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Record W4210429724 · doi:10.1037/ccp0000714

The temporal relationships between therapist adherence and patient outcomes in dialectical behavior therapy.

2022· article· en· W4210429724 on OpenAlexaff
Melanie S. Harned, Robert Gallop, Sara C. Schmidt, Kathryn E. Korslund

Bibliographic record

VenueJournal of Consulting and Clinical Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsToronto Metropolitan University
FundersNational Institute on Drug AbuseNational Institute of Mental HealthNational Institute for Health and Care Research
KeywordsPsycINFODialectical behavior therapyPsychologyClinical psychologyPopulationPsychotherapistMEDLINEMedicinePsychiatryBorderline personality disorder

Abstract

fetched live from OpenAlex

OBJECTIVE: Although Dialectical Behavior Therapy (DBT) is a well-established evidence-based psychotherapy, little is known about the role of therapist adherence in promoting positive outcomes. This study evaluated the temporal relationships between therapist adherence to DBT and patient outcomes, as well as potential moderators of these relationships. METHOD: Data were from six clinical trials conducted in research and community settings with a variety of patient populations. In these trials, trained observers rated 83 therapists for adherence during 1,262 DBT individual therapy sessions with 288 patients. Patient outcomes included suicide attempts, nonsuicidal self-injury (NSSI), treatment dropout, psychiatric hospitalizations, and global functioning. Longitudinal mixed-effects models evaluated the time-ordered, bidirectional relationships between adherence and outcomes. RESULTS: = .01, η = 0.26) predicted higher subsequent therapist adherence, and the latter relationship was moderated by patient population. CONCLUSIONS: Therapist adherence improves several key patient outcomes and retention, highlighting the importance of delivering DBT with adherence to the manual. Therapists may find it easier to deliver DBT adherently to more severely impaired patients. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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 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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.204
GPT teacher head0.478
Teacher spread0.274 · 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 teacher head, 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

Citations14
Published2022
Admission routes1
Has abstractyes

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