The promise and peril of mobile health applications for diabetes and endocrinology.
TL;DR: A review of medical apps focused on endocrine disease is conducted, highlighting the need to understand more fully the medical value of these apps to patients.
Abstract: We are in the midst of what some have called a "mobile health revolution". Medical applications ("apps") for mobile phones are proliferating in the marketplace and clinicians are likely encountering patients with questions about the medical value of these apps. We conducted a review of medical apps focused on endocrine disease. We found a higher percentage of relevant apps in our searches of the iPhone app store compared with the Android marketplace. For our diabetes search in the iPhone store, the majority of apps (33%) focused on health tracking (blood sugars, insulin doses, carbohydrates), requiring manual entry of health data. Only two apps directly inputted blood sugars from glucometers attached to the mobile phone. The remainder of diabetes apps were teaching/training apps (22%), food reference databases (8%), social blogs/forums (5%), and physician directed apps (8%). We found a number of insulin dose calculator apps which technically meet criteria for being a medically regulated mobile application, but did not find evidence for FDA-approval despite their availability to consumers. Far fewer apps were focused on other endocrine disease and included medical reference for the field of endocrinology, access to endocrine journals, height predictors, medication trackers, and fertility apps. Although mobile health apps have great potential for improving chronic disease care, they face a number of challenges including lack of evidence of clinical effectiveness, lack of integration with the health care delivery system, the need for formal evaluation and review and organized searching for health apps, and potential threats to safety and privacy.
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TL;DR: An increasing trend in published articles on health-related misinformation and the role of social media in its propagation is observed, and the most extensively studied topics involving misinformation relate to vaccination, Ebola and Zika Virus, although others, such as nutrition, cancer, fluoridation of water and smoking also featured.
773 citations
Cites background from "The promise and peril of mobile hea..."
...This is perhaps surprising, as health promotion and public health researchers now pay considerable attention to the potential of the internet as a tool to diffuse health-related information (Chew and Eysenbach, 2010; Ritterband and Tate, 2009; Murray et al., 2009; Scanfeld et al., 2010; Signorini et al., 2011) , employing smart phones and other mobile technologies in preventative interventions (Abroms et al., 2013; Eng and Lee, 2013; Free et al., 2013; Steinhubl et al., 2015) ....
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TL;DR: Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions, and may represent a medium by which these interventions could be translated for widespread use.
Abstract: Background: Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another. Objective: The purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors. Methods: Electronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature. Results: All monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory. Conclusions: Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings. [J Med Internet Res 2014;16(8):e192]
455 citations
Cites background from "The promise and peril of mobile hea..."
...There has been a call for study of health apps [33-35], due to their widespread use and the absence of guidelines for determining their adherence to standard practices....
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TL;DR: The usability of diabetes apps for patients aged 50 or older was moderate to good, but this result applied mainly to apps offering a small range of functions, and Multifunctional apps performed considerably worse in terms of usability.
Abstract: Background: A multitude of mhealth (mobile health) apps have been developed in recent years to support effective self-management of patients with diabetes mellitus type 1 or 2. Objective: We carried out a systematic review of all currently available diabetes apps for the operating systems iOS and Android. We considered the number of newly released diabetes apps, range of functions, target user groups, languages, acquisition costs, user ratings, available interfaces, and the connection between acquisition costs and user ratings. Additionally, we examined whether the available applications serve the special needs of diabetes patients aged 50 or older by performing an expert-based usability evaluation. Methods: We identified relevant keywords, comparative categories, and their specifications. Subsequently, we performed the app review based on the information given in the Google Play Store, the Apple App Store, and the apps themselves. In addition, we carried out an expert-based usability evaluation based on a representative 10% sample of diabetes apps. Results: In total, we analyzed 656 apps finding that 355 (54.1%) offered just one function and 348 (53.0%) provided a documentation function. The dominating app language was English (85.4%, 560/656), patients represented the main user group (96.0%, 630/656), and the analysis of the costs revealed a trend toward free apps (53.7%, 352/656). The median price of paid apps was €1.90. The average user rating was 3.6 stars (maximum 5). Our analyses indicated no clear differences in the user rating between free and paid apps. Only 30 (4.6%) of the 656 available diabetes apps offered an interface to a measurement device.
