Evidence map›Paper›PMID 34479391›Full record

ArticleYearbook of medical informatics2021

The Use and Promise of Conversational Agents in Digital Health.

Tilman Dingler, Dominika Kwasnicka, Jing Wei, Enying Gong, Brian Oldenburg

Abstract read
In one paragraph

Article in Yearbook of medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing 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.

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

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

  1. Pooled it
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  4. Chatbots for breast cancer education: a systematic review and meta-analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Pooled it
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  9. Conversational Agents to Support Pain Management: A Scoping Review.European journal of pain (London, England) · 2025
    Article
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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

5 authors.

Tilman DinglerNHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, School of Computing and Information Systems, University of Melbourne, Parkville, Australia.
Dominika KwasnickaNHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Jing WeiNHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, School of Computing and Information Systems, University of Melbourne, Parkville, Australia.
Enying GongNHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Brian OldenburgNHMRC CRE in Digital Technology to Transform Chronic Disease Outcomes, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo describe the use and promise of conversational agents in digital health-including health promotion andprevention-and how they can be combined with other new technologies to provide healthcare at home.

methodA narrative review of recent advances in technologies underpinning conversational agents and their use and potential for healthcare and improving health outcomes.

resultsBy responding to written and spoken language, conversational agents present a versatile, natural user interface and have the potential to make their services and applications more widely accessible. Historically, conversational interfaces for health applications have focused mainly on mental health, but with an increase in affordable devices and the modernization of health services, conversational agents are becoming more widely deployed across the health system. We present our work on context-aware voice assistants capable of proactively engaging users and delivering health information and services. The proactive voice agents we deploy, allow us to conduct experience sampling in people's homes and to collect information about the contexts in which users are interacting with them.

conclusionIn this article, we describe the state-of-the-art of these and other enabling technologies for speech and conversation and discuss ongoing research efforts to develop conversational agents that "live" with patients and customize their service offerings around their needs. These agents can function as 'digital companions' who will send reminders about medications and appointments, proactively check in to gather self-assessments, and follow up with patients on their treatment plans. Together with an unobtrusive and continuous collection of other health data, conversational agents can provide novel and deeply personalized access to digital health care, and they will continue to become an increasingly important part of the ecosystem for future healthcare delivery.

Indexed as

Health PromotionHealth Services AccessibilitySpeech Recognition SoftwareTelemedicineCommunicationHumansMonitoring, PhysiologicUser-Computer Interface

Identifiers

PMID34479391
PMCPMC8416202

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.