Social determinants of unmet need for primary care: a systematic review
Bibliographic record
Abstract
BACKGROUND: Despite primary care being largely free at the point of delivery, many Canadians experience challenges in accessing the services they need. A systematic review was conducted to summarize the evidence on the level of unmet need for primary care in Canada and its social determinants. METHODS: MEDLINE, Embase, Cochrane, and Web of Science databases were screened from inception to December 2023 using relevant search terms for primary care and unmet healthcare needs. Quantitative observational studies in the English language that included Canadian adults aged 18 years and older and focused on unmet needs for primary care were included. The risk of bias in the studies was assessed using either the Joanna Briggs Institute (JBI) critical appraisal checklist or the Newcastle-Ottawa Scale. The included studies were synthesized narratively. RESULTS: Forty-six studies met the inclusion criteria for this review. Of the included studies, 96% were cross-sectional in design and 91% had low risk of bias. The prevalence of unmet need, mostly self-reported, varied between 6.6% and 25.2% in national studies. Social determinants of unmet needs were heterogeneous across studies. Findings suggest that unmet need for primary care is related to having low income, mental health diagnoses, and chronic conditions, and negatively associated with older age, having better-perceived health, and having a family physician. CONCLUSIONS: Universal access to primary care is the founding principle of the Canadian healthcare system. However, we found evidence suggesting that the extent to which primary care needs are met is influenced by social determinants of health. Further research is needed to improve our understanding of the mechanisms of unmet primary care needs in Canada. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021285074.
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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 | 0.012 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".