Smart phones are useful for food intake and physical activity surveys

The Effectiveness of Wearable Devices in Non-Communicable Diseases to Manage Physical Activity and Nutrition: Where We Are?

Wearable devices are increasingly popular in clinical and non-clinical populations as a tool for exercise prescription, monitoring of daily physical activity and nutrition, and health-related parameters management. In this regard, smart devices not only assist people in pursuing a healthier lifestyle, but also provide a constant stream of physiological and metabolic data for management of non-communicable diseases (NCDs). Although the benefits of lifestyle-based interventions (exercise and nutrition) for NCDs are well known, the potential of wearable devices to promote healthy behaviors in clinical populations is still controversial. In this narrative review, we aimed to discuss the current application of wearable devices in NCDs, highlighting their role in prescribing and monitoring daily physical activity and dietary habits in the population living with chronic diseases. None of the studies considered specifically addressed the efficacy of the use of wearable devices, and limited are those that incorporate monitoring of both physical activity and nutrition for NCDs. However, there is evidence that such devices have helped improve physical activity levels, physical fitness, body composition, and metabolic and psychological parameters. Therefore, the authors believe that the benefits obtained from the use of wearable devices are likely to translate to public health and represent one of the important tools for the development of prevention plans in everyday life and clinical practice for optimal patient management.

Multi-Device Nutrition Control

Precision nutrition is a popular eHealth topic among several groups, such as athletes, people with dementia, rare diseases, diabetes, and overweight. Its implementation demands tight nutrition control, starting with nutritionists who build up food plans for specific groups or individuals. Each person then follows the food plan by preparing meals and logging all food and water intake. However, the discipline demanded to follow food plans and log food intake results in high dropout rates. This article presents the concepts, requirements, and architecture of a solution that assists the nutritionist in building up and revising food plans and the user following them. It does so by minimizing human-computer interaction by integrating the nutritionist and user systems and introducing off-the-shelf IoT devices in the system, such as temperature sensors, smartwatches, smartphones, and smart bottles. An interaction time analysis using the keystroke-level model provides a baseline for comparison in future work addressing both the use of machine learning and IoT devices to reduce the interaction effort of users.

Studying health-related internet and mobile device use using web logs and smartphone records

Many people use the internet to seek information that will help them understand their body and their health. Motivations for such behaviors are numerous. For example, users may wish to figure out a medical condition by searching for symptoms they experience. Similarly, they may seek more information on how to treat conditions they have been diagnosed with or seek resources on how to live a healthy life. With the ubiquitous availability of the internet, searching and finding relevant information is easier than ever before and a widespread phenomenon. To understand how people use the internet for health-related information, we use data from a sample of 1,959 internet users. A unique combination of data containing four months of users' browsing histories and mobile application use on computers and mobile devices allows us to study which health websites they visited, what information they searched for and which health applications they used. Survey data inform us about users' socio-demographic background, medical conditions and other health-related behaviors. Results show that women, young users, users with a university education and nonsmokers are most likely to use the internet and mobile applications for health-related purposes. On search engines, internet users most frequently search for pharmacies, symptoms of medical conditions and pain. Moreover, users seem most interested in information on how to live a healthy life, alternative medicine, mental health and women's health. With this study, we extend the field's understanding of who seeks and consumes health information online, what users look for as well as how individuals use mobile applications to monitor their health. Moreover, we contribute to methodological research by exploring new sources of data for understanding humans, their preferences and behaviors.

Considerations for the Development of Mobile Phone Apps to Support Diabetes Self-Management: Systematic Review

Background

There is increased research interest in the use of mobile phone apps to support diabetes management. However, there are divergent views on what constitute the minimum standards for inclusion in the development of mobile phone apps. Mobile phone apps require an evidence-based approach to development which will consequently impact on their effectiveness. Therefore, comprehensive information on developmental considerations could help designers and researchers to develop innovative and effective patient-centered self-management mobile phone apps for diabetes patients.

Objective

This systematic review examined the developmental considerations adopted in trials that engaged mobile phone applications for diabetes self-management.

