Evidence map›Paper›PMID 37213199›Full record

ArticleJournal of participatory medicine2023

Examining Patient Engagement in Chatbot Development Approaches for Healthy Lifestyle and Mental Wellness Interventions: Scoping Review.

Chikku Sadasivan, Christofer Cruz, Naomi Dolgoy, Ashley Hyde, Sandra Campbell, Margaret McNeely, Eleni Stroulia, Puneeta Tandon

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of participatory medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Validating LLM judges for automated oversight of patient communication.medRxiv : the preprint server for health sciences · 2026
    Article
  2. Article
  3. Allies not enemies-creating a more empathetic and uplifting patient experience through technology and art.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025
    Review
  4. Article
  5. Review
  6. Article
  7. 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

8 authors.

Chikku SadasivanDepartment of Medicine, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0003-2065-3837
Christofer CruzDepartment of Medicine, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0001-9568-3948
Naomi DolgoyDepartment of Physical Therapy, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0001-5699-2844
Ashley HydeDepartment of Medicine, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0001-6356-1209
Sandra CampbellJohn W Scott Health Sciences Library, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0002-9347-3880
Margaret McNeelyDepartment of Physical Therapy, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0003-4376-4847
Eleni StrouliaDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0002-8784-8236
Puneeta TandonDepartment of Medicine, University of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0003-0486-0174

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChatbots are growing in popularity as they offer a range of potential benefits to end users and service providers.

objectiveOur scoping review aimed to explore studies that used 2-way chatbots to support healthy eating, physical activity, and mental wellness interventions. Our objectives were to report the nontechnical (eg, unrelated to software development) approaches for chatbot development and to examine the level of patient engagement in these reported approaches.

methodsOur team conducted a scoping review following the framework proposed by Arksey and O'Malley. Nine electronic databases were searched in July 2022. Studies were selected based on our inclusion and exclusion criteria. Data were then extracted and patient involvement was assessed.

results16 studies were included in this review. We report several approaches to chatbot development, assess patient involvement where possible, and reveal the limited detail available on reporting of patient involvement in the chatbot implementation process. The reported approaches for development included: collaboration with knowledge experts, co-design workshops, patient interviews, prototype testing, the Wizard of Oz (WoZ) procedure, and literature review. Reporting of patient involvement in development was limited; only 3 of the 16 included studies contained sufficient information to evaluate patient engagement using the Guidance for Reporting Involvement of Patients and Public (GRIPP2).

conclusionsThe approaches reported in this review and the identified limitations can guide the inclusion of patient engagement and the improved documentation of engagement in the chatbot development process for future health care research. Given the importance of end user involvement in chatbot development, we hope that future research will more systematically report on chatbot development and more consistently and actively engage patients in the codevelopment process.

Indexed as

chatbotscodevelopmentpatient engagementpatient involvementvirtual assistants

Identifiers

PMID37213199
PMCPMC10242458

What OpenQuestion holds

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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.