Parental Perspective on the Challenges and Coping Mechanisms in Raising a Child with Autism
Bibliographic record
Abstract
This qualitative study delves into the lived experiences and challenges faced by parents raising children with Autism Spectrum Disorder (ASD) in Davao City, Philippines. It examines parents' coping mechanisms to navigate these challenges, showcasing their resilience. Drawing on Bronfenbrenner's Ecological Systems Theory and Goffman's Labeling Theory, the study seeks to understand the contextual influences on parents' experiences. The participants include five parents, primarily mothers aged between 30 to 40, from diverse socioeconomic backgrounds. The study employed opportunistic and purposive sampling techniques to recruit participants. Thematic analysis was used to analyze the collected data with informed consent. The emerging issues include navigating understanding and awareness, accessing support and resources, and emotional and practical adjustment. Parents utilized coping mechanisms such as education, advocacy, and building support networks. The findings highlight parents' significant challenges due to societal stigma and educational limitations. However, the study also identifies positive outcomes, such as fostering supportive environments through open communication and strong support networks. This collaborative approach involving parents, professionals, and families is crucial for enhancing the well-being of both parents and children with Autism.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| 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".