Digital Therapeutics for Obesity and Eating-Related Problems

Kim, Meelim; Choi, Hyo Geun

doi:10.3803/enm.2021.107

Cited by 27 publications

(23 citation statements)

References 33 publications

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“…Under these circumstances, the importance of artificial intelligence is being emphasized [ 10 , 32 , 33 ]. As the data obtained from DTx are continuous data obtained in real time through sensors (e.g., gait, inhaler usage, blood sugar changes, and sleep patterns), artificial intelligence can be used to recognize patterns from these data [ 32 ].…”

Section: Concepts Of Digital Biomarkers and Exposure-response Of Dtxmentioning

confidence: 99%

Clinical Evaluation of Digital Therapeutics: Present and Future

Huh

Lee

et al. 2022

Healthc Inform Res

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Objectives: Digital therapeutics (DTx) are software-based therapeutic interventions based on clinical evidence. Randomized clinical trials (RCTs) are often the source of clinical evidence, similar to conventional drugs or medical devices. However, novel approaches such as the use of real-world data or digital biomarkers are also utilized. This article aimed to review how DTx products have been clinically evaluated. Methods: DTx products approved by the US Food and Drug Administration as of 2020 were reviewed and products with sufficient published information were selected. Pivotal clinical trials were analyzed according to the elements of the Consolidated Standards of Reporting Trials (CONSORT) guideline. Case reviews were presented for other clinical evaluation strategies, considering the small number of publications. Results: Most approved DTx products used RCTs for clinical evaluations. Similar to conventional RCTs, parallel-group designs with statistical hypothesis testing were adopted. However, DTx trials were often not blinded due to practical issues and involved various comparator groups. In addition, DTx products could be readily evaluated in home-based settings and delivered through the internet. Other evaluation approaches included retrospective analyses using insurance claims data or usage data, which enabled long-term evaluations of effectiveness. Digital biomarkers obtained from real-time and continuous log data were also used to improve the objectiveness of endpoints. Conclusions: RCTs accounted for the majority of DTx evaluations. The designs of DTx trials were comparable to those of drug or device trials, but blinding and comparator elements were often different. Furthermore, the use of real-world data and digital biomarkers are also being tried.

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Section: Concepts Of Digital Biomarkers and Exposure-response Of Dtxmentioning

confidence: 99%

Clinical Evaluation of Digital Therapeutics: Present and Future

Huh

Lee

et al. 2022

Healthc Inform Res

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“…Digital therapeutics is an emerging field of application that involves the use of digital technology for health care [ 97 ]. It has been growing steadily with the development of several new programs and apps [ 98 , 99 ].…”

Section: Discussionmentioning

confidence: 99%

Health-Related Indicators Measured Using Earable Devices: Systematic Review

Choi¹,

Jeon²,

Kim³

et al. 2022

JMIR Mhealth Uhealth

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Background Earable devices are novel, wearable Internet of Things devices that are user-friendly and have potential applications in mobile health care. The position of the ear is advantageous for assessing vital status and detecting diseases through reliable and comfortable sensing devices. Objective Our study aimed to review the utility of health-related indicators derived from earable devices and propose an improved definition of disease prevention. We also proposed future directions for research on the health care applications of earable devices. Methods A systematic review was conducted of the PubMed, Embase, and Web of Science databases. Keywords were used to identify studies on earable devices published between 2015 and 2020. The earable devices were described in terms of target health outcomes, biomarkers, sensor types and positions, and their utility for disease prevention. Results A total of 51 articles met the inclusion criteria and were reviewed, and the frequency of 5 health-related characteristics of earable devices was described. The most frequent target health outcomes were diet-related outcomes (9/51, 18%), brain status (7/51, 14%), and cardiovascular disease (CVD) and central nervous system disease (5/51, 10% each). The most frequent biomarkers were electroencephalography (11/51, 22%), body movements (6/51, 12%), and body temperature (5/51, 10%). As for sensor types and sensor positions, electrical sensors (19/51, 37%) and the ear canal (26/51, 51%) were the most common, respectively. Moreover, the most frequent prevention stages were secondary prevention (35/51, 69%), primary prevention (12/51, 24%), and tertiary prevention (4/51, 8%). Combinations of ≥2 target health outcomes were the most frequent in secondary prevention (8/35, 23%) followed by brain status and CVD (5/35, 14% each) and by central nervous system disease and head injury (4/35, 11% each). Conclusions Earable devices can provide biomarkers for various health outcomes. Brain status, healthy diet status, and CVDs were the most frequently targeted outcomes among the studies. Earable devices were mostly used for secondary prevention via monitoring of health or disease status. The potential utility of earable devices for primary and tertiary prevention needs to be investigated further. Earable devices connected to smartphones or tablets through cloud servers will guarantee user access to personal health information and facilitate comfortable wearing.

