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

Game Changer: Investing in Digital Play to Advance Children's Learning and Health

Based on a literature review and interviews with digital learning experts, explores how digital games can foster skills and knowledge for better academic performance and health. Makes recommendations for government research, partnerships, and media

A comparison of video conferencing and in-person health coaching approaches in combination with mHealth devices on weight loss, physical activity, and glycemic control

Background: Compare health coaching efficacy on weight loss, physical activity, and glycemic control between individualized video conferencing (VC), in-person (IP) and control (CG) groups of adults with high BMI. Methods: Thirty adults (BMI≥30 kg/m2) were randomly assigned to create three groups of 10 members each. Participants received a wireless accelerometer watch and weight scale to sync with their personal smartphones and downloaded apps. Participants assigned to VC and IP received weekly health coaching individualized based on data uploaded over the 12-wk intervention. Steps/day and weight loss were analyzed via analyses of covariance (ANCOVA). Between-group ANOVAs analyzed post-intervention changes in weight (kg), glucose, HbA1c, and HOMA-IR. Results: Weight loss (8.23±4.5kg; 7.7%) was greater (pp≤.05); VC consistently had the higher step/day averages. No between-group differences were found for any glycemic control markers. Conclusion: Our innovative, multidisciplinary, telemedicine health coaching delivered through video conferencing led to favorable changes in weight loss, physical activity, and HOMA-IR that surpassed changes when health coaching was delivered in person or was absent. Future studies using video conferencing to investigate health coaching delivered in group and individualized formats and for other population subgroups are needed as are studies investigating the impact of weight loss on other health outcomes (e.g. lipid profile, glycemic control, and inflammatory markers)

Outlook Magazine, Summer 2016

https://digitalcommons.wustl.edu/outlook/1198/thumbnail.jp

Empowering Diabetes Patient with Mobile Health Technologies

Chronic diseases, especially diabetes mellitus, are huge public health burden. Therefore, new health care models for sharing the responsibility for care among health care providers and patients themselves are needed. The concept of empowerment promotes patient’s active involvement and control over their own health. It can be achieved through education, self-management, and shared decision making. All these aspects can be covered by mobile health technologies, the so-called mHealth. This term comprises mobile phones, patient monitoring devices, tablets, personal digital assistants, other wireless devices, and numerous apps. Many challenges of diabetics can be addressed by mHealth, including glycemic control, nutrition control, physical activity, high blood pressure, medication adherence, obesity, education, diabetic retinopathy screening, diabetic foot screening, and psychosocial care. However, mHealth plays only minor role in diabetes management, despite numerous apps on the market. Namely, these apps have many shortcomings and the majority of them does not include important functions. Moreover, these apps lack the perceived additional benefit by the user and the ease of use, important factors for acceptance of mHealth. Studies of diabetes apps regarding usability and accessibility have shown moderate results. Beside improvements of apps usability, the future of diabetes mHealth lies probably in personalized education and self-management with the help of decision support systems. At the same time, work on artificial pancreas is in progress and smartphone could be used as user interface

Investigating the use of mobile technology to promote active lifestyles and improved glycaemic control in individuals with type 2 diabetes

The purpose of this thesis was to examine the potential of using mobile technology to promote active lifestyles and improved glycaemic control in individuals with Type 2 diabetes. Chapter 1 introduced the research area, thesis rationale, and the design and structure of the thesis. Five studies were undertaken as part of this thesis. This first (Chapter 2) was a systematic and integrated literature review examining the effectiveness, acceptability and feasibility of using mobile technology to promote active living in adults with Type 2 Diabetes. The second (Chapter 3) presented the challenges and solutions of combining glucose and activity data sets measured continuously using mobile technology. The third (Chapter 4) examined the physical activity, sedentary behaviour and glucose patterns of adults with Type 2 diabetes in a free-living setting using mobile technology. The fourth (Chapter 5) examined the individual glycaemic response in adults with Type 2 Diabetes to interrupting prolonged sedentary behaviour in a controlled setting. Study five (Chapter 6) explored the experiences of, and attitudes towards, using mobile technologies to promote active living in adults with Type 2 diabetes. The final chapter (Chapter 7) discussed the findings of these studies in the wider context of the thesis and how the findings can be used to positively impact diabetes care and future research.The purpose of this thesis was to examine the potential of using mobile technology to promote active lifestyles and improved glycaemic control in individuals with Type 2 diabetes. Chapter 1 introduced the research area, thesis rationale, and the design and structure of the thesis. Five studies were undertaken as part of this thesis. This first (Chapter 2) was a systematic and integrated literature review examining the effectiveness, acceptability and feasibility of using mobile technology to promote active living in adults with Type 2 Diabetes. The second (Chapter 3) presented the challenges and solutions of combining glucose and activity data sets measured continuously using mobile technology. The third (Chapter 4) examined the physical activity, sedentary behaviour and glucose patterns of adults with Type 2 diabetes in a free-living setting using mobile technology. The fourth (Chapter 5) examined the individual glycaemic response in adults with Type 2 Diabetes to interrupting prolonged sedentary behaviour in a controlled setting. Study five (Chapter 6) explored the experiences of, and attitudes towards, using mobile technologies to promote active living in adults with Type 2 diabetes. The final chapter (Chapter 7) discussed the findings of these studies in the wider context of the thesis and how the findings can be used to positively impact diabetes care and future research

