User-centered Design:Development of a Web-based Self-help Intervention for Partners of Cancer Patients
Bibliographic record
Abstract
Background/purpose: Many people living with cancer experience depression. Research suggests that the therapeutic effect of exercise on depression is similar to pharmacotherapy or psychological intervention, yet cancer survivors are under-exercising compared to recommended doses. Self-efficacy may be a factor to explain exercise engagement. This cross-sectional study investigated whether exercise task self-efficacy (ETSE) was associated with exercise engagement, further examining differences between cancer survivors with and without elevated depressive symptoms. Methods: Ninety-seven cancer survivors (60.8 ±9.9 years) were mailed self-report questionnaires on ETSE, exercise engagement, and depressive symptoms. A Hospital Anxiety and Depression Scale D cutoff score (≥8) was used to assign participants to a symptomatic (n = 34) or non-symptomatic group (n = 63). An independent t-test was used to examine differences in ETSE between groups. Correlational analyses were used to examine relationships between exercise task self-efficacy and exercise engagement. Results: There was a significant difference in the degree of exercise task self-efficacy between cancer survivors with (M=35.74, SD= 31.47) and without (M=57.30, SD= 26.71) depressive symptoms, t(95) =_3.56, p<0.01, with a large effect size (d =0.74). A positive association was found between ETSE and exercise engagement, r(95)= 0.49, p<0.01, which was similar for both groups. Conclusions: Exercise task self-efficacy appears to influence exercise engagement independently of mood status, but people with higher levels of depression symptoms tend to have lower self-efficacy. Therefore, future research should examine interventions to enhance exercise task self-efficacy, thereby potentially increasing exercise engagement in cancer survivors. Research Implications: These findings demonstrated that cancer survivors with depressive symptoms have low ETSE and that ETSE can predict exercise engagement. This suggests a role for enhancing ETSE to influence exercise engagement in cancer survivors. Future research could investigate causality between ETSE and exercise engagement and interventions to enhance ETSE. The findings of the present study could assist with more definitive research which could aid clinicians interested in behavioral change with regard to exercise engagement and improvement of depressive symptomatology in cancer survivors. Practice Implications: The findings illustrate that exercise self-efficacy predicts exercise engagement, independently of mood. Therefore, clinicians working with depressed or non-depressed cancer survivors should initially target increasing exercise self-efficacy as opposed to reinforcing the positive health benefits of increased physical activity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".