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Record W2990385050 · doi:10.1002/jclp.22902

Physiological and behavioral effects of interpersonal validation: A multilevel approach to examining a core intervention strategy among self‐injuring adolescents and their mothers

2019· article· en· W2990385050 on OpenAlexaff
Erin A. Kaufman, Megan Puzia, Donald A. Godfrey, Sheila E. Crowell

Bibliographic record

VenueJournal of Clinical Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsWestern University
FundersAmerican Psychological Foundation
KeywordsPsychologyMultilevel modelIntervention (counseling)Interpersonal communicationCore (optical fiber)Clinical psychologyValidation testInterpersonal relationshipDevelopmental psychologyPsychotherapistPsychometricsSocial psychologyTest validityPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: The current study examined how teaching an interpersonal validation-oriented skill from dialectical behavior therapy affects behavioral and biological indices of self-inflicted injury (SII) risk among self-injuring adolescents and their mothers (n = 30 dyads), and typical control mother-daughter dyads (n = 30). METHOD: Behavioral indicators of family functioning (e.g., cohesion, coercion, and invalidation) and a physiological index of emotion dysregulation (respiratory sinus arrhythmia [RSA]) were examined across two conflict tasks (pre- and postskills training). RESULTS: Dyads' subjective affect and observed behavior generally improved when practicing validation. Findings indicate mother-, daughter-, and dyad-level behavior accounted for significant variance in RSA reactivity. CONCLUSIONS: Results demonstrate that teaching a single skill on one occasion can have detectable effects on biosocial functioning, with important implications for the etiology and treatment of SII.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.167
GPT teacher head0.443
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations45
Published2019
Admission routes1
Has abstractyes

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