Evidence map›Paper›PMID 36190749›Full record

ArticleJournal of medical Internet research2022

Conversational Agents in Health Care: Scoping Review of Their Behavior Change Techniques and Underpinning Theory.

Laura Martinengo, Ahmad Ishqi Jabir, Westin Wei Tin Goh, Nicholas Yong Wai Lo, Moon-Ho Ringo Ho, Tobias Kowatsch, Rifat Atun, Susan Michie, Lorainne Tudor Car

Registry-linked trialAbstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05694507 (Evaluation of Chatbot for Mental Well-being), which is not on this map. Cited by 29 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 4 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.

NCT05694507 nacompletednot on this mapstarted 2023, after this paper: background citation

Evaluation of Chatbot for Mental Well-being: A Randomized Controlled Trial

TypeinterventionalSponsorChinese University of Hong KongRan2023 to 2023Enrolled293ConditionsMental Well-being, Mental Health LiteracyArmsMental Well-being Chatbot
3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

9 authors.

Laura MartinengoLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0003-3539-7207
Ahmad Ishqi JabirLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0001-6864-9867
Westin Wei Tin GohLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0001-7989-1050
Nicholas Yong Wai LoLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0001-5054-8857
Moon-Ho Ringo HoSchool of Social Sciences, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0001-9021-5141
Tobias KowatschInstitute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-5939-4145
Rifat AtunDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Cambridge, MA, United States.ORCID 0000-0002-1531-5983
Susan MichieUCL Centre for Behaviour Change, University College London, London, United Kingdom.ORCID 0000-0003-0063-6378
Lorainne Tudor CarLee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore.ORCID 0000-0001-8414-7664

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundConversational agents (CAs) are increasingly used in health care to deliver behavior change interventions. Their evaluation often includes categorizing the behavior change techniques (BCTs) using a classification system of which the BCT Taxonomy v1 (BCTTv1) is one of the most common. Previous studies have presented descriptive summaries of behavior change interventions delivered by CAs, but no in-depth study reporting the use of BCTs in these interventions has been published to date.

objectiveThis review aims to describe behavior change interventions delivered by CAs and to identify the BCTs and theories guiding their design.

methodsWe searched PubMed, Embase, Cochrane's Central Register of Controlled Trials, and the first 10 pages of Google and Google Scholar in April 2021. We included primary, experimental studies evaluating a behavior change intervention delivered by a CA. BCTs coding followed the BCTTv1. Two independent reviewers selected the studies and extracted the data. Descriptive analysis and frequent itemset mining to identify BCT clusters were performed.

resultsWe included 47 studies reporting on mental health (n=19, 40%), chronic disorders (n=14, 30%), and lifestyle change (n=14, 30%) interventions. There were 20/47 embodied CAs (43%) and 27/47 CAs (57%) represented a female character. Most CAs were rule based (34/47, 72%). Experimental interventions included 63 BCTs, (mean 9 BCTs; range 2-21 BCTs), while comparisons included 32 BCTs (mean 2 BCTs; range 2-17 BCTs). Most interventions included BCTs 4.1 "Instruction on how to perform a behavior" (34/47, 72%), 3.3 "Social support" (emotional; 27/47, 57%), and 1.2 "Problem solving" (24/47, 51%). A total of 12/47 studies (26%) were informed by a behavior change theory, mainly the Transtheoretical Model and the Social Cognitive Theory. Studies using the same behavior change theory included different BCTs.

conclusionsThere is a need for the more explicit use of behavior change theories and improved reporting of BCTs in CA interventions to enhance the analysis of intervention effectiveness and improve the reproducibility of research.

Indexed as

Behavior TherapySocial SupportDelivery of Health CareFemaleHumansReproducibility of Resultsbehavior changebehavior change techniqueschatbotconversational agentmHealth

Identifiers

PMID36190749
PMCPMC9577715

What OpenQuestion holds

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LicenceCC BY
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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.