Evidence map›Paper›PMID 30010941›Full record

SynthesisJournal of the American Medical Informatics Association : JAMIA2018

Conversational agents in healthcare: a systematic review.

Liliana Laranjo, Adam G Dunn, Huong Ly Tong, Ahmet Baki Kocaballi, Jessica Chen, Rabia Bashir, Didi Surian, Blanca Gallego, Farah Magrabi, Annie Y S Lau and 1 more

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

Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07223736 (Postpartum Education Via Artificial Intelligence for Recovery and Loneliness), which is not on this map. Cited by 413 papers, 21 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
413citing 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.

NCT07223736 narecruitingnot on this mapstarted 2026, after this paper: background citation

Postpartum Education Via Artificial Intelligence for Recovery and Loneliness (PEARL): A Randomized Controlled Trial

TypeinterventionalSponsorUniversity of California, San DiegoRan2026 to 2026Enrolled130ConditionsPelvic Floor Disorder, Loneliness, Postpartum, Mental HealthArmsGenerative artificial intelligence (genAI) postpartum chatbot, Standard of Care (SOC)
3 · Its place in the literature

Who cites it

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

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353 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

11 authors.

Liliana LaranjoCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Adam G DunnCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Huong Ly TongCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Ahmet Baki KocaballiCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Jessica ChenCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Rabia BashirCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Didi SurianCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Blanca GallegoCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Farah MagrabiCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Annie Y S LauCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Enrico CoieraCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Our objective was to review the characteristics, current applications, and evaluation measures of conversational agents with unconstrained natural language input capabilities used for health-related purposes. Methods: We searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search strategy. Studies were included if they focused on consumers or healthcare professionals; involved a conversational agent using any unconstrained natural language input; and reported evaluation measures resulting from user interaction with the system. Studies were screened by independent reviewers and Cohen's kappa measured inter-coder agreement. Results: The database search retrieved 1513 citations; 17 articles (14 different conversational agents) met the inclusion criteria. Dialogue management strategies were mostly finite-state and frame-based (6 and 7 conversational agents, respectively); agent-based strategies were present in one type of system. Two studies were randomized controlled trials (RCTs), 1 was cross-sectional, and the remaining were quasi-experimental. Half of the conversational agents supported consumers with health tasks such as self-care. The only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04). Patient safety was rarely evaluated in the included studies. Conclusions: The use of conversational agents with unconstrained natural language input capabilities for health-related purposes is an emerging field of research, where the few published studies were mainly quasi-experimental, and rarely evaluated efficacy or safety. Future studies would benefit from more robust experimental designs and standardized reporting. Protocol Registration: The protocol for this systematic review is registered at PROSPERO with the number CRD42017065917.

Indexed as

Natural Language ProcessingSpeech Recognition SoftwareArtificial IntelligenceCommunicationDelivery of Health Care

Identifiers

PMID30010941
PMCPMC6118869

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.