Use of m-Health Technology for Preventive Interventions to Tackle Cardiometabolic Conditions and Other Non-Communicable Diseases in Latin America- Challenges and Opportunities

In Latin America, cardiovascular disease (CVD) mortality rates will increase by an estimated 145% from 1990 to 2020. Several challenges related to social strains, inadequate public health infrastructure, and underfinanced healthcare systems make cardiometabolic conditions and non-communicable diseases (NCDs) difficult to prevent and control. On the other hand, the region has high mobile phone coverage, making mobile health (mHealth) particularly attractive to complement and improve strategies toward prevention and control of these conditions in low- and middle-income countries. In this article, we describe the experiences of three Centers of Excellence for prevention and control of NCDs sponsored by the National Heart, Lung, and Blood Institute with mHealth interventions to address cardiometabolic conditions and other NCDs in Argentina, Guatemala, and Peru. The nine studies described involved the design and implementation of complex interventions targeting providers, patients and the public. The rationale, design of the interventions, and evaluation of processes and outcomes of each of these studies are described, together with barriers and enabling factors associated with their implementation.Fil: Beratarrechea, Andrea Gabriela. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Diez Canseco, Francisco. Universidad Peruana Cayetano Heredia; PerúFil: Irazola, Vilma. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Miranda, Jaime. Universidad Peruana Cayetano Heredia; PerúFil: Ramirez Zea, Manuel. Institute of Nutrition of Central America and Panama; GuatemalaFil: Rubinstein, Adolfo Luis. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review

Background: The public health impact of health and well-being digital interventions is dependent upon sufficient real-world uptake and engagement. Uptake is currently largely dependent on popularity indicators (eg, ranking and user ratings on app stores), which may not correspond with effectiveness, and rapid disengagement is common. Therefore, there is an urgent need to identify factors that influence uptake and engagement with health and well-being apps to inform new approaches that promote the effective use of such tools. Objective: This review aimed to understand what is known about influences on the uptake of and engagement with health and well-being smartphone apps among adults. Methods: We conducted a systematic review of quantitative, qualitative, and mixed methods studies. Studies conducted on adults were included if they focused on health and well-being smartphone apps reporting on uptake and engagement behavior. Studies identified through a systematic search in Medical Literature Analysis and Retrieval System Online, or MEDLARS Online (MEDLINE), EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO, Scopus, Cochrane library databases, DataBase systems and Logic Programming (DBLP), and Association for Computing Machinery (ACM) Digital library were screened, with a proportion screened independently by 2 authors. Data synthesis and interpretation were undertaken using a deductive iterative process. External validity checking was undertaken by an independent researcher. A narrative synthesis of the findings was structured around the components of the capability, opportunity, motivation, behavior change model and the theoretical domains framework (TDF). Results: Of the 7640 identified studies, 41 were included in the review. Factors related to uptake (U), engagement (E), or both (B) were identified. Under capability, the main factors identified were app literacy skills (B), app awareness (U), available user guidance (B), health information (E), statistical information on progress (E), well-designed reminders (E), features to reduce cognitive load (E), and self-monitoring features (E). Availability at low cost (U), positive tone, and personalization (E) were identified as physical opportunity factors, whereas recommendations for health and well-being apps (U), embedded health professional support (E), and social networking (E) possibilities were social opportunity factors. Finally, the motivation factors included positive feedback (E), available rewards (E), goal setting (E), and the perceived utility of the app (E). Conclusions: Across a wide range of populations and behaviors, 26 factors relating to capability, opportunity, and motivation appear to influence the uptake of and engagement with health and well-being smartphone apps. Our recommendations may help app developers, health app portal developers, and policy makers in the optimization of health and well-being apps

Evaluating the impact of physical activity apps and wearables: interdisciplinary review

Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines

Ideas and Enhancements Related to Mobile Applications to Support Type 1 Diabetes

Background: Mobile devices have become increasingly important to young people who now use them to access a wide variety of health-related information. Research and policy related to the integration of health information and support with this technology do not effectively consider the viewpoint of a younger patient. Views of young people with type 1 diabetes are vital in developing quality services and improving their own health-related quality of life (HRQOL), yet research on their lifestyle and use of Web and mobile technology to support their condition and in non–health-related areas is sparse. Objective: To develop insight into young people with type 1 diabetes and their current use of Web and mobile technology and its potential impact on HRQOL. This can be achieved by constructing an in-depth picture of their day-to-day experiences from qualitative interviewing and exploring how they make use of technology in their lives and in relation to their condition and treatment. The goal was then to build something to help them, using the researcher’s technical expertise and seeking users’ opinions during the design and build, utilizing sociotechnical design principles. Methods: Data were collected by semistructured, in-depth qualitative interviews (N=9) of young people with type 1 diabetes aged 18-21. Interviews were transcribed and loaded onto NVivo for theme identification. Data analysis was undertaken during initial interviews (n=4) to locate potential ideas and enhancements for technical development. Latter interviews (n=5) assisted in the iterative sociotechnical design process of the development and provided additional developmental ideas. Results: Six themes were identified providing an understanding of how participants lived with and experienced their condition and how they used technology. Four technological suggestions for improvement were taken forward for prototyping. One prototype was developed as a clinically approved app. A number of ideas for new mobile apps and enhancements to currently existing apps that did not satisfactorily cater to this age group’s requirements for use in terms of design and functionality were suggested by interviewees but were not prototyped. Conclusions: This paper outlines the nonprototyped suggestions from interviewees and argues that young people with type 1 diabetes have a key role to play in the design and implementation of new technology to support them and improve HRQOL. It is vital to include and reflect on their suggestions as they have a radically different view of technology than either their parents or practitioners. We need to consider the relationship to technology that young people with type 1 diabetes have, and then reflect on how this might make a difference to them and when it might not be a suitable mechanism to use

