What does receiving autism diagnosis in adulthood look like? Stakeholders’ experiences and inputs
Bibliographic record
Abstract
INTRODUCTION: The age of diagnosis is crucial for optimal health outcomes; however, some individuals with Autism Spectrum Disorder (ASD) may not be diagnosed until adulthood. Limited information is available about the lived experience of receiving a diagnosis during adulthood. Thus, we aimed to investigate stakeholders' experiences about the ASD diagnosis during adulthood. METHOD: We interviewed 18 individuals including 13 adults with ASD who had received a late diagnosis during adulthood and 5 parents of individuals with ASD from various Canadian provinces. RESULTS: Using a thematic analysis, three main themes emerged: (a) noticing differences and similarities, (b) hindering elements to diagnosis, and (c) emotional response to diagnostic odyssey. CONCLUSION: This study adds to the literature about experiences of receiving ASD diagnosis in adulthood. Given the impact of diagnosis on individuals, it is important to minimize the barriers to ensure individuals who require ASD-related supports can access them in a timely and effective manner. This study highlights the importance of receiving an ASD diagnosis and facilitates positive health outcomes. The findings from the current study can be used to guide adult diagnostic processes and practices to help make ASD diagnosis more accessible.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".