Adherence to evidence-based guidelines among diabetes self-management apps

Breland, Jessica Y.; Yeh, Vivian M.; Yu, Jessica

doi:10.1007/s13142-013-0205-4

Cited by 84 publications

(74 citation statements)

References 22 publications

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“…This study also noted the great difficulty in maintaining longitudinal use of apps, and that PwD tended to stop using diary apps when they felt they had stabilized. The affective nature of interventions must be carefully considered, with [4] noting how tracking could increase feelings of disease burden while [6] questioned the clinical validity of many of these apps. Such inconclusive results suggest the need for further research to better understand the individual components that make up these apps, and how to improve them as tools for supporting better self-management practices.…”

Section: Efficacy and Known Barriers To Adoptionmentioning

confidence: 99%

Data, Data Everywhere, and Still Too Hard to Link

Katz

Price

Holland

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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For those with chronic conditions, such as Type 1 diabetes, smartphone apps offer the promise of an affordable, convenient, and personalized disease management tool. However, despite significant academic research and commercial development in this area, diabetes apps still show low adoption rates and underwhelming clinical outcomes. Through user-interaction sessions with 16 people with Type 1 diabetes, we provide evidence that commonly used interfaces for diabetes self-management apps, while providing certain benefits, can fail to explicitly address the cognitive and emotional requirements of users. From analysis of these sessions with eight such user interface designs, we report on user requirements, as well as interface benefits, limitations, and then discuss the implications of these findings. Finally, with the goal of improving these apps, we identify 3 questions for designers, and review for each in turn: current shortcomings, relevant approaches, exposed challenges, and potential solutions.

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Section: Efficacy and Known Barriers To Adoptionmentioning

confidence: 99%

Data, Data Everywhere, and Still Too Hard to Link

Katz

Price

Holland

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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“…Schoffman and colleagues found that 61 % of mobile apps targeting childhood obesity did not include any evidence-based behavioral strategies [6]. Breland and colleagues found that 14 % of diabetes mobile apps did not include any evidencebased behavioral strategies and 33 % included only one of six possible strategies [7]. The lack of evidence is especially concerning because public opinion is beginning to coalesce in support of these apps.…”

Section: Do Mhealth Apps Work?mentioning

confidence: 99%

How behavioral science can advance digital health

Pagoto

Bennett

2013

Behav. Med. Pract. Policy Res.

138

102

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The field of behavioral science has produced myriad data on health behavior change strategies and leveraged such data into effective human-delivered interventions to improve health. Unfortunately, the impact of traditional health behavior change interventions has been heavily constrained by patient and provider burden, limited ability to measure and intervene upon behavior in real time, variable adherence, low rates of implementation, and poor third-party coverage. Digital health technologies, including mobile phones, sensors, and online social networks, by being available in real time, are being explored as tools to increase our understanding of health behavior and to enhance the impact of behavioral interventions. The recent explosion of industry attention to the development of novel health technologies is exciting but has far outpaced research. This Special Section of Translational Behavioral Medicine, Smartphones, Sensors, and Social Networks: A New Age of Health Behavior Change features a collection of studies that leverage health technologies to measure, change, and/or understand health behavior. We propose five key areas in which behavioral science can improve the impact of digital health technologies on public health. First, research is needed to identify which health technologies actually impact behavior and health outcomes. Second, we need to understand how online social networks can be leveraged to impact health behavior on a large scale. Third, a team science approach is needed in the developmental process of health technologies. Fourth, behavioral scientists should identify how a balance can be struck between the fast pace of innovation and the much slower pace of research. Fifth, behavioral scientists have an integral role in informing the development of health technologies and facilitating the movement of health technologies into the healthcare system. KEYWORDS Digital health, mHealth, Social networksThe efficacy of traditional health behavior change interventions has long been constrained by expense, patient burden, and variable adherence. Current models of health care which limit our access to patients to face-to-face visits reduce our ability to gain an accurate understanding of the antecedents and consequences of behavior and to intervene in moments when patients most need help. Digital health technologies, including mobile phones, sensors, and online social networks, by being available in real time, are being explored as ways to enhance our ability to understand health behavior and intervene upon it more effectively. mHealth, a segment of the digital health market that leverages mobile technologies to solve health problems, has reached its tipping point. A rapidly growing body of evidence demonstrates the efficacy of mHealth approaches across a wide range of conditions, populations, and settings. mHealth has also attracted a explosion of industry attention. An extremely diverse group of companies are capitalizing on the mHealth market, which is projected to reach over $23 billion in r...

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“…This reflects the overall lack of educational apps in the marketplace to support diabetes self-management. 8,9 The lack of reference to evidence-based medicine or research requires attention as it is currently impossible to know how many apps are designed robustly based on evidence-based medicine or research. 8 In the United Kingdom it is not uncommon for people to start drinking before the age of 18.…”

Section: Discussionmentioning

confidence: 99%

“…The authors concluded it was impossible to know how many apps on the market were founded on evidence-based medicine. 8 Breland et al 9 . This study examined the extent to which 227 diabetes self-management apps addressed the American Association of Diabetes Educators self-management behaviors (AADE7).…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

The Role of Mobile Applications in Improving Alcohol Health Literacy in Young Adults With Type 1 Diabetes

Tamony

Holt

Barnard

2015

J Diabetes Sci Technol

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Background: Mobile health (mHealth) is an expanding field which includes the use of social media and mobile applications (apps). Apps are used in diabetes self-management but it is unclear whether these are being used to support safe drinking of alcohol by people with type 1 diabetes (T1DM). Alcohol health literacy is poor among young adults with T1DM despite specific associated risks.Methods: Systematic literature review followed by critical appraisal of commercially available apps. An eSurvey investigating access to mHealth technology, attitudes toward apps for diabetes management and their use to improve alcohol health literacy was completed by participants. Results:Of 315 articles identified in the literature search, 7 met the inclusion criteria. Ten diabetes apps were available, most of which lacked the educational features recommended by clinical guidelines. In all, 27 women and 8 men with T1DM, aged 19-31 years were surveyed. Of them, 32 had access to a smartphone/tablet; 29 used apps; 20 used/had used diabetes apps; 3 had used apps related to alcohol and diabetes; 11 had discussed apps with their health care team; 22 felt more communication with their health care team would increase awareness of alcohol-associated risks. Conclusions:Use of mobile apps is commonplace but the use of apps to support safe drinking in this population was rare. Most participants expressed a preference for direct communication with their health care teams about this subject. Further research is needed to determine the preferences of health care professionals and how they can best support young adults in safe drinking.

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Adherence to evidence-based guidelines among diabetes self-management apps

Cited by 84 publications

References 22 publications

Data, Data Everywhere, and Still Too Hard to Link

Data, Data Everywhere, and Still Too Hard to Link

How behavioral science can advance digital health

The Role of Mobile Applications in Improving Alcohol Health Literacy in Young Adults With Type 1 Diabetes

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