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

mHealth: providing a mindfulness app for women with chronic pelvic pain in gynaecology outpatient clinics: qualitative data analysis of user experience and lessons learnt

OBJECTIVES: To determine whether a pre-existing smartphone app to teach mindfulness meditation is acceptable to women with chronic pelvic pain (CPP) and can be integrated into clinical practice within the National Health Service (NHS) CPP pathways, and to inform the design of a potential randomised clinical trial. DESIGN: A prestudy patient and public involvement (PPI) group to collect feedback on the acceptability of the existing app and study design was followed by a three-arm randomised feasibility trial. In addition, we undertook interviews and focus groups with patients and staff to explore app usability and acceptability. We also obtained participant comments on the research process, such as acceptability of the study questionnaires. SETTING: Two gynaecology clinics within Barts Health NHS, London, UK. PARTICIPANTS: Patients with CPP lasting ≥6 months with access to smartphone or personal computer and understanding of basic English. INTERVENTION: The intervention was mindfulness meditation content plus additional pain module delivered by a smartphone app. Active controls received muscle relaxation content from the same app. Passive (waiting list) controls received usual care. MAIN OUTCOME MEASURES: Themes on user feedback, app usability and integration, and reasons for using/not using the app. RESULTS: The use of the app was low in both active groups. Patients in the prestudy PPI group, all volunteers, were enthusiastic about the app (convenience, content, portability, flexibility, ease of use). Women contributing to the interview or focus group data (n=14), from a 'real world' clinic (some not regular app users), were less positive, citing as barriers lack of opportunities/motivation to use the app and lack of familiarity and capabilities with technology. Staff (n=7) were concerned about the potential need for extra support for them and for the patients, and considered the app needed organisational backing and peer acceptance. CONCLUSION: The opinions of prestudy PPI volunteers meeting in their private time may not represent those of patients recruited at a routine clinic appointment. It may be more successful to codesign/codevelop an app with typical users than to adapt existing apps for use in real-world clinical populations. TRIAL REGISTRATION NUMBER: ISRCTN10925965

Seamless Interactions Between Humans and Mobility Systems

As mobility systems, including vehicles and roadside infrastructure, enter a period of rapid and profound change, it is important to enhance interactions between people and mobility systems. Seamless human—mobility system interactions can promote widespread deployment of engaging applications, which are crucial for driving safety and efficiency. The ever-increasing penetration rate of ubiquitous computing devices, such as smartphones and wearable devices, can facilitate realization of this goal. Although researchers and developers have attempted to adapt ubiquitous sensors for mobility applications (e.g., navigation apps), these solutions often suffer from limited usability and can be risk-prone. The root causes of these limitations include the low sensing modality and limited computational power available in ubiquitous computing devices. We address these challenges by developing and demonstrating that novel sensing techniques and machine learning can be applied to extract essential, safety-critical information from drivers natural driving behavior, even actions as subtle as steering maneuvers (e.g., left-/righthand turns and lane changes). We first show how ubiquitous sensors can be used to detect steering maneuvers regardless of disturbances to sensing devices. Next, by focusing on turning maneuvers, we characterize drivers driving patterns using a quantifiable metric. Then, we demonstrate how microscopic analyses of crowdsourced ubiquitous sensory data can be used to infer critical macroscopic contextual information, such as risks present at road intersections. Finally, we use ubiquitous sensors to profile a driver’s behavioral patterns on a large scale; such sensors are found to be essential to the analysis and improvement of drivers driving behavior.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163127/1/chendy_1.pd

Usability of TeleFOT Nomadic and Aftermarket Devices [D1.8]

This deliverable reports on the Usability activities undertaken in TeleFOT mainly within WPs 4.8 and 4.10. These planned to support the Sub-Project 4 of TeleFOT in Evaluation and Assessment of nomadic devices within the national Field Operational Tests (FOTs). The key objective of WP4.8 in this regard is to provide measurable data that allows comparing usability and user experience of different driver assistance services whilst the key objective of WP4.10 is to identify and define the target and actual technical performance metrics for the Nomadic Devices (NDs) used. Two approaches are described in this Deliverable which have been utilised within TeleFOT for evaluating the usability of the nomadic and aftermarket devices tested within the TeleFOT FOTs. The first approach describes the feedback received from the TeleFOT participants with regard to their user experiences with the devices tested during the FOTs. To complement this information, each test site was asked to supply usability information specifically related to the time taken and the number of user interactions (aka button presses) to access certain functions within their ND. These included time and interactions to access the main menu and primary function, or adjust the volume, as well as to start up and shut down. The participants’ opinions on the design of the device, user interface, initial reactions and benefits to the NDs were then recorded as were ‘Other Issues’ which related to participants’ perceived usefulness, reliability and ease to interpret the information offered by the ND. This method allowed in-depth information to be captured surrounding issues which may have influenced the use of the ND during the FOT and/or common issues which arose. The second approach involved expert evaluations undertaken by HMI analysts working at the test-sites on a number of devices that were tested within TeleFOT. Not all of the devices that were tested within TeleFOT were subjected to expert evaluations. However, the procedure for such evaluations is described along with the results

Determining the Feasibility of Traffic Management Through Mobile Applications in China

The rapid urbanization of China causes traffic problems in its cities. This Interactive Qualifying Project (IQP) aims to determine the feasibility of improving Chinese traffic conditions by applying Smart City initiatives, specifically through mobile applications. The project researches the functions of popular mobile applications for traffic management in the United States and China. With guidance from our sponsor, Dr. Lu Huang of the Zhejiang Smart City Research Center, we surveyed the public from both countries. We explore the current traffic situations in the United States and China, and determine the feasibility of each application’s function. This project provides direction for the development of future Chinese mobile applications and sustainable traffic management research