Experiences of caregivers of children with severe self‐injurious behavior: An interpretive, descriptive study
Bibliographic record
Abstract
AIM: To describe the experiences of children with self-injurious behavior (SIB) through the lens of family caregivers to inform the development of relevant interventions. METHOD: SIB in children with autism spectrum disorder is challenging to understand and manage. Furthermore, our understanding of the impact of SIB on families is limited. We performed an exploratory qualitative study using interpretive description methodology. Semi-structured one-on-one interviews were conducted as the primary data collection technique. A purposive convenience sampling technique was used for the recruitment of participants through several clinics at one institution. Enrollment continued until 12 participants were recruited, at which time consensus was reached by the study team that sufficient data had been obtained to develop a depth of understanding of key elements of the caregiver perspective. Data were then analysed using a thematic analysis approach to develop overarching themes. RESULTS: Three main themes were developed from the analysis of the data: the pervasive impact of SIB; lack of resources to turn toward; and the presence of silver linings. Participants described in some detail the many elements of their children's condition that led to a pervasive impact far beyond the child themselves. This experience was augmented by stigma and the lack of available resources. Despite these challenges, there was a strong sense of resilience and hope. INTERPRETATION: Our study provides insights into the patterns of experiences of family caregivers of children with SIB. These results have far-reaching implications ranging from the clinical need for enhanced care and collaboration with affected families, the call for researchers to further develop effective treatments, and lastly highlighting the need to work with policymakers to advocate for resources to support children with SIB 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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".