Improving attitudes towards children with disabilities in a school context: a cluster randomized intervention study
Bibliographic record
Abstract
AIM: although inclusive education of disabled children is now an accepted practice, it is often challenged by negative peer attitudes. We undertook an interventional study aimed at improving students' attitudes towards their disabled peers. METHOD: the participants were students from the 7th grade of twelve paired schools (1509 students from 62 classes; age 12-13y), randomly allocated to an intervention group (205 males, 285 females) or a control group (132 males, 165 females). The intervention consisted of a mandatory comprehensive educational project on disability. The Chedoke-McMaster Attitudes Towards Children with Handicaps Scale (CATCH) was used to assess children's attitudes before (T0) and after (T1) intervention. The hierarchical structure of the data was taken into account by adjusting standard deviations and using linear multilevel models. RESULTS: seven hundred and eighty-four students had at least one score on the three domains (cognitive, affective, behavioural) of the CATCH at T0 and T1. The final scores were higher than baseline scores (total scores, intervention group: baseline score 25.6 (SD=5.4), final score 26.8 (5.9), p<0.001; CONTROL GROUP: baseline 25.2 (5.4), final 26.0 (5.7), p<0.009) with no significant difference between the intervention and control groups. Individual score changes over time were associated with baseline score (p<0.001 for total and all sub-scores). Lower improvement in attitudes was found in students from schools with special units for their peers with cognitive impairment for total (p=0.013), affective (p<0.001), and behavioural (p=0.001) scores, while higher improvement existed for the cognitive domain (p=0.029). INTERPRETATION: although we found no effect of our intervention, we found an improvement in attitudes in the intervention and control groups that could be a result of the nature of the scales and questionnaires the students had to complete before the intervention.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".