Adaptive intervention design in mobile health: Intervention design and development in the Cell Phone Intervention for You trial.

BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.

Feasibility, acceptability and potential effectiveness of a mobile health (mHealth) weight management programme for New Zealand adults

Background
Mobile health (mHealth) behaviour change programmes use mobile phones and the internet to deliver health information and behaviour change support to participants. Such programmes offer a potentially cost-effective way to reach many individuals who do not currently access weight loss services. We developed a mHealth weight management programme using proven face-to-face behaviour change techniques and incorporating target population input. Our aim was to evaluate the feasibility, acceptability and potential effectiveness of this programme for ethnically diverse adults with a view to informing a larger trial.

Results
Fifty three adults who had a BMI of ≥25 kg/m2 and wanted to lose weight (81% female, mean age 42 years, mean BMI 35.7 kg/m2, 26% Maori, 34% Pacific) received the eight-week mHealth weight loss programme. Anthropometric measures were taken at two face-to-face assessments at baseline and 12-weeks (i.e. four weeks after cessation of intervention).

Twelve-week follow-up measurements were available for 36/53 participants (68%). Non-completers were younger and more likely to be male and of Pacific ethnicity. Thirty five participants (66%) reported reading ‘all or most’ text messages sent and 96% responded to at least one text data collection question over the eight-week active intervention period. Eighty one per cent of participants logged in to the study website at least once during the eight-week study period. In the intention-to-treat analysis, mean weight change was -1.0 kg (SD 3.1) at 12 weeks (p = 0.024) and change in BMI was -0.34 kg/m2 (SD 1.1) (p = 0.026). In the completers only analysis (n = 36), mean weight change was -1.4 kg (SD 3.6) (p = 0.023) and change in BMI was -0.50 kg/m2 (SD 1.3) (p = 0.025).

Conclusions
A mHealth weight management programme is feasible to deliver to an ethnically diverse population. Changes in body weight and BMI at 12 weeks indicate that the programme could be effective in supporting people with weight loss. However, the high dropout rate indicates a need for further improvements to the programme.

Biomedical sensing analyzer (BSA) for mobile-health (mHealth)-LTE

The rapid expansion of mobile-based systems, the capabilities of smartphone devices, as well as the radio access and cellular network technologies are the wind beneath the wing of mobile health (mHealth). In this paper, the concept of biomedical sensing analyzer (BSA) is presented, which is a novel framework, devised for sensor-based mHealth applications. The BSA is capable of formulating the Quality of Service (QoS) measurements in an end-to-end sense, covering the entire communication path (wearable sensors, link-technology, smartphone, cell-towers, mobile-cloud, and the end-users). The characterization and formulation of BSA depend on a number of factors, including the deployment of application-specific biomedical sensors, generic link-technologies, collection, aggregation, and prioritization of mHealth data, cellular network based on the Long-Term Evolution (LTE) access technology, and extensive multidimensional delay analyses. The results are studied and analyzed in a LabView 8.5 programming environment.

Predictive data mining for converged internet of things: a mobile health perspective

Mobile Health (mHealth) is now emerging with Internet of Things (IoT), Cloud and big data along with the prevalence of smart wearable devices and sensors. There is also the emergence of smart environments such as smart homes, cars, highways, cities, factories and grids. Presently, it is difficult to quickly forecast or prevent urgent health situations in real-time as health data are analyzed offline by a physician. Sensors are expected to be overloaded by demands of providing health data from IoT networks and smart environments. This paper proposes to resolve the problems by introducing an inference system so that life-threatening situations can be prevented in advance based on a short and long term health status prediction. This prediction is inferred from personal health information that is built by big data in Cloud. The inference system can also resolve the problem of data overload in sensor nodes by reducing data volume and frequency to reduce workload in sensor nodes. This paper presents a novel idea of tracking down and predicting a personal health status as well as intelligent functionality of inference in sensor nodes to interface IoT networks

Servizi e applicazioni di mobile health nei progetti di telemedicina ospedale-territorio

L'obiettivo della tesi è di descrivere l'importanza attuale della comunicazione mobile nel settore dell'assistenza sanitaria e di mostrare la perfetta integrazione tra tecnologie mobili e telemedicina, in particolare nei progetti di telemedicina ospedale-territorio.

