Evidence map›Paper›PMID 34723404›Full record

ArticleClinical psychology & psychotherapy2021

Psychotherapists' acceptance of telepsychotherapy during the COVID-19 pandemic: A machine learning approach.

Vera Békés, Katie Aafjes-van Doorn, Sigal Zilcha-Mano, Tracy Prout, Leon Hoffman

Open access · bronzeAbstract read
In one paragraph

Article in Clinical psychology & psychotherapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
6.5field-weighted citation impact, top 3% of its field
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

18 citing papers in PubMed, 40 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Vera BékésFerkauf Graduate School of Psychology, Yeshiva University, New York, New York, USA.ORCID https://orcid.org/0000-0003-3043-5155
Katie Aafjes-van DoornFerkauf Graduate School of Psychology, Yeshiva University, New York, New York, USA.ORCID https://orcid.org/0000-0003-2584-5897
Sigal Zilcha-ManoDepartment of Psychology, University of Haifa, Haifa, Israel.ORCID https://orcid.org/0000-0002-5645-4429
Tracy ProutFerkauf Graduate School of Psychology, Yeshiva University, New York, New York, USA.ORCID https://orcid.org/0000-0002-3650-5890
Leon HoffmanNew York Psychoanalytic Institute, New York, New York, USA.ORCID https://orcid.org/0000-0001-7466-5513
Yeshiva University · USNew York Psychoanalytic Society and Institute · USUniversity of Haifa · IL

Funding

China American Psychoanalytic Alliance
6 · The paper itself

Abstract

objectiveThis study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID-19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future.

methodTherapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self-doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample.

resultsAttitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self-doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self-doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out-of-sample dataset.

conclusionsTherapists' professional self-doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID-19 and should be addressed in future training and research.

Indexed as

COVID-19TelemedicineAdultHumansMachine LearningPandemicsPsychotherapistsPsychotherapySARS-CoV-2COVID-19machine learningonline therapytelepsychotherapytherapistsUTAUT model

Identifiers

PMID34723404
PMCPMC8652775
OpenAlexW3209228312

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.