Designing personal exercise monitoring employing multiple modes of delivery: Implications from a qualitative study on heart rate monitoring

Feasibility and Acceptability of a Mobile Health Exercise Intervention for Inactive Adults: 3-Arm Randomized Controlled Pilot Trial

BACKGROUND

Objective monitoring of self-directed physical activity (PA) is a common approach used in both fitness and health settings to promote exercise behavior, but adherence has been poor. Newer mobile health (mHealth) technologies could be a cost-effective approach to broadening accessibility and providing support for PA behavior change; yet, the optimal method of delivery of such interventions is still unclear.

OBJECTIVE

This study aimed to determine the feasibility and acceptability of an mHealth exercise intervention delivered in combination with objective monitoring in 3 ways: health education emails, asynchronous exercise videos, or synchronous videoconference exercise classes.

METHODS

Physically inactive (<30 min/wk) adults (cisgender women aged 31.5, SD 11.3 years, cisgender men aged 34.1, SD 28.9 years, and nonbinary individuals aged 22.0, SD 0 years) were randomized (1:1:1) to 8 weeks of increasing PA behavioral support: level 1 (health education+objective monitoring, n=26), level 2 (asynchronous contact, level 1+prerecorded exercise videos, n=30), or level 3 (synchronous contact, level 1+videoconference group exercise, n=28). Participants used a heart rate monitor during exercise and a mobile app for interaction. Primary outcomes were feasibility (accrual, retention, and adherence) and acceptability (user experience survey). Secondary outcomes assessed at baseline and 8 weeks included resting heart rate, self-reported PA, and quality of life. The exercise dose was evaluated throughout the intervention.

RESULTS

Between August 2020 and August 2021, 204 adults were screened for eligibility. Out of 135 eligible participants, 84 (62%) enrolled in the study. Retention was 50% (13/26) in level 1, 60% (18/30) in level 2 and 82% (23/28) in level 3, while adherence was 31% (8/26) in level 1, 40% (12/30) in level 2 and 75% (21/28) in level 3. A total of 83% (70/84) of the study sample completed the intervention, but low response rates (64%, 54/84) were observed postintervention at week-8 assessments. Program satisfaction was highest in participants receiving exercise videos (level 2, 80%, 8/10) or exercise classes (level 3, 80%, 12/15), while only 63% (5/8) of level 1 reported the program as enjoyable. Level 3 was most likely to recommend the program (87%, 13/15), compared to 80% (8/10) in level 2 and 46% (5/8) in level 1. Self-reported PA significantly increased from baseline to intervention in level 3 (P<.001) and level 2 (P=.003), with no change in level 1. Level 3 appeared to exercise at higher doses throughout the intervention.

CONCLUSIONS

Only the videoconference exercise class intervention met feasibility criteria, although postintervention response rates were low across all groups. Both videoconference and prerecorded videos had good acceptability, while objective monitoring and health education alone were not feasible or acceptable. Future studies are needed to examine the effectiveness of videoconference exercise interventions on health-related outcomes during nonpandemic times and how asynchronous interventions might maximize adherence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05192421; https://clinicaltrials.gov/study/NCT05192421.

Development of Elderly Life Quality Database in Thailand with a Correlation Feature Analysis

Understanding the context of the elderly is very important for determining guidelines that improve their quality of life. One problem in Thailand, in this context, is that each organization involved in caring for the elderly has its own separate data collection, resulting in mismatches that negatively affect government agencies in their monitoring. This study proposes the development of a central database for elderly care and includes a study of factors affecting their quality of life. The proposed system can be used to collect data, manage data, perform data analysis with multiple linear regression, and display results via a web application in visualizations of many forms, such as graphs, charts, and spatial data. In addition, our system would replace paper forms and increase efficiency in work, as well as in storage and processing. In an observational case study, we include 240 elderly in village areas 5, 6, 7, and 8, in the Makham Tia subdistrict, Muang district, Surat Thani province, Thailand. Data were analyzed with multiple linear regression to predict the level of quality of life by using other indicators in the data gathered. This model uses only 14 factors of the available 39. Moreover, this model has an accuracy of 86.55%, R-squared = 69.11%, p-Value < 2.2×10−16, and Kappa = 0.7994 at 95% confidence. These results can make subsequent data collection more comfortable and faster as the number of questions is reduced, while revealing with good confidence the level of quality of life of the elderly. In addition, the system has a central database that is useful for elderly care organizations in the community, in support of planning and policy setting for elderly care.

A Review of Virtual Coaching Systems in Healthcare: Closing the Loop With Real-Time Feedback

This review focuses on virtual coaching systems that were designed to enhance healthcare interventions, combining the available sensing and system-user interaction technologies. In total, more than 1,200 research papers have been retrieved and evaluated for the purposes of this review, which were obtained from three online databases (i.e.,PubMed, Scopus and IEEE Xplore) using an extensive set of search keywords. After applying exclusion criteria, the remaining 41 research papers were used to evaluate the status of virtual coaching systems over the past 10 years and assess current and future trends in this field. The results suggest that in home coaching systems were mainly focused in promoting physical activity and a healthier lifestyle, while a wider range of medical domains was considered in systems that were evaluated in lab environment. In home patient monitoring with IoT devices and sensors was mostly limited to activity trackers, pedometers and heart rate monitoring. Real-time evaluations and personalized patient feedback was also found to be rather lacking in home coaching systems and this is the most alarming find of this analysis. Feasibility studies in controlled environment and an ongoing active research on Horizon 2020 funded projects, show that the future trends in this field are aiming to close the loop with automated patient monitoring, real-time evaluations and more precise interventions.

