MOS-SSS; and affective state was assessed using the depression subscale from the Depression Anxiety Stress Scale (DASS-21). Analysis Multiple linear regression was used to investigate the relative importance of each social cognitive predictor on self-efficacy, after controlling for age. Results Our analyses revealed statistically significant associations between self-efficacy and performance accomplishment (health-directed behavior; β = .20), verbal persuasion (informational support; β = .41), and affective state (depressive symptoms; β = −.44) at P < .05. Vicarious learning (β = −.15) did not significantly predict self-efficacy. The model was statistically significant ( P < .001) explaining 43% of the self-efficacy variance. Conclusion Performance accomplishment experiences, verbal persuasion strategies, and affective states may be the target of interventions to modify health promotion self-efficacy among older adults, in environments that require physical and social distancing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".