Development and Pilot Testing of a Measure of Potential Barriers and Facilitators to the Use of a Standardized Assessment Tool
Bibliographic record
Abstract
INTRODUCTION: Standardized assessment tools (SATs) are essential to evidence-based assessment practices. Identifying what impedes clinicians' use of a SAT can help tailor strategies promoting its use in clinical practice. This article presents the development of the "Measure of potential barriers and facilitators to the Use of a Standardized assessment Tool (MUST)" questionnaire. Preliminary findings are also reported from pilot testing in which the MUST was used to investigate occupational therapists' (OTs) perceptions of potential barriers and facilitators to the use of the Activities of Daily Living Profile (ADL Profile), a SAT evaluating independence in everyday activities of cognitively impaired adults. METHODS: The MUST was administered to 41 OTs attending continuing education workshops on the ADL Profile. Internal consistency was explored using Chronbach alpha. Descriptive statistics were used to analyze scores for each statement. RESULTS: Internal consistency for subscales related to clinicians' characteristics (α = 0.7) and to the SAT's characteristics (α = 0.8) were adequate but lower for the subscale related to the clinical setting (α = 0.6). OTs' perceptions of potential barriers were associated with: OTs' perceived self-efficacy; ADL Profile's applicability to OTs' clienteles; ADL Profile's compatibility with values promoted in the work setting and with clients' preferences; limited peer support; time to implement the ADL Profile. DISCUSSION: The MUST, a theory-informed questionnaire, may prove useful in identifying potential barriers needing to be addressed in continuing education training promoting the use of SATs by clinicians. The MUST is quick to administer and initial testing provides support for its internal consistency.
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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 | 0.033 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".