We evaluated 66 apps within the usability evaluation. On average, apps were rated best regarding the criterion “comprehensibility” (4.0 out of 5.0), while showing a lack of “fault tolerance” (2.8 out of 5.0). Of the 66 apps, 48 (72.7%) offered the ability to read the screen content aloud. The number of functions was significantly negative correlated with usability. The presence of documentation and analysis functions reduced the usability score significantly by 0.36 and 0.21 points. Conclusions: A vast number of diabetes apps already exist, but the majority offer similar functionalities and combine only one to two functions in one app. Patients and physicians alike should be involved in the app development process to a greater extent. We expect that the data transmission of health parameters to physicians will gain more importance in future applications.
The usability of diabetes apps for patients aged 50 or older was moderate to good. But this result applied mainly to apps offering a small range of functions. Multifunctional apps performed considerably worse in terms of usability. Moreover, the presence of a documentation or analysis function resulted in significantly lower usability scores. The operability of accessibility features for diabetes apps was quite limited, except for the feature “screen reader”. [J Med Internet Res 2014;16(4):e104]
370 citations
Cites background or methods or result from "The promise and peril of mobile hea..."
...At the moment, the input of the measured blood glucose values occurs manually in most of the cases, as earlier findings of Eng et al [5] and Chomutare et al [6] confirm....
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...At the moment, the input of the measured blood glucose values occurs manually in most of the cases, as earlier findings of Eng et al [5] and Chomutare et al [6] confirm....
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...Until now, just a few reviews of diabetes apps had been conducted [3,5,6,16]....
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...At the same time, many apps offered similar functionalities, mostly a documentation function, which is consistent with earlier findings of Martínez-Pérez et al [3], Eng et al [5], Chomutare et al [6], and Demidowich et al [16]....
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...Within the health care sector, apps are supporting the management of illnesses, thereby promoting health awareness and well-being [3-5]....
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TL;DR: App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations and the main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income.
Abstract: Background Mobile phone use and the adoption of healthy lifestyle software apps ("health apps") are rapidly proliferating. There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions to change, and actual health behaviors. Objective The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended guidelines for fruit and vegetable intake and physical activity. Methods Data on users of mobile devices and health apps were analyzed from the National Cancer Institute's 2015 Health Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss. Results From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+ years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a mobile device, especially if that person was a college graduate (OR 3.30). Individuals with apps were significantly more likely to report intentions to improve fruit (63.8% with apps vs 58.5% without apps, P=.01) and vegetable (74.9% vs 64.3%, P Conclusions The main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income. Although differences persist for gender, age, and educational attainment, many individual sociodemographic factors are becoming less potent in influencing engagement with mobile devices and health app use. App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations.
363 citations
TL;DR: Patients with low health literacy were less likely to use HIT tools or perceive them as easy or useful, but they perceived information on HIT as private, and health literacy score was positively associated with trust in health care.