Self-management di malattie croniche in sistemi di mobile Health: sviluppo di un modello agent-based per casi di diabete

L'obiettivo della tesi è proporre e motivare l'adozione di un modello computazionale Agent-Based nell'ambito del Self-Management di malattie croniche in un sistema di mobile Health. Viene quindi affrontata in maniera approfondita la tematica del mobile Health, settore in grande espansione che vede l'introduzione massiccia dei dispositivi mobili (smartphone, tablet, PDA) in ambito sanitario, e quella del Self-Managment di malattie croniche, un processo di cura caratterizzato dalla partecipazione autonoma del paziente stesso, fornendo una panoramica dei vari approcci computazionali sviluppati. Successivamente vengono presentate le peculiarità dei modelli computazionali risultati dalle ricerche in letteratura strumenti innovati nell'ambito. Nel caso di studio viene adottata la tecnica di modellazione Agent-Based per sviluppare un modello a supporto di malati cronici affetti da diabete mellito di tipo 1. Con la successiva implementazione sulla piattaforma di simulazione MASON, vengono eseguiti diversi esperimenti per dimostrare la fattibilità dell’approccio adottato nell'ambito del Self-Management di malattie croniche.

Childhood obesity treatment: integrating mobile health technology into a paediatric obesity service

Background: The management of childhood obesity is challenging. Aims: Thesis, i) reviews the evidence for lifestyle treatment of obesity, ii) explores cardiometabolic burden in childhood obesity, iii) explores whether changes in body composition predicts change in insulin sensitivity (IS), iv) develops and evaluates a lifestyle obesity intervention; v) develops a mobile health application for obesity treatment and vi) tests the application in a clinical trial. Methods: In Study 1, systematic reviews and meta-analyses of the 12‐month effects of lifestyle and mHealth interventions were conducted. In Study 2, the prevalence of cardiometabolic burden was estimated in a consecutive series of 267 children. In Study 3, body composition was estimated with bioelectrical impedance analysis (BIA) and dual x-ray absorptiometry (DXA) and linear regression analyses were used to estimate the extent to which each methods predicted change in IS. Study 4 describes the development of the Temple Street W82GO Healthy Lifestyle intervention for clinical obesity in children and a controlled study of treatment effect in 276 children is reported. Study 5 describes the development and testing of the Reactivate Mobile Obesity Application. Study 6 outlines the development and preliminary report from a clinical effectiveness trial of Reactivate. Results: In Study 1, meta--‐analyses BMI SDS changed by -0.16 (-0.24,‐0.07, p<0.01) and -0.03 (-0.13, 0.06, p=0.48). In study 2, cardiometabolic comorbidities were common (e.g. hypertension in 49%) and prevalence increased as obesity level increased. In Study 3, BC changes significantly predicted changes in IS. In Study 4, BMI SDS was significantly reduced in W82GO compared to controls (p<0.001). In Study 5, the Reactivate application had good usability indices and preliminary 6‐month process report data from Study 6, revealed a promising effect for Reactivate. Conclusions: W82GO and Reactivate are promising forms of treatment.

Randomized Trial for a Mobile Health Approach to Increase Uptake of Cervical Cancer Screening in Tanzania

Background: Largely due to low availability and uptake of screening in low- and middle-income countries, cervical cancer is the second ranked cancer among women in these countries. This is a tragedy because cervical cancer is one of the most preventable carcinomas. This thesis will investigate behaviour change methods, which capitalize on the recent exponential increase in ownership of mobile phones in Tanzania, to increase uptake of cervical cancer screening (CCS) in the Kilimanjaro region of Tanzania. Objectives: 1) To evaluate the effectiveness of behaviour change messages delivered via short message service (SMS) on the uptake of CCS in the Kilimanjaro region; 2) to evaluate the effectiveness of a transportation eVoucher on the uptake of CCS in the Kilimanjaro region; 3) to explore characteristics associated with CCS uptake in the Kilimanjaro region; and 4) to determine the attitudes towards and perceived benefit of behaviour change SMS messages and eVouchers intended to increase uptake of CCS. Methods: In the Kilimanjaro Region, 853 women participated in a randomized controlled trial. Baseline data was collected through self-report through systematic stratified random sampling. Participants were randomized to one of three groups: a control group, a group receiving behaviour change messages delivered via SMS, or a group receiving a travel eVoucher and identical SMS as the SMS group. A fieldworker recorded participants attending screening at the CCS clinics and administered a post-screening survey. The follow-up period was two months from the time of the participant’s enrolment. Logistic regression (both for the combined and stratified data sets) was used to determine associations between the behaviour change interventions, baseline characteristics and cervical cancer screening uptake. Results: All participants receiving SMS messages (SMS or eVoucher group) were more likely to attend cervical cancer screening in comparison with the control group. 83% of participants who attended screening shared the information contained in the messages with others. Conclusions: Behaviour change messages delivered via SMS and transportation eVouchers have the potential to increase uptake of cervical cancer screening in the Kilimanjaro region of Tanzania. Harnessing this potential will require implementing these interventions alongside other methods to achieve maximum impact.

