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Sullivan MO, Curtin M, Flynn R, Cronin C, Mahony JO, Trujillo J. Telehealth interventions for transition to self-management in adolescents with allergic conditions: A systematic review. Allergy 2024; 79:861-883. [PMID: 38041398 DOI: 10.1111/all.15963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/14/2023] [Accepted: 11/19/2023] [Indexed: 12/03/2023]
Abstract
Telehealth is an emerging approach that uses technology to provide healthcare remotely. Recent publications have outlined the importance of supporting the transition to self-management of adolescents with allergic conditions. However, no synthesis of the evidence base on the use and impact of telehealth interventions for this purpose has been conducted to date. This review achieves these aims, in addition to exploring the language use surrounding these interventions, and their implementation. Four databases were searched systematically. References were independently screened by two reviewers. Methodological quality was assessed using the Mixed Methods Appraisal Tool. A narrative synthesis was undertaken. Eighteen articles were included, reporting on 15 telehealth interventions. A total of 86% targeted adolescents with asthma. Mobile applications were the most common telehealth modality used, followed by video-conferencing, web-based, virtual reality and artificial intelligence. Five intervention content categories were identified; educational, monitoring, behavioural, psychosocial and healthcare navigational. Peer and/or healthcare professional interaction, gamification and tailoring may increase engagement. The studies showed positive effects of the interventions or no difference from active controls, in self-management outcomes such as knowledge, health outcomes such as quality-of-life, and economic outcomes such as healthcare utilization. The most common implementation outcomes reported were acceptability, appropriateness, feasibility and fidelity.
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Affiliation(s)
- Meg O' Sullivan
- University College Cork, Cork, Ireland
- Cork University Hospital, Cork, Ireland
| | | | | | | | | | - Juan Trujillo
- University College Cork, Cork, Ireland
- Cork University Hospital, Cork, Ireland
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2
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Cohen Rodrigues TR, de Buisonjé DR, Reijnders T, Santhanam P, Kowatsch T, Breeman LD, Janssen VR, Kraaijenhagen RA, Atsma DE, Evers AW. Human cues in eHealth to promote lifestyle change: An experimental field study to examine adherence to self-help interventions. Internet Interv 2024; 35:100726. [PMID: 38370288 PMCID: PMC10869898 DOI: 10.1016/j.invent.2024.100726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 01/27/2024] [Accepted: 02/07/2024] [Indexed: 02/20/2024] Open
Abstract
eHealth lifestyle interventions without human support (self-help interventions) are generally less effective, as they suffer from lower adherence levels. To solve this, we investigated whether (1) using a text-based conversational agent (TCA) and applying human cues contribute to a working alliance with the TCA, and whether (2) adding human cues and establishing a positive working alliance increase intervention adherence. Participants (N = 121) followed a TCA-supported app-based physical activity intervention. We manipulated two types of human cues: visual (ie, message appearance) and relational (ie, message content). We employed a 2 (visual cues: yes, no) x 2 (relational cues: yes, no) between-subjects design, resulting in four experimental groups: (1) visual and relational cues, (2) visual cues only, (3) relational cues only, or (4) no human cues. We measured the working alliance with the Working Alliance Inventory Short Revised form and intervention adherence as the number of days participants responded to the TCA's messages. Contrary to expectations, the working alliance was unaffected by using human cues. Working alliance was positively related to adherence (t(78) = 3.606, p = .001). Furthermore, groups who received visual cues showed lower adherence levels compared to those who received relational cues only or no cues (U = 1140.5, z = -3.520, p < .001). We replicated the finding that establishing a working alliance contributes to intervention adherence, independently of the use of human cues in a TCA. However, we were unable to show that adding human cues impacted the working alliance and increased adherence. The results indicate that adding visual cues to a TCA may even negatively affect adherence, possibly because it may create confusion concerning the true nature of the coach, which may prompt unrealistic expectations.
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Affiliation(s)
| | | | - Thomas Reijnders
- Health, Medical, and Neuropsychology Unit, Leiden University, the Netherlands
| | - Prabhakaran Santhanam
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Tobias Kowatsch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Instiute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St.Gallen, St. Gallen, Switzerland
| | - Linda D. Breeman
- Health, Medical, and Neuropsychology Unit, Leiden University, the Netherlands
| | - Veronica R. Janssen
- Health, Medical, and Neuropsychology Unit, Leiden University, the Netherlands
- Department of Cardiology, Leiden University Medical Center, the Netherlands
| | - Roderik A. Kraaijenhagen
- NDDO Institute for Prevention and Early Diagnostics (NIPED), Amsterdam, the Netherlands
- Vital10, Amsterdam, the Netherlands
| | - Douwe E. Atsma
- Department of Cardiology, Leiden University Medical Center, the Netherlands
| | - Andrea W.M. Evers
- Health, Medical, and Neuropsychology Unit, Leiden University, the Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
- Medical Delta, Leiden University, Technical University of Delft, Erasmus University Rotterdam, the Netherlands
| | - the BENEFIT consortium
- Health, Medical, and Neuropsychology Unit, Leiden University, the Netherlands
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Instiute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St.Gallen, St. Gallen, Switzerland
- Department of Cardiology, Leiden University Medical Center, the Netherlands
- NDDO Institute for Prevention and Early Diagnostics (NIPED), Amsterdam, the Netherlands
- Vital10, Amsterdam, the Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
- Medical Delta, Leiden University, Technical University of Delft, Erasmus University Rotterdam, the Netherlands
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Ulrich S, Gantenbein AR, Zuber V, Von Wyl A, Kowatsch T, Künzli H. Development and Evaluation of a Smartphone-Based Chatbot Coach to Facilitate a Balanced Lifestyle in Individuals With Headaches (BalanceUP App): Randomized Controlled Trial. J Med Internet Res 2024; 26:e50132. [PMID: 38265863 PMCID: PMC10851123 DOI: 10.2196/50132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/20/2023] [Accepted: 12/12/2023] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Primary headaches, including migraine and tension-type headaches, are widespread and have a social, physical, mental, and economic impact. Among the key components of treatment are behavior interventions such as lifestyle modification. Scalable conversational agents (CAs) have the potential to deliver behavior interventions at a low threshold. To our knowledge, there is no evidence of behavioral interventions delivered by CAs for the treatment of headaches. OBJECTIVE This study has 2 aims. The first aim was to develop and test a smartphone-based coaching intervention (BalanceUP) for people experiencing frequent headaches, delivered by a CA and designed to improve mental well-being using various behavior change techniques. The second aim was to evaluate the effectiveness of BalanceUP by comparing the intervention and waitlist control groups and assess the engagement and acceptance of participants using BalanceUP. METHODS In an unblinded randomized controlled trial, adults with frequent headaches were recruited on the web and in collaboration with experts and allocated to either a CA intervention (BalanceUP) or a control condition. The effects of the treatment on changes in the primary outcome of the study, that is, mental well-being (as measured by the Patient Health Questionnaire Anxiety and Depression Scale), and secondary outcomes (eg, psychosomatic symptoms, stress, headache-related self-efficacy, intention to change behavior, presenteeism and absenteeism, and pain coping) were analyzed using linear mixed models and Cohen d. Primary and secondary outcomes were self-assessed before and after the intervention, and acceptance was assessed after the intervention. Engagement was measured during the intervention using self-reports and usage data. RESULTS A total of 198 participants (mean age 38.7, SD 12.14 y; n=172, 86.9% women) participated in the study (intervention group: n=110; waitlist control group: n=88). After the intervention, the intention-to-treat analysis revealed evidence for improved well-being (treatment: β estimate=-3.28, 95% CI -5.07 to -1.48) with moderate between-group effects (Cohen d=-0.66, 95% CI -0.99 to -0.33) in favor of the intervention group. We also found evidence of reduced somatic symptoms, perceived stress, and absenteeism and presenteeism, as well as improved headache management self-efficacy, application of behavior change techniques, and pain coping skills, with effects ranging from medium to large (Cohen d=0.43-1.05). Overall, 64.8% (118/182) of the participants used coaching as intended by engaging throughout the coaching and completing the outro. CONCLUSIONS BalanceUP was well accepted, and the results suggest that coaching delivered by a CA can be effective in reducing the burden of people who experience headaches by improving their well-being. TRIAL REGISTRATION German Clinical Trials Register DRKS00017422; https://trialsearch.who.int/Trial2.aspx?TrialID=DRKS00017422.