Abstract: Background: Approximately one-half of American adults exhibit low health literacy and thus struggle to find and use health information. Low health literacy is associated with negative outcomes including overall poorer health. Health information technology (HIT) makes health information available directly to patients through electronic tools including patient portals, wearable technology, and mobile apps. The direct availability of this information to patients, however, may be complicated by misunderstanding of HIT privacy and information sharing. Objective: The purpose of this study was to determine whether health literacy is associated with patients’ use of four types of HIT tools: fitness and nutrition apps, activity trackers, and patient portals. Additionally, we sought to explore whether health literacy is associated with patients’ perceived ease of use and usefulness of these HIT tools, as well as patients’ perceptions of privacy offered by HIT tools and trust in government, media, technology companies, and health care. This study is the first wide-scale investigation of these interrelated concepts. Methods: Participants were 4974 American adults (n=2102, 42.26% male, n=3146, 63.25% white, average age 43.5, SD 16.7 years). Participants completed the Newest Vital Sign measure of health literacy and indicated their actual use of HIT tools, as well as the perceived ease of use and usefulness of these applications. Participants also answered questions regarding information privacy and institutional trust, as well as demographic items. Results: Cross-tabulation analysis indicated that adequate versus less than adequate health literacy was significantly associated with use of fitness apps (P=.02), nutrition apps (P<.001), activity trackers (P<.001), and patient portals (P<.001). Additionally, greater health literacy was significantly associated with greater perceived ease of use and perceived usefulness across all HIT tools after controlling for demographics. Regarding privacy perceptions of HIT and institutional trust, patients with greater health literacy often demonstrated decreased privacy perceptions for HIT tools including fitness apps (P<.001) and nutrition apps (P<.001). Health literacy was negatively associated with trust in government (P<.001), media (P<.001), and technology companies (P<.001). Interestingly, health literacy score was positively associated with trust in health care (P=.03). Conclusions: Patients with low health literacy were less likely to use HIT tools or perceive them as easy or useful, but they perceived information on HIT as private. Given the fast-paced evolution of technology, there is a pressing need to further the understanding of how health literacy is related to HIT app adoption and usage. This will ensure that all users receive the full health benefits from these technological advances, in a manner that protects health information privacy, and that users engage with organizations and providers they trust. [J Med Internet Res 2016;18(10):e264]
294 citations
References
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TL;DR: It is concluded that high-quality, adequately powered trials of optimized interventions are required to evaluate effects on objective outcomes.
Abstract: Background
Mobile technologies could be a powerful media for providing individual level support to health care consumers. We conducted a systematic review to assess the effectiveness of mobile technology interventions delivered to health care consumers.
1,518 citations
"The promise and peril of mobile hea..." refers background in this paper
...They concluded that there was evidence for the effectiveness of text messaging interventions for increasing adherence in antiretroviral therapy and smoking cessation studies, but that results were not consistent for other areas (11)....
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TL;DR: The aim is to assess Sweet Talk, a text‐messaging support system designed to enhance self‐efficacy, facilitate uptake of intensive insulin therapy and improve glycaemic control in paediatric patients with Type 1 diabetes.
Abstract: Aims To assess Sweet Talk, a text-messaging support system designed to enhance self-efficacy, facilitate uptake of intensive insulin therapy and improve glycaemic control in paediatric patients with Type 1 diabetes. Methods One hundred and twenty-six patients fulfilled the eligibility criteria; Type 1 diabetes for > 1 year, on conventional insulin therapy, aged 8–18 years. Ninety-two patients were randomized to conventional insulin therapy ( n = 28), conventional therapy and Sweet Talk ( n = 33) or intensive insulin therapy and Sweet Talk ( n = 31). Goal-setting at clinic visits was reinforced by daily text-messages from the Sweet Talk software system, containing personalized goal-specific prompts and messages tailored to patients’ age, sex and insulin regimen. Results HbA 1c did not change in patients on conventional therapy without or with Sweet Talk (10.3 ± 1.7 vs. 10.1 ± 1.7%), but improved in patients randomized to intensive therapy and Sweet Talk (9.2 ± 2.2%, 95% CI − 1.9, − 0.5, P < 0.001). Sweet Talk was associated with improvement in diabetes self-efficacy (conventional therapy 56.0 ± 13.7, conventional therapy plus Sweet Talk 62.1 ± 6.6, 95% CI +2.6, +7.5, P = 0.003) and self-reported adherence (conventional therapy 70.4 ± 20.0, conventional therapy plus Sweet Talk 77.2 ± 16.1, 95% CI +0.4, +17.4, P = 0.042). When surveyed, 82% of patients felt that Sweet Talk had improved their diabetes self-management and 90% wanted to continue receiving messages. Conclusions Sweet Talk was associated with improved self-efficacy and adherence; engaging a classically difficult to reach group of young people. While Sweet Talk alone did not improve glycaemic control, it may have had a role in supporting the introduction of intensive insulin therapy. Scheduled, tailored text messaging offers an innovative means of supporting adolescents with diabetes and could be adapted for other health-care settings and chronic diseases. Diabet. Med. 23, 1332–1338 (2006)
554 citations
TL;DR: Adults with type 2 diabetes using WellDoc's software achieved statistically significant improvements in A1c and patient satisfaction with the system was clinically and statistically significant.
