Experiences and preferences of people without access to primary care
Bibliographic record
Abstract
Objective To understand the health care–seeking behaviour and preferences of people in Canada who report not having a primary care clinician (PCC; family doctor or nurse practitioner). Design An anonymous, online, national cross-sectional survey was conducted. It was available from September 2022 to October 2022 in English and French. Responses were weighted based on sociodemographic factors to approximate the population of Canada. Setting Canada. Participants People aged 18 years or older. Main outcome measures Characteristics, health care–seeking behaviour, and preferences of people without a primary care clinician compared to people with one. Results A total of 9279 completed surveys were analyzed. About 21.8% of respondents said they did not have a primary care clinician. Among these, 83.1% said they were trying to find one and 66.2% of those looking reported doing so for over 1 year. Fewer men (vs women) (78.0% vs 89.3%; P<.001) and people without supplementary health benefits (vs with) (72.1% vs 85.8%; P<.001) reported looking. More people without a primary care clinician (vs with) indicated they tried getting care from a walk-in clinic (71.8% vs 41.2%; P<.001), but fewer reported their needs being met (40.6% vs 55.3%; P<.001). More people without a primary care clinician responded favourably to potential team- and neighbourhood-based care reforms. Conclusion People without a regular family doctor or nurse practitioner face several challenges. Many are trying to find one, but cannot. They value relationship-based care yet are more likely to use walk-in clinics and less likely to be satisfied with that care compared to people with a primary care clinician. Reforms should align with the values and preferences of those without primary care.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".