Development of a Survey to Explore Factors Influencing the Adoption of Best Practices for Diabetic Foot Ulcer Offloading
Bibliographic record
Abstract
PURPOSE: The primary purpose of this study was to develop 2 survey tools to explore factors influencing adoption of best practices for diabetic foot ulcer offloading treatment in primary health care settings. One survey was intended for the patients receiving care for a diabetic foot ulcer in primary health care settings and the other was intended for the health professionals providing treatment. The second purpose of this study was to evaluate the psychometric properties of the 2 surveys. DESIGN: Development and validation of survey instruments. METHODS: Two surveys were developed using a published guide. Following review of pertinent literature and identification of variables to be measured, a bank of items was developed and pretested to determine clarity of the item and responses. Psychometric testing comprised measurement of content validity index (CVI) and intraclass correlation coefficient (ICC). Only items obtaining satisfactory CVI and ICC scores were included in the final version of the surveys. RESULTS: The final version of the patient survey contained 41 items and the final version of the survey for health care professionals contained 21 items. The patient-intended survey's items demonstrate high content validity scores and satisfactory test-retest reliability scores. The overall CVI score was 0.98. Forty of the 49 items eligible for testing obtain satisfactory ICC scores. One item's test-retest reliability could not be tested but it was retained based on its high CVI. The health professional-intended survey, an overall CVI score of 0.91 but items had lower ICC scores (63%, 31 of the 49 items), did not achieve a satisfactory ICC score for inclusion in the final instrument. CONCLUSION: This project led to development of 2 instruments designed to identify and explore factors influencing adoption of best practices for diabetic foot ulcer offloading treatment in the primary health care setting. Future research and testing is required to translate these French surveys into English and additional languages, in order to reach a broader population.
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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 | 0.022 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".