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Affiliation(s)
- Sandra Ulrich
- School of Applied Psychology, Zurich University of Applied Sciences, Zurich, Switzerland
| | - Andreas R Gantenbein
- Pain and Research Unit, ZURZACH Care, Bad Zurzach, Switzerland
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Viktor Zuber
- School of Applied Psychology, Zurich University of Applied Sciences, Zurich, Switzerland
| | - Agnes Von Wyl
- School of Applied Psychology, Zurich University of Applied Sciences, Zurich, Switzerland
| | - Tobias Kowatsch
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St.Gallen, St. Gallen, Switzerland
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Hansjörg Künzli
- School of Applied Psychology, Zurich University of Applied Sciences, Zurich, Switzerland
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Cook D, Peters D, Moradbakhti L, Su T, Da Re M, Schuller BW, Quint J, Wong E, Calvo RA. A text-based conversational agent for asthma support: Mixed-methods feasibility study. Digit Health 2024; 10:20552076241258276. [PMID: 38894942 PMCID: PMC11185032 DOI: 10.1177/20552076241258276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 05/13/2024] [Indexed: 06/21/2024] Open
Abstract
Objective Millions of people in the UK have asthma, yet 70% do not access basic care, leading to the largest number of asthma-related deaths in Europe. Chatbots may extend the reach of asthma support and provide a bridge to traditional healthcare. This study evaluates 'Brisa', a chatbot designed to improve asthma patients' self-assessment and self-management. Methods We recruited 150 adults with an asthma diagnosis to test our chatbot. Participants were recruited over three waves through social media and a research recruitment platform. Eligible participants had access to 'Brisa' via a WhatsApp or website version for 28 days and completed entry and exit questionnaires to evaluate user experience and asthma control. Weekly symptom tracking, user interaction metrics, satisfaction measures, and qualitative feedback were utilised to evaluate the chatbot's usability and potential effectiveness, focusing on changes in asthma control and self-reported behavioural improvements. Results 74% of participants engaged with 'Brisa' at least once. High task completion rates were observed: asthma attack risk assessment (86%), voice recording submission (83%) and asthma control tracking (95.5%). Post use, an 8% improvement in asthma control was reported. User satisfaction surveys indicated positive feedback on helpfulness (80%), privacy (87%), trustworthiness (80%) and functionality (84%) but highlighted a need for improved conversational depth and personalisation. Conclusions The study indicates that chatbots are effective for asthma support, demonstrated by the high usage of features like risk assessment and control tracking, as well as a statistically significant improvement in asthma control. However, lower satisfaction in conversational flexibility highlights rising expectations for chatbot fluency, influenced by advanced models like ChatGPT. Future health-focused chatbots must balance conversational capability with accuracy and safety to maintain engagement and effectiveness.
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Affiliation(s)
- Darren Cook
- Dyson School of Design Engineering, Imperial College London, London, UK
| | - Dorian Peters
- Dyson School of Design Engineering, Imperial College London, London, UK
| | - Laura Moradbakhti
- Dyson School of Design Engineering, Imperial College London, London, UK
| | - Ting Su
- Dyson School of Design Engineering, Imperial College London, London, UK
| | - Marco Da Re
- Dyson School of Design Engineering, Imperial College London, London, UK
| | - Bjorn W. Schuller
- Dyson School of Design Engineering, Imperial College London, London, UK
| | | | - Ernie Wong
- Imperial College Healthcare NHS Trust, London, UK
| | - Rafael A. Calvo
- Dyson School of Design Engineering, Imperial College London, London, UK
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Ollier J, Suryapalli P, Fleisch E, von Wangenheim F, Mair JL, Salamanca-Sanabria A, Kowatsch T. Can digital health researchers make a difference during the pandemic? Results of the single-arm, chatbot-led Elena+: Care for COVID-19 interventional study. Front Public Health 2023; 11:1185702. [PMID: 37693712 PMCID: PMC10485275 DOI: 10.3389/fpubh.2023.1185702] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 07/24/2023] [Indexed: 09/12/2023] Open
Abstract
Background The current paper details findings from Elena+: Care for COVID-19, an app developed to tackle the collateral damage of lockdowns and social distancing, by offering pandemic lifestyle coaching across seven health areas: anxiety, loneliness, mental resources, sleep, diet and nutrition, physical activity, and COVID-19 information. Methods The Elena+ app functions as a single-arm interventional study, with participants recruited predominantly via social media. We used paired samples T-tests and within subjects ANOVA to examine changes in health outcome assessments and user experience evaluations over time. To investigate the mediating role of behavioral activation (i.e., users setting behavioral intentions and reporting actual behaviors) we use mixed-effect regression models. Free-text entries were analyzed qualitatively. Results Results show strong demand for publicly available lifestyle coaching during the pandemic, with total downloads (N = 7'135) and 55.8% of downloaders opening the app (n = 3,928) with 9.8% completing at least one subtopic (n = 698). Greatest areas of health vulnerability as assessed with screening measures were physical activity with 62% (n = 1,000) and anxiety with 46.5% (n = 760). The app was effective in the treatment of mental health; with a significant decrease in depression between first (14 days), second (28 days), and third (42 days) assessments: F2,38 = 7.01, p = 0.003, with a large effect size (η2G = 0.14), and anxiety between first and second assessments: t54 = 3.7, p = <0.001 with a medium effect size (Cohen d = 0.499). Those that followed the coaching program increased in net promoter score between the first and second assessment: t36 = 2.08, p = 0.045 with a small to medium effect size (Cohen d = 0.342). Mediation analyses showed that while increasing number of subtopics completed increased behavioral activation (i.e., match between behavioral intentions and self-reported actual behaviors), behavioral activation did not mediate the relationship to improvements in health outcome assessments. Conclusions Findings show that: (i) there is public demand for chatbot led digital coaching, (ii) such tools can be effective in delivering treatment success, and (iii) they are highly valued by their long-term user base. As the current intervention was developed at rapid speed to meet the emergency pandemic context, the future looks bright for other public health focused chatbot-led digital health interventions.
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Affiliation(s)
- Joseph Ollier
- Mobiliar Lab for Analytics, Chair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Pavani Suryapalli
- Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
| | - Elgar Fleisch
- Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
- Centre for Digital Health Interventions, Chair of Information Management, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Florian von Wangenheim
- Mobiliar Lab for Analytics, Chair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Centre for Digital Health Interventions, Chair of Information Management, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Jacqueline Louise Mair
- Centre for Digital Health Interventions, Chair of Information Management, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Alicia Salamanca-Sanabria
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore
| | - Tobias Kowatsch
- Centre for Digital Health Interventions, Chair of Information Management, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St. Gallen, St. Gallen, Switzerland
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Teepe GW, Lukic YX, Kleim B, Jacobson NC, Schneider F, Santhanam P, Fleisch E, Kowatsch T. Development of a digital biomarker and intervention for subclinical depression: study protocol for a longitudinal waitlist control study. BMC Psychol 2023; 11:186. [PMID: 37349832 PMCID: PMC10288725 DOI: 10.1186/s40359-023-01215-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 05/18/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND Depression remains a global health problem, with its prevalence rising worldwide. Digital biomarkers are increasingly investigated to initiate and tailor scalable interventions targeting depression. Due to the steady influx of new cases, focusing on treatment alone will not suffice; academics and practitioners need to focus on the prevention of depression (i.e., addressing subclinical depression). AIM With our study, we aim to (i) develop digital biomarkers for subclinical symptoms of depression, (ii) develop digital biomarkers for severity of subclinical depression, and (iii) investigate the efficacy of a digital intervention in reducing symptoms and severity of subclinical depression. METHOD Participants will interact with the digital intervention BEDDA consisting of a scripted conversational agent, the slow-paced breathing training Breeze, and actionable advice for different symptoms. The intervention comprises 30 daily interactions to be completed in less than 45 days. We will collect self-reports regarding mood, agitation, anhedonia (proximal outcomes; first objective), self-reports regarding depression severity (primary distal outcome; second and third objective), anxiety severity (secondary distal outcome; second and third objective), stress (secondary distal outcome; second and third objective), voice, and breathing. A subsample of 25% of the participants will use smartwatches to record physiological data (e.g., heart-rate, heart-rate variability), which will be used in the analyses for all three objectives. DISCUSSION Digital voice- and breathing-based biomarkers may improve diagnosis, prevention, and care by enabling an unobtrusive and either complementary or alternative assessment to self-reports. Furthermore, our results may advance our understanding of underlying psychophysiological changes in subclinical depression. Our study also provides further evidence regarding the efficacy of standalone digital health interventions to prevent depression. Trial registration Ethics approval was provided by the Ethics Commission of ETH Zurich (EK-2022-N-31) and the study was registered in the ISRCTN registry (Reference number: ISRCTN38841716, Submission date: 20/08/2022).
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Affiliation(s)
- Gisbert W. Teepe
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006 Zürich, Switzerland
| | - Yanick X. Lukic
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006 Zürich, Switzerland
| | - Birgit Kleim
- Department of Psychology, Experimental Psychopathology and Psychotherapy, Binzmühlestrasse 14, Box 8, 8050 Zürich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, Lenggstrasse 31, 8032 Zürich, Switzerland
| | - Nicholas C. Jacobson
- Departments of Biomedical Data Science and Psychiatry, Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, 46 Centerra Parkway, Lebanon, NH 03766 USA
| | - Fabian Schneider
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006 Zürich, Switzerland
| | - Prabhakaran Santhanam
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006 Zürich, Switzerland
| | - Elgar Fleisch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006 Zürich, Switzerland
- Centre for Digital Health Intervention, Institute of Technology Management, University of St.Gallen, Dufourstrasse 40a, 9000 St. Gallen, Switzerland
| | - Tobias Kowatsch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006 Zürich, Switzerland
- Centre for Digital Health Intervention, Institute of Technology Management, University of St.Gallen, Dufourstrasse 40a, 9000 St. Gallen, Switzerland
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Castro O, Mair JL, Salamanca-Sanabria A, Alattas A, Keller R, Zheng S, Jabir A, Lin X, Frese BF, Lim CS, Santhanam P, van Dam RM, Car J, Lee J, Tai ES, Fleisch E, von Wangenheim F, Tudor Car L, Müller-Riemenschneider F, Kowatsch T. Development of "LvL UP 1.0": a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders. Front Digit Health 2023; 5:1039171. [PMID: 37234382 PMCID: PMC10207359 DOI: 10.3389/fdgth.2023.1039171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 04/06/2023] [Indexed: 05/28/2023] Open
Abstract
Background Non-communicable diseases (NCDs) and common mental disorders (CMDs) are the leading causes of death and disability worldwide. Lifestyle interventions via mobile apps and conversational agents present themselves as low-cost, scalable solutions to prevent these conditions. This paper describes the rationale for, and development of, "LvL UP 1.0″, a smartphone-based lifestyle intervention aimed at preventing NCDs and CMDs. Materials and Methods A multidisciplinary team led the intervention design process of LvL UP 1.0, involving four phases: (i) preliminary research (stakeholder consultations, systematic market reviews), (ii) selecting intervention components and developing the conceptual model, (iii) whiteboarding and prototype design, and (iv) testing and refinement. The Multiphase Optimization Strategy and the UK Medical Research Council framework for developing and evaluating complex interventions were used to guide the intervention development. Results Preliminary research highlighted the importance of targeting holistic wellbeing (i.e., both physical and mental health). Accordingly, the first version of LvL UP features a scalable, smartphone-based, and conversational agent-delivered holistic lifestyle intervention built around three pillars: Move More (physical activity), Eat Well (nutrition and healthy eating), and Stress Less (emotional regulation and wellbeing). Intervention components include health literacy and psychoeducational coaching sessions, daily "Life Hacks" (healthy activity suggestions), breathing exercises, and journaling. In addition to the intervention components, formative research also stressed the need to introduce engagement-specific components to maximise uptake and long-term use. LvL UP includes a motivational interviewing and storytelling approach to deliver the coaching sessions, as well as progress feedback and gamification. Offline materials are also offered to allow users access to essential intervention content without needing a mobile device. Conclusions The development process of LvL UP 1.0 led to an evidence-based and user-informed smartphone-based intervention aimed at preventing NCDs and CMDs. LvL UP is designed to be a scalable, engaging, prevention-oriented, holistic intervention for adults at risk of NCDs and CMDs. A feasibility study, and subsequent optimisation and randomised-controlled trials are planned to further refine the intervention and establish effectiveness. The development process described here may prove helpful to other intervention developers.
