Evidence map›Paper›PMID 40966680›Full record

SynthesisJMIR mHealth and uHealth2025

Engagement With Conversational Agent-Enabled Interventions in Cardiometabolic Disease Self-Management: Systematic Review.

Nick Kashyap, Ann Tresa Sebastian, Chris Lynch, Paul Jansons, Ralph Maddison, Tilman Dingler, Brian Oldenburg

Abstract readSystematic Review
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Review
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

7 authors.

Nick KashyapSchool of Psychology and Public Health, La Trobe University, Melbourne, Australia.ORCID 0009-0008-6577-2454
Ann Tresa SebastianInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID 0000-0002-9291-4525
Chris LynchSchool of Psychology and Public Health, La Trobe University, Melbourne, Australia.ORCID 0000-0001-9503-6994
Paul JansonsInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID 0000-0002-8766-0516
Ralph MaddisonInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia.ORCID 0000-0001-8564-5518
Tilman DinglerDelft University of Technology, Delft, The Netherlands.ORCID 0000-0001-6180-7033
Brian OldenburgSchool of Psychology and Public Health, La Trobe University, Melbourne, Australia.ORCID 0000-0002-7712-5413

Funding

National Health and Medical Research Council 2020-2024: ID 1170937
6 · The paper itself

Abstract

backgroundWell-designed conversational agents can improve health care capacity to meet the dynamic and complex needs of people self-managing cardiometabolic diseases (CMD). However, a lack of empirical evidence on conversational agent-enabled intervention design features and their impact on engagement make it challenging to comprehensively evaluate effectiveness. This review synthesizes evidence on conversational agent-enabled intervention design features and how they impact on engagement to inform the development of more engaging conversational agent-enabled interventions that effectively help people with CMD to self-manage their condition.

objectiveThe aim of the study is to synthesize evidence pertaining to conversational agent-enabled intervention design features and their impact on engagement of people self-managing CMD.

methodsSearches were conducted in Ovid (MEDLINE), Web of Science, and Scopus databases. Inclusion criteria were primary research studies reporting on conversational agent-enabled interventions that included measures of engagement and included adults with CMD. Data extraction captured perspectives of people with CMD on various design features of conversational agent-enabled interventions.

resultsOf 1366 studies identified for screening, 20 were included in the review. In total, 18 of these were qualitative or quasi-experimental evaluations of conversational agent-enabled intervention prototypes. Five domains of design features that impact user engagement with conversational agent-enabled interventions emerged: communication style, functionality, accessibility, visual appearance, and personality.

conclusionsAcross all 5 domains, integrating redundancy and anthropomorphism were identified as effective strategies for improving engagement by increasing user autonomy and investment. Future research should adopt design strategies that are inclusive and adaptive to the diverse needs of users and aligned with the unique considerations relevant to conversational agent-enabled interventions.

trial registrationPROSPERO CRD42023431579; https://tinyurl.com/3srmzw8f. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/52973.

Indexed as

Cardiovascular DiseasesCommunicationMetabolic DiseasesPatient ParticipationSelf-ManagementHumanscardiovascular diseasechatbotchronic diseasediabetesdigital assistantdigital healthqualitativeuser experience

Identifiers

PMID40966680
PMCPMC12491886

What Socratic 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 Socratic graph.