Development of a battery of tests to measure attitudes and intended behaviours of dental students towards people with disability or those in marginalised groups
Bibliographic record
Abstract
INTRODUCTION: Recommended curricula in Special Care Dentistry (SCD) outline learning objectives that include the domain of attitudes and behaviours, but these are notoriously difficult to measure. The aims of this study were (i) to develop a test battery comprising adapted and new scales to evaluate values, attitudes and intentions of dental students towards people with disability and people in marginalised groups and (ii) to determine reliability (interitem consistency) and validity of the scales within the test battery. MATERIALS AND METHODS: A literature search identified pre-existing measures and models for the assessment of attitudes in healthcare students. Adaptation of three pre-existing scales was undertaken, and a new scale was developed based upon the Theory of Planned Behaviour (TPB) using an elicitation survey. These scales underwent a process of content validation. The three adapted scales and the TPB scale were piloted by 130 students at 5 different professional stages, from 4 different countries. RESULTS: The scales were adjusted to ensure good internal reliability, variance, distribution, and face and content validity. In addition, the different scales showed good divergent validity. DISCUSSION: These results are positive, and the scales now need to be validated in the field. CONCLUSIONS: It is hoped that these tools will be useful to educators in SCD to evaluate the impact of teaching and clinical exposure on their 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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".