Development and psychometric properties of the Attitudes Toward Intellectual Disability Questionnaire – Short Form
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background Understanding public attitudes towards people with intellectual disability (ID) can help orient activities to promote the social inclusion of this group. The ATTitudes toward Intellectual Disability (ATTID) questionnaire is a validated 67‐item tool used to assess attitudes towards people with ID from a multidimensional perspective. It is based on a five‐factor model tapping into cognitive, emotional and behavioural components of attitudes. In order to facilitate international research, the goal of this study was to develop a short version that would retain the long form's psychometric properties. Methods Analyses were conducted on a sample of 1608 respondents who completed the full‐length ATTID. A four‐step test refinement procedure was used to reduce the number of items. The first two steps involved a Cronbach's alpha analysis. Items retained were then reviewed to assess face validity. Correlations between factors were calculated, and a factor analysis was performed to compare the original and short forms. Results The number of items in the ATTID was reduced from 67 to 35. The short form maintained good overall reliability. The correlational pattern between factors in both the long and short form is generally the same. The factor analysis of the short form showed a similar five‐factor structure with some loss of variance. Conclusions We recommend the short form be used when administration time is an issue, particularly in a research context. Replication studies with new samples are needed to further assess the psychometric properties of the ATTID‐Short Form.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it