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Affiliation(s)
- Oscar Castro
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Jacqueline Louise Mair
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Alicia Salamanca-Sanabria
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Aishah Alattas
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Roman Keller
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Shenglin Zheng
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Ahmad Jabir
- Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Xiaowen Lin
- Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Bea Franziska Frese
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Centre for Digital Health Interventions,Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
| | - Chang Siang Lim
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Prabhakaran Santhanam
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Rob M. van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington DC, DC, United States
| | - Josip Car
- Centre for Population Health Sciences, LKCMedicine, Nanyang Technological University, Singapore, Singapore
- Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Jimmy Lee
- Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
- Research Division, Institute of Mental Health, Singapore, Singapore
- North Region & Department of Psychosis, Institute of Mental Health, Singapore, Singapore
| | - E Shyong Tai
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Elgar Fleisch
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Centre for Digital Health Interventions,Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
| | - Florian von Wangenheim
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Lorainne Tudor Car
- Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
- Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Falk Müller-Riemenschneider
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Digital Health Center, Berlin Institute of Health, Charite University Medical Centre Berlin, Berlin, Germany
| | - Tobias Kowatsch
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St. Gallen, St. Gallen, Switzerland
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8
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Mair JL, Castro O, Salamanca-Sanabria A, Frese BF, von Wangenheim F, Tai ES, Kowatsch T, Müller-Riemenschneider F. Exploring the potential of mobile health interventions to address behavioural risk factors for the prevention of non-communicable diseases in Asian populations: a qualitative study. BMC Public Health 2023; 23:753. [PMID: 37095486 PMCID: PMC10123969 DOI: 10.1186/s12889-023-15598-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 04/04/2023] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Changing lifestyle patterns over the last decades have seen growing numbers of people in Asia affected by non-communicable diseases and common mental health disorders, including diabetes, cancer, and/or depression. Interventions targeting healthy lifestyle behaviours through mobile technologies, including new approaches such as chatbots, may be an effective, low-cost approach to prevent these conditions. To ensure uptake and engagement with mobile health interventions, however, it is essential to understand the end-users' perspectives on using such interventions. The aim of this study was to explore perceptions, barriers, and facilitators to the use of mobile health interventions for lifestyle behaviour change in Singapore. METHODS Six virtual focus group discussions were conducted with a total of 34 participants (mean ± SD; aged 45 ± 3.6 years; 64.7% females). Focus group recordings were transcribed verbatim and analysed using an inductive thematic analysis approach, followed by deductive mapping according to perceptions, barriers, facilitators, mixed factors, or strategies. RESULTS Five themes were identified: (i) holistic wellbeing is central to healthy living (i.e., the importance of both physical and mental health); (ii) encouraging uptake of a mobile health intervention is influenced by factors such as incentives and government backing; (iii) trying out a mobile health intervention is one thing, sticking to it long term is another and there are key factors, such as personalisation and ease of use that influence sustained engagement with mobile health interventions; (iv) perceptions of chatbots as a tool to support healthy lifestyle behaviour are influenced by previous negative experiences with chatbots, which might hamper uptake; and (v) sharing health-related data is OK, but with conditions such as clarity on who will have access to the data, how it will be stored, and for what purpose it will be used. CONCLUSIONS Findings highlight several factors that are relevant for the development and implementation of mobile health interventions in Singapore and other Asian countries. Recommendations include: (i) targeting holistic wellbeing, (ii) tailoring content to address environment-specific barriers, (iii) partnering with government and/or local (non-profit) institutions in the development and/or promotion of mobile health interventions, (iv) managing expectations regarding the use of incentives, and (iv) identifying potential alternatives or complementary approaches to the use of chatbots, particularly for mental health.
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Affiliation(s)
- Jacqueline Louise Mair
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore.
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
| | - Oscar Castro
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore.
| | - Alicia Salamanca-Sanabria
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore
| | - Bea Franziska Frese
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore
| | - Florian von Wangenheim
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - E Shyong Tai
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Tobias Kowatsch
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St.Gallen, St.Gallen, Switzerland
| | - Falk Müller-Riemenschneider
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Digital Health Center, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
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Salamanca-Sanabria A, Jabir AI, Lin X, Alattas A, Kocaballi AB, Lee J, Kowatsch T, Tudor Car L. Exploring the Perceptions of mHealth Interventions for the Prevention of Common Mental Disorders in University Students in Singapore: Qualitative Study. J Med Internet Res 2023; 25:e44542. [PMID: 36939808 PMCID: PMC10131767 DOI: 10.2196/44542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 02/08/2023] [Accepted: 02/24/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND Mental health interventions delivered through mobile health (mHealth) technologies can increase the access to mental health services, especially among university students. The development of mHealth intervention is complex and needs to be context sensitive. There is currently limited evidence on the perceptions, needs, and barriers related to these interventions in the Southeast Asian context. OBJECTIVE This qualitative study aimed to explore the perception of university students and mental health supporters in Singapore about mental health services, campaigns, and mHealth interventions with a focus on conversational agent interventions for the prevention of common mental disorders such as anxiety and depression. METHODS We conducted 6 web-based focus group discussions with 30 university students and one-to-one web-based interviews with 11 mental health supporters consisting of faculty members tasked with student pastoral care, a mental health first aider, counselors, psychologists, a clinical psychologist, and a psychiatrist. The qualitative analysis followed a reflexive thematic analysis framework. RESULTS The following 6 main themes were identified: a healthy lifestyle as students, access to mental health services, the role of mental health promotion campaigns, preferred mHealth engagement features, factors that influence the adoption of mHealth interventions, and cultural relevance of mHealth interventions. The interpretation of our findings shows that students were reluctant to use mental health services because of the fear of stigma and a possible lack of confidentiality. CONCLUSIONS Study participants viewed mHealth interventions for mental health as part of a blended intervention. They also felt that future mental health mHealth interventions should be more personalized and capable of managing adverse events such as suicidal ideation.
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Affiliation(s)
- Alicia Salamanca-Sanabria
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise, Singapore, Singapore
| | - Ahmad Ishqi Jabir
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Xiaowen Lin
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Aishah Alattas
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise, Singapore, Singapore
| | - A Baki Kocaballi
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia
- School of Computer Science, University of Technology Sydney, Sydney, Australia
| | - Jimmy Lee
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Research Division, Institute of Mental Health, Singapore, Singapore
- Department of Psychosis, Institute of Mental Health, Singapore, Singapore
| | - Tobias Kowatsch
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise, Singapore, Singapore
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St. Gallen, St. Gallen, Switzerland
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Lorainne Tudor Car
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom
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10
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Adabla S, Nabors LA, Sanyaolu O, Olaniyan A, Bernstein JA. Scoping review: multiple stakeholders and child asthma management interventions. J Asthma 2023:1-10. [PMID: 36744817 DOI: 10.1080/02770903.2023.2176775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE This study reviewed research to identify interventions aimed at improving asthma management among children by educating parents and other professionals. DATA SOURCES PubMed, Medline, and Embase databases were utilized. STUDY SELECTIONS Three databases were searched for child asthma management interventions published between 2012-2022 in English. Search terms included children, asthma, intervention(s), community pediatrics, coaches, schools, and stakeholders. Inclusion criteria were being an experimental study focused on children with asthma (birth-18 years), including stakeholder involvement, education, and a community focus. The search yielded 153 articles; nine were reviewed. RESULTS In general, stakeholders developed programs that resulted in improvements in asthma symptoms, knowledge of asthma management, perceptions of health care, and decreased emergency health care visits. Successful interventions involved education about asthma management, providing medications, and partnerships with school staff, healthcare teams, and community members. Effective coordination and communication contributed to successful program implementation. Using technology for asthma management education was effective in tracking access to care and facilitated the delivery of medications. CONCLUSION The findings indicate that interventions were effective in improving child asthma management. Stakeholder partnerships were critical to the effectiveness of interventions. Marketing the intervention and encouraging communication with parents also fostered success. Being able to assess the home environment and staying in contact with parents were barriers to these interventions. Conducting randomized controlled trials using the interventions found effective in these studies to assess change in symptoms and emergency care visits over time would yield important information about their long-term success and cost for implementation.
