Is language ability associated with behaviors of concern in autism? A systematic review
Bibliographic record
Abstract
This review systematically synthesized evidence on the association between structural language ability and behaviors of concern (BoC) in autism. Four databases were searched for studies that included >10 autistic participants, measures of structural language (content and/or form of language) and BoC, and an analysis of their association. BoCs included self-injurious behavior (SIB), aggression, tantrums, and externalizing behavior. Methodological quality of studies were assessed using the Newcastle Ottawa Scale. Forty-five publications (n = 11,961) were included. Forty studies were cross-sectional and five were prospective cohort studies. Over 70% of the studies investigating expressive language and SIB (n = 10), aggression (n = 5), tantrums (n = 3), and externalizing behavior (n = 17) reported an inverse association, where lower expressive language ability was associated with increased BoC. Eleven out of sixteen studies of combined expressive and receptive language reported an inverse relationship with SIB or aggression. All outcomes were rated as moderate to very low certainty of evidence. This review highlights evidence showing an inverse association between expressive or combined language ability and SIB, and externalizing behavior in autism. However, further high-quality studies that use standardized, consistent measures of language and behavior and investigate longitudinal associations are needed. Early detection and support for reduced structural language difficulties have substantial potential to assist in reducing BoC.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".