Mobile Phone and Wearable Sensor-Based mHealth Approach for Psychiatric Disorders and Symptoms : Systematic Review and Link to the m-RESIST Project

Background: Mobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and validating an innovative therapeutic program for treatment-resistant schizophrenia. The program exploits information from mobile phones and wearable sensors for behavioral tracking to support intervention administration. Objective: To systematically review original studies on sensor-based mHealth apps aimed at uncovering associations between sensor data and symptoms of psychiatric disorders in order to support the m-RESIST approach to assess effectiveness of behavioral monitoring in therapy. Methods: A systematic review of the English-language literature, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed through Scopus, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases. Studies published between September 1, 2009, and September 30, 2018, were selected. Boolean search operators with an iterative combination of search terms were applied. Results: Studies reporting quantitative information on data collected from mobile use and/or wearable sensors, and where that information was associated with clinical outcomes, were included. A total of 35 studies were identified; most of them investigated bipolar disorders, depression, depression symptoms, stress, and symptoms of stress, while only a few studies addressed persons with schizophrenia. The data from sensors were associated with symptoms of schizophrenia, bipolar disorders, and depression. Conclusions: Although the data from sensors demonstrated an association with the symptoms of schizophrenia, bipolar disorders, and depression, their usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.Peer reviewe

Time-course of exercise and its association with 12-month bone changes

<p>Abstract</p> <p>Background</p> <p>Exercise has been shown to have positive effects on bone density and strength. However, knowledge of the time-course of exercise and bone changes is scarce due to lack of methods to quantify and qualify daily physical activity in long-term. The aim was to evaluate the association between exercise intensity at 3, 6 and 12 month intervals and 12-month changes in upper femur areal bone mineral density (aBMD) and mid-femur geometry in healthy premenopausal women.</p> <p>Methods</p> <p>Physical activity was continuously assessed with a waist-worn accelerometer in 35 healthy women (35-40 years) participating in progressive high-impact training. To describe exercise intensity, individual average daily numbers of impacts were calculated at five acceleration levels (range 0.3-9.2 <it>g</it>) during time intervals of 0-3, 0-6, and 0-12 months. Proximal femur aBMD was measured with dual x-ray absorptiometry and mid-femur geometry was evaluated with quantitative computed tomography at the baseline and after 12 months. Physical activity data were correlated with yearly changes in bone density and geometry, and adjusted for confounding factors and impacts at later months of the trial using multivariate analysis.</p> <p>Results</p> <p>Femoral neck aBMD changes were significantly correlated with 6 and 12 months' impact activity at high intensity levels (> 3.9 <it>g</it>, <it>r </it>being up to 0.42). Trochanteric aBMD changes were associated even with first three months of exercise exceeding 1.1 <it>g </it>(<it>r </it>= 0.39-0.59, <it>p </it>< 0.05). Similarly, mid-femoral cortical bone geometry changes were related to even first three months' activity (<it>r </it>= 0.38-0.52, <it>p </it>< 0.05). In multivariate analysis, 0-3 months' activity did not correlate with bone change at any site after adjusting for impacts at later months. Instead, 0-6 months' impacts were significant correlates of 12-month changes in femoral neck and trochanter aBMD, mid-femur bone circumference and cortical bone attenuation even after adjustment. No significant correlations were found at the proximal or distal tibia.</p> <p>Conclusion</p> <p>The number of high acceleration impacts during 6 months of training was positively associated with 12-month bone changes at the femoral neck, trochanter and mid-femur. These results can be utilized when designing feasible training programs to prevent bone loss in premenopausal women.</p> <p>Trial registration</p> <p>Clinical trials.gov NCT00697957</p

A theory-driven system model to promote physical activity in the working environment with a persuasive and gamified application

Abstract Physical activity (PA) is important to prevent and lessen the risks of various diseases as well as progress in physical and mental health. Employees expend a lot of time at their workplace such as office environment. Working efficiency may be harmfully affected if the worker is physically inactive. The purpose of this study was to design a system model to guide employees at their workplace on their PA promotion. We propose a system model integrating the psychological theory known as Self-determination Theory (SDT) which indicates that people can be motivated extrinsically through the fulfilment of three psychological needs: autonomy, competence, and relatedness. To do this, game elements such as points, badges and leaderboard were applied into the system model. We utilized the system model to design a gamified persuasive application. We developed a prototype of PA promotion app using the User-Centered Design (UCD) process. We conducted UCD iteration and pilot-tested the prototype of an app with end users. They used the prototype of an app to perform some activities e.g. walking after breakfast and lunch hour. We found that it brings a positive impact on the employees in promoting their PA in their workplace. The result of the study will be used to build an actual persuasive application with gamification techniques

Do nudges work?:using personal normative message in mHealth intervention to dissuade from physical inactivity

Abstract Physical inactivity leads to a high risk of medical complications and triggering substantial health care expenses. The goal of the project within which the research is conducted is to explore the effect of the use of nudges to dissuade individuals from physical inactivity. This study is aimed to design and develop a zero/low-cost nudging mHealth intervention that allows users to check their time with normative messages when walking. This intervention is then utilised for individuals to investigate whether it stimulates physical activity. The design of the nudging intervention is followed by an iterative Design Thinking process. The result of the pilot study has shown us that participants highlighted personal normative message installed as a screensaver in a smartphone as a zero-cost solution to dissuade their physical inactivity. Our future effort is to access this intervention by experimental design studies with quantitative and qualitative surveys, which will be carried out with students to measure physical activity behavioural change

