Bibliographic record
Abstract
PURPOSE: Autism spectrum disorders are the most common developmental disorders, affecting 1 in 165 Canadian children. Although the experiences of the caregivers of children with autism have been examined to some extent, a thorough investigation of the benefits of this experience is warranted. METHODS: The lived experiences of 8 married female primary caregivers of children with autism were assessed through a phenomenological study involving background questionnaires and one-on-one, semistructured interviews. All recruited participants completed the study. RESULTS: Benefits were found in all areas of questioning, including financial, social, familial, health, and employment implications, in addition to benefits arising from activities and involvements taken on as a result of raising a child with autism. The findings shed light on an unconventional aspect of the effects of raising a child with autism. CONCLUSIONS: Costs to these women's experiences were not predominant, and benefits arising from the caregiving role lead to positive accounts of their lived experiences. Results have broader implications for the understanding of the primary caregiver situation and the improvement of interactions with individuals with these lived experiences. In this way, clinical nurse specialists may encourage and contribute to support systems that foster a positive experience for caregivers of children with autism spectrum disorder, the children they care for, and their families.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.203 | 0.027 |
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".