Factors Influencing Resilience in Siblings of Children With Disabilities: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Siblings, who have the longest relationship with individuals with disabilities, may experience both negative and positive impacts. While some siblings face emotional challenges, others exhibit personal growth. The concept of resilience offers insight into these differing responses. OBJECTIVE: This study aims to analyze factors influencing the resilience of siblings of children with disabilities. METHODS: A cross-sectional study was conducted with 118 sibling-parent pairs from 7 special schools in Padang, Indonesia, using random sampling. Siblings completed 3 questionnaires: the Child and Youth Resilience Measure-Revised, a modified version of the Multidimensional Measure of Religiousness/Spirituality, and the Multidimensional Scale of Perceived Social Support. Parents completed a demographic form and the Parenting Style and Dimensions Questionnaire. Data were analyzed using chi-square tests, Mann-Whitney tests, and logistic regression with model diagnostics. RESULTS: Resilience was significantly associated with parenting style (P=.009), social support (P=.005), and spirituality (P=.001). In multivariate analysis, spirituality was the most influential predictor of high resilience (odds ratio [OR]=.39, 95% CI 0.17-0.94), followed by social support (OR=.31, 95% CI 0.12-0.83), and parenting style (OR=.09, 95% CI 0.01-0.83). The logistic regression model had a good fit (Hosmer-Lemeshow p=0.821) and explained 39.2% of the variance in sibling resilience (Nagelkerke R²=0.392). CONCLUSIONS: Spirituality played a key role in promoting resilience among siblings of children with disabilities. Nursing interventions should consider culturally grounded approaches that enhance spiritual, emotional, and family support systems to build resilience in this population.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".