Evidence map›Paper›PMID 38609510›Full record

ArticleNpj mental health research2022

A computational approach to measure the linguistic characteristics of psychotherapy timing, responsiveness, and consistency.

Adam S Miner, Scott L Fleming, Albert Haque, Jason A Fries, Tim Althoff, Denise E Wilfley, W Stewart Agras, Arnold Milstein, Jeff Hancock, Steven M Asch and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Npj mental health research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Beyond Detection: Towards Actionable Sensing Research in Clinical Mental Healthcare.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2024
    Article
  3. Article
  4. Article
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

13 authors.

Adam S Miner *Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA. aminer@stanford.edu.
Scott L Fleming *Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
Albert HaqueDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Jason A FriesCenter for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
Tim AlthoffAllen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA.
Denise E WilfleyDepartments of Psychiatry, Medicine, Pediatrics, and Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA.
W Stewart AgrasDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Arnold MilsteinClinical Excellence Research Center, Stanford University, Stanford, CA, USA.
Jeff HancockDepartment of Communication, Stanford University, Stanford, CA, USA.
Steven M AschVA Palo Alto Health Care System, Palo Alto, CA, USA.
Shannon Wiltsey StirmanDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Bruce A ArnowDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Nigam H ShahCenter for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Spectrum Stanford Center for clinical and Translational Research and EducationUL1TR001085 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$37.1M
Spectrum Stanford Center for clinical and Translational Research and EducationKL2TR001083 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$4.9M
Biomedical Data Science Graduate Training at StanfordT32LM012409 · NLM · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2016 to 2020
$1.5M
NCATS NIH HHS KL2 TR001083NCATS NIH HHS UL1 TR001085NCATS NIH HHS UL1 TR003142NLM NIH HHS T32 LM012409
6 · The paper itself

Abstract

Although individual psychotherapy is generally effective for a range of mental health conditions, little is known about the moment-to-moment language use of effective therapists. Increased access to computational power, coupled with a rise in computer-mediated communication (telehealth), makes feasible the large-scale analyses of language use during psychotherapy. Transparent methodological approaches are lacking, however. Here we present novel methods to increase the efficiency of efforts to examine language use in psychotherapy. We evaluate three important aspects of therapist language use - timing, responsiveness, and consistency - across five clinically relevant language domains: pronouns, time orientation, emotional polarity, therapist tactics, and paralinguistic style. We find therapist language is dynamic within sessions, responds to patient language, and relates to patient symptom diagnosis but not symptom severity. Our results demonstrate that analyzing therapist language at scale is feasible and may help answer longstanding questions about specific behaviors of effective therapists.

Identifiers

PMID38609510
PMCPMC10956022

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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.