Quality of reporting in chiropractic mixed methods research: a methodological review protocol
Bibliographic record
Abstract
BACKGROUND: Mixed methods designs are increasingly used in health care research to enrich findings. However, little is known about the frequency of use of this methodology in chiropractic research, or the quality of reporting among chiropractic studies using mixed methods. OBJECTIVE: To quantify the use and quality of mixed methods in chiropractic research, and explore the association of study characteristics (e.g., authorship, expertise, journal impact factor, country and year of publication) with reporting quality. METHODS: We will conduct a systematic search of MEDLINE, EMBASE, CINAHL, and the Index to Chiropractic Literature to identify all chiropractic mixed methods studies published from inception of each database to December 31, 2020. Articles reporting the use of both qualitative and quantitative methods, or mixed qualitative methods, will be included. Pairs of reviewers will perform article screening, data extraction, risk of bias with the Mixed Methods Appraisal Tool (MMAT), and appraisal of reporting quality using the Good Reporting of A Mixed Methods Study (GRAMMS) guideline. We will explore the correlation between GRAMMS and MMAT scores, and construct generalized estimating equations to explore factors associated with reporting quality. DISCUSSION: This will be the first methodological review to examine the reporting quality of published mixed methods studies involving chiropractic research. The results of our review will inform opportunities to improve reporting in chiropractic mixed methods studies. Our results will be disseminated in a peer-reviewed publication and presented publicly at conferences and as part of a doctoral thesis.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | Metaresearch Domain: Reporting · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.296 | 0.417 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.007 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".