A persuasive mHealth behavioral change intervention for promoting physical activity in the workplace:feasibility randomized controlled trial

Abstract Background: Employees in an office setting are more likely to remain physically inactive. Physical inactivity has become one of the major barriers to overcoming the risk factors for anxiety, depression, coronary heart disease, certain cancers, and type 2 diabetes. Currently, there is a gap in mobile health (mHealth) apps to promote physical activity (PA) for workers in the workplace. Studies on behavior change theories have concluded that health apps generally lack the use of theoretical constructs. Objective: The objective of this study was to study the feasibility of a persuasive app aimed at encouraging PA among employees and to understand the motivational aspects behind the implementation of mHealth apps among office workers. Methods: A 4-week study using a mixed methods (quantitative and qualitative) design was conducted with office-based employees in cities in 4 countries: Oulu, Finland; Carlow, Ireland; London, United Kingdom; and Dhaka, Bangladesh. Of the 220 invited participants (experimental group, n=115; control group, n=105), 84 participated (experimental group, n=56; control group, n=28), consisting of working-age volunteers working in an office setting. Participants used 2 different interventions: The experimental group used an mHealth app for PA motivation, and the control group used a paper diary. The purpose was to motivate employees to engage in healthier behavior regarding the promotion of PA in the workplace. A user-centered design process was followed to design, develop, and evaluate the mHealth app, incorporating self-determination theory (SDT) and using game elements. The paper diary had no specific theory-driven approach, design technique, nor game elements. Results: Compliance with app usage remained relatively low, with 27 participants (experimental group, n=20; control group, n=7) completing the study. The results support the original hypothesis that the mHealth app would help increase PA (ie, promoting daily walking in the workplace) in comparison to a paper diary (P=.033). The mHealth app supported 2 of the basic SDT psychological needs, namely autonomy (P=.004) and competence (P=.014), but not the needs of relatedness (P=.535). Conclusions: The SDT-based mHealth application motivated employees to increase their PA in the workplace. However, compliance with app usage remained low. Future research should further develop the app based on user feedback and test it in a larger sample

Measuring the influence of a persuasive application to promote physical activity

Abstract A fundamental challenge for employees in the office environment is the difficulty of being physically active. The long-term effect of physical inactivity can lower work effectiveness and cause health problems. The non-substantial indication from recent research suggests that persuasive techniques can create a significant impact on motivating people. This study investigates the overall influence of using a persuasive application in promoting physical activity in the workplace, such as office environment. To motivate individuals for healthier behaviour, we implemented and tested an application incorporating Self Determination Theory (SDT). We conducted an eight week long usability evaluation of the application, using the UTAUT model. The questionnaires were based on the factors: Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Behavioural Intention, and Use Behaviour. We found that our persuasive application was satisfactory to motivate users for physical activity promotion

Machine-learning models for activity class prediction:a comparative study of feature selection and classification algorithms

Abstract Purpose: Machine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropriate combination of feature subsets and prediction algorithms for activity class prediction from hip-based raw acceleration data. Methods: The hip-based raw acceleration data collected from 27 participants was split into training (70 %) and validation (30 %) subsets. A total of 206 time- (TD) and frequencydomain (FD) features were extracted from 6-second non-overlapping windows of the signal. Feature selection was done using seven filter-based, two wrapper-based, and one embedded algorithm, and classification was performed with artificial neural network (ANN), support vector machine (SVM), and random forest (RF). For every combination between the feature selection method and the classifiers, the most appropriate feature subsets were found and used for model training within the training set. These models were then validated with the left-out validation set. Results: The appropriate number of features for the ANN, SVM, and RF ranged from 20 to 45. Overall, the accuracy of all the three classifiers was higher when trained with feature subsets generated using filter-based methods compared with when they were trained with wrapper-based methods (range: 78.1 %–88 % vs. 66 %–83.5 %). TD features that reflect how signals vary around the mean, how they differ with one another, and how much and how often they change were more frequently selected via the feature selection methods. Conclusions: A subset of TD features from raw accelerometry could be sufficient for ML-based activity classification if properly selected from different axes

Towards value propositions for persuasive health and wellbeing applications

Abstract Recently, considerable attention has been given to health and wellbeing applications, specifically to persuasive applications. Persuasive applications refer to any interactive computing system designed to transform users’ behaviours and attitudes. One of the major challenges of today’s world is that health and wellbeing applications are not sustainable and scientifically designed. However, value proposition (VP) as a denominator might enhance the efficacy of the persuasive health and wellbeing applications. Research has shown little evidence on the VPs in health and wellbeing applications. This paper proposes key VPs for the persuasive health and wellbeing applications. A literature review was conducted based on relevant articles on the value within the health domain. Hence, narrative synthesis literature review approach had been used. We proposed and evaluated these VPs into our built persuasive health and wellbeing applications. We found that the VPs works well with our applications which might enhance their efficacy in the long run