What matters most to patients about primary healthcare: mixed-methods patient priority setting exercises within the PREFeR (PRioritiEs For Research) project
Bibliographic record
Abstract
OBJECTIVES: To identify patient-generated priority topics for future primary care research in British Columbia (BC), Canada within a diverse patient population. DESIGN: Mixed-methods priority setting exercises framed by the dialogue model, using the nominal group technique (rank-ordered scoring) and province-wide online surveys capturing importance ratings of the top 10 primary healthcare topics from patients and primary care providers. SETTING: BC, Canada. PARTICIPANTS: Topic identification was completed by 10 patient partners (7 female, 3 male) from the BC Primary Health Care Research Network Patient Advisory; online surveys were completed by 464 patients and 173 primary care providers. RESULTS: The 10 members recruited to the patient advisory provided over 80 experiences of what stood out for them in BC primary care, which were grouped thematically into 18 topics, 10 of which were retained in province-wide surveys. Top-rated survey topics for both patients (n=464) and providers (n=173) included being unable to find a regular family doctor/other primary healthcare provider, support for living with chronic conditions, mental health resources and information sharing, including electronic medical records. However, all 10 topics were rated important, on average, by both groups. CONCLUSIONS: The current project activities demonstrate the feasibility of including patients in priority setting exercises for primary healthcare in general, rather than focusing on a condition-specific population or disease area. There was considerable overlap between patient-generated topics and topics previously identified by other stakeholders, but patients identified two additional topics (mental health resources, improve and strengthen patient-provider communication). More similarities than differences in topic importance between patients and providers emerged in the online surveys. The project activities that follow (rapid literature reviews, multistakeholder dialogue) will highlight under-researched topics and inform the development of specific research questions.
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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 | 0.076 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".