A mobile health network disaster management system

A common occurrence in almost all full-scale natural disasters is the rapid destruction of the telecommunication infrastructure as the inevitable unfolds, which tends to halt the necessary communications between the humanitarian operators and the people in need. In such scenarios, the deployment of wireless networks would provide fast and temporary remedies, however these networks normally do not provide services to the end-users and ordinary people, instead they provide connectivity between groups of end-users administered by a local service provider. From a range of services provided to the end-users by the humanitarian operators, healthcare is by far the top priority. This is considered through the utilization of smartphones in a Mobile Health (mHealth) perspective, which is an emerging concept for monitoring and tracking end-user health conditions. This article considers an mHealth system used in a tsunami-stricken disaster scenario, including a discussion on the most recent advances of Device to Device (D2D) and LTE-Direct technologies.

The effectiveness of mobile-health behaviour change interventions for cardiovascular disease self-management: a systematic review

BACKGROUND: Mobile wireless devices (mHealth) have been used to deliver cardiovascular disease self-management interventions to educate and support patients in making healthy lifestyle changes. This systematic review aimed to determine the effectiveness of mHealth interventions on behavioural lifestyle changes and medication adherence for cardiovascular disease self-management. METHODS: A comprehensive literature search was conducted from inception through to 3 March 2015 using MEDLINE, PubMed, PsycINFO, EMBASE and The Cochrane Library. Eligible studies used an experimental trial design to determine the effectiveness of an mHealth intervention to change lifestyle behaviours in any cardiovascular disease population. Data extracted included intervention and comparison group characteristics with a specific focus on the use of behaviour change techniques. RESULTS: Seven studies met our inclusion criteria and were included in the qualitative synthesis. All interventions were delivered in part by mobile phone text messaging. Three studies were effective at improving adherence to medication and two studies increased physical activity behaviour. No effects were observed on dietary behaviour or smoking cessation, measured in one study each. Simple text messaging interventions appeared to be most effective; however, no clear relationships were found between study findings and intervention dose, duration or behaviour change techniques targeted. CONCLUSIONS: Our review found mHealth has the potential to change lifestyle behaviour. Results are still limited to a small number of trials, inconsistent outcome measures and ineffective reporting of intervention characteristics. Large scale, longitudinal studies are now warranted to gain a clear understanding of the effects of mHealth on behaviour change in the cardiovascular disease population.

Sistemi di Mobile-Health per il monitoraggio e l'assistenza alla gravidanza

Con il termine "Mobile-Health" si intende l’uso di tecnologie mobili in ambito medico-sanitario. Questa tesi si propone di fornire un quadro generale di come i sistemi di Mobile-Health possano aiutare nell'assistenza e nel monitoraggio della gravidanza. Attraverso l'analisi delle ricerche effettuate in questo campo, e lo studio dei sistemi attualmente utilizzati in ambito ospedaliero, si cerca di valutare se effettivamente questo tipo di tecnologie può fornire un contributo significativo nell'assistere le donne incinte. Viene trattato il tema del Self-Management che riguarda appunto l'auto-gestione della propria condizione di salute attraverso l’uso di tecnologie mobili. Vengono introdotti problemi e complicazioni della gravidanza e i corrispettivi trattamenti. Si analizzano studi e ricerche che riguardano dispositivi e software per le donne incinte, compreso il tema delle “app mediche”. Infine, grazie al contributo delle dottoresse Iliana Colonna e Marina Carfagna (coordinatrici ostetriche negli ospedali di Rimini e Cesena), si presenta una panoramica sull’attuale uso di tecnologie nei reparti ospedalieri di ostetricia.

Secure and Privacy-aware Data Collection and Processing in Mobile Health Systems

Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data.

Privacy-enabled mobile-health (mhealth)-based diabetic solution

Diabetes is one of the leading chronic diseases affecting the lives of millions globally and early detection and treatment of this disease can serve to improve the quality of life for patients as well as suspend further health complications arising from diabetes. Continuous Glucose Monitors (CGM) and Insulin Pumps (IP) have been widely deployed to monitor the sugar levels in the blood stream and inject appropriate amounts of insulin to compensate for the underperforming pancreas functions of the patients’ bodies and thereby may provide appropriate treatment solutions for many diabetic sufferers. With the invention and deployment of Smartphones, the quality and performance associated with treating diabetes has reached new heights, however the privacy and security of mobilebased diabetic systems remain in ongoing challenges. This paper aims to focus on the privacy and security challenges of Mobile-Health (mHealth)-based Diabetic solutions.