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“…Reasons for poor adherence include inconvenience of treatments, forgetfulness, fear of adverse effects (e.g., with topical corticosteroids), and poor understanding of treatments and disease chronicity [ 7 ]. Exploring new ways to improve patients’ self-efficacy and treatment adherence is important, as it may improve the patient’s overall treatment outcome and quality of life and reduce the economic burden of AD [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…These are evidence-based, software-driven therapeutic interventions that are delivered to patients online and can be used as a supplement to—or replacement for—existing treatments [ 8 ]. They were initially developed for diabetes care and are now increasingly being used for various chronic conditions [ 9 – 12 ]. Few studies have explored the benefits of digital interventions in the context of AD, and these focused on a single aspect of disease management such as psychological support, remote patient monitoring, or medication reminders [ 13 – 16 ].…”

Section: Introductionmentioning

confidence: 99%

Clinical Efficacy of a Digital Intervention for Patients with Atopic Dermatitis: a Prospective Single-Center Study

Guðmundsdóttir

Ballarini²,

Ámundadóttir

et al. 2022

Dermatol Ther (Heidelb)

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Introduction Improving disease awareness and treatment adherence is key for the long-term management of atopic dermatitis (AD). Digital interventions can support patients in disease self-management and adopting a healthier lifestyle through behavioral modifications. We aimed to test the clinical efficacy of a digital program in patients with AD. Methods Adults with mild-to-severe AD were recruited for a 6-week feasibility study. The intervention was delivered through a mobile app and consisted of symptom and trigger education, treatment reminders, lifestyle coaching, and healthy lifestyle support. Here we report the secondary outcomes of intervention efficacy on clinical symptoms, as assessed by Scoring Atopic Dermatitis (SCORAD) and Patient-Oriented Eczema Measure (POEM), on health-related quality of life (HR QoL) as assessed by Dermatology Life Quality Index (DLQI), and changes in behaviors related to disease management as assessed by a six-item questionnaire. Results Twenty of 21 patients (95.2%) completed the program (81% female, mean age 31.4 years, mean time from diagnosis 26.8 years). Clinical symptoms and patient-reported global severity improved by 44% and 46%, respectively, while HR QoL improved by 41% ( p < 0.001 for all measures). Adherence to treatments and preventive measures improved from pre- to post-intervention, including skincare, avoidance of triggers, and disease-related knowledge. A significant interaction was observed between increased treatment adherence and clinical improvement, such that larger clinical improvements were observed in patients with higher treatment adherence. Conclusion Patients with AD are open to and can benefit from a digitally delivered targeted intervention, as demonstrated by significant improvements in treatment adherence and related clinical outcomes. Supplementary Information The online version contains supplementary material available at 10.1007/s13555-022-00821-y.

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Digital Therapeutics for Obesity and Eating-Related Problems

Cited by 27 publications

References 33 publications

Clinical Evaluation of Digital Therapeutics: Present and Future

Clinical Evaluation of Digital Therapeutics: Present and Future

Health-Related Indicators Measured Using Earable Devices: Systematic Review

Clinical Efficacy of a Digital Intervention for Patients with Atopic Dermatitis: a Prospective Single-Center Study

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