Web-Based Peer Navigation for Men with Prostate Cancer and Their Family Caregivers: A Pilot Feasibility Study
Bibliographic record
Abstract
This study assessed the feasibility, acceptability and potential effects of True North Peer Navigation (PN)—a web-based peer navigation program for men with prostate cancer (PC) and their family caregivers. A one-arm, pre-post pilot feasibility study was conducted at two cancer centres in Canada. Participants were matched through a web-app with a specially trained peer navigator who assessed needs and barriers to care, provided support and encouraged a proactive approach to health for 3 months. Descriptive statistics were calculated, along with paired t-tests. True North PN was feasible, with 57.9% (84/145) recruitment, 84.5% (71/84) pre-questionnaire, 77.5% (55/71) app registration, 92.7% (51/55) match and 66.7% (34/51) post-questionnaire completion rates. Mean satisfaction with Peer Navigators was 8.4/10 (SD 2.15), mean program satisfaction was 6.8/10 (SD 2.9) and mean app usability was 60/100 (SD 14.8). At 3 months, mean ± SE patient/caregiver activation had improved by 11.5 ± 3.4 points (p = 0.002), patient quality of life by 1.1 ± 0.2 points (p < 0.0001), informational support by 0.4 ± 0.17 points (p = 0.03), practical support by 0.5 ± 0.25 points (p = 0.04) and less need for support related to fear of recurrence among patients by 0.4 ± 19 points (p = 0.03). The True North web-based peer navigation program is highly feasible and acceptable among PC patients and caregivers, and the associated improvements in patient and caregiver activation are promising. A randomized controlled trial is warranted to determine 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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".