Effectiveness of a Wearable Fitness Tracker: Practice Implications in Allied Health -- a Single Case Study

ABSTRACT Purpose: The purpose of this single case study was to examine the effectiveness of utilizing a wearable fitness tracker device in self-monitoring behavior change in complying with prescribed treatment. It was hypothesized that using a wearable self-monitoring device while involved in the treatment of multiple medical conditions will be beneficial to behavioral compliance and behavioral change in an overweight type 2 diabetic, geriatric subject being treated by a multidisciplinary health team utilizing an integrated treatment model. Methods: An exploratory single case study research design is employed to explore those situations in which the intervention, a wearable monitoring device, is employed. This observational case study model was applied to the utility of self-monitoring wearable smart technology marketed as FitBit for self-monitoring activity and exercise over a 36-week period. Results: After the 36-week intervention program, results revealed qualitative improvements in the (1) active minutes, (2) steps taken and (3) miles walked by the subject. In addition, the technology reported on calories burned, sleep hours and minutes logged and liquid consumed during each 24-hour period. The integrated allied health team was able to monitor changes made over time and noted improved time dedicated to exercise, walking and total miles walked. On miles walked per day, the results show that the subject increased miles walked from less than one mile per day to more than 4.6 miles per day which approached the recommended 5 miles per day goal. The calorie monitor aided the subject in changing calorie intake from that which exceeded 3500 per day to the recommended 2500 calories per day. Furthermore, the hours slept per night changed from less than 6.8 per night to 8.1 per day. Conclusions: It was concluded that a 36-week intervention program can be an effective intervention methodology for improved health and well-being as measured by standard healthcare and wellness markers utilizing a wearable fitness tracker device like the Fitbit. While further research is needed with a larger sample, it is therefore recommended that allied health professionals consider the utilization of wearable smart technology as an adjunct to self-monitoring and compliance with treatment planning and follow-up care with allied health care providers

The Determinants of Physical Activity, Self-Monitoring of Blood Glucose, and Poor Glycemic Control Among Individuals Diagnosed With Type 2 Diabetes in Saudi Arabia: A Cross-Sectional Study Based on the Saudi Health Interview Survey (SHIS)

The prevalence of diabetes and poor glycemic control in Saudi Arabia has increased that contributed to the growing number of deaths in Saudi Arabia. It is known that type 2 diabetes (T2DM) can be prevented but there is a lack information about the magnitude of the of diabetes at national level as well as the risk factors for physical activity (PA), self-monitoring of blood glucose (SMBG), and poor glycemic. Thus, through utilizing Health promotion model (HPM), the aims are to examine the personal factors, cognitive-perceptual, and behavioral determinants of three outcomes; physical activity, SMBG, and poor glycemic control. A secondary data (Saudi health interview survey-2013) was used with two sample sizes for examining PA and SMBG (808 participants who reported to have T2DM and were 18 year or older) and poor glycemic control (391 participants who reported to have T2DM and had data about their blood glucose level) outcomes. Bivariate and multivariate logistic regression were conducted to address the research questions at alpha level of 0.05. The results showed that the prevalence of physical activity, SMBG, and poor glycemic control, were 9.1%, 55.4%, and 34%, respectively. Younger age (Adjusted odds ratio [AOR] = 2.84), and higher education (AOR = 3.14) were associated with PA, while health professional support for treatment (HPST) was inversely associated with PA (AOR = 0.35). Factors associated with SMBG were obesity (Adjusted prevalence ratio [APR] = 1.20), middle (APR = 1.30) and higher (APR =1.49) education, while shorter diabetes duration (AOR = 0.78 for \u3c 5 years and 0.78 for 5-9 years) and Eastern region (AOR = 0.66) were inversely associated with SMBG. For poor glycemic control, the only predictor was Eastern region (AOR = 1.55) compared to the Central region. Further analysis showed that region of residence, education, diabetes duration, and age were prominent predictors of all cognitive-perceptual and behavioral outcomes. The study suggested individualizing plan of care for diabetic patients due to disparity in the personal factors. The study supported the urgent change in the healthcare system to adapt healthcare professional team-based care. Finally, longitudinal studies at both national and regional levels are needed to determine the causal relationship focusing on both personal and psychological factors

Research Advances: January 2014

The VA has a comprehensive research agenda to help the newest generation of Veterans -- those returning from operations Enduring Freedom, Iraqi Freedom, and New Dawn. In addition to exploring new treatments for traumatic brain injury and other complex blast-related injuries, VA researchers are examining ways to improve the delivery of health care services for these Veterans and promote their reintegration back into their families, communities, and workplaces.This publication reviews recent advances in research about Veterans' health and well-being

Role of Continuous Glucose Monitoring Technology for Type 2 Diabetes Management

Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 201