Livelihood support for caregivers of children with developmental disabilities: findings from a scoping review and stakeholder survey
Bibliographic record
Abstract
PURPOSE: Poverty amongst families with a child with disability adversely impacts child and family quality of life. We aimed to identify existing approaches to livelihood support for caregivers of children with developmental disabilities in low- and middle-income countries. METHODS: This mixed-method study incorporated a scoping literature review and online stakeholder survey. We utilised the World Health Organization community-based rehabilitation (CBR) matrix as a guiding framework for knowledge synthesis and descriptively analysed the included articles and survey responses. RESULTS: We included 11 peer-reviewed publications, 6 grey literature articles, and 49 survey responses from stakeholders working in 22 countries. Identified programmes reported direct and indirect strategies for livelihood support targeting multiple elements of the CBR matrix; particularly skills development, access to social protection measures, and self-employment; frequently in collaboration with specialist partners, and as one component of a wider intervention. Self-help groups were also common. No publications examined effectiveness of livelihood support approaches in mitigating poverty, with most describing observational studies at small scale. CONCLUSION: Whilst stakeholders describe a variety of direct and indirect approaches to livelihood support for caregivers of children with disabilities, there is a lack of published literature on content, process, and impact to inform future programme development and delivery.
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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 | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".