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Affiliation(s)
- Samuel Adabla
- Health Promotion and Education Program, School of Human Services, University of Cincinnati, Cincinnati, OH, USA
| | - Laura A Nabors
- Health Promotion and Education Program, School of Human Services, University of Cincinnati, Cincinnati, OH, USA
| | - Olutosin Sanyaolu
- Health Promotion and Education Program, School of Human Services, University of Cincinnati, Cincinnati, OH, USA
| | - Afolakemi Olaniyan
- Health Promotion and Education Program, School of Human Services, University of Cincinnati, Cincinnati, OH, USA
| | - Jonathan A Bernstein
- Department of Internal Medicine, Division of Immunology/Allergy Section, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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11
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Eysenbach G, May R. Developing a Technical-Oriented Taxonomy to Define Archetypes of Conversational Agents in Health Care: Literature Review and Cluster Analysis. J Med Internet Res 2023; 25:e41583. [PMID: 36716093 PMCID: PMC9926340 DOI: 10.2196/41583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/20/2022] [Accepted: 12/19/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The evolution of artificial intelligence and natural language processing generates new opportunities for conversational agents (CAs) that communicate and interact with individuals. In the health domain, CAs became popular as they allow for simulating the real-life experience in a health care setting, which is the conversation with a physician. However, it is still unclear which technical archetypes of health CAs can be distinguished. Such technical archetypes are required, among other things, for harmonizing evaluation metrics or describing the landscape of health CAs. OBJECTIVE The objective of this work was to develop a technical-oriented taxonomy for health CAs and characterize archetypes of health CAs based on their technical characteristics. METHODS We developed a taxonomy of technical characteristics for health CAs based on scientific literature and empirical data and by applying a taxonomy development framework. To demonstrate the applicability of the taxonomy, we analyzed the landscape of health CAs of the last years based on a literature review. To form technical design archetypes of health CAs, we applied a k-means clustering method. RESULTS Our taxonomy comprises 18 unique dimensions corresponding to 4 perspectives of technical characteristics (setting, data processing, interaction, and agent appearance). Each dimension consists of 2 to 5 characteristics. The taxonomy was validated based on 173 unique health CAs that were identified out of 1671 initially retrieved publications. The 173 CAs were clustered into 4 distinctive archetypes: a text-based ad hoc supporter; a multilingual, hybrid ad hoc supporter; a hybrid, single-language temporary advisor; and, finally, an embodied temporary advisor, rule based with hybrid input and output options. CONCLUSIONS From the cluster analysis, we learned that the time dimension is important from a technical perspective to distinguish health CA archetypes. Moreover, we were able to identify additional distinctive, dominant characteristics that are relevant when evaluating health-related CAs (eg, input and output options or the complexity of the CA personality). Our archetypes reflect the current landscape of health CAs, which is characterized by rule based, simple systems in terms of CA personality and interaction. With an increase in research interest in this field, we expect that more complex systems will arise. The archetype-building process should be repeated after some time to check whether new design archetypes emerge.
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Affiliation(s)
| | - Richard May
- Harz University of Applied Sciences, Wernigerode, Germany
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12
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Simonovic N, Taber JM, Scherr CL, Dean M, Hua J, Howell JL, Chaudhry BM, Wain KE, Politi MC. Uncertainty in healthcare and health decision making: Five methodological and conceptual research recommendations from an interdisciplinary team. J Behav Med 2022. [DOI: 10.1007/s10865-022-00384-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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13
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Martinengo L, Lum E, Car J. Evaluation of chatbot-delivered interventions for self-management of depression: Content analysis. J Affect Disord 2022; 319:598-607. [PMID: 36150405 DOI: 10.1016/j.jad.2022.09.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 09/07/2022] [Accepted: 09/13/2022] [Indexed: 10/14/2022]
Abstract
BACKGROUND Conversational agents (CAs) or chatbots are increasingly used for depression, anxiety, and wellbeing management. CAs are considered acceptable and helpful. However, little is known about the adequacy of CA responses. This study assessed the structure, content, and user-customization of mental health CA dialogues with users with depression or at risk of suicide. METHODS We used content analysis to examine the dialogues of CAs previously included in three assessments of mental health apps (depression education, self-guided cognitive behavioural therapy, and suicide prevention) performed between 2019 and 2020. Two standardized user personas with depression were developed to interact with the CA. All conversations were saved as screenshots, transcribed verbatim, and coded inductively. RESULTS Nine CAs were included. Seven CAs (78%) had Android and iOS versions; five CAs (56%) had at least 500,000 downloads. The analysis generated eight categories: self-introduction, personalization, appropriateness of CA responses, conveying empathy, guiding users through mood-boosting activities, mood monitoring, suicide risk management, and others. CAs could engage in empathic, non-judgemental conversations with users, offer support, and guide psychotherapeutic exercises. LIMITATIONS CA evaluations were performed using standardized personas, not real-world users. CAs were included for evaluation only if retrieved in the search strategies associated with the previous assessment studies. CONCLUSION Assessed CAs offered anonymous, empathic, non-judgemental interactions that align with evidence for face-to-face psychotherapy. CAs from app stores are not suited to provide comprehensive suicide risk management. Further research should evaluate the effectiveness of CA-led interventions in mental health care and in enhancing suicide risk management strategies.
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Affiliation(s)
- Laura Martinengo
- Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore
| | - Elaine Lum
- Health Services & Systems Research, Duke-NUS Medical School, Singapore
| | - Josip Car
- Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore; Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom.
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14
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Southgate G, Yassaee AA, Harmer MJ, Livesey H, Pryde K, Roland D. Use of Telemedicine in Pediatric Services for 4 Representative Clinical Conditions: Scoping Review. J Med Internet Res 2022; 24:e38267. [DOI: 10.2196/38267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/21/2022] [Accepted: 09/02/2022] [Indexed: 11/13/2022] Open
Abstract
Background
Telemedicine is becoming routine in health care. Postpandemic, a universal return to face-to-face consultations may risk a loss of some of the advantages of telemedicine. However, rapid implementation and adoption without robust evaluation of usability, efficacy, and effectiveness could potentially lead to suboptimal health outcomes and downstream challenges to providers.
Objective
This review assesses telemedicine interventions against international guidance and sufficiency of evidence to support postpandemic utilization in pediatric settings.
Methods
This scoping review was performed following searches on PubMed, Embase, and CINAHL databases on April 15, 2021, and May 31, 2022, and examined studies focused on telemedicine, remote consultation, video call, or remote patient monitoring in children (0-18 years) receiving outpatient care for diabetes, asthma, epilepsy, or renal disease. Exclusion criteria included studies published before 2011 as the technologies used have likely been improved or replaced, studies in adult populations or where it was not possible to disaggregate data for participants younger than 18 years as the focus of the review was on pediatric care, and studies not published in English. Data were extracted by 4 authors, and the data were corroborated by a second reviewer. Studies were examined for feasibility and usability, clinical and process outcomes, and cost-effectiveness.
Results
Of the 3158 studies identified, 56 were suitable for final inclusion and analysis. Data on feasibility or usability of interventions (48 studies) were overwhelmingly positive in support of telemedicine interventions, with common themes including convenience, perceived cost savings, and ease of use. However, use in preference to usual care was rarely explored. Clinical and process outcome data (31 studies) were mostly positive. Across all studies, there was limited measurement of standardized clinical outcomes, although these were more commonly reported in asthma (peak flow) and diabetes (glycated hemoglobin [HbA1c]). Implementation science data generally supported cost-effectiveness of telemedicine with a reduction of health care costs.
Conclusions
There is promising evidence supporting telemedicine in pediatric settings. However, there is a lack of evaluation of telemedicine in comparison with usual outpatient care for noninferiority of clinical outcomes, and this review highlights the need for a more standardized approach to evaluation of digital interventions.
