Evidence map›Paper›PMID 31681047›Full record

ArticleFrontiers in psychiatry2019

Key Considerations for Incorporating Conversational AI in Psychotherapy.

Adam S Miner, Nigam Shah, Kim D Bullock, Bruce A Arnow, Jeremy Bailenson, Jeff Hancock

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 7 pooled it
6.9field-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

42 citing papers in PubMed, 7 syntheses or guidelines pooled it, 131 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

6 authors at 1 institution in 1 country.

Adam S MinerDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States.
Nigam ShahStanford Center for Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA, United States.
Kim D BullockDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States.
Bruce A ArnowDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States.
Jeremy BailensonDepartment of Communication, Stanford University, Stanford, CA, United States.
Jeff HancockDepartment of Communication, Stanford University, Stanford, CA, United States.
Stanford University · US

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
Institutional Career Development Core (KL2)KL2TR003143 · NCATS · STANFORD UNIVERSITY · PI ASCH, STEVEN M. · 2019 to 2023
$8.7M
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
NCATS NIH HHS KL2 TR001083NCATS NIH HHS KL2 TR003143NCATS NIH HHS UL1 TR001085NCATS NIH HHS UL1 TR003142
6 · The paper itself

Abstract

Conversational artificial intelligence (AI) is changing the way mental health care is delivered. By gathering diagnostic information, facilitating treatment, and reviewing clinician behavior, conversational AI is poised to impact traditional approaches to delivering psychotherapy. While this transition is not disconnected from existing professional services, specific formulations of clinician-AI collaboration and migration paths between forms remain vague. In this viewpoint, we introduce four approaches to AI-human integration in mental health service delivery. To inform future research and policy, these four approaches are addressed through four dimensions of impact: access to care, quality, clinician-patient relationship, and patient self-disclosure and sharing. Although many research questions are yet to be investigated, we view safety, trust, and oversight as crucial first steps. If conversational AI isn't safe it should not be used, and if it isn't trusted, it won't be. In order to assess safety, trust, interfaces, procedures, and system level workflows, oversight and collaboration is needed between AI systems, patients, clinicians, and administrators.

Indexed as

artificial intelligencechatbotconversational AIdigital assistantexpert systemshuman–computer interactionnatural language processingpsychotherapy

Identifiers

PMID31681047
PMCPMC6813224
OpenAlexW2980364910

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.