Program standards and student competencies among global chiropractic accreditation agencies: a content analysis
Bibliographic record
Abstract
BACKGROUND: Accreditation of healthcare provider training programs ensures graduate competency and provides a means for programs to improve. Accreditation consistency assures the public that healthcare providers have similar basic training across world regions. Currently, it is unknown if chiropractic accrediting agencies have congruent standards globally. Therefore, the purpose of this study was to investigate similarities and differences in student competencies and program standards among four chiropractic accreditation agencies worldwide. METHODS: A quantitative content analysis was performed on accreditation standards from regional international accreditation agencies responsible for accrediting the majority of the world's chiropractic degree programs. Agencies included the Council on Chiropractic Education (United States), the European Council on Chiropractic Education (Europe, United Kingdom, South Africa), the Council on Chiropractic Education Australasia (Australia, New Zealand, Malaysia), and the Council on Chiropractic Education Canada (Canada). The contents of the accrediting standards were coded using a standardized coding list. A modified Delphi technique was used by 21 international experts from December 1, 2023, to April 18, 2024. After four rounds of consideration to achieve consensus, the contents were analyzed for frequency and congruence of coded items across the accrediting agencies' standards. A two-way analysis of variance was conducted to identify if there were any differences among the accreditation agencies. RESULTS: = 0.87 for program standards; thus, the models' predictions align with the observed data. CONCLUSIONS: The study findings demonstrate congruence for student competencies and program standards among chiropractic accreditation agencies across multiple geographic regions. The patterns of content were stable and consistent across the four accrediting agencies, with no evidence of differential effects among the agencies. In addition, this study provides essential details and standardized codes for agencies' documents, which may facilitate dialogue and comprehension among agencies, educators, regulators, governing officials, and other stakeholders in chiropractic education. STUDY REGISTRATION: The study protocol was prospectively registered with Open Science Framework on November 30, 2023 https://doi.org/10.17605/OSF.IO/259WC .
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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 | 0.017 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".