Adaptation and Validation of the Indonesian Version of Attitudes toward Sexuality Questionnaire in Individuals with Intellectual Disability (ASQ-ID)
Bibliographic record
Abstract
Background: Sexuality is an integral part of adult human life, including for individuals with a disability. Even though sexuality is a fundamental right of human life, however, for a person with an intellectual disability, expressing and exploring sexuality is limited. This study aimed to determine the reliability and validity of ASQ-ID in the Indonesian language. Methods: A cross-sectional observational study designed for adaptation and validation of the Attitudes toward Sexuality Questionnaire in Intellectual Disability (ASQ-ID) of the Indonesian version was conducted in 2019. The study subjects were 617 students of Universitas Diponegoro, Indonesia. The translation process was composed of 5 steps: translation, synthesis, back translation, and semantic and conceptual analysis testing. Exploratory Factor Analysis (EFA) with principal component analysis (PCA) as a method of extraction and varimax rotation was used to identify the structure/dimensionality of observed data and identify clusters of inter-correlated variables. Pearson's r-correlation test was used to evaluate the correlation between the original and Indonesian adaptation of ASQ-ID. Cronbach-alpha was computed across all factors/sub-scales to examine the internal consistency of the adapted questionnaire. Results: Reliability analysis showed Cronbach alpha and composite reliability of items of the Indonesia version of ASQ-ID was high. EFA analysis revealed 7 emerging factors and 28 items of solutions. The items were re-group into 4 sub-scales based on the original ASQ-ID sub-scales. Conclusion: The Indonesian version of ASQ-ID has high validity and reliability in measuring the attitudes toward sexuality in individuals with 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 | 0.008 | 0.010 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".