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15
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de Buisonjé DR, Reijnders T, Cohen Rodrigues TR, Prabhakaran S, Kowatsch T, Lipman SA, Bijmolt THA, Breeman LD, Janssen VR, Kraaijenhagen RA, Kemps HMC, Evers AWM. Investigating Rewards and Deposit Contract Financial Incentives for Physical Activity Behavior Change Using a Smartphone App: Randomized Controlled Trial. J Med Internet Res 2022; 24:e38339. [PMID: 36201384 DOI: 10.2196/38339] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 08/04/2022] [Accepted: 08/11/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Financial incentive interventions for improving physical activity have proven to be effective but costly. Deposit contracts (in which participants pledge their own money) could be an affordable alternative. In addition, deposit contracts may have superior effects by exploiting the power of loss aversion. Previous research has often operationalized deposit contracts through loss framing a financial reward (without requiring a deposit) to mimic the feelings of loss involved in a deposit contract. OBJECTIVE This study aimed to disentangle the effects of incurring actual losses (through self-funding a deposit contract) and loss framing. We investigated whether incentive conditions are more effective than a no-incentive control condition, whether deposit contracts have a lower uptake than financial rewards, whether deposit contracts are more effective than financial rewards, and whether loss frames are more effective than gain frames. METHODS Healthy participants (N=126) with an average age of 22.7 (SD 2.84) years participated in a 20-day physical activity intervention. They downloaded a smartphone app that provided them with a personalized physical activity goal and either required a €10 (at the time of writing: €1=US $0.98) deposit up front (which could be lost) or provided €10 as a reward, contingent on performance. Daily feedback on incentive earnings was provided and framed as either a loss or gain. We used a 2 (incentive type: deposit or reward) × 2 (feedback frame: gain or loss) between-subjects factorial design with a no-incentive control condition. Our primary outcome was the number of days participants achieved their goals. The uptake of the intervention was a secondary outcome. RESULTS Overall, financial incentive conditions (mean 13.10, SD 6.33 days goal achieved) had higher effectiveness than the control condition (mean 8.00, SD 5.65 days goal achieved; P=.002; ηp2=0.147). Deposit contracts had lower uptake (29/47, 62%) than rewards (50/50, 100%; P<.001; Cramer V=0.492). Furthermore, 2-way analysis of covariance showed that deposit contracts (mean 14.88, SD 6.40 days goal achieved) were not significantly more effective than rewards (mean 12.13, SD 6.17 days goal achieved; P=.17). Unexpectedly, loss frames (mean 10.50, SD 6.22 days goal achieved) were significantly less effective than gain frames (mean 14.67, SD 5.95 days goal achieved; P=.007; ηp2=0.155). CONCLUSIONS Financial incentives help increase physical activity, but deposit contracts were not more effective than rewards. Although self-funded deposit contracts can be offered at low cost, low uptake is an important obstacle to large-scale implementation. Unexpectedly, loss framing was less effective than gain framing. Therefore, we urge further research on their boundary conditions before using loss-framed incentives in practice. Because of limited statistical power regarding some research questions, the results of this study should be interpreted with caution, and future work should be done to confirm these findings. TRIAL REGISTRATION Open Science Framework Registries osf.io/34ygt; https://osf.io/34ygt.
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Affiliation(s)
- David R de Buisonjé
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, Netherlands
| | - Thomas Reijnders
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, Netherlands
- Department of Human-Centered Design, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Talia R Cohen Rodrigues
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, Netherlands
| | - Santhanam Prabhakaran
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Tobias Kowatsch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St. Gallen, St. Gallen, Switzerland
| | - Stefan A Lipman
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - Tammo H A Bijmolt
- Faculty of Economics and Business, University of Groningen, Groningen, Netherlands
| | - Linda D Breeman
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, Netherlands
| | - Veronica R Janssen
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Hareld M C Kemps
- Department of Cardiology, Máxima Medical Center, Veldhoven, Netherlands
| | - Andrea W M Evers
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, Netherlands
- Medical Delta, Leiden University, Technical University Delft, Erasmus University, Delft, Netherlands
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16
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Wilson L, Marasoiu M. The Development and Use of Chatbots in Public Health: Scoping Review. JMIR Hum Factors 2022; 9:e35882. [PMID: 36197708 PMCID: PMC9536768 DOI: 10.2196/35882] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 07/14/2022] [Accepted: 08/02/2022] [Indexed: 01/13/2023] Open
Abstract
Background Chatbots are computer programs that present a conversation-like interface through which people can access information and services. The COVID-19 pandemic has driven a substantial increase in the use of chatbots to support and complement traditional health care systems. However, despite the uptake in their use, evidence to support the development and deployment of chatbots in public health remains limited. Recent reviews have focused on the use of chatbots during the COVID-19 pandemic and the use of conversational agents in health care more generally. This paper complements this research and addresses a gap in the literature by assessing the breadth and scope of research evidence for the use of chatbots across the domain of public health. Objective This scoping review had 3 main objectives: (1) to identify the application domains in public health in which there is the most evidence for the development and use of chatbots; (2) to identify the types of chatbots that are being deployed in these domains; and (3) to ascertain the methods and methodologies by which chatbots are being evaluated in public health applications. This paper explored the implications for future research on the development and deployment of chatbots in public health in light of the analysis of the evidence for their use. Methods Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines for scoping reviews, relevant studies were identified through searches conducted in the MEDLINE, PubMed, Scopus, Cochrane Central Register of Controlled Trials, IEEE Xplore, ACM Digital Library, and Open Grey databases from mid-June to August 2021. Studies were included if they used or evaluated chatbots for the purpose of prevention or intervention and for which the evidence showed a demonstrable health impact. Results Of the 1506 studies identified, 32 were included in the review. The results show a substantial increase in the interest of chatbots in the past few years, shortly before the pandemic. Half (16/32, 50%) of the research evaluated chatbots applied to mental health or COVID-19. The studies suggest promise in the application of chatbots, especially to easily automated and repetitive tasks, but overall, the evidence for the efficacy of chatbots for prevention and intervention across all domains is limited at present. Conclusions More research is needed to fully understand the effectiveness of using chatbots in public health. Concerns with the clinical, legal, and ethical aspects of the use of chatbots for health care are well founded given the speed with which they have been adopted in practice. Future research on their use should address these concerns through the development of expertise and best practices specific to public health, including a greater focus on user experience.
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Affiliation(s)
- Lee Wilson
- Centre for Policy Futures, University of Queensland, St Lucia, Queensland, Australia
| | - Mariana Marasoiu
- Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom
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17
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Dhinagaran DA, Martinengo L, Ho MHR, Joty S, Kowatsch T, Atun R, Tudor Car L. Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER): Development of a Conceptual Framework. JMIR Mhealth Uhealth 2022; 10:e38740. [PMID: 36194462 PMCID: PMC9579935 DOI: 10.2196/38740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/02/2022] [Accepted: 08/26/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Conversational agents (CAs), also known as chatbots, are computer programs that simulate human conversations by using predetermined rule-based responses or artificial intelligence algorithms. They are increasingly used in health care, particularly via smartphones. There is, at present, no conceptual framework guiding the development of smartphone-based, rule-based CAs in health care. To fill this gap, we propose structured and tailored guidance for their design, development, evaluation, and implementation. OBJECTIVE The aim of this study was to develop a conceptual framework for the design, evaluation, and implementation of smartphone-delivered, rule-based, goal-oriented, and text-based CAs for health care. METHODS We followed the approach by Jabareen, which was based on the grounded theory method, to develop this conceptual framework. We performed 2 literature reviews focusing on health care CAs and conceptual frameworks for the development of mobile health interventions. We identified, named, categorized, integrated, and synthesized the information retrieved from the literature reviews to develop the conceptual framework. We then applied this framework by developing a CA and testing it in a feasibility study. RESULTS The Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER) conceptual framework includes 8 iterative steps grouped into 3 stages, as follows: design, comprising defining the goal, creating an identity, assembling the team, and selecting the delivery interface; development, including developing the content and building the conversation flow; and the evaluation and implementation of the CA. They were complemented by 2 cross-cutting considerations-user-centered design and privacy and security-that were relevant at all stages. This conceptual framework was successfully applied in the development of a CA to support lifestyle changes and prevent type 2 diabetes. CONCLUSIONS Drawing on published evidence, the DISCOVER conceptual framework provides a step-by-step guide for developing rule-based, smartphone-delivered CAs. Further evaluation of this framework in diverse health care areas and settings and for a variety of users is needed to demonstrate its validity. Future research should aim to explore the use of CAs to deliver health care interventions, including behavior change and potential privacy and safety concerns.
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Affiliation(s)
| | - Laura Martinengo
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Moon-Ho Ringo Ho
- School of Social Sciences, Nanyang Technological University Singapore, Singapore, Singapore
| | - Shafiq Joty
- School of Computer Sciences and Engineering, Nanyang Technological University Singapore, Singapore, Singapore
| | - Tobias Kowatsch
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St Gallen, St Gallen, Switzerland
- 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
| | - Rifat Atun
- Department of Global Health & Population, Department of Health Policy & Management, Harvard TH Chan School of Public Health, Harvard University, Cambridge, MA, United States
- Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Cambridge, MA, United States
- Health Systems Innovation Lab, Harvard TH Chan School of Public Health, Harvard University, Cambridge, MA, United States
| | - Lorainne Tudor Car
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
- Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom
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18
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Lee D, Agarwal A, Ali Z, Xiong R, Spencer E, Hemmons J, Lacko H, Delgado MK. Real-Time Measurement of Patient Reported Outcomes and Opioid Use Following Urologic Procedures using Automated Text Messaging. Urology 2022; 170:83-90. [PMID: 36115429 DOI: 10.1016/j.urology.2022.07.059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/06/2022] [Accepted: 07/20/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To evaluate opioid consumption and patient-reported pain intensity following urologic procedures. METHODS Adult patients were consented following a urologic procedure, and data was collected through post-operative day 28 in a large tertiary care academic health system. An automated text messaging platform was used to collect patient reported pain intensity, ability to manage pain, and opioid use measured in oxycodone 5 mg tablet equivalents. Outcomes were weighted based on the inverse probability of response to yield representative estimates. RESULTS 1015 (51.8%) patients responded to the text-message survey. The median number of pills prescribed was 10 (IQR 6-10), and the median number of pills taken was 2 (IQR 0-6). By postoperative day 7, the median tablets taken overall was 0. Over the study period, 60.1% (6566) of all tablets prescribed were left unused, and 38.4% of patients did not use any of the prescribed opioids. Across urologic procedures, 6 tablets would accommodate the 75th percentile of patient-reported use, with the exception of major open procedures. CONCLUSIONS In this study utilizing real-time measurement of opioid use and pain levels with text messaging, there was evidence of dramatic over-prescription of opioids relative to use and pain levels. Patient-reported data, collected via text messaging, can support clinicians and policy leaders in forming national guidelines on evidence-based best practices, personalizing prescriptions and guide shared decision making to decrease opioid excess.