Methods

A comprehensive search strategy was implemented across 5 electronic databases; Medline, Scopus, Social Science Citation Index, the Cochrane Central Register of Controlled Trials and Cumulative Index of Nursing and Allied Health Literature (CINALHL) and supplemented by reference list from identified studies. Study quality was evaluated using the Joanna Briggs Critical appraisal checklist for trials. Information on developmental factors (health behavioral theory, functionality, pilot testing, user and clinical expert involvements, data privacy and app security) were assessed across experimental studies using a template developed for the review.

Results

A total of 11 studies (10 randomized controlled trials and 1 quasi-experimental trial) that fitted the inclusion criteria were identified. All the included studies had the functionality of self-monitoring of blood glucose. However, only some of them included functions for data analytics (7/11, 63.6%), education (6/11, 54.5%) and reminder (6/11, 54.5%). There were 5/11(45.5%) studies with significantly improved glycosylated hemoglobin in the intervention groups where educational functionality was present in the apps used in the 5 trials. Only 1 (1/11, 9.1%) study considered health behavioral theory and user involvement, while 2 (2/11, 18.1%) other studies reported the involvement of clinical experts in the development of their apps. There were 4 (4/11, 36.4%) studies which referred to data security and privacy considerations during their app development while 7 (7/12, 63.6%) studies provided information on pilot testing of apps before use in the full trial. Overall, none of the studies provided information on all developmental factors assessed in the review.

Conclusions

There is a lack of elaborate and detailed information in the literature regarding the factors considered in the development of apps used as interventions for diabetes self-management. Documentation and inclusion of such vital information will foster a transparent and shared decision-making process that will ultimately lead to the development of practical and user-friendly self-management apps that can enhance the quality of life for diabetes patients.

Smartphone Applications for Educating and Helping Non-motivating Patients Adhere to Medication That Treats Mental Health Conditions: Aims and Functioning

Background: Patients prescribed with medication that treats mental health conditions benefit the most compared to those prescribed with other types of medication. However, they are also the most difficult to adhere. The development of mobile health (mHealth) applications ("apps") to help patients monitor their adherence is fast growing but with limited evidence on their efficacy. There is no evidence on the content of these apps for patients taking psychotropic medication. The aim of this study is to identify and evaluate the aims and functioning of available apps that are aiming to help and educate patients to adhere to medication that treats mental health conditions. Method: Three platform descriptions (Apple, Google, and Microsoft) were searched between October 2015 and February 2016. Included apps need to focus on adherence to medication that treats mental health conditions and use at least a reinforcement strategy. Descriptive information was extracted and apps evaluated on a number of assessment criteria using content analysis. Results: Sixteen apps were identified. All apps included self-monitoring properties like reminders and psycho-educational properties like mood logs. It was unclear how the latter were used or how adherence was measured. Major barriers to medication adherence like patients' illness and medication beliefs and attitudes were not considered nor where information to patients about mediation side effects. Very few apps were tailored and none was developed based on established theories explaining the processes for successful medication adherence like cognitions and beliefs. Reported information on app development and validation was poor. Discussion: A variety of apps with different properties that tackle both intentional and unintentional non-adherence from a different perspective are identified. An evidence-based approach and co-creation with patients is needed. This will ensure that the apps increase the possibility to impact on non-adherence. Theories like social cognition models can be useful in ensuring that patients' education, motivation, skills, beliefs, and type of adherence are taken into consideration when developing the apps. Findings from this study can help clinicians and patients make informed choices and pursue policy-makers to integrate evidence when developing future apps. Quality-assurance tools are needed to ensure the apps are systematically evaluated.

Effectiveness of a smartphone application for improving healthy lifestyles, a randomized clinical trial (EVIDENT II): study protocol

BACKGROUND

New technologies could facilitate changes in lifestyle and improve public health. However, no large randomized, controlled studies providing scientific evidence of the benefits of their use have been made. The aims of this study are to develop and validate a smartphone application, and to evaluate the effect of adding this tool to a standardized intervention designed to improve adherence to the Mediterranean diet and to physical activity. An evaluation is also made of the effect of modifying habits upon vascular structure and function, and therefore on arterial aging.

