Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study.

asthma chatbot chronic diseases conversational agent digital health intervention eHealth feasibility study intervention design mHealth

Journal

Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882

Informations de publication

Date de publication:
17 02 2021
Historique:
received: 16 10 2020
accepted: 22 01 2021
revised: 19 11 2020
pubmed: 24 1 2021
medline: 18 5 2021
entrez: 23 1 2021
Statut: epublish

Résumé

Successful management of chronic diseases requires a trustful collaboration between health care professionals, patients, and family members. Scalable conversational agents, designed to assist health care professionals, may play a significant role in supporting this collaboration in a scalable way by reaching out to the everyday lives of patients and their family members. However, to date, it remains unclear whether conversational agents, in such a role, would be accepted and whether they can support this multistakeholder collaboration. With asthma in children representing a relevant target of chronic disease management, this study had the following objectives: (1) to describe the design of MAX, a conversational agent-delivered asthma intervention that supports health care professionals targeting child-parent teams in their everyday lives; and (2) to assess the (a) reach of MAX, (b) conversational agent-patient working alliance, (c) acceptance of MAX, (d) intervention completion rate, (e) cognitive and behavioral outcomes, and (f) human effort and responsiveness of health care professionals in primary and secondary care settings. MAX was designed to increase cognitive skills (ie, knowledge about asthma) and behavioral skills (ie, inhalation technique) in 10-15-year-olds with asthma, and enables support by a health professional and a family member. To this end, three design goals guided the development: (1) to build a conversational agent-patient working alliance; (2) to offer hybrid (human- and conversational agent-supported) ubiquitous coaching; and (3) to provide an intervention with high experiential value. An interdisciplinary team of computer scientists, asthma experts, and young patients with their parents developed the intervention collaboratively. The conversational agent communicates with health care professionals via email, with patients via a mobile chat app, and with a family member via SMS text messaging. A single-arm feasibility study in primary and secondary care settings was performed to assess MAX. Results indicated an overall positive evaluation of MAX with respect to its reach (49.5%, 49/99 of recruited and eligible patient-family member teams participated), a strong patient-conversational agent working alliance, and high acceptance by all relevant stakeholders. Moreover, MAX led to improved cognitive and behavioral skills and an intervention completion rate of 75.5%. Family members supported the patients in 269 out of 275 (97.8%) coaching sessions. Most of the conversational turns (99.5%) were conducted between patients and the conversational agent as opposed to between patients and health care professionals, thus indicating the scalability of MAX. In addition, it took health care professionals less than 4 minutes to assess the inhalation technique and 3 days to deliver related feedback to the patients. Several suggestions for improvement were made. This study provides the first evidence that conversational agents, designed as mediating social actors involving health care professionals, patients, and family members, are not only accepted in such a "team player" role but also show potential to improve health-relevant outcomes in chronic disease management.

Sections du résumé

BACKGROUND
Successful management of chronic diseases requires a trustful collaboration between health care professionals, patients, and family members. Scalable conversational agents, designed to assist health care professionals, may play a significant role in supporting this collaboration in a scalable way by reaching out to the everyday lives of patients and their family members. However, to date, it remains unclear whether conversational agents, in such a role, would be accepted and whether they can support this multistakeholder collaboration.
OBJECTIVE
With asthma in children representing a relevant target of chronic disease management, this study had the following objectives: (1) to describe the design of MAX, a conversational agent-delivered asthma intervention that supports health care professionals targeting child-parent teams in their everyday lives; and (2) to assess the (a) reach of MAX, (b) conversational agent-patient working alliance, (c) acceptance of MAX, (d) intervention completion rate, (e) cognitive and behavioral outcomes, and (f) human effort and responsiveness of health care professionals in primary and secondary care settings.
METHODS
MAX was designed to increase cognitive skills (ie, knowledge about asthma) and behavioral skills (ie, inhalation technique) in 10-15-year-olds with asthma, and enables support by a health professional and a family member. To this end, three design goals guided the development: (1) to build a conversational agent-patient working alliance; (2) to offer hybrid (human- and conversational agent-supported) ubiquitous coaching; and (3) to provide an intervention with high experiential value. An interdisciplinary team of computer scientists, asthma experts, and young patients with their parents developed the intervention collaboratively. The conversational agent communicates with health care professionals via email, with patients via a mobile chat app, and with a family member via SMS text messaging. A single-arm feasibility study in primary and secondary care settings was performed to assess MAX.
RESULTS
Results indicated an overall positive evaluation of MAX with respect to its reach (49.5%, 49/99 of recruited and eligible patient-family member teams participated), a strong patient-conversational agent working alliance, and high acceptance by all relevant stakeholders. Moreover, MAX led to improved cognitive and behavioral skills and an intervention completion rate of 75.5%. Family members supported the patients in 269 out of 275 (97.8%) coaching sessions. Most of the conversational turns (99.5%) were conducted between patients and the conversational agent as opposed to between patients and health care professionals, thus indicating the scalability of MAX. In addition, it took health care professionals less than 4 minutes to assess the inhalation technique and 3 days to deliver related feedback to the patients. Several suggestions for improvement were made.
CONCLUSIONS
This study provides the first evidence that conversational agents, designed as mediating social actors involving health care professionals, patients, and family members, are not only accepted in such a "team player" role but also show potential to improve health-relevant outcomes in chronic disease management.

Identifiants

pubmed: 33484114
pii: v23i2e25060
doi: 10.2196/25060
pmc: PMC7929753
doi:

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

e25060

Subventions

Organisme : NIDA NIH HHS
ID : P30 DA029926
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK124428
Pays : United States

Informations de copyright

©Tobias Kowatsch, Theresa Schachner, Samira Harperink, Filipe Barata, Ullrich Dittler, Grace Xiao, Catherine Stanger, Florian v Wangenheim, Elgar Fleisch, Helmut Oswald, Alexander Möller. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.02.2021.

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Auteurs

Tobias Kowatsch (T)

Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.
Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise, Singapore-ETH Centre, Singapore, Singapore.
Centre for Digital Health Interventions, Institute of Technology Management, University of St Gallen, St Gallen, Switzerland.

Theresa Schachner (T)

Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.

Samira Harperink (S)

Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.

Filipe Barata (F)

Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.

Ullrich Dittler (U)

Fakultät Digitale Medien, Campus Furtwangen, Hochschule Furtwangen University, Furtwangen, Germany.

Grace Xiao (G)

Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, MD, United States.

Catherine Stanger (C)

Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Hanover, NH, United States.

Florian V Wangenheim (F)

Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.
Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise, Singapore-ETH Centre, Singapore, Singapore.

Elgar Fleisch (E)

Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.
Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise, Singapore-ETH Centre, Singapore, Singapore.
Centre for Digital Health Interventions, Institute of Technology Management, University of St Gallen, St Gallen, Switzerland.

Helmut Oswald (H)

Department of Child and Adolescent Health, Cantonal Hospital Winterthur, Winterthur, Switzerland.

Alexander Möller (A)

Division of Respiratory Medicine and Childhood Research Center, University Children's Hospital Zurich, Zurich, Switzerland.

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