Abstract: Background: Less than 63% of individuals with diabetes meet professional guidelines target of hemoglobin A1c <7.0%, and only 7% meet combined glycemic, lipid, and blood pressure goals. The primary study aim was to assess the impact on A1c of a cell phone-based diabetes management software system used with web-based data analytics and therapy optimization tools. Secondary aims examined health care provider (HCP) adherence to prescribing guidelines and assessed HCPs' adoption of the technology. Methods: Thirty patients with type 2 diabetes were recruited from three community physician practices for a 3-month study and evenly randomized. The intervention group received cell phone-based software designed by endocrinologists and CDEs (WellDoc™ Communications, Inc., Baltimore, MD). The software provided real-time feedback on patients' blood glucose levels, displayed patients' medication regimens, incorporated hypo- and hyperglycemia treatment algorithms, and requested additional data needed to evaluate...
405 citations
TL;DR: The performance of smartphone applications in assessing melanoma risk is highly variable, and 3 of 4 smartphone applications incorrectly classified 30% or more of melanomas as unconcerning.
Abstract: Objective To measure the performance of smartphone applications that evaluate photographs of skin lesions and provide the user with feedback about the likelihood of malignancy. Design Case-control diagnostic accuracy study. Setting Academic dermatology department. Participants and Materials Digital clinical images of pigmented cutaneous lesions (60 melanoma and 128 benign control lesions) with a histologic diagnosis rendered by a board-certified dermatopathologist, obtained before biopsy from patients undergoing lesion removal as a part of routine care. Main Outcome Measures Sensitivity, specificity, and positive and negative predictive values of 4 smartphone applications designed to aid nonclinician users in determining whether their skin lesion is benign or malignant. Results Sensitivity of the 4 tested applications ranged from 6.8% to 98.1%; specificity, 30.4% to 93.7%; positive predictive value, 33.3% to 42.1%; and negative predictive value, 65.4% to 97.0%. The highest sensitivity for melanoma diagnosis was observed for an application that sends the image directly to a board-certified dermatologist for analysis; the lowest, for applications that use automated algorithms to analyze images. Conclusions The performance of smartphone applications in assessing melanoma risk is highly variable, and 3 of 4 smartphone applications incorrectly classified 30% or more of melanomas as unconcerning. Reliance on these applications, which are not subject to regulatory oversight, in lieu of medical consultation can delay the diagnosis of melanoma and harm users.
378 citations
"The promise and peril of mobile hea..." refers background in this paper
...This could have adverse health consequences, as outlined by a recent study of dermatologic apps for detecting suspicious skin lesions (28)....
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TL;DR: A public-private partnership to define and instantiate an “open” mHealth architecture could support medical discovery and evidence-based practice about managing and preventing chronic disease.
Abstract: Chronic diseases like diabetes, asthma, and obesity account for 46% of global disease burden ( 1 ). The traditional model of episodic care in clinic and hospital-based settings is suboptimal for improving chronic disease outcomes ( 2 ). Mobile communication devices, in conjunction with Internet and social media, present opportunities to enhance disease prevention and management by extending health interventions beyond the reach of traditional care—an approach referred to as mHealth ( 3 ). However, mHealth is emerging as a patchwork of incompatible applications (“apps”) serving narrow, albeit valuable, needs, and thus could benefit from more coordinated development ( 4 ). A public-private partnership to define and instantiate an “open” mHealth architecture (described below), in the context of economic incentives and enabling policies, could support medical discovery and evidence-based practice about managing and preventing chronic disease.
333 citations
"The promise and peril of mobile hea..." refers background in this paper
...This includes applications (which we will refer to as ‘apps’ hereafter) that run on mobile phones, sensors that track vital signs and health activities, and cloud-based computing systems (4, 5)....
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