Real-World Effectiveness of a Digital Therapeutic in Improving Glycaemic Control in South Asians Living with Type 2 Diabetes

Sosale, Aravind; Shaikh, Maaz; Shah, Abhishek; Chawla, Rajeev; Makkar, Brij; Kesavadev, Jothydev; Joshi, Shilpa; Deshpande, Neeta; Agarwal, Sanjay; Maheshwari, Anuj; Madhu, SV; Saboo, Banshi D.

doi:10.2337/db18-866-p

Cited by 4 publications

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“…A total of 22 studies were from European countries, including Italy [ 44 , 45 ], Switzerland [ 30 , 46 - 52 ], France [ 53 , 54 ], Portugal [ 55 ], The Netherlands [ 56 ], the United Kingdom [ 57 - 61 ], Spain [ 62 , 63 ], and Sweden [ 64 ]. Moreover, 8 studies originated from Asian countries: Philippines [ 65 ], China [ 66 ], Japan [ 67 , 68 ], Pakistan [ 69 ], India [ 70 , 71 ], and Hong Kong [ 72 ]. Other geographic regions acknowledged in the studies of this review were Australia [ 73 , 74 ], Canada [ 75 ], New Zealand [ 76 , 77 ], South Africa [ 78 ], and the United States of America [ 79 - 89 ].…”

Section: Resultsmentioning

confidence: 99%

“…A variety of study designs were used in the included studies, comprising 20 case studies [ 44 , 48 , 51 , 61 - 63 , 66 , 69 , 71 , 73 - 79 , 82 , 84 , 85 , 89 ], 4 surveys [ 55 , 56 , 59 , 65 ], 3 observational studies [ 53 , 86 , 87 ], 11 randomized controlled trials [ 46 , 49 , 50 , 57 , 64 , 67 , 72 , 80 , 81 , 83 , 88 ], 3 diagnostic accuracy studies [ 58 , 60 , 68 ], 3 controlled before and after studies [ 30 , 45 , 70 ], 2 ongoing trials [ 51 , 54 ], and 1 pilot study [ 47 ] ( Figure 3 ).…”

Section: Resultsmentioning

confidence: 99%

“…The types of literature included 25 journal articles [ 44 , 48 , 55 - 57 , 61 - 65 , 67 , 69 , 72 , 74 - 76 , 80 - 87 , 89 ], 11 conference abstracts [ 45 , 47 , 49 , 50 , 52 , 59 , 70 , 71 , 73 , 78 , 79 ], 4 conference papers [ 30 , 46 , 66 , 77 ], 1 poster abstract [ 68 ], 4 electronic preprints [ 53 , 58 , 60 , 88 ], and 2 clinical trial protocols [ 51 , 54 ].…”

Section: Resultsmentioning

confidence: 99%

“…Conversational agents were delivered through a variety of means in the included studies. Most (n=23) were smartphone apps [ 30 , 46 - 50 , 53 , 55 , 58 - 61 , 64 , 67 , 70 , 71 , 75 , 77 , 81 , 83 , 85 , 86 , 88 ]; web based (n=5) [ 57 , 66 , 73 , 74 , 82 ]; desktop computer based (n=2) [ 65 , 79 ]; used smartphone-embedded software (n=6; eg, Siri, Google Assistant, Alexa, etc) [ 44 , 51 , 62 , 76 , 84 , 87 ], Telegram [ 45 , 78 ], WeChat [ 72 ], SMS and multimedia messaging service [ 89 ], Windows live messenger [ 56 ], or Facebook Messenger [ 52 , 80 ]; and 4 were made available on more than 1 platform [ 53 , 59 , 68 , 83 ]. Three studies did not specify the method of conversational agent delivery [ 54 , 63 , 69 ].…”

Section: Resultsmentioning

confidence: 99%

“…A total of 10 studies employed fixed text user inputs [ 30 , 46 , 47 , 49 , 50 , 52 , 54 , 58 , 83 , 88 ], with 2 additional studies enabling fixed text and image inputs [ 67 , 68 ]. Moreover, 19 studies allowed free text user inputs [ 45 , 48 , 51 , 56 , 57 , 60 , 61 , 66 , 69 , 70 , 72 , 74 , 77 , 78 , 80 , 81 , 85 , 86 , 89 ], and 4 studies used both fixed and free text user inputs [ 53 , 64 , 65 , 73 ]. Speech was enabled in 8 studies [ 44 , 55 , 63 , 71 , 76 , 79 , 82 , 84 ], whereas free text and speech were employed in 3 studies [ 62 , 75 , 87 ].…”

