The Lived Experiences of Mothers Raising Children with Autism Spectrum Disorder in Ethiopia
Bibliographic record
Abstract
Autism Spectrum Disorder (ASD) is a complex neurological condition characterized by impairments in social interaction, communication, and behavior. In Ethiopia, mothers of children with autism face unique responsibilities and challenges in caring for their affected children compared to other family members. This study delves into the lived experiences of these mothers, focusing on their reactions upon detecting autism in their children, the primary challenges they encounter in nurturing and caring for their children with ASD, the support they receive from the community and schools, and their feelings regarding the future career prospects of their children with autism. To conduct this investigation, a qualitative research approach, specifically employing a phenomenological research design, was utilized. Data collection was facilitated through semi-structured interviews, and the study targeted six regular schools and one autism center. A purposive selection process identified fifteen mothers of children with ASD as key informants. The subsequent data analysis centered on thematic areas outlined in the interview guides, which served as leading questions. Additionally, two cohesive case stories were developed as integral components of the study. The findings revealed that a majority of the respondent mothers/guardians felt overwhelmed by the demands of caring for their children with autism. They also highlighted the negative attitudes of others and the lack of specialized services, compounded by a shortage of trained personnel, which significantly exacerbated their challenges and complicated their caregiving responsibilities. In light of the study's outcomes, it is recommended that the concerned federal ministries become actively involved in promoting and coordinating interventions to support mothers/guardians and their children with autism. This involvement is crucial to ensure that appropriate services and assistance are readily available to address the needs of these individuals.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 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".