Peer coaching through mHealth targeting physical activity in people with Parkinson disease: feasibility study

BACKGROUND: Long-term engagement in exercise and physical activity mitigates the progression of disability and increases quality of life in people with Parkinson disease (PD). Despite this, the vast majority of individuals with PD are sedentary. There is a critical need for a feasible, safe, acceptable, and effective method to assist those with PD to engage in active lifestyles. Peer coaching through mobile health (mHealth) may be a viable approach. OBJECTIVE: The purpose of this study was to develop a PD-specific peer coach training program and a remote peer-mentored walking program using mHealth technology with the goal of increasing physical activity in persons with PD. We set out to examine the feasibility, safety, and acceptability of the programs along with preliminary evidence of individual-level changes in walking activity, self-efficacy, and disability in the peer mentees. METHODS: A peer coach training program and a remote peer-mentored walking program using mHealth was developed and tested in 10 individuals with PD. We matched physically active persons with PD (peer coaches) with sedentary persons with PD (peer mentees), resulting in 5 dyads. Using both Web-based and in-person delivery methods, we trained the peer coaches in basic knowledge of PD, exercise, active listening, and motivational interviewing. Peer coaches and mentees wore FitBit Zip activity trackers and participated in daily walking over 8 weeks. Peer dyads interacted daily via the FitBit friends mobile app and weekly via telephone calls. Feasibility was determined by examining recruitment, participation, and retention rates. Safety was assessed by monitoring adverse events during the study period. Acceptability was assessed via satisfaction surveys. Individual-level changes in physical activity were examined relative to clinically important differences. RESULTS: Four out of the 5 peer pairs used the FitBit activity tracker and friends function without difficulty. A total of 4 of the 5 pairs completed the 8 weekly phone conversations. There were no adverse events over the course of the study. All peer coaches were "satisfied" or "very satisfied" with the training program, and all participants were "satisfied" or "very satisfied" with the peer-mentored walking program. All participants would recommend this program to others with PD. Increases in average steps per day exceeding the clinically important difference occurred in 4 out of the 5 mentees. CONCLUSIONS: Remote peer coaching using mHealth is feasible, safe, and acceptable for persons with PD. Peer coaching using mHealth technology may be a viable method to increase physical activity in individuals with PD. Larger controlled trials are necessary to examine the effectiveness of this approach.This study is supported by Boston Roybal Center for Active Lifestyle Interventions (RALI Boston), Grant #P30 AG048785, and the American Parkinson Disease Association, Massachusetts chapter. The authors would like to thank Nicole Sullivan, SOT, for her assistance with data management and data collection and Nick Wendel, DPT, for his assistance with data collection. Additionally, the authors would like to thank the participants in this study for their time, effort, and insights. (P30 AG048785 - Boston Roybal Center for Active Lifestyle Interventions (RALI Boston); American Parkinson Disease Association, Massachusetts chapter)Accepted manuscrip

Analysis of Effectiveness and Psychological Techniques Implemented in mHealth Solutions for Middle-Aged and Elderly Adults with Type 2 Diabetes : A Narrative Review of the Literature

Background: in diabetes, multiple mHealth solutions were produced and implemented for self-management behaviors. However, little research on the effectiveness of psychological techniques implemented within these mHealth solutions was carried out, and even less with the elderly population where technological barriers might exist. Reliable evidence generated through a comprehensive evaluation of mHealth interventions may accelerate its growth for successful long-term implementation and to help to experience mHealth benefits in an enhanced way in all ages. Objective: this study aimed to review mHealth solutions for diabetes self-management in older adults (adherence to treatments and glycemic control) by analyzing the effectiveness of specific psychological techniques implemented. Methods: a narrative review was conducted following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. PubMed (Medline) and American Psychological Association (APA) PsycInfo databases were searched for published papers that addressed eHealth solutions' effectiveness for diabetes self-management. Studies in English, Spanish, and/or German of any design were screened, with no time constraints regarding the year of publication. A qualitative analysis of the selected papers was conducted in several steps. Results: this review found 38 studies setting up and analyzing mHealth solutions for older adults. Most research showed improvements in HbA1c, self-management behaviors, and medication adherence in T2DM patients post intervention. However, different mid-to-long term effects were found across studies, specifically concerning the maintenance and adherence to healthy behaviors. The most employed psychological framework was CBT, including techniques such as self-monitoring of outcome behaviors (mostly targeting glycemia measurements and healthy habits as physical activity and/or diet), tailored motivational feedback from medical staff, and psychoeducation or health coaches. The most successful mHealth intervention combined the feature of tailored feedback messages, interactive communication with healthcare professionals, and multifaceted functions. Conclusions: there is a lack of elaborate and detailed information in the literature regarding the factors considered in the design and development of mHealth solutions used as interventions for T2DM self-management in the elderly. Documentation and inclusion of such vital information will foster a transparent and shared decision-making process that will ultimately lead to the development of useful and user-friendly self-management apps that can enhance the quality of life for diabetes patients. Further research adapting mHealth solutions to older adults' sensory deficits is necessary

