Relationships Between Self-Injurious Behaviors, Pain Reactivity, and β-Endorphin in Children and Adolescents With Autism
Bibliographic record
Abstract
OBJECTIVE: Autism and certain associated behaviors including self-injurious behaviors (SIB) and atypical pain reactivity have been hypothesized to result from excessive opioid activity. The objective of this study was to examine the relationships between SIB, pain reactivity, and β-endorphin levels in autism. METHODS: Study participants were recruited between 2007 and 2012 from day care centers and included 74 children and adolescents diagnosed with autism (according to DSM-IV-TR, ICD-10, and CFTMEA) and intellectual disability. Behavioral pain reactivity and SIB were assessed in 3 observational situations (parents at home, 2 caregivers at day care center, a nurse and child psychiatrist during blood drawing) using validated quantitative and qualitative scales. Plasma β-endorphin concentrations were measured in 57 participants using 2 different immunoassay methods. RESULTS: A high proportion of individuals with autism displayed SIB (50.0% and 70.3% according to parental and caregiver observation, respectively). The most frequent types of SIB were head banging and hand biting. An absence or decrease of overall behavioral pain reactivity was observed in 68.6% and 34.2% of individuals with autism according to parental and caregiver observation, respectively. Those individuals with hyporeactivity to daily life accidental painful stimuli displayed higher rates of self-biting (P < .01, parental evaluation). No significant correlations were observed between β-endorphin level and SIB or pain reactivity assessed in any of the 3 observational situations. CONCLUSIONS: The absence of any observed relationships between β-endorphin level and SIB or pain reactivity and the conflicting results of prior opioid studies in autism tend to undermine support for the opioid theory of autism. New perspectives are discussed regarding the relationships found in this study between SIB and hyporeactivity to pain.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".