Evidence map›Paper›PMID 31628789›Full record

ReviewJMIR mental health2019

Conversational Agents in the Treatment of Mental Health Problems: Mixed-Method Systematic Review.

Hannah Gaffney, Warren Mansell, Sara Tai

Registry-linked trialAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in JMIR mental health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04859647 (Client-led Online Therapy for People Diagnosed With Bipolar Disorder), which is not on this map. Cited by 116 papers, 21 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
116citing papers in PubMed, 21 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.

NCT04859647 nacompletednot on this mapstarted 2021, after this paper: background citation

Client-led Online Therapy for People Diagnosed With Bipolar Disorder

TypeinterventionalSponsorUniversity of ManchesterRan2021 to 2022Enrolled10ConditionsBipolar Spectrum DisorderArmsMethod of Levels Therapy
3 · Its place in the literature

Who cites it

116 citing papers in PubMed, 21 syntheses or guidelines pooled it.

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  13. Effectiveness and Acceptability of Conversational Agents for Smoking Cessation: A Systematic Review and Meta-analysis.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023
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56 more citing papers are in PubMed but not listed here.

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

3 authors.

Hannah GaffneyDivision of Psychology & Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-9561-2488
Warren MansellDivision of Psychology & Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-5697-1784
Sara TaiDivision of Psychology & Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-8316-5796

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe use of conversational agent interventions (including chatbots and robots) in mental health is growing at a fast pace. Recent existing reviews have focused exclusively on a subset of embodied conversational agent interventions despite other modalities aiming to achieve the common goal of improved mental health.

objectiveThis study aimed to review the use of conversational agent interventions in the treatment of mental health problems.

methodsWe performed a systematic search using relevant databases (MEDLINE, EMBASE, PsycINFO, Web of Science, and Cochrane library). Studies that reported on an autonomous conversational agent that simulated conversation and reported on a mental health outcome were included.

resultsA total of 13 studies were included in the review. Among them, 4 full-scale randomized controlled trials (RCTs) were included. The rest were feasibility, pilot RCTs and quasi-experimental studies. Interventions were diverse in design and targeted a range of mental health problems using a wide variety of therapeutic orientations. All included studies reported reductions in psychological distress postintervention. Furthermore, 5 controlled studies demonstrated significant reductions in psychological distress compared with inactive control groups. In addition, 3 controlled studies comparing interventions with active control groups failed to demonstrate superior effects. Broader utility in promoting well-being in nonclinical populations was unclear.

conclusionsThe efficacy and acceptability of conversational agent interventions for mental health problems are promising. However, a more robust experimental design is required to demonstrate efficacy and efficiency. A focus on streamlining interventions, demonstrating equivalence to other treatment modalities, and elucidating mechanisms of action has the potential to increase acceptance by users and clinicians and maximize reach.

Indexed as

artificial intelligencechatbotconversational agentdigital healthmental healthpsychiatrystress, pychologicaltherapy, computer-assisted

Identifiers

PMID31628789
PMCPMC6914342

What OpenQuestion holds

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Registered trials

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.