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Record W4407740829 · doi:10.1080/20473869.2025.2464314

Challenges and supporting strategies of Nepali parents of children with autism spectrum conditions

2025· article· en· W4407740829 on OpenAlexaff
Mukti Thapaliya

Bibliographic record

VenueInternational Journal of Developmental Disabilities · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsNepaliAutismPsychologyDevelopmental psychologyAutism spectrum disorder

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.039
GPT teacher head0.369
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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