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Record W2469025273 · doi:10.1177/1049731516656803

Implementation and Evaluation of the Skills Training in Affective and Interpersonal Regulation (STAIR) in a Community Setting in the Context of Childhood Sexual Abuse

2016· article· en· W2469025273 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch on Social Work Practice · 2016
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsCanadian Rheumatology AssociationMcGill University
Fundersnot available
KeywordsSexual abuseClinical psychologyPsychologyContext (archaeology)Interpersonal communicationIntervention (counseling)Social skillsInterpersonal relationshipPsychiatryPoison controlSuicide preventionMedicine

Abstract

fetched live from OpenAlex

Purpose: The objective of this article is to describe the implementation of the Skills Training in Affective and Interpersonal Regulation (STAIR), a manualized, evidence-based cognitive behavioral group treatment for childhood trauma at Cedar Centre, a community-based trauma treatment center, and describe the preliminary evaluation of the effectiveness of the treatment. Method: Pre- and postmeasurements of emotion regulation, interpersonal problems, and traumatic stress symptoms using psychometrically validated instruments were collected. Outcomes were assessed for 85 individuals who experienced childhood sexual abuse and participated in the first cycles of intervention at the center. Results: Results indicated significant reductions in difficulties in emotion regulation, interpersonal problems, and trauma symptoms among participants from pretreatment to posttreatment. Discussion: Overall, there was a positive response to the adoption and integration of the STAIR intervention into the program. Qualitative assessment identified the benefits perceived by both facilitators and group participants.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.141
GPT teacher head0.503
Teacher spread0.363 · 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