Challenges and supporting strategies of Nepali parents of children with autism spectrum conditions
Bibliographic record
Abstract
Recognizing parents’ understanding helps to develop interventions, educational programs, and community support systems for students with autism spectrum disorder (ASD). This study explored Nepali parents’ perspectives on supporting and educating their children with ASD. A qualitative phenomenological design was employed to capture in-depth lived experiences of parents of children with ASD, focusing on their approaches to supporting, caring for, and raising their children. A representative sample of five parents was purposely selected to participate in this study. Their experiences in supporting and educating their children with ASD were explored through semi-structured interviews. Data were analysed using the recursive process of thematic analysis. The data elicited two prominent themes: (i) challenges in supporting children with ASD and (ii) supporting and coping strategies for managing these challenges. Parents identified several barriers, including social, physical, and psychological challenges; financial constraints; and a lack of resources. Despite these obstacles, effective coping mechanisms emerged, such as family support, respite care, professional assistance, adaptive parenting strategies, and acceptance. The results underscore the importance of parental awareness programmes to foster positive acceptance of children with ASD. Additionally, the study highlights the need for the Nepali government to provide adequate, need-based funding and resources to support children with ASD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".