Validation of the attitudes toward intellectual disability – ATTID questionnaire
Bibliographic record
Abstract
BACKGROUND: Individuals with an intellectual disability (ID) continue to experience major obstacles towards social, educational and vocational integration. Negative attitudes toward persons with ID has remained relevant over time and has led to discrimination and stigma. OBJECTIVE: The present study describes the development of a new questionnaire for tapping into the general population's attitudes toward individuals with ID and addresses its psychometric properties. METHODS: Adopting a multidimensional perspective, the Attitudes Toward Intellectual Disability Questionnaire (ATTID) was developed from a series of previously validated instruments and principles from the Montreal Declaration on Intellectual Disability (2004). The ATTID was administered by phone to 1605 randomly selected adult men and women, stratified by region in the Province of Quebec, Canada. RESULTS: The ATTID yielded a five-factor structure overlapping the tri-partite model of attitudes. The cognitive component was represented by two factors: knowledge of capacity and rights and knowledge of causes of ID. The affective component tapped into two factors: discomfort and sensitivity/compassion. Finally, the behavioural component emerged as a single factor. The ATTID had good internal consistency with Cronbach's alpha coefficients ranging from 0.59 to 0.89 for the five factors and of 0.92 for the overall questionnaire. Test-retest reliability yielded correlations from 0.62 to 0.83 for the five factors. CONCLUSION: The ATTID can be used to measure attitudes among different populations and allows comparisons over time within the same population as a function of various intervention strategies for de-stigmatising ID.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".