Questionnaires used to assess barriers of clinical guideline use among physicians are not comprehensive, reliable, or valid: a scoping review
Bibliographic record
Abstract
OBJECTIVE: This study described the number and characteristics of questionnaires used to assess barriers of guideline use among physicians. STUDY DESIGN AND SETTING: A scoping review was conducted. MEDLINE and EMBASE were searched from 2005 to June 2016. English-language studies that administered a questionnaire to assess barriers of guideline use among practicing physicians were eligible. Summary statistics were used to report study and questionnaire characteristics. Questionnaire content was assessed with a checklist of 57 known barriers. RESULTS: Each of the 178 included studies administered a unique questionnaire. The number of questionnaires increased yearly from 2005 to 2015. Few were pilot-tested (50, 28.1%) or tested for psychometric properties (3, 1.7%). Two were based on theory. None probed for the full range of known barriers. Ten included a free-text option. The majority assessed professional barriers (177, 99.4%) but few of the 14 factors within this domain. Questionnaire characteristics did not change over time. CONCLUSION: Organizations administered questionnaires that were not reliable or valid and did not comprehensively assess barriers and may have selected interventions unlikely to promote guideline use. Research is needed to construct a questionnaire that is practical, adaptable, and robust and leads to the selection of interventions that support guideline use.
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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 | 0.065 | 0.233 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".