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Affiliation(s)
- Daniel Lee
- Division of Urology, University of Pennsylvania Health System, Philadelphia, PA; Corporal Michael J Crescenz Veterans Affairs Medical Center, Philadelphia, PA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA.
| | - Anish Agarwal
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA; Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA; Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA
| | - Zarina Ali
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA
| | - Ruiying Xiong
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA
| | - Evan Spencer
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jessica Hemmons
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia, PA
| | - Hannah Lacko
- Department of Orthopaedic Surgery, University of Pennsylvania, Philadelphia, PA
| | - Mucio K Delgado
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA; Department of Emergency Medicine, Philadelphia Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
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19
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Shan Y, Ji M, Xie W, Qian X, Li R, Zhang X, Hao T. Language Use in Conversational Agent-Based Health Communication: Systematic Review. J Med Internet Res 2022; 24:e37403. [PMID: 35802407 PMCID: PMC9308072 DOI: 10.2196/37403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 05/11/2022] [Accepted: 06/12/2022] [Indexed: 11/23/2022] Open
Abstract
Background Given the growing significance of conversational agents (CAs), researchers have conducted a plethora of relevant studies on various technology- and usability-oriented issues. However, few investigations focus on language use in CA-based health communication to examine its influence on the user perception of CAs and their role in delivering health care services. Objective This review aims to present the language use of CAs in health care to identify the achievements made and breakthroughs to be realized to inform researchers and more specifically CA designers. Methods This review was conducted by following the protocols of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 statement. We first designed the search strategy according to the research aim and then performed the keyword searches in PubMed and ProQuest databases for retrieving relevant publications (n=179). Subsequently, 3 researchers screened and reviewed the publications independently to select studies meeting the predefined selection criteria. Finally, we synthesized and analyzed the eligible articles (N=11) through thematic synthesis. Results Among the 11 included publications, 6 deal exclusively with the language use of the CAs studied, and the remaining 5 are only partly related to this topic. The language use of the CAs in these studies can be roughly classified into six themes: (1) personal pronouns, (2) responses to health and lifestyle prompts, (3) strategic wording and rich linguistic resources, (4) a 3-staged conversation framework, (5) human-like well-manipulated conversations, and (6) symbols and images coupled with phrases. These derived themes effectively engaged users in health communication. Meanwhile, we identified substantial room for improvement based on the inconsistent responses of some CAs and their inability to present large volumes of information on safety-critical health and lifestyle prompts. Conclusions This is the first systematic review of language use in CA-based health communication. The results and limitations identified in the 11 included papers can give fresh insights into the design and development, popularization, and research of CA applications. This review can provide practical implications for incorporating positive language use into the design of health CAs and improving their effective language output in health communication. In this way, upgraded CAs will be more capable of handling various health problems particularly in the context of nationwide and even worldwide public health crises.
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Affiliation(s)
- Yi Shan
- School of Foreign Studies, Nantong University, Nantong, China
| | - Meng Ji
- School of Languages and Cultures, University of Sydney, Sydney, Australia
| | - Wenxiu Xie
- Department of Computer Science, City University of Hong Kong, Hong Kong, China
| | - Xiaobo Qian
- School of Computer Science, South China Normal University, Guangzhou, China
| | - Rongying Li
- School of Artificial Intelligence, South China Normal University, Guangzhou, China
| | - Xiaomin Zhang
- Department of Linguistics, Macquarie University, Sydney, Australia
| | - Tianyong Hao
- School of Computer Science, South China Normal University, Guangzhou, China
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20
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Weeks R, Cooper L, Sangha P, Sedoc J, White S, Toledo A, Gretz S, Lahav D, Martin N, Michel A, Lee JH, Slonim N, Bar-Zeev N. COVID-19 Vaccine Communication via Chatbot: A Qualitative Study on Message Preferences of Young Adults and Public Health Workers in Urban American Communities. J Med Internet Res 2022; 24:e38418. [PMID: 35737898 PMCID: PMC9301547 DOI: 10.2196/38418] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/25/2022] [Accepted: 06/14/2022] [Indexed: 11/26/2022] Open
Abstract
Background Automated conversational agents, or chatbots, have a role in reinforcing evidence-based guidance delivered through other media and offer an accessible, individually tailored channel for public engagement. In early-to-mid 2021, young adults and minority populations disproportionately affected by COVID-19 in the United States were more likely to be hesitant toward COVID-19 vaccines, citing concerns regarding vaccine safety and effectiveness. Successful chatbot communication requires purposive understanding of user needs. Objective We aimed to review the acceptability of messages to be delivered by a chatbot named VIRA from Johns Hopkins University. The study investigated which message styles were preferred by young, urban-dwelling Americans as well as public health workers, since we anticipated that the chatbot would be used by the latter as a job aid. Methods We conducted 4 web-based focus groups with 20 racially and ethnically diverse young adults aged 18-28 years and public health workers aged 25-61 years living in or near eastern-US cities. We tested 6 message styles, asking participants to select a preferred response style for a chatbot answering common questions about COVID-19 vaccines. We transcribed, coded, and categorized emerging themes within the discussions of message content, style, and framing. Results Participants preferred messages that began with an empathetic reflection of a user concern and concluded with a straightforward, fact-supported response. Most participants disapproved of moralistic or reasoning-based appeals to get vaccinated, although public health workers felt that such strong statements appealing to communal responsibility were warranted. Responses tested with humor and testimonials did not appeal to the participants. Conclusions To foster credibility, chatbots targeting young people with vaccine-related messaging should aim to build rapport with users by deploying empathic, reflective statements, followed by direct and comprehensive responses to user queries. Further studies are needed to inform the appropriate use of user-customized testimonials and humor in the context of chatbot communication.
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Affiliation(s)
- Rose Weeks
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 415 N Washington Street 5th Floor, Baltimore, US
| | - Lyra Cooper
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 415 N Washington Street 5th Floor, Baltimore, US
| | - Pooja Sangha
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 415 N Washington Street 5th Floor, Baltimore, US
| | - João Sedoc
- Stern School of Business, New York University, New York, US
| | - Sydney White
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 415 N Washington Street 5th Floor, Baltimore, US
| | | | | | | | - Nina Martin
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, US
| | - Alexandra Michel
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 415 N Washington Street 5th Floor, Baltimore, US
| | - Jae Hyoung Lee
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 415 N Washington Street 5th Floor, Baltimore, US
| | | | - Naor Bar-Zeev
- International Vaccine Access Center, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 415 N Washington Street 5th Floor, Baltimore, US
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21
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Jakob R, Harperink S, Rudolf AM, Fleisch E, Haug S, Mair JL, Salamanca-Sanabria A, Kowatsch T. Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review. J Med Internet Res 2022; 24:e35371. [PMID: 35612886 PMCID: PMC9178451 DOI: 10.2196/35371] [Citation(s) in RCA: 71] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 03/31/2022] [Accepted: 04/09/2022] [Indexed: 12/14/2022] Open
Abstract
Background Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions. Objective This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks. Methods A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings. Results The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%). Conclusions This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app’s intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.
