A proof-of-concept study of vicarious extinction learning and autonomic synchrony in parent–child dyads and posttraumatic stress disorder
Bibliographic record
Abstract
Though threat-extinction models continue to inform scientific study of traumatic stress, knowledge of learning and extinction as mechanisms linking exposure to psychopathology remains critically limited among youth. This proof-of-concept study advances the study of threat-extinction in youth by determining feasibility of electrodermal stimulation (EDS), vicarious extinction learning via their parent, and social threat learning in pediatric PTSD (pPTSD). Typically developing (TD) and PTSD-diagnosed youth in 45 mother-child dyads completed an extinction learning paradigm. The use of EDS was first investigated in a cohort of TD youth (n = 20) using a 2-day paradigm without vicarious extinction, while direct (for TD and pPTSD) and vicarious (for pPTSD) extinction were investigated in a 3-day paradigm (n = 25). Threat acquisition and extinction were monitored using skin-conductance response (SCR) and behavioral expectations of EDS. Using Bayesian modeling to accommodate this pilot sample, our results demonstrate: (1) EDS-conditioning to be highly feasible and well-tolerated across TD and trauma-exposed youth, (2) Successful direct and vicarious extinction learning in trauma-exposed youth, and (3) PTSD-associated patterns in extinction learning and physiological synchrony between parent-child dyads. In summary, these novel approaches have the potential to advance translational studies in the mechanistic understanding of parent-child transmission of risk and youth psychopathology.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".