A Web-Based Intervention to Reduce Distress After Prostate Cancer Treatment: Development and Feasibility of the Getting Down to Coping Program in Two Different Clinical Settings
Bibliographic record
Abstract
BACKGROUND: Distress after prostate cancer treatment is a substantial burden for up to one-third of men diagnosed. Physical and emotional symptoms and health service use can intensify, yet men are reticent to accept support. To provide accessible support that can be cost effectively integrated into care pathways, we developed a unique, Web-based, self-guided, cognitive-behavior program incorporating filmed and interactive peer support. OBJECTIVE: To assess feasibility of the intervention among men experiencing distress after prostate cancer treatment. Demand, acceptability, change in distress and self-efficacy, and challenges for implementation in clinical practice were measured. METHODS: A pre-post, within-participant comparison, mixed-methods research design was followed. Phase I and II were conducted in primary care psychological service and secondary care cancer service, respectively. Men received clinician-generated postal invitations: phase I, 432 men diagnosed <5 years; phase II, 606 men diagnosed <3.5 years. Consent was Web-based. Men with mild and moderate distress were enrolled. Web-based assessment included demographic, disease, treatment characteristics; distress (General Health Questionnaire-28); depression (Patient Health Questionnaire-9); anxiety (General Anxiety Disorder Scale-7); self-efficacy (Self-Efficacy for Symptom Control Inventory); satisfaction (author-generated, Likert-type questionnaire). Uptake and adherence were assessed with reference to the persuasive systems design model. Telephone interviews explored participant experience (phase II, n=10); interviews with health care professionals (n=3) explored implementation issues. RESULTS: A total of 135 men consented (phase I, 61/432, 14.1%; phase II, 74/606, 12.2%); from 96 eligible men screened for distress, 32% (30/96) entered the intervention (phase I, n=10; phase II, n=20). Twenty-four completed the Web-based program and assessments (phase I, n=8; phase II, n=16). Adherence for phase I and II was module completion rate 63% (mean 2.5, SD 1.9) versus 92% (mean 3.7, SD 1.0); rate of completing cognitive behavior therapy exercises 77% (mean 16.1, SD 6.2) versus 88% (mean 18.6, SD 3.9). Chat room activity occurred among 63% (5/8) and 75% (12/16) of men, respectively. In phase I, 75% (6/8) of men viewed all the films; in phase II, the total number of unique views weekly was 16, 11, 11, and 10, respectively. The phase II mood diary was completed by 100% (16/16) of men. Satisfaction was high for the program and films. Limited efficacy testing indicated improvement in distress baseline to post intervention: phase I, P=.03, r=-.55; phase II, P=.001, r=-.59. Self-efficacy improved for coping P=.02, r=-.41. Service assessment confirmed ease of assimilation into clinical practice and clarified health care practitioner roles. CONCLUSIONS: The Web-based program is acceptable and innovative in clinical practice. It was endorsed by patients and has potential to positively impact the experience of men with distress after prostate cancer treatment. It can potentially be delivered in a stepped model of psychological support in primary or secondary care. Feasibility evidence is compelling, supporting further evaluative research to determine clinical and cost effectiveness.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".