Rehabilitation, the Great Absentee of Virtual Coaching in Medical Care: Scoping Review

BACKGROUND

In the last few years, several studies have focused on describing and understanding how virtual coaches (ie, coaching program or smart device aiming to provide coaching support through a variety of application contexts) could be key drivers for health promotion in home care settings. As there has been enormous technological progress in the field of artificial intelligence and data processing in the past decade, the use of virtual coaches gains an augmented attention in the considerations of medical innovations.

OBJECTIVE

This scoping review aimed at providing an overview of the applications of a virtual coach in the clinical field. In particular, the review focused on the papers that provide tangible information for coaching activities with an active implication for engaging and guiding patients who have an ongoing plan of care.

METHODS

We aimed to investigate the use of the term virtual coach in the clinical field performing a methodical review of the relevant literature indexed on PubMed, Scopus, and Embase databases to find virtual coach papers focused on specific activities dealing with clinical or medical contexts, excluding those aimed at surgical settings or electronic learning purposes.

RESULTS

After a careful revision of the inclusion and exclusion criteria, 46 records were selected for the full-text review. Most of the identified articles directly or indirectly addressed the topic of physical activity. Some papers were focused on the use of virtual coaching (VC) to manage overweight or nutritional issues. Other papers dealt with technological interfaces to facilitate interactions with patients suffering from different chronic clinical conditions such as heart failure, chronic obstructive pulmonary disease, depression, and chronic pain.

CONCLUSIONS

Although physical activity is a healthy practice that is most encouraged by a virtual coach system, in the current scenario, rehabilitation is the great absentee. This paper gives an overview of the tangible applications of this tool in the medical field and may inspire new ideas for future research on VC.

What Adherence Measures Should Be Used in Trials of Home-Based Rehabilitation Interventions? A Systematic Review of the Validity, Reliability, and Acceptability of Measures

OBJECTIVE

To systematically review methods for measuring adherence used in home-based rehabilitation trials and to evaluate their validity, reliability, and acceptability.

DATA SOURCES

In phase 1 we searched the CENTRAL database, NHS Economic Evaluation Database, and Health Technology Assessment Database (January 2000 to April 2013) to identify adherence measures used in randomized controlled trials of allied health professional home-based rehabilitation interventions. In phase 2 we searched the databases of MEDLINE, Embase, CINAHL, Allied and Complementary Medicine Database, PsycINFO, CENTRAL, ProQuest Nursing and Allied Health, and Web of Science (inception to April 2015) for measurement property assessments for each measure.

STUDY SELECTION

Studies assessing the validity, reliability, or acceptability of adherence measures.

DATA EXTRACTION

Two reviewers independently extracted data on participant and measure characteristics, measurement properties evaluated, evaluation methods, and outcome statistics and assessed study quality using the COnsensus-based Standards for the selection of health Measurement INstruments checklist.

DATA SYNTHESIS

In phase 1 we included 8 adherence measures (56 trials). In phase 2, from the 222 measurement property assessments identified in 109 studies, 22 high-quality measurement property assessments were narratively synthesized. Low-quality studies were used as supporting data. StepWatch Activity Monitor validly and acceptably measured short-term step count adherence. The Problematic Experiences of Therapy Scale validly and reliably assessed adherence to vestibular rehabilitation exercises. Adherence diaries had moderately high validity and acceptability across limited populations. The Borg 6 to 20 scale, Bassett and Prapavessis scale, and Yamax CW series had insufficient validity. Low-quality evidence supported use of the Joint Protection Behaviour Assessment. Polar A1 series heart monitors were considered acceptable by 1 study.

CONCLUSIONS

Current rehabilitation adherence measures are limited. Some possess promising validity and acceptability for certain parameters of adherence, situations, and populations and should be used in these situations. Rigorous evaluation of adherence measures in a broader range of populations is needed.

Understanding persuasion contexts in health gamification: A systematic analysis of gamified health behavior change support systems literature

BACKGROUND

Gamification is increasingly used as a design strategy when developing behavior change support systems in the healthcare domain. It is commonly agreed that understanding the contextual factors is critical for successful gamification, but systematic analyses of the persuasive contexts have been lacking so far within gamified health intervention studies.

OBJECTIVES AND METHODS

Through a persuasion context analysis of the gamified health behavior change support systems (hBCSSs) literature, we inspect how the contextual factors have been addressed in the prior gamified health BCSS studies. The implications of this study are to provide the practitioners and researchers examples of how to conduct a systematic analysis to help guide the design and research on gamified health BCSSs. The ideas derived from the analysis of the included studies will help identify potential pitfalls and shortcomings in both the research and implementations of gamified health behavior change support systems.

RESULTS

We systematically analyzed the persuasion contexts of 15 gamified health intervention studies. According to our results, gamified hBCSSs are implemented under different facets of lifestyle change and treatments compliance, and use a multitude of technologies and methods. We present a set of ideas and concepts to help improve endeavors in studying gamified health intervention through comprehensive understanding of the persuasive contextual factors.

CONCLUSIONS

Future research on gamified hBCSSs should systematically compare the different combinations of contextual factors, related theories, chosen gamification strategies, and the study of outcomes to help understand how to achieve the most efficient use of gamification on the different aspects of healthcare. Analyzing the persuasion context is essential to achieve this. With the attained knowledge, those planning health interventions can choose the 'tried-and-tested' approaches for each particular situation, rather than develop solutions in an ad-hoc manner.

The quantified patient: a patient participatory culture

The Quantified Self Movement, which aims to improve various aspects of life and health through recording and reviewing daily activities and biometrics, is a new and upcoming practice of self monitoring that holds much promise. Now, the most underutilized resource in ambulatory health care, the patient, can participate like never before, and the patient's Quantified Self can be directly monitored and remotely accessed by health care professionals.