Quality of Life Among Families of Children With Intellectual Disabilities: A Slovene Study
Bibliographic record
Abstract
Abstract The main goal of the study was to provide and contrast data on quality of life for families in Slovenia that have children with intellectual disabilities and developmental disabilities (IDD) and families that have children with intellectual disabilities and autism spectrum disorders (ASD). The sample comprised 25 families with children with IDD and 19 families with children with ASD selected from schools in several villages in Slovenia. The data were collected using the FQOLS‐2006. The data analysis exploring the relationship between the two study groups (IDD and ASD) using the six measurement dimensions (Importance, Attainment, Satisfaction, Opportunities, Initiative, Stability) showed the mean ratings for all six measurement dimensions were higher for the IDD group than for the ASD group, although both groups rated Importance quite highly. Within the nine domains examined, there were some differences between the two groups. For the two main outcome measures, Attainment and Satisfaction, the scores for Satisfaction were consistently higher for the IDD group than for the ASD group. A combination of qualitative and quantitative data revealed that two of the nine domains, Family Relationships and Community Interaction, appear to contribute positively to family quality of life for both groups in this sample, while family life relating to the other seven domains requires remediation. Data from this family quality of life study provides evidence to suggest to policy makers and service providers that there might be a substantial amount of work to be done in the future to provide appropriate and efficient support for families with children with disabilities, especially for those with ASD, so that these families can lead lives of quality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".