METHODS/DESIGN

A randomized, double-blind, multicenter, parallel group clinical trial will be carried out. A total of 1215 subjects under 70 years of age from the EVIDENT trial will be included. Counseling common to both groups (control and intervention) will be provided on adaptation to the Mediterranean diet and on physical activity. The intervention group moreover will receive training on the use of a smartphone application designed to promote a healthy diet and increased physical activity, and will use the application for three months. The main study endpoints will be the changes in physical activity, assessed by accelerometer and the 7-day Physical Activity Recall (PAR) interview, and adaptation to the Mediterranean diet, as evaluated by an adherence questionnaire and a food frequency questionnaire (FFQ). Evaluation also will be made of vascular structure and function based on central arterial pressure, the radial augmentation index, pulse velocity, the cardio-ankle vascular index, and carotid intima-media thickness.

DISCUSSION

Confirmation that the new technologies are useful for promoting healthier lifestyles and that their effects are beneficial in terms of arterial aging will have important clinical implications, and may contribute to generalize their application in favor of improved population health.

TRIAL REGISTRATION

Clinical Trials.gov Identifier: NCT02016014.

Smartphone medication adherence apps: potential benefits to patients and providers

OBJECTIVES

To provide an overview of medication adherence, discuss the potential for smartphone medication adherence applications (adherence apps) to improve medication nonadherence, evaluate features of adherence apps across operating systems (OSs), and identify future opportunities and barriers facing adherence apps.

PRACTICE DESCRIPTION

Medication nonadherence is a common, complex, and costly problem that contributes to poor treatment outcomes and consumes health care resources. Nonadherence is difficult to measure precisely, and interventions to mitigate it have been largely unsuccessful.

PRACTICE INNOVATION

Using smartphone adherence apps represents a novel approach to improving adherence. This readily available technology offers many features that can be designed to help patients and health care providers improve medication-taking behavior.

MAIN OUTCOME MEASURES

Currently available apps were identified from the three main smartphone OSs (Apple, Android, and Blackberry). In addition, desirable features for adherence apps were identified and ranked by perceived importance to user desirability using a three-point rating system: 1, modest; 2, moderate; or 3, high. The 10 highest-rated apps were installed and subjected to user testing to assess app attributes using a standard medication regimen. RESULTS 160 adherence apps were identified and ranked. These apps were most prevalent for the Android OS. Adherence apps with advanced functionality were more prevalent on the Apple iPhone OS. Among all apps, MyMedSchedule, MyMeds, and RxmindMe rated the highest because of their basic medication reminder features coupled with their enhanced levels of functionality.

CONCLUSION

Despite being untested, medication apps represent a possible strategy that pharmacists can recommend to nonadherent patients and incorporate into their practice.

Behavioral lifestyle intervention in the treatment of obesity

This article provides an overview of research regarding adult behavioral lifestyle intervention for obesity treatment. We first describe two trials using a behavioral lifestyle intervention to induce weight loss in adults, the Diabetes Prevention Program (DPP) and the Look AHEAD (Action for Health in Diabetes) trial. We then review the three main components of a behavioral lifestyle intervention program: behavior therapy, an energy- and fat-restricted diet, and a moderate- to vigorous-intensity physical activity prescription. Research regarding the influence of dietary prescriptions focusing on macronutrient composition, meal replacements, and more novel dietary approaches (such as reducing dietary variety and energy density) on weight loss is examined. Methods to assist with meeting physical activity goals, such as shortening exercise bouts, using a pedometer, and having access to exercise equipment within the home, are reviewed. To assist with improving weight loss outcomes, broadening activity goals to include resistance training and a reduction in sedentary behavior are considered. To increase the accessibility of behavioral lifestyle interventions to treat obesity in the broader population, translation of efficacious interventions such as the DPP, must be undertaken. Translational studies have successfully altered the DPP to reduce treatment intensity and/or used alternative modalities to implement the DPP in primary care, worksite, and church settings; several examples are provided. The use of new methodologies or technologies that provide individualized treatment and real-time feedback, and which may further enhance weight loss in behavioral lifestyle interventions, is also discussed.