Exploring the Unmet Needs of Primary Caregivers of Autistic Children and Its Implications for Social Work Practice in Ghana
Bibliographic record
Abstract
Caring for an autistic child is fraught with various difficulties and may present unmet needs that could affect the overall well‐being of caregivers and children themselves. Consequently, gaining insight into the unmet needs of these caregivers is imperative for the development of targeted and effective interventions to enhance their quality of life and improve their ability to care for their children. Using a descriptive qualitative research design, this study engaged 10 primary caregivers of autistic children in Ghana to understand their unmet needs. Data were collected through in‐depth interviews and thematically analyzed. The analysis revealed the urgent need for financial support for primary caregivers, the availability of more special schools, and the services of trained professionals in the field of autism. Caregivers also called for the intensification of public education to help reorient the perspectives of the general population on the autism condition. Based on the findings, some recommendations for policy and practice were made. The implications of the findings for social work are also discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".