Evidence map›Paper›PMID 32149717›Full record

ArticleJMIR research protocols2020

Effectiveness of Conversational Agents (Virtual Assistants) in Health Care: Protocol for a Systematic Review.

Caroline de Cock, Madison Milne-Ives, Michelle Helena van Velthoven, Abrar Alturkistani, Ching Lam, Edward Meinert

Abstract read
In one paragraph

Article in JMIR research protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  7. Virtual humans in geriatric care: an integrative review.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Review
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  20. [Expectations of generation Y for digital health innovations].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2022
    Article
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

6 authors.

Caroline de Cock *Digitally Enabled Preventative Health Research Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0001-7585-9598
Madison Milne-IvesDigitally Enabled Preventative Health Research Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0001-7628-882X
Michelle Helena van VelthovenDigitally Enabled Preventative Health Research Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0003-1245-8759
Abrar AlturkistaniDepartment of Primary Care and Public Health, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-7935-8870
Ching LamDigitally Enabled Preventative Health Research Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-9137-749X
Edward Meinert *Digitally Enabled Preventative Health Research Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0003-2484-3347

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundConversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with potential to automate a diverse range of health-related activities supporting the general public, patients, and physicians. Multiple studies have reported the development of these agents, and recent systematic reviews have described the scope of use of conversational agents in health care. However, there is scarce research on the effectiveness of these systems; thus, their viability and applicability are unclear.

objectiveThe objective of this systematic review is to assess the effectiveness of conversational agents in health care and to identify limitations, adverse events, and areas for future investigation of these agents.

methodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols will be used to structure this protocol. The focus of the systematic review is guided by a population, intervention, comparator, and outcome framework. A systematic search of the PubMed (Medline), EMBASE, CINAHL, and Web of Science databases will be conducted. Two authors will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal.

resultsAs of January 2020, we have begun a preliminary literature search and piloting of the study selection process.

conclusionsThis systematic review aims to clarify the effectiveness, limitations, and future applications of conversational agents in health care. Our findings may be useful to inform the future development of conversational agents and promote the personalization of patient care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/16934.

Indexed as

artificial intelligenceavatarchatbotconversational agentdigital healthintelligent assistantspeech recognition softwarevirtual assistantvirtual coachvirtual health carevirtual nursingvoice recognition software

Identifiers

PMID32149717
PMCPMC7091022

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.