Social capital of families of children with neurodevelopmental disabilities in South India
Bibliographic record
Abstract
Abstract Aim To investigate the social capital of families with children with neurodevelopmental disabilities in South India receiving a community‐based early intervention (Enabling Inclusion®) program and to explore determinants and associations between social capital and program duration, socio‐demographic factors, family empowerment, and caregiver burden. Method Using purposive sampling in a cross‐sectional study design, 217 families (n = 71 received short Enabling Inclusion [<5 months]; n = 146 received long Enabling Inclusion [>9 months]) were recruited and completed the Short Adapted Social Capital Tool (SASCAT: cognitive, structural), measures of family empowerment, and caregiver strain. Descriptive statistics, regression, and correlations were used for analyses. Results In 52.1% of participants, low cognitive and structural social capital was observed. Higher odds of low structural social capital were observed for mothers with primary versus secondary education (adjusted odds ratio [OR] = 0.35; 95% confidence interval [CI] 0.13–0.90; p = 0.029); and caregivers of children with cerebral palsy versus autism (OR = 4.66; 95% CI 1.02–21.21; p = 0.046). Significant associations were found between structural social capital, the child's age, and support group membership (χ2 = 6.29; 4.70; degrees of freedom [df] = 2; 1; p = 0.04; p = 0.02 respectively), as well as between cognitive social capital and other disability in the family (χ2 = 4.62, df = 1, p = 0.03). Interpretation While program duration was not found to mediate social capital, mother's education and child's diagnosis emerged as key influential factors, warranting their consideration in interventions supporting families of children with neurodevelopmental disabilities in low‐ and‐middle‐income countries and elsewhere.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".