Mental Health Outcomes Among Caregivers of Children with Intellectual Disabilities: A Quantitative Study
Bibliographic record
Abstract
The relationship between parental mental health outcomes, including anxiety, depression, and stress regarding caregivers of children with intellectual disabilities, exists in abundance in academic literature. However, Pakistan faces limited research on this topic precisely when it comes to mental health outcomes, i.e., depression, anxiety, and stress among caregivers of children with intellectual disabilities. Therefore, the objective of this study is to overcome this gap. The research intends to address the current literature gap of knowledge through effects-based policy recommendations and support upcoming academic studies. Caregivers of at least one child with intellectual disabilities below eighteen years old participated in this research through purposive sampling within a cross-sectional correlational design. The correlational analysis depicts a significant association between stress, anxiety, and depression among caregivers of children with intellectual disabilities. Hayes Process 4.1, Model 4 confirmed the positive and significant mediating role of anxiety between stress and depression. The research findings were discussed with relevant literature while proposing social welfare measures through counseling, peer networks, mental health assistance programs combined with educational guidance for children, and advocacy for government-operated intellectual disabilities education facilities. The government needs to establish effective policies that enable ongoing caregiver counseling support together with effective intellectual disability treatment solutions for children.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".