Section: Resultsmentioning

confidence: 99%

See 4 more Smart Citations

Conversational Agents in Health Care: Scoping Review and Conceptual Analysis

Car¹,

Dhinagaran²,

Kyaw³

et al. 2020

J Med Internet Res

317

197

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Background Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. Objective This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. Methods We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. Results The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. Conclusions The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Conversational Agents in Health Care: Scoping Review and Conceptual Analysis

Car¹,

Dhinagaran²,

Kyaw³

et al. 2020

J Med Internet Res

317

197

View full text Add to dashboard Cite

show abstract

Early Development of a Virtual Coach for Healthy Coping Interventions in Type 2 Diabetes Mellitus: Validation Study

Bassi¹,

Donadello²,

Gabrielli³

et al. 2022

JMIR Form Res

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Background Mobile health solutions aimed at monitoring tasks among people with diabetes mellitus (DM) have been broadly applied. However, virtual coaches (VCs), embedded or not in mobile health, are considered valuable means of improving patients’ health-related quality of life and ensuring adherence to self-care recommendations in diabetes management. Despite the growing need for effective, healthy coping digital interventions to support patients’ self-care and self-management, the design of psychological digital interventions that are acceptable, usable, and engaging for the target users still represents the main challenge, especially from a psychosocial perspective. Objective This study primarily aims to test VC interventions based on psychoeducational and counseling approaches to support and promote healthy coping behaviors in adults with DM. As a preliminary study, university students have participated in it and have played the standardized patients’ (SPs) role with the aim of improving the quality of the intervention protocol in terms of user acceptability, experience, and engagement. The accuracy of users’ role-playing is further analyzed. Methods This preliminary study is based on the Obesity-Related Behavioral Intervention Trial model, with a specific focus on its early phases. The healthy coping intervention protocol was initially designed together with a team of psychologists following the main guidelines and recommendations for psychoeducational interventions for healthy coping in the context of DM. The protocol was refined with the support of 3 experts in the design of behavioral intervention technologies for mental health and well-being, who role-played 3 SPs’ profiles receiving the virtual coaching intervention in a Wizard of Oz setting via WhatsApp. A refined version of the healthy coping protocol was then iteratively tested with a sample of 18 university students (mean age 23.61, SD 1.975 years) in a slightly different Wizard of Oz evaluation setting. Participants provided quantitative and qualitative postintervention feedback by reporting their experiences with the VC. Clustering techniques on the logged interactions and dialogs between the VC and users were collected and analyzed to identify additional refinements for future VC development. Results Both quantitative and qualitative analyses showed that the digital healthy coping intervention was perceived as supportive, motivating, and able to trigger self-reflection on coping strategies. Analyses of the logged dialogs showed that most of the participants accurately played the SPs’ profile assigned, confirming the validity and usefulness of this testing approach in preliminary assessments of behavioral digital interventions and protocols. Conclusions This study outlined an original approach to the early development and iterative testing of digital healthy coping interventions for type 2 DM. Indeed, the intervention was well-accepted and proved its effectiveness in the definition and refinement of the initial protocol and of the user experience with a VC before directly involving real patients in its subsequent use and testing.

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Conversational Agents in Health Care: Scoping Review and Conceptual Analysis (Preprint)

Car¹,

Dhinagaran²,

Kyaw³

et al. 2019

Preprint

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BACKGROUND Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. OBJECTIVE This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. METHODS We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. RESULTS The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. CONCLUSIONS The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

show abstract

Real-World Effectiveness of a Digital Therapeutic in Improving Glycaemic Control in South Asians Living with Type 2 Diabetes

Cited by 4 publications

References 0 publications

Conversational Agents in Health Care: Scoping Review and Conceptual Analysis

Conversational Agents in Health Care: Scoping Review and Conceptual Analysis

Early Development of a Virtual Coach for Healthy Coping Interventions in Type 2 Diabetes Mellitus: Validation Study

Conversational Agents in Health Care: Scoping Review and Conceptual Analysis (Preprint)

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