Mobile primary health care clinics for Indigenous populations in Australia, Canada, New Zealand and the United States: a systematic scoping review
Bibliographic record
Abstract
Abstract Background Mobile clinics have been used to deliver primary health care to populations that otherwise experience difficulty in accessing services. Indigenous populations in Australia, Canada, New Zealand, and the United States experience greater health inequities than non-Indigenous populations. There is increasing support for Indigenous-governed and culturally accessible primary health care services which meet the needs of Indigenous populations. There is some support for primary health care mobile clinics implemented specifically for Indigenous populations to improve health service accessibility. The purpose of this review is to scope the literature for evidence of mobile primary health care clinics implemented specifically for Indigenous populations in Australia, Canada, New Zealand, and the United States. Methods This review was undertaken using the Joanna Brigg Institute (JBI) scoping review methodology. Review objectives, inclusion criteria and methods were specified in advance and documented in a published protocol. The search included five academic databases and an extensive search of the grey literature. Results The search resulted in 1350 unique citations, with 91 of these citations retrieved from the grey literature and targeted organisational websites. Title, abstract and full-text screening was conducted independently by two reviewers, with 123 citations undergoing full text review. Of these, 39 citations discussing 25 mobile clinics, met the inclusion criteria. An additional 14 citations were snowballed from a review of the reference lists of included citations. Of these 25 mobile clinics, the majority were implemented in Australia (n = 14), followed by United States (n = 6) and Canada (n = 5). No primary health mobile clinics specifically for Indigenous people in New Zealand were retrieved. There was a pattern of declining locations serviced by mobile clinics with an increasing population. Furthermore, only 13 mobile clinics had some form of evaluation. Conclusions This review identifies geographical gaps in the implementation of primary health care mobile clinics for Indigenous populations in Australia, Canada, New Zealand, and the United States. There is a paucity of evaluations supporting the use of mobile clinics for Indigenous populations and a need for organisations implementing mobile clinics specifically for Indigenous populations to share their experiences. Engaging with the perspectives of Indigenous people accessing mobile clinic services is imperative to future evaluations. Registration The protocol for this review has been peer-reviewed and published in JBI Evidence Synthesis (doi: 10.11124/JBISRIR-D-19-00057).
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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 | 0.016 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.014 | 0.020 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".