“It’s Improving Screening Rates, it’s Catching Things Early, and it’s Empowering People”: A Qualitative Study of BETTER WISE
Bibliographic record
Abstract
Context: BETTER WISE is a comprehensive and structured approach for cancer and chronic disease prevention and screening (CCDPS) that addresses cancer survivorship and screens for lifestyle risks and poverty in patients aged 40 to 65. Objective: To describe the impact, barriers and facilitators of BETTER WISE. Study Design and Analysis: Qualitative study: 17 focus groups and 48 key informant interviews were conducted, transcribed and analyzed employing thematic analysis using a constant comparative method. Written feedback (585 feedback forms) from patients was also collected and analyzed. Setting: 13 primary care settings (urban, rural and remote) in Alberta, Ontario, and Newfoundland and Labrador, Canada. Participants: Primary care team members (N=132) including clinicians, managers and clerical staff participated in focus groups or one-on-one key informant telephone interviews. Additionally, patients submitted 585 written feedback forms. Intervention: 1,005 patients were invited for a one-hour visit with a “prevention practitioner” (PP), a member of the primary care team with training in CCDPS and the BETTER WISE approach. PPs met with patients one-on-one to provide them with an overview of their individual risk for chronic diseases, eligibility for screening, and assistance with lifestyle counselling. Results: Four main themes were identified: 1) Impact on patients: Patients appreciated the BETTER WISE approach and found it empowering. They caught health concerns that were overlooked and reported improved lifestyle changes; 2) Impact on primary care providers (PCPs): PPs reported improved teamwork, increased knowledge of CCDPS, and better relationships with patients and physicians; 3) The main barrier to implementation of BETTER WISE was the onset of the COVID-19 pandemic, which: i) changed prevention visits to phone visits, ii) put screening tests on hold, and iii) added hardship on patients and PCPs as focus shifted to emergencies, acute care, and COVID-19 screening and vaccinations; 4) Facilitators of the implementation of BETTER WISE included: i) buy-in from PPs, physicians, and patients, ii) good relationship and team culture within primary care teams, and iii) alignment with CCDPS activities already happening at the clinics. Conclusion: Despite the interruption of the COVID-19 pandemic, the participating primary care clinics completed the BETTER WISE study and the BETTER WISE approach had a positive impact on patients and PCPs.
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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 | 0.022 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".