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Affiliation(s)
- Robert Jakob
- Centre for Digital Health Interventions, Department of Management, Technology and Economics, ETH Zurich, Zurich, Switzerland
| | - Samira Harperink
- Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
| | - Aaron Maria Rudolf
- Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
| | - Elgar Fleisch
- Centre for Digital Health Interventions, Department of Management, Technology and Economics, ETH Zurich, Zurich, Switzerland.,Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland.,Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise, Singapore, Singapore
| | - Severin Haug
- Swiss Research Institute for Public Health and Addiction, Zurich University, Zurich, Switzerland
| | - Jacqueline Louise Mair
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Alicia Salamanca-Sanabria
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise, Singapore, Singapore
| | - Tobias Kowatsch
- Centre for Digital Health Interventions, Department of Management, Technology and Economics, ETH Zurich, Zurich, Switzerland.,Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland.,Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise, Singapore, Singapore
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22
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Iio M, Sato M, Narita M, Yamamoto-Hanada K, Oishi T, Kishino A, Kawaguchi T, Nishi R, Nagata M, Ohya Y. Development and Feasibility of a Mobile Asthma App for Children and Their Caregivers: Mixed Methods Study. JMIR Form Res 2022; 6:e34509. [PMID: 35594073 PMCID: PMC9166665 DOI: 10.2196/34509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/18/2022] [Accepted: 03/30/2022] [Indexed: 11/17/2022] Open
Abstract
Background Mobile health apps can support the self-management of pediatric asthma. Previous studies on mobile apps for children aged >7 years with asthma are limited, and most reports on asthma apps do not consider interactions between the children and their caregivers. Therefore, we developed an asthma app for children aged 0-12 years and their caregivers based on the results of our previous study regarding user needs. Objective The aim of this study was to evaluate the feasibility of a developed mobile app for children with asthma and their caregivers and to modify and complete the app according to the feasibility results. Methods We recruited children diagnosed with persistent asthma by an allergy specialist at 2 children’s hospitals, 1 university hospital, 2 general hospitals, and 1 pediatric clinic. Thereafter, the app usage was assessed, and questionnaires were administered. This study used convergent mixed methods, including providing user feedback about the pediatric asthma app, completing questionnaire surveys regarding preferences, and obtaining quantitative data about app usage. Quantitative data were analyzed based on the ratings provided for the app features used by the participants, and the usage of the app features was analyzed using descriptive statistics. Qualitative data were analyzed via a descriptive qualitative research analysis and were used to identify codes from the content-characteristic words. Results In total, 30 pairs of children aged 2-12 years and their caregivers responded to the 3-month survey, and 20 pairs of children aged 4-12 years and their caregivers responded to the 6-month survey. In the 3- and 6-month surveys, “record” was the most commonly used feature by both caregivers and children. The average access logs per month among the 20 pairs ranged from 50 to 79 in the 6-month survey. The number of access logs decreased over time. In the qualitative results, app utilization difficulties were identified for 6 categories: record, preparing, alert settings, change settings, mobile phone owner, and display and motivation. Regarding app feasibility, 60% (12/20) of the caregivers strongly agreed or agreed for all evaluation items, while 63% (7/11) of the children strongly agreed or agreed for 6 items, excluding satisfaction. In the qualitative results, feasibility evaluation of the app was classified into 3 categories: high feasibility of the app, improvement points for the app, and personal factors preventing app utilization. Based on the results of the feasibility analysis, the final version of the app was modified and completed. Conclusions The app feasibility among children with asthma and their caregivers was generally good. Children aged 7-12 years used elements such as record, quiz, and manga. This app can support the continuous self-management of pediatric asthma. However, efforts must be taken to maintain and improve the app quality. Trial Registration UMIN Clinical Trials Registry UMIN000039058; https://tinyurl.com/3na9zyf8
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Affiliation(s)
- Misa Iio
- College of Nursing, Kanto Gakuin University, Yokohama, Japan
| | - Miori Sato
- Allergy Center, National Center for Child Health and Development, Setagaya, Japan
| | - Masami Narita
- Department of Pediatrics, Kyorin University School of Medicine, Kyorin University, Mitaka, Japan
| | | | - Taku Oishi
- Department of Pediatrics, Kochi Medical School, Kochi University, Nankoku, Japan
| | - Ai Kishino
- Division of Pediatrics, Tokyo Bay Urayasu Ichikawa Medical Center, Urayasu, Japan
| | | | - Rin Nishi
- Division of Pediatrics, Yutenji Family Clinic, Meguro, Japan
| | - Mayumi Nagata
- College of Nursing, Kanto Gakuin University, Yokohama, Japan
| | - Yukihiro Ohya
- Allergy Center, National Center for Child Health and Development, Setagaya, Japan
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23
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Martinengo L, Jabir AI, Goh WWT, Lo NYW, Ho MHR, Kowatsch T, Atun R, Michie S, Tudor Car L. Conversational agents in healthcare: a scoping review of their behavior change techniques and underpinning theory (Preprint). J Med Internet Res 2022; 24:e39243. [PMID: 36190749 PMCID: PMC9577715 DOI: 10.2196/39243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/05/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
Background Conversational agents (CAs) are increasingly used in health care to deliver behavior change interventions. Their evaluation often includes categorizing the behavior change techniques (BCTs) using a classification system of which the BCT Taxonomy v1 (BCTTv1) is one of the most common. Previous studies have presented descriptive summaries of behavior change interventions delivered by CAs, but no in-depth study reporting the use of BCTs in these interventions has been published to date. Objective This review aims to describe behavior change interventions delivered by CAs and to identify the BCTs and theories guiding their design. Methods We searched PubMed, Embase, Cochrane’s Central Register of Controlled Trials, and the first 10 pages of Google and Google Scholar in April 2021. We included primary, experimental studies evaluating a behavior change intervention delivered by a CA. BCTs coding followed the BCTTv1. Two independent reviewers selected the studies and extracted the data. Descriptive analysis and frequent itemset mining to identify BCT clusters were performed. Results We included 47 studies reporting on mental health (n=19, 40%), chronic disorders (n=14, 30%), and lifestyle change (n=14, 30%) interventions. There were 20/47 embodied CAs (43%) and 27/47 CAs (57%) represented a female character. Most CAs were rule based (34/47, 72%). Experimental interventions included 63 BCTs, (mean 9 BCTs; range 2-21 BCTs), while comparisons included 32 BCTs (mean 2 BCTs; range 2-17 BCTs). Most interventions included BCTs 4.1 “Instruction on how to perform a behavior” (34/47, 72%), 3.3 “Social support” (emotional; 27/47, 57%), and 1.2 “Problem solving” (24/47, 51%). A total of 12/47 studies (26%) were informed by a behavior change theory, mainly the Transtheoretical Model and the Social Cognitive Theory. Studies using the same behavior change theory included different BCTs. Conclusions There is a need for the more explicit use of behavior change theories and improved reporting of BCTs in CA interventions to enhance the analysis of intervention effectiveness and improve the reproducibility of research.
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Affiliation(s)
- Laura Martinengo
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Ahmad Ishqi Jabir
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Westin Wei Tin Goh
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Nicholas Yong Wai Lo
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
| | - Moon-Ho Ringo Ho
- School of Social Sciences, Nanyang Technological University Singapore, Singapore, Singapore
| | - Tobias Kowatsch
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- School of Medicine, University of St.Gallen, St. Gallen, Switzerland
- 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
| | - Rifat Atun
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Cambridge, MA, United States
- Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Cambridge, MA, United States
- Health Systems Innovation Lab, Harvard T.H. Chan School of Public Health, Harvard University, Cambridge, MA, United States
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Harvard University, Cambridge, MA, United States
| | - Susan Michie
- UCL Centre for Behaviour Change, University College London, London, United Kingdom
| | - Lorainne Tudor Car
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore
- Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom
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24
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Smriti D, Kao TSA, Rathod R, Shin JY, Peng W, Williams J, Mujib MI, Colosimo M, Huh-Yoo J. MICA: Motivational Interviewing Conversational Agent for Parents as Proxies for their Children in Healthy Eating (Preprint). JMIR Hum Factors 2022; 9:e38908. [PMID: 36206036 PMCID: PMC9587490 DOI: 10.2196/38908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 08/05/2022] [Accepted: 08/06/2022] [Indexed: 12/02/2022] Open
Abstract
Background Increased adoption of off-the-shelf conversational agents (CAs) brings opportunities to integrate therapeutic interventions. Motivational Interviewing (MI) can then be integrated with CAs for cost-effective access to it. MI can be especially beneficial for parents who often have low motivation because of limited time and resources to eat healthy together with their children. Objective We developed a Motivational Interviewing Conversational Agent (MICA) to improve healthy eating in parents who serve as a proxy for health behavior change in their children. Proxy relationships involve a person serving as a catalyst for behavior change in another person. Parents, serving as proxies, can bring about behavior change in their children. Methods We conducted user test sessions of the MICA prototype to understand the perceived acceptability and usefulness of the MICA prototype by parents. A total of 24 parents of young children participated in 2 user test sessions with MICA, approximately 2 weeks apart. After parents’ interaction with the MICA prototype in each user test session, we used qualitative interviews to understand parents’ perceptions and suggestions for improvements in MICA. Results Findings showed participants’ perceived usefulness of MICAs for helping them self-reflect and motivating them to adopt healthier eating habits together with their children. Participants further suggested various ways in which MICA can help them safely manage their children’s eating behaviors and provide customized support for their proxy needs and goals. Conclusions We have discussed how the user experience of CAs can be improved to uniquely offer support to parents who serve as proxies in changing the behavior of their children. We have concluded with implications for a larger context of designing MI-based CAs for supporting proxy relationships for health behavior change.
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Affiliation(s)
- Diva Smriti
- College of Computing and Informatics, Drexel University, Philadelphia, PA, United States
| | - Tsui-Sui Annie Kao
- College of Nursing, Michigan State University, East Lansing, MI, United States
| | - Rahil Rathod
- Tata Consultancy Services, Edison, NJ, United States
| | - Ji Youn Shin
- College of Design, University of Minnesota, Minneapolis, MN, United States
| | - Wei Peng
- College of Communication Arts and Sciences, Michigan State University, East Lansing, MI, United States
| | - Jake Williams
- College of Computing and Informatics, Drexel University, Philadelphia, PA, United States
| | - Munif Ishad Mujib
- College of Computing and Informatics, Drexel University, Philadelphia, PA, United States
| | | | - Jina Huh-Yoo
- College of Computing and Informatics, Drexel University, Philadelphia, PA, United States
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25
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Ollier J, Nißen M, von Wangenheim F. The Terms of "You(s)": How the Term of Address Used by Conversational Agents Influences User Evaluations in French and German Linguaculture. Front Public Health 2022; 9:691595. [PMID: 35071147 PMCID: PMC8767023 DOI: 10.3389/fpubh.2021.691595] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 12/03/2021] [Indexed: 11/26/2022] Open
Abstract
Background: Conversational agents (CAs) are a novel approach to delivering digital health interventions. In human interactions, terms of address often change depending on the context or relationship between interlocutors. In many languages, this encompasses T/V distinction—formal and informal forms of the second-person pronoun “You”—that conveys different levels of familiarity. Yet, few research articles have examined whether CAs' use of T/V distinction across language contexts affects users' evaluations of digital health applications. Methods: In an online experiment (N = 284), we manipulated a public health CA prototype to use either informal or formal T/V distinction forms in French (“tu” vs. “vous”) and German (“du” vs. “Sie”) language settings. A MANCOVA and post-hoc tests were performed to examine the effects of the independent variables (i.e., T/V distinction and Language) and the moderating role of users' demographic profile (i.e., Age and Gender) on eleven user evaluation variables. These were related to four themes: (i) Sociability, (ii) CA-User Collaboration, (iii) Service Evaluation, and (iv) Behavioral Intentions. Results: Results showed a four-way interaction between T/V Distinction, Language, Age, and Gender, influencing user evaluations across all outcome themes. For French speakers, when the informal “T form” (“Tu”) was used, higher user evaluation scores were generated for younger women and older men (e.g., the CA felt more humanlike or individuals were more likely to recommend the CA), whereas when the formal “V form” (“Vous”) was used, higher user evaluation scores were generated for younger men and older women. For German speakers, when the informal T form (“Du”) was used, younger users' evaluations were comparable regardless of Gender, however, as individuals' Age increased, the use of “Du” resulted in lower user evaluation scores, with this effect more pronounced in men. When using the formal V form (“Sie”), user evaluation scores were relatively stable, regardless of Gender, and only increasing slightly with Age. Conclusions: Results highlight how user CA evaluations vary based on the T/V distinction used and language setting, however, that even within a culturally homogenous language group, evaluations vary based on user demographics, thus highlighting the importance of personalizing CA language.
