Adapting a Widely Used Children's Disability Attitudes Measure: Validation of the Maryland East‐African Children's Attitudes Towards Disabilities (MEACAD) Scale
Bibliographic record
Abstract
ABSTRACT Background The Chedoke‐McMaster Attitudes Towards Children with Handicaps (CATCH), a 36‐item scale, is widely used to assess children's attitudes toward peers with disabilities. While recognized for its strong validity and reliability, it was developed nearly four decades ago in Canada for children aged 9 to 13 and no longer fully aligns with diverse geographical and cultural contexts today. We examine children's attitudes toward children with disabilities in Kampala, Uganda, using a culturally‐tailored, shorter, and updated version of the CATCH scale. We establish the construct validity of the scale by testing three hypotheses grounded in existing literature. Methods We cross‐sectionally examined the attitudes of 375 children aged 6 to 9 years in Kampala in the Summer of 2024. Findings Through rigorous scale validation steps, we offer a modernized, age‐appropriate, and concise 15‐item adaptation—one of the first in the East African context. The revised scale demonstrated strong construct validity along with good internal consistency. Conclusions Future research should evaluate the scale's psychometric properties across broader age groups, geographical regions, and socioeconomic contexts to enhance its robustness as a modern multi‐dimensional scale for measuring children's attitudes toward peers with disabilities. We introduce the Maryland‐East African Children's Attitudes toward Disabilities (MEACAD) scale.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".