Doctors of chiropractic working with or within integrated healthcare delivery systems: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Back and neck pain are the leading causes of disability worldwide. Doctors of chiropractic (DCs) are trained to manage these common conditions and can provide non-pharmacological treatment aligned with international clinical practice guidelines. Although DCs practice in over 90 countries, chiropractic care is rarely available within integrated healthcare delivery systems. A lack of DCs in private practice, particularly in low-income communities, may also limit access to chiropractic care. Improving collaboration between medical providers and community-based DCs, or embedding DCs in medical settings such as hospitals or community health centres, will improve access to evidence-based care for musculoskeletal conditions. METHODS AND ANALYSES: This scoping review will map studies of DCs working with or within integrated healthcare delivery systems. We will use the recommended six-step approach for scoping reviews. We will search three electronic data bases including Medline, Embase and Web of Science. Two investigators will independently review all titles and abstracts to identify relevant records, screen the full-text articles of potentially admissible records, and systematically extract data from selected articles. We will include studies published in English from 1998 to 2020 describing medical settings that have established formal relationships with community-based DCs (eg, shared medical record) or where DCs practice in medical settings. Data extraction and reporting will be guided by the Proctor Conceptual Model for Implementation Research, which has three domains: clinical intervention, implementation strategies and outcome measurement. Stakeholders from diverse clinical fields will offer feedback on the implications of our findings via a web-based survey. ETHICS AND DISSEMINATION: Ethics approval will not be obtained for this review of published and publicly accessible data, but will be obtained for the web-based survey. Our results will be disseminated through conference presentations and a peer-reviewed publication. Our findings will inform implementation strategies that support the adoption of chiropractic care within integrated healthcare delivery systems.
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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 | 0.111 | 0.090 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.067 | 0.015 |
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".