Integrating Behavioral Trigger Messages into a mHealth System Design for Chronic Disease Management

Recent changes in health information technology have dramatically altered the face, delivery, and management of healthcare particularly as it relates to mHealth. With increases in smart phone ownership, mHealth potentially has the ability to provide far-reaching transformation of chronic disease management particularly when aligned with behavioral change theories and persuasive technology. MHealth applications have an advantage over computers and various print communications as the consumer can engage with the application at any time and at any location. The Interactive Health Communication Application (IHCA) states that by combining support mechanisms such as behavior change theories into electronic devices as a method to transmit or receive health information can potentially lead to changes in knowledge, motivation and self-efficacy. Adding constructs of the Fogg Behavior Model, Social Cognitive Theory and Persuasive Technology to the IHCA framework can create an engaged persuasive system leading to improvements in self-efficacy, self-management and knowledge. The hypotheses for our study are 1) participants will demonstrate improved scores on self-efficacy, knowledge and self-management following the intervention period, 2) participants will be more engaged in the usage of capABILITY following behavioral triggers, and 3) participants who receive spark triggers involving motivation will engage in the utilization of capABILITY faster than those who receive facilitator triggers. The results of this study provide important findings for 1) mHealth system design utilizing IHCA with new constructs for chronic disease management, 2) design and develop of persuasive spark and facilitator trigger messages, and 3) understanding of user engagement when behavioral (spark and facilitator) trigger messages are utilized. The findings of the study revealed that self-efficacy, self-management, and knowledge did improve post intervention. In addition, the study showed that spark triggers continually cued participants to engage with capABILITY quicker than facilitator triggers

Analysis of Effectiveness and Psychological Techniques Implemented in mHealth Solutions for Middle-Aged and Elderly Adults with Type 2 Diabetes: A Narrative Review of the Literature

Diabetis; Gent gran; Tècniques psicològiquesDiabetes; Elderly; Psychological techniquesDiabetes; Ancianos; Técnicas psicológicaBackground: in diabetes, multiple mHealth solutions were produced and implemented for self-management behaviors. However, little research on the effectiveness of psychological techniques implemented within these mHealth solutions was carried out, and even less with the elderly population where technological barriers might exist. Reliable evidence generated through a comprehensive evaluation of mHealth interventions may accelerate its growth for successful long-term implementation and to help to experience mHealth benefits in an enhanced way in all ages. Objective: this study aimed to review mHealth solutions for diabetes self-management in older adults (adherence to treatments and glycemic control) by analyzing the effectiveness of specific psychological techniques implemented. Methods: a narrative review was conducted following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. PubMed (Medline) and American Psychological Association (APA) PsycInfo databases were searched for published papers that addressed eHealth solutions’ effectiveness for diabetes self-management. Studies in English, Spanish, and/or German of any design were screened, with no time constraints regarding the year of publication. A qualitative analysis of the selected papers was conducted in several steps. Results: this review found 38 studies setting up and analyzing mHealth solutions for older adults. Most research showed improvements in HbA1c, self-management behaviors, and medication adherence in T2DM patients post intervention. However, different mid-to-long term effects were found across studies, specifically concerning the maintenance and adherence to healthy behaviors. The most employed psychological framework was CBT, including techniques such as self-monitoring of outcome behaviors (mostly targeting glycemia measurements and healthy habits as physical activity and/or diet), tailored motivational feedback from medical staff, and psychoeducation or health coaches. The most successful mHealth intervention combined the feature of tailored feedback messages, interactive communication with healthcare professionals, and multifaceted functions. Conclusions: there is a lack of elaborate and detailed information in the literature regarding the factors considered in the design and development of mHealth solutions used as interventions for T2DM self-management in the elderly. Documentation and inclusion of such vital information will foster a transparent and shared decision-making process that will ultimately lead to the development of useful and user-friendly self-management apps that can enhance the quality of life for diabetes patients. Further research adapting mHealth solutions to older adults’ sensory deficits is necessary.This research received no external funding