A methodological review protocol of the use of Bayesian factor analysis in primary care research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background : The development of questionnaires for primary care practice and research is of increasing interest in the literature. In settings where valuable prior knowledge or preliminary data is available, Bayesian factor analysis can be used to incorporate such information when conducting questionnaire construct validation. This protocol outlines a methodological review that will summarize evidence on the current use of Bayesian factor analysis in the primary care literature. Methods : A comprehensive search strategy has been developed and will be used to identify relevant literature (research studies in primary care) indexed in Medline, Scopus, EMBASE, CINAHL and Cochrane Library. The search strategy includes terms and synonyms for Bayesian factor analysis and primary care. The reference lists of relevant articles being identified will be screened to find further relevant studies. At least two reviewers will independently extract data and resolve discrepancies through consensus. Descriptive analyses will summarize the use and reporting of Bayesian factor analysis approaches for validating questionnaires applicable to primary care. Discussion: This methodological review will provide a comprehensive overview of the current use and reporting of Bayesian factor analysis in primary care and will provide recommendations for its proper future use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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: Methods · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | medium |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Other design | 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 | 0.020 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.015 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it