Temporal Changes in Effect Sizes of Studies Comparing Individuals With and Without Autism
Bibliographic record
Abstract
Importance: The definition and nature of autism have been highly debated, as exemplified by several revisions of the DSM (DSM-III, DSM-IIIR, DSM-IV, and DSM-5) criteria. There has recently been a move from a categorical view toward a spectrum-based view. These changes have been accompanied by a steady increase in the prevalence of the condition. Changes in the definition of autism that may increase heterogeneity could affect the results of autism research; specifically, a broadening of the population with autism could result in decreasing effect sizes of group comparison studies. Objective: To examine the correlation between publication year and effect size of autism-control group comparisons across several domains of published autism neurocognitive research. Data Sources: This meta-analysis investigated 11 meta-analyses obtained through a systematic search of PubMed for meta-analyses published from January 1, 1966, through January 27, 2019, using the search string autism AND (meta-analysis OR meta-analytic). The last search was conducted on January 27, 2019. Study Selection: Meta-analyses were included if they tested the significance of group differences between individuals with autism and control individuals on a neurocognitive construct. Meta-analyses were only included if the tested group difference was significant and included data with a span of at least 15 years. Data Extraction and Synthesis: Data were extracted and analyzed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline using fixed-effects models. Main Outcomes and Measures: Estimated slope of the correlation between publication year and effect size, controlling for differences in methods, sample size, and study quality. Results: The 11 meta-analyses included data from a total of 27 723 individuals. Demographic data such as sex and age were not available for the entire data set. Seven different psychological and neurologic constructs were analyzed based on data from these meta-analyses. Downward temporal trends for effect size were found for all constructs (slopes: -0.067 to -0.003), with the trend being significant in 5 of 7 cases: emotion recognition (slope: -0.028 [95% CI, -0.048 to -0.007]), theory of mind (-0.045 [95% CI, -0.066 to -0.024]), planning (-0.067 [95% CI, -0.125 to -0.009]), P3b amplitude (-0.048 [95% CI, -0.093 to -0.004]), and brain size (-0.047 [95% CI, -0.077 to -0.016]). In contrast, 3 analogous constructs in schizophrenia, a condition that is also heterogeneous but with no reported increase in prevalence, did not show a similar trend. Conclusions and Relevance: The findings suggest that differences between individuals with autism and those without the diagnosis have decreased over time and that possible changes in the definition of autism from a narrowly defined and homogenous population toward an inclusive and heterogeneous population may reduce our capacity to build mechanistic models of the condition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.202 | 0.460 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.032 |
| Bibliometrics | 0.009 | 0.015 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".