Attachment in autistic children as measured with the strange situation procedure: a systematic review and a meta-analysis
Bibliographic record
Abstract
Since the inception of attachment theory, parent-child relationships has been examined in different populations, including autistic children. Attachment in autistic children has been measured using inconsistent separation-reunion procedures, making it difficult to examine whether autistic children are more or less likely to develop a secure attachment compared to non-autistic children. This study aims to meta-analyze data from studies that have assessed attachment in autistic children using a standardized version of the Strange Situation Procedure. Using the CASCADE catalogue, we identified six studies (n = 202). Results revealed that 45.6% were classified as secure, 18.7% as avoidant, 8.5% as resistant, and 27.2% as disorganized, which was statistically similar to the proportions of attachment categories in general population. Moderator analyses revealed a higher proportion of secure attachment among older children and more recently published studies. Future research should focus on unifying methodological approaches to studying attachment in autistic children.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".