The Clinician Guideline Determinants Questionnaire was developed and validated to support tailored implementation planning
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
OBJECTIVES: The purpose of this research was to generate and validate a questionnaire that identifies determinants of guideline use from the clinician perspective. STUDY DESIGN AND SETTING: From January 2017 to March 2018, a seven-member six-country multidisciplinary team used a five-step multimethod design to search for and compile determinant frameworks, map items to determinants (content validity), select the best items for each determinant (content validity), refine wording of determinants and items (face validity), merge or separate items (construct validity), and review the final questionnaire. RESULTS: The Clinician Guideline Determinants Questionnaire includes four sections: clinician demographic information (including two determinants: attitudes about/experience with guidelines), 26 close-ended items reflecting clinician- and guideline-specific determinants, four open-ended items reflecting enablers and barriers perceived as most important, and three items on learning style (preferred sources of guideline information). CONCLUSION: The Clinician Guideline Determinants Questionnaire is a comprehensive, validated instrument that addresses multiple potential determinants specific to guideline use from a clinician perspective. The Questionnaire can be used at multiple time points in the guideline development cycle to assess determinants of the use of new, updated, or adapted guidelines and before and after interventions to assess their impact on the determinants of guideline use. In future research, we will establish psychometric properties of the new questionnaire.
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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 | 0.058 | 0.176 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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