A Meta-analysis of Outcome Studies of Autistic Adults: Quantifying Effect Size, Quality, and Meta-regression.
David Mason, Simone J Capp, Gavin R Stewart and 4 others
PMID 33200352WHAT IT FOUND
About half of autistic adults have poor outcomes in employment, independence, and relationships.
Higher adult IQ predicted fewer poor outcomes, but did not significantly predict good or fair outcomes. Samples were often unrepresentative, and outcome definitions varied widely.
Key findings
01The pooled estimate for the percentage of participants with a good outcome was 20.0%, for fair outcome 26.6%, and for poor outcome 49.3%.
02IQ in adulthood significantly predicted the proportion of individuals rated as having a poor outcome, but neither IQ in childhood or adulthood significantly predicted proportions of good and fair outcomes when adjusting for multiple comparisons.
03The main finding from the methodological assessment was that participants included in these outcome studies are unlikely to be representative of the autism population as a whole.
STILL TO COME
How it was doneWhat they foundWhat it means for PTsWhat it means for OTsWhat it means for SLPs
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What it does not show
The studies included had very high heterogeneity, meaning the results are difficult to generalise to all autistic adults. Most samples were drawn from clinical or therapeutic settings and were unlikely to represent the wider autism population. Attrition bias was present, as participants lost to follow-up tended to have lower IQs, potentially skewing results toward more able participants. The definition of 'outcome' was restricted to employment, independent living, and relationships, ignoring subjective well-being or personal goals. Data on key predictors like language and autism severity were insufficient for analysis.
Declared interests
The study was funded by the Medical Research Council and King's College London.
The easy way to misread this
Do not interpret the lack of significant prediction for 'good' outcomes by IQ as evidence that IQ is irrelevant. The authors state the models may have lacked statistical power due to the small number of studies, and the high heterogeneity means these pooled percentages should not be applied to individual patient prognoses.