“Realizing the problem wasn’t necessarily me”: the meaning of childhood adversity and resilience in the lives of autistic adults
Bibliographic record
Abstract
Purpose There is evidence that childhood adversity is correlated with poor health outcomes across the lifespan. Resilience results when internal and external protective factors in childhood mitigate this relationship. However, among children on the autism spectrum, these relationships are understudied, and little is known about the characteristics and role of adversity and resilience in their in their lives. This study interprets these phenomena as experienced by autistic young adults.Methods Initially, we conducted community engagement with five members of the autism community who advised on the research question, research design, and analysis. Subsequently, four autistic young adults, three women and one non-binary, aged 19–27, were recruited to participate in semi-structured interviews via phone, video conference, and online chat. Credibility checking interviews followed data analysis.Results Through interpretative phenomenological analysis we identified themes related to the negative effects of adversity, including social disconnection, mental and emotional well-being, sense of self, and development into young adulthood. Resilience developed in places of refuge and identity and was evident in their transitions into young adulthood.Conclusion These findings provide direction for decreasing adversity and fostering resilience in children and adolescents on the autism spectrum.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".