Validated instruments used to measure attitudes of healthcare students and professionals towards patients with physical disability: a systematic review
Bibliographic record
Abstract
BACKGROUND: Instruments to detect changes in attitudes towards people with disabilities are important for evaluation of training programs and for research. While we were interested in instruments specific for medical students, we aimed to systematically review the medical literature for validated survey instruments used to measure attitudes of healthcare students and professionals towards patients with physical disability. METHODS: We electronically searched Medline, EMBASE, PsycINFO, Health and Psychosocial Instruments. We included papers reporting on the development and/or validation of survey instruments to measure attitudes of healthcare students and professionals towards patients with physical disability. We excluded papers in which the attitudes were not measured in a provider-patient context. Two reviewers carried out titles and abstracts screening, full texts screening, and data abstraction in a duplicate and independent manner using standardized and pilot tested forms. RESULTS: We identified seven validated survey instruments used for healthcare students and professionals. These instruments were originally developed for the following target populations: general population (n = 4); dental students (n = 1); nursing students (n = 1); and rehabilitation professionals (n = 1). The types of validity reported for these instruments were content validity (n = 3), criterion-related validity (n = 1), construct validity (n = 2), face validity (n = 1), discriminant validity (n = 1), and responsiveness (n = 1). The most widely validated and used tool (ATDP) was developed in the late 1960s while the most recent instrument was developed in the early 1990s. CONCLUSION: Of the seven identified validated instruments, less than half were specifically designed for healthcare students and professionals and none for medical students. There is a need to develop and validate a contemporary instrument specifically for medical students.
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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 | 0.030 | 0.144 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".