mActive-Smoke: A Prospective Observational Study Using Mobile Health Tools to Assess the Association of Physical Activity With Smoking Urges

The Impact of Wearable Technologies in Health Research: Scoping Review

Background

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.

Objective

In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.

Methods

We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.

Results

We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).

Conclusions

Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.

Mobile health apps use among Jordanian outpatients: A descriptive study

Our purpose in this descriptive cross-sectional study was to examine the prevalence of mobile health (mHealth) apps use, factors associated with downloading mHealth apps, and to describe characteristics of mHealth apps use among Jordanian patients in government-sponsored outpatient clinics. A total of 182 (41.6%) of the 438 outpatients who completed questionnaires downloaded mHealth apps. Common reasons for downloading mHealth apps included tracking physical activity, losing weight, learning exercises, as well as monitoring, and controlling diet. More than two thirds of the users (70%) stopped using the apps they downloaded due to loss of interest, lack of anticipated support, too time consuming, or better apps available. The most common personal reasons for never downloading mHealth apps were lack of interest, in good health, and the most common technical reasons included a limited data plan, lack of trust, cost, and complexity of the apps. We also found that gender, age, weight, and educational level influenced the decision whether to download mHealth apps or not. We have shown the potential in mHealth apps use among Jordanian patients is promising, and health care systems must adopt this technology as well as work through population needs and preferences to supply it.

Using Mobile Health Tools to Assess Physical Activity Guideline Adherence and Smoking Urges: Secondary Analysis of mActive-Smoke

Background

Rates of cigarette smoking are decreasing because of public health initiatives, pharmacological aids, and clinician focus on smoking cessation. However, a sedentary lifestyle increases cardiovascular risk, and therefore, inactive smokers have a particularly enhanced risk of cardiovascular disease.

Objective

In this secondary analysis of mActive-Smoke, a 12-week observational study, we investigated adherence to guideline-recommended moderate-to-vigorous physical activity (MVPA) in smokers and its association with the urge to smoke.

Methods

We enrolled 60 active smokers (≥3 cigarettes per day) and recorded continuous step counts with the Fitbit Charge HR. MVPA was defined as a cadence of greater than or equal to 100 steps per minute. Participants were prompted to report instantaneous smoking urges via text message 3 times a day on a Likert scale from 1 to 9. We used a mixed effects linear model for repeated measures, controlling for demographics and baseline activity level, to investigate the association between MVPA and urge.

Results

A total of 53 participants (mean age 40 [SD 12] years, 57% [30/53] women, 49% [26/53] nonwhite, and 38% [20/53] obese) recorded 6 to 12 weeks of data. Data from 3633 person-days were analyzed, with a mean of 69 days per participant. Among all participants, median daily MVPA was 6 min (IQR 2-13), which differed by sex (12 min [IQR 3-20] for men vs 3.5 min [IQR 1-9] for women; P=.004) and BMI (2.5 min [IQR 1-8.3] for obese vs 10 min [IQR 3-15] for nonobese; P=.04). The median total MVPA minutes per week was 80 (IQR 31-162). Only 10% (5/51; 95% CI 4% to 22%) of participants met national guidelines of 150 min per week of MVPA on at least 50% of weeks. Adjusted models showed no association between the number of MVPA minutes per day and mean daily smoking urge (P=.72).

Conclusions

The prevalence of MVPA was low in adult smokers who rarely met national guidelines for MVPA. Given the poor physical activity attainment in smokers, more work is required to enhance physical activity in this population.

Mobile Health Technologies in Cardiopulmonary Disease

Mobile health (mHealth) technologies are modernizing medicine by affording greater patient engagement, monitoring, outreach, and health-care delivery. The cardiopulmonary fields have led the integration of mHealth into clinical practice and research. mHealth technologies in these areas include smartphone applications, wearable devices, and handheld devices, among others, and provide real-time monitoring of numerous important physiological measurements and other key parameters. Use of mHealth-compatible devices has increased in recent years, and age and socioeconomic gaps of ownership are narrowing. These tools provide physicians and researchers with a better understanding of an individual's health and well-being. mHealth interventions have shown utility in the prevention, monitoring, and management of atrial fibrillation, heart failure, and myocardial infarction. With the growing prevalence of cardiopulmonary disease, mHealth technologies may become a more essential element of care within and outside of traditional health-care settings. mHealth is continuously developing as a result of technologic advancements and better understandings of mHealth utility. However, there is little regulation on the mHealth platforms available for commercial use and even fewer guidelines on implementing evidence-based practices into mHealth technologies. Online security is another challenge and necessitates development in data collection infrastructure to manage the extraordinary volume of patient data. Continued research on long-term implications of mHealth technology and the integration of effective interventions into clinical practice is required.