Evidence map›Paper›PMID 39913486›Full record

ArticleJournal of consulting and clinical psychology2025

Association of machine-learning-rated supportive counseling skills with psychotherapy outcome.

Xinyao Zhang, Simon B Goldberg, Scott A Baldwin, Michael J Tanana, Lauren M Weitzman, Shrikanth S Narayanan, David C Atkins, Zac E Imel

Abstract read
In one paragraph

Article in Journal of consulting and clinical psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xinyao ZhangDepartment of Educational Psychology, University of Utah.ORCID 0000-0001-6227-3205
Simon B GoldbergDepartment of Counseling Psychology, University of Wisconsin-Madison.
Scott A BaldwinDepartment of Psychology, Brigham Young University.
Michael J TananaLyssn.io.
Lauren M WeitzmanDepartment of Educational Psychology, University of Utah.
Shrikanth S NarayananMing Hsieh Department of Electrical and Computer Engineering, University of Southern California.
David C AtkinsLyssn.io.
Zac E ImelDepartment of Educational Psychology, University of Utah.

Funding

Implementation of Technology-Based Evaluation of Motivational InterviewingR01AA018673 · NIAAA · UNIVERSITY OF WASHINGTON · PI ATKINS, DAVID CHARLES, NARAYANAN, SHRIKANTH · 2010 to 2020
$5.9M
Mindfulness training delivered via mobile health to reduce depression and anxietyK23AT010879 · NCCIH · UNIVERSITY OF WISCONSIN-MADISON · PI GOLDBERG, SIMON B · 2020 to 2024
$786k
NCCIH NIH HHS K23 AT010879NIAAA NIH HHS R01 AA018673NIH HHS
6 · The paper itself

Abstract

objectiveThis study applied a machine-learning-based skill assessment system to investigate the association between supportive counseling skills (empathy, open questions, and reflections) and treatment outcomes. We hypothesized that higher empathy and higher use of open questions and reflections would be associated with greater symptom reduction.

methodWe used a data set with 2,974 sessions, 610 clients, and 48 therapists collected from a university counseling center, which included 845,953 rated therapist statements. Client outcome was routinely monitored by the Counseling Center Assessment of Psychological Symptoms Instruments. Therapists' skills were measured via computer by a bidirectional-long-short-term-memory-based system that rated use of supportive counseling skills. We used multilevel modeling to separate the between-therapist and the within-therapist associations of the skills and outcome.

resultsUse of open questions and reflections was associated with client symptom reduction between therapists but not within therapists. We did not find significant associations between therapist empathy and client symptom reduction but found that empathy was negatively associated with clients' baseline symptom level within therapists.

conclusionsTherapist exploration of clients' experience and expression of understanding may be important skills that are associated with clients' better outcomes. This study highlights the importance of support counseling skills, as well as the potential of machine-learning-based measures in psychotherapy research. We discuss the limitations of the study, including the limitations related to the speaker recognition system and potential reasons for the lack of association between empathy and client outcome. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Indexed as

Clinical CompetenceCounselingEmpathyMachine LearningProfessional-Patient RelationsPsychotherapyAdultFemaleHumansMaleMiddle AgedTreatment OutcomeYoung Adult

Identifiers

PMID39913486
PMCPMC11804870

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.