Autonomic dysregulation and self‐injurious thoughts and behaviours in children and young people: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background Self‐injurious thoughts and behaviours (SITBs) have been associated with dysfunction of the Autonomic Nervous System (ANS) in children and young people, suggesting that objective ANS measures may aid assessment of suicide risk, but a systematic synthesis of this literature is currently lacking. Methods Following a pre‐registered protocol (PROSPERO CRD42022327605), we conducted a systematic search of PubMed, Medline, Embase, PsycINFO, and Web of Science, for empirical studies published until 10th May 2022 that compared indices of ANS functioning in individuals aged 0–25 years with versus without SITBs, or reported continuous associations between ANS measures and SITBs. Study quality was assessed with the Newcastle‐Ottawa Scales. Pooled effect sizes (Hedge's g) were estimated with random‐effects meta‐analytic models. Results Twenty studies (1979 participants) were included in our systematic review, with 16 included in meta‐analyses. Results suggested that SITBs were associated with altered cardiac indices of arousal ( g = −0.328, p < 0.001), which was driven by lower heart rate variability in individuals with SITBs ( g = −0.375, p = 0.025). Overall results for electrodermal activity were not significant ( g = 0.026, p = 0.857), but subgroup analyses showed increased activity in studies of individuals who engaged specifically in non‐suicidal self‐harm ( g = 0.249, p = 0.014) but decreased activity in the remaining studies ( g = −0.567, p = 0.004). Conclusions Our systematic review and meta‐analysis found evidence of reduced parasympathetic regulation as well as more tentative evidence of altered electrodermal activity in children and young people displaying SITBs. Future longitudinal studies should test the clinical utility of these markers for detecting and monitoring suicide risk.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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 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".