Prostate Cancer Survivors’ and Caregivers’ Experiences Using Behavior Change Techniques during a Web-Based Self-Management and Physical Activity Program: A Qualitative Study
Bibliographic record
Abstract
Both men with prostate cancer and their caregivers report experiencing a number of challenges and health consequences, and require programs to help support the cancer patient-caregiver dyad. A tailored, web-based, psychosocial and physical activity self-management program (TEMPO), which implements behavior change techniques to help facilitate behavior change for the dyads was created and its acceptability was tested in a qualitative study. The purpose of this secondary analysis was to explore the dyads' experiences using behavior change techniques to change behavior and address current needs and challenges while enrolled in TEMPO. Multiple semi-structured interviews were conducted with 19 prostate cancer-caregiver dyads over the course of the program, resulting in 46 transcripts that were analyzed using an inductive thematic analysis. Results revealed four main themes: (1) learning new behavior change techniques, (2) engaging with behavior change techniques learned in the past, (3) resisting full engagement with behavior change techniques, and (4) experiencing positive outcomes from using behavior change techniques. The dyads' discussions of encountering behavior change techniques provided unique insight into the process of learning and implementing behavior change techniques through a web-based self-management program, and the positive outcomes that resulted from behavior changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".