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Affiliation(s)
- Joseph Ollier
- Chair of Technology Marketing, Department of Management, Economics and Technology (D-MTEC), ETH Zürich, Zurich, Switzerland.,Centre for Digital Health Interventions (CDHI), Department of Management, Economics and Technology (D-MTEC), ETH Zürich, Zurich, Switzerland
| | - Marcia Nißen
- Chair of Technology Marketing, Department of Management, Economics and Technology (D-MTEC), ETH Zürich, Zurich, Switzerland.,Centre for Digital Health Interventions (CDHI), Department of Management, Economics and Technology (D-MTEC), ETH Zürich, Zurich, Switzerland
| | - Florian von Wangenheim
- Chair of Technology Marketing, Department of Management, Economics and Technology (D-MTEC), ETH Zürich, Zurich, Switzerland.,Centre for Digital Health Interventions (CDHI), Department of Management, Economics and Technology (D-MTEC), ETH Zürich, Zurich, Switzerland
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Skvortsova A, Cohen Rodrigues T, de Buisonjé D, Kowatsch T, Santhanam P, Veldhuijzen DS, van Middendorp H, Evers A. Increasing the Effectiveness of a Physical Activity Smartphone Intervention With Positive Suggestions: Randomized Controlled Trial. J Med Internet Res 2022; 24:e32130. [PMID: 35230245 PMCID: PMC8924786 DOI: 10.2196/32130] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/29/2021] [Accepted: 12/07/2021] [Indexed: 01/19/2023] Open
Abstract
Background eHealth interventions have the potential to increase the physical activity of users. However, their effectiveness varies, and they often have only short-term effects. A possible way of enhancing their effectiveness is to increase the positive outcome expectations of users by giving them positive suggestions regarding the effectiveness of the intervention. It has been shown that when individuals have positive expectations regarding various types of interventions, they tend to benefit from these interventions more. Objective The main objective of this web-based study is to investigate whether positive suggestions can change the expectations of participants regarding the effectiveness of a smartphone physical activity intervention and subsequently enhance the number of steps the participants take during the intervention. In addition, we study whether suggestions affect perceived app effectiveness, engagement with the app, self-reported vitality, and fatigue of the participants. Methods This study involved a 21-day fully automated physical activity intervention aimed at helping participants to walk more steps. The intervention was delivered via a smartphone-based app that delivered specific tasks to participants (eg, setting activity goals or looking for social support) and recorded their daily step count. Participants were randomized to either a positive suggestions group (69/133, 51.9%) or a control group (64/133, 48.1%). Positive suggestions emphasizing the effectiveness of the intervention were implemented in a web-based flyer sent to the participants before the intervention. Suggestions were repeated on days 8 and 15 of the intervention via the app. Results Participants significantly increased their daily step count from baseline compared with 21 days of the intervention (t107=−8.62; P<.001) regardless of the suggestions. Participants in the positive suggestions group had more positive expectations regarding the app (B=−1.61, SE 0.47; P<.001) and higher expected engagement with the app (B=3.80, SE 0.63; P<.001) than the participants in the control group. No effects of suggestions on the step count (B=−22.05, SE 334.90; P=.95), perceived effectiveness of the app (B=0.78, SE 0.69; P=.26), engagement with the app (B=0.78, SE 0.75; P=.29), and vitality (B=0.01, SE 0.11; P=.95) were found. Positive suggestions decreased the fatigue of the participants during the 3 weeks of the intervention (B=0.11, SE 0.02; P<.001). Conclusions Although the suggestions did not affect the number of daily steps, they increased the positive expectations of the participants and decreased their fatigue. These results indicate that adding positive suggestions to eHealth physical activity interventions might be a promising way of influencing subjective but not objective outcomes of interventions. Future research should focus on finding ways of strengthening the suggestions, as they have the potential to boost the effectiveness of eHealth interventions. Trial Registration Open Science Framework 10.17605/OSF.IO/CWJES; https://osf.io/cwjes
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Affiliation(s)
- Aleksandrina Skvortsova
- Department of Psychology, McGill University, Montreal, QC, Canada.,Health, Medical and Neuropsychology, Faculty of Social and Behavioural Sciences, Leiden, Netherlands
| | - Talia Cohen Rodrigues
- Health, Medical and Neuropsychology, Faculty of Social and Behavioural Sciences, Leiden, Netherlands
| | - David de Buisonjé
- Health, Medical and Neuropsychology, Faculty of Social and Behavioural Sciences, Leiden, Netherlands
| | - Tobias Kowatsch
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland.,Centre for Digital Health Interventions, Institute of Technology Management, University of St.Gallen, St.Gallen, Switzerland
| | - Prabhakaran Santhanam
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Dieuwke S Veldhuijzen
- Health, Medical and Neuropsychology, Faculty of Social and Behavioural Sciences, Leiden, Netherlands
| | - Henriët van Middendorp
- Health, Medical and Neuropsychology, Faculty of Social and Behavioural Sciences, Leiden, Netherlands
| | - Andrea Evers
- Health, Medical and Neuropsychology, Faculty of Social and Behavioural Sciences, Leiden, Netherlands.,Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands.,Medical Delta, Leiden University, Technical University Delft and Erasmus University, Leiden, Delft, Rotterdam, Netherlands
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Keller R, Hartmann S, Teepe GW, Lohse KM, Alattas A, Tudor Car L, Müller-Riemenschneider F, von Wangenheim F, Mair JL, Kowatsch T. Digital Behavior Change Interventions for the Prevention and Management of Type 2 Diabetes: Systematic Market Analysis. J Med Internet Res 2022; 24:e33348. [PMID: 34994693 PMCID: PMC8783286 DOI: 10.2196/33348] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/22/2021] [Accepted: 11/15/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Advancements in technology offer new opportunities for the prevention and management of type 2 diabetes. Venture capital companies have been investing in digital diabetes companies that offer digital behavior change interventions (DBCIs). However, little is known about the scientific evidence underpinning such interventions or the degree to which these interventions leverage novel technology-driven automated developments such as conversational agents (CAs) or just-in-time adaptive intervention (JITAI) approaches. OBJECTIVE Our objectives were to identify the top-funded companies offering DBCIs for type 2 diabetes management and prevention, review the level of scientific evidence underpinning the DBCIs, identify which DBCIs are recognized as evidence-based programs by quality assurance authorities, and examine the degree to which these DBCIs include novel automated approaches such as CAs and JITAI mechanisms. METHODS A systematic search was conducted using 2 venture capital databases (Crunchbase Pro and Pitchbook) to identify the top-funded companies offering interventions for type 2 diabetes prevention and management. Scientific publications relating to the identified DBCIs were identified via PubMed, Google Scholar, and the DBCIs' websites, and data regarding intervention effectiveness were extracted. The Diabetes Prevention Recognition Program (DPRP) of the Center for Disease Control and Prevention in the United States was used to identify the recognition status. The DBCIs' publications, websites, and mobile apps were reviewed with regard to the intervention characteristics. RESULTS The 16 top-funded companies offering DBCIs for type 2 diabetes received a total funding of US $2.4 billion as of June 15, 2021. Only 4 out of the 50 identified publications associated with these DBCIs were fully powered randomized controlled trials (RCTs). Further, 1 of those 4 RCTs showed a significant difference in glycated hemoglobin A1c (HbA1c) outcomes between the intervention and control groups. However, all the studies reported HbA1c improvements ranging from 0.2% to 1.9% over the course of 12 months. In addition, 6 interventions were fully recognized by the DPRP to deliver evidence-based programs, and 2 interventions had a pending recognition status. Health professionals were included in the majority of DBCIs (13/16, 81%,), whereas only 10% (1/10) of accessible apps involved a CA as part of the intervention delivery. Self-reports represented most of the data sources (74/119, 62%) that could be used to tailor JITAIs. CONCLUSIONS Our findings suggest that the level of funding received by companies offering DBCIs for type 2 diabetes prevention and management does not coincide with the level of evidence on the intervention effectiveness. There is considerable variation in the level of evidence underpinning the different DBCIs and an overall need for more rigorous effectiveness trials and transparent reporting by quality assurance authorities. Currently, very few DBCIs use automated approaches such as CAs and JITAIs, limiting the scalability and reach of these solutions.
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Affiliation(s)
- Roman Keller
- Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise, Singapore-ETH Centre, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Sven Hartmann
- Centre for Digital Health Interventions, Institute of Technology Management, University of St Gallen, St Gallen, Switzerland
| | - Gisbert Wilhelm Teepe
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Kim-Morgaine Lohse
- Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Aishah Alattas
- Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise, Singapore-ETH Centre, Singapore, Singapore
| | - Lorainne Tudor Car
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.,Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Falk Müller-Riemenschneider
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Florian von Wangenheim
- Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise, Singapore-ETH Centre, Singapore, Singapore.,Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Jacqueline Louise Mair
- Future Health Technologies Programme, Campus for Research Excellence and Technological Enterprise, Singapore-ETH Centre, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Tobias Kowatsch
- 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.,Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
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