Multinational landscape of health app policy: toward regulatory consensus on digital health

Diao, James A.; Venkatesh, Kaushik P.; Raza, Marium M.; Kvedar, Joseph C.

doi:10.1038/s41746-022-00604-x

Cited by 8 publications

(6 citation statements)

References 8 publications

(7 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, platforms and databases of mental health smartphone-based interventions have been developed [ 99 , 100 ], including information on the characteristics of the intervention, functions included, population for whom they are directed, evidence-based validation, professional support, and expert reviews. Future directions point toward international expert consensus, providing homogeneous valid indications on digital solutions’ regulation [ 101 ] and clinical validation [ 102 ].…”

Section: Discussionmentioning

confidence: 99%

Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies

Anmella¹,

Sanabra²,

Primé-Tous³

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

Background Many people attending primary care (PC) have anxiety-depressive symptoms and work-related burnout compounded by a lack of resources to meet their needs. The COVID-19 pandemic has exacerbated this problem, and digital tools have been proposed as a solution. Objective We aimed to present the development, feasibility, and potential effectiveness of Vickybot, a chatbot aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout, and detecting suicide risk in patients from PC and health care workers. Methods Healthy controls (HCs) tested Vickybot for reliability. For the simulation study, HCs used Vickybot for 2 weeks to simulate different clinical situations. For feasibility and effectiveness study, people consulting PC or health care workers with mental health problems used Vickybot for 1 month. Self-assessments for anxiety (Generalized Anxiety Disorder 7-item) and depression (Patient Health Questionnaire-9) symptoms and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every 2 weeks. Feasibility was determined from both subjective and objective user-engagement indicators (UEIs). Potential effectiveness was measured using paired 2-tailed t tests or Wilcoxon signed-rank test for changes in self-assessment scores. Results Overall, 40 HCs tested Vickybot simultaneously, and the data were reliably transmitted and registered. For simulation, 17 HCs (n=13, 76% female; mean age 36.5, SD 9.7 years) received 98.8% of the expected modules. Suicidal alerts were received correctly. For the feasibility and potential effectiveness study, 34 patients (15 from PC and 19 health care workers; 76% [26/34] female; mean age 35.3, SD 10.1 years) completed the first self-assessments, with 100% (34/34) presenting anxiety symptoms, 94% (32/34) depressive symptoms, and 65% (22/34) work-related burnout. In addition, 27% (9/34) of patients completed the second self-assessment after 2 weeks of use. No significant differences were found between the first and second self-assessments for anxiety (t8=1.000; P=.34) or depressive (t8=0.40; P=.70) symptoms. However, work-related burnout scores were moderately reduced (z=−2.07, P=.04, r=0.32). There was a nonsignificant trend toward a greater reduction in anxiety-depressive symptoms and work-related burnout with greater use of the chatbot. Furthermore, 9% (3/34) of patients activated the suicide alert, and the research team promptly intervened with successful outcomes. Vickybot showed high subjective UEI (acceptability, usability, and satisfaction), but low objective UEI (completion, adherence, compliance, and engagement). Vickybot was moderately feasible. Conclusions The chatbot was useful in screening for the presence and severity of anxiety and depressive symptoms, and for detecting suicidal risk. Potential effectiveness was shown to reduce work-related burnout but not anxiety or depressive symptoms. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising but suggest the need to adapt and enhance the smartphone-based solution to improve engagement. A consensus on how to report UEIs and validate digital solutions, particularly for chatbots, is required.

show abstract

Section: Discussionmentioning

confidence: 99%

Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies

Anmella¹,

Sanabra²,

Primé-Tous³

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…Efforts to regulate AI prescriptively are both celebrated and vilified, 51 perceived as decelerating progress until we better understand the true impact of these technologies and prepare health systems to support innovative ideas. While standalone medical device regulation aims to distribute liability more evenly across the stakeholder spectrum and thus increase the regulatory impact on healthcare outcomes, 52,53 it often deflects attention from the core issues of the liability process, for example, for a telehealth device designed to triage patients, to an encounter with outpatient clinics, to hospitalization, and post-discharge digital care. The current paradigm fails to promote trust and the safe development and integration of DHIs.…”

Section: Data Value Predicament In Health Innovationmentioning

confidence: 99%

Telehealth’s Role Enabling Sustainable Innovation and Circular Economies in Health

Kalogeropoulos¹

2023

THMT

View full text Add to dashboard Cite

Digital health interventions, including the use of telehealth augmented by artificial intelligence (AI), support an increasingly broad range of improvement goals for prevention and treatment. Limitations obstructing the many digital benefits of the targeted healthcare innovations from reaching their full potential include the lack of robust usability and user-centered design, nimble regulatory policy, and lack of adequate high-quality evidence and methodologies to evaluate the performance generalization and clinical robustness. We explore health innovation using different value systems and solutions proposed to overcome the fundamental limitations arising in the data value system. We propose a new telehealth paradigm and incorporate intervention designs, which combine clinical innovation with innovation in data resource development. Machine learning and AI have the potential to enable circular economies for digital and health innovation, in which sustainable solutions can be offered within a data-enabled collaborative and shared digital ecosystem. Alignment of industry standards, adjustments to regulatory policies, and the embrace of new governance models for telehealth-based innovation are essential for this new approach for health innovation scaling, clinical adoption, and social innovation.

show abstract

“…The prevalence of mental health issues, such as anxiety and depression, has reached alarming levels, leading to an increasing demand for effective interventions and support systems globally [19][20][21] . Advancements in technology have paved the way for the development of mental health apps and software, which can potentially play a significant role in addressing these concerns [22][23][24][25][26][27] . Amidst these challenges, the healthcare sector has turned to digital solutions, with mental health applications (apps) emerging as a promising frontier in delivering scalable and accessible therapeutic interventions 19,[28][29][30][31][32] .…”

Section: Introductionmentioning

confidence: 99%

Perspectives on Mental Health Digital Platforms: A Usability Study with Ergonomics Design Students

Ngabo-Woods

2023

Preprint

View full text Add to dashboard Cite

The prevalence of mental health issues has reached alarming levels globally. In response, the integration of technology in mental health care, particularly through mental health apps, has emerged as a promising frontier for delivering scalable and accessible therapeutic interventions. However, the effectiveness of these apps is contingent upon their usability. This study explores the critical link between the usability of mental health apps and their efficacy in managing mental health symptoms. Focusing on university students, the research investigates how usability influences user experience, engagement, and adherence to mental health interventions. It also examines the role of usability in reducing barriers to seeking professional help and the variations in usability perceptions. Through a usability study of a mental health app pilot platform, this research seeks to provide actionable insights for future design and development, emphasizing the need for user-friendly interfaces that effectively support mental health outcomes. The findings aim to contribute to the broader understanding of digital mental health interventions and their role in addressing the escalating mental health crisis.

show abstract

Multinational landscape of health app policy: toward regulatory consensus on digital health

Cited by 8 publications

References 8 publications

Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies

Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies

Telehealth’s Role Enabling Sustainable Innovation and Circular Economies in Health

Perspectives on Mental Health Digital Platforms: A Usability Study with Ergonomics Design Students

Contact Info

Product

Resources

About