Profile of adults users of smartphone applications for monitoring the level of physical activity and associated factors: A cross-sectional study.

Background: There are currently more than 200 million smartphones in Brazil. The potential of mobile technologies for favorable changes in health behavior such as physical activity has been previously described in the literature. Results of surveys in developed countries indicate that applications (APPs) are developed for people who are better educated, younger, and with higher incomes compared to non-users. However, the profile of users in developing countries like Brazil is not well-known. Understanding the profile of APP users might ease the development turned to physically inactive people and those at higher cardiovascular risk. Furthermore, the physiological and functional factors associated with the use of such APP are unknown. Objectives: To characterize the profile of APP users to monitor the physical activity level (PAL) and assess the demographic, socioeconomic, clinical, physiological, and functional characteristics associated with the use of smartphone APPs to monitor physical activity in Brazilian adults. Methods: We assessed 176 asymptomatic men and 178 women (43 ± 12 years; 27 ± 5 kg/m2). We initially asked participants about their current use of a smartphone APP containing PAL monitoring functionality, such as exercise session logs and/or step counts. In a cross-sectional design, we investigated schooling, socioeconomic status (Critério Brasil), and classic self-reported cardiovascular risk factors. We evaluated several physiological and functional variables such as maximum O2 consumption on a treadmill (VO2 max), blood pressure, body composition (bioelectrical impedance), handgrip strength, and isokinetic muscle strength of the dominant lower limb. Participants used a triaxial accelerometer for 7 days to quantify daily physical activity. We also assessed health-related quality of life (WHOQOL BREF), perceived stress (PSS14 Scale), and the built environment (NEWS Scale). We compared continuous variables using the Student's t-test and categorical variables using the χ2 test, between APP users and non-users. After univariate analysis, we included the main variables associated with the use of APP in a multiple logistic regression model. Results: One hundred and two participants (28.3%), unrelated to gender, reported using a smartphone APP for physical activity at the time of assessment. Except for perceived stress and the built environment that were not associated with the use of APP, users of APP were younger and had higher education, lower cardiovascular risk, better socioeconomic status, a better quality of life, better cardiorespiratory function, better body composition, greater physical fitness and more moderate to vigorous physical activity in daily life. The results of the multiple logistic regression showed that age, hypertension, VO2 max, socioeconomic status (Critério Brasil), and quality of life (WHOQOL BREF total score) were the variables most significantly associated with the use of the APP. Conclusions: Our results indicate that smartphone APPs to monitor physical activity are developed for younger adults with better socioeconomic status, lower cardiovascular risk, higher quality of life, and greater cardiorespiratory fitness. Greater efforts are needed to develop a science-based APP for people who most need this technology, enabling greater potential to prevent undesirable health outcomes in asymptomatic adults.

Self-Administered Six-Minute Walk Test Using a Free Smartphone App in Asymptomatic Adults: Reliability and Reproducibility.

BACKGROUND: The 6-min walk test (6MWT) is a simple, inexpensive, reliable, and reproducible test that provides a reasonable estimate of the cardiorespiratory fitness (CRF). We aimed to assess the reliability and reproducibility of a self-administered 6MWT in asymptomatic adults using a free smartphone app. METHODS: In the 1st phase, 93 participants underwent a supervised 6MWT (6MWTsup) in a 30 m indoor corridor, using a triaxial accelerometer and their smartphones to compare the total step counts and to develop a 6-min walk distance (6MWD) prediction equation. In the 2nd phase, 25 participants performed the 6MWTsup and two self-administered 6MWTs outdoors (6MWTsa1 and 6MWTsa2, at least 48 h apart) using a free smartphone app. RESULTS: The agreement between accelerometer- and app-based total step counts was limited (mean difference, -58.7 steps (-8.7%): 95% confidence interval, -326.5 (-46.8%) to 209.1 (29.3%)). The best algorithm for predicting the 6MWTsupm included: 795.456 + (0.815 heightm app-steps) - (1.620 ageyears) - (3.005 weightkg) - (1.155 app-steps), R2 = 0.609). The intraclass correlation coefficient between 6MWTsa2 and 6MWTsa1 was excellent (0.91: 0.81-0.96). The coefficient of variation was 6.4%. The agreement between the two self-administered tests was narrow (-1.9 (0.2%) meters: -57.4 (-9.5%) to 61.3 (9.9%)). CONCLUSIONS: The self-administered 6MWT has excellent reliability and reproducibility in asymptomatic adults, being a valuable tool for assessing CRF in community-based interventions.

Use of a Smartphone App to Increase Physical Activity Levels in Insufficiently Active Adults: Feasibility Sequential Multiple Assignment Randomized Trial (SMART).

BACKGROUND: The sequential multiple assignment randomized trial (SMART) design allows for changes in the intervention during the trial period. Despite its potential and feasibility for defining the best sequence of interventions, so far, it has not been utilized in a smartphone/gamified intervention for physical activity. OBJECTIVE: We aimed to investigate the feasibility of the SMART design for assessing the effects of a smartphone app intervention to improve physical activity in adults. We also aimed to describe the participants' perception regarding the protocol and the use of the app for physical activity qualitatively. METHODS: We conducted a feasibility 24-week/two-stage SMART in which 18 insufficiently active participants (<10,000 steps/day) were first randomized to group 1 (smartphone app only), group 2 (smartphone app + tailored messages), and a control group (usual routine during the protocol). Participants were motivated to increase their step count by at least 2000 steps/day each week. Based on the 12-week intermediate outcome, responders continued the intervention and nonresponders were rerandomized to subsequent treatment, including a new group 3 (smartphone app + tailored messages + gamification) in which they were instructed to form groups to use several game elements available in the chosen app (Pacer). We considered responders as those with any positive slope in the linear relationship between weeks and steps per day at the end of the first stage of the intervention. We compared the accelerometer-based steps per day before and after the intervention, as well as the slopes of the app-based steps per day between the first and second stages of the intervention. RESULTS: Twelve participants, including five controls, finished the intervention. We identified two responders in group 1. We did not observe relevant changes in the steps per day either throughout the intervention or compared with the control group. However, the rerandomization of five nonresponders led to a change in the slope of the steps per day (median -198 steps/day [IQR -279 to -103] to 20 steps/day [IQR -204 to 145]; P=.08). Finally, in three participants from group 2, we observed an increase in the number of steps per day up to the sixth week, followed by an inflection to baseline values or even lower (ie, a quadratic relationship). The qualitative analysis showed that participants' reports could be classified into the following: (1) difficulty in managing the app and technology or problems with the device, (2) suitable response to the app, and (3) difficulties to achieve the goals. CONCLUSIONS: The SMART design was feasible and changed the behavior of steps per day after rerandomization. Rerandomization should be implemented earlier to take advantage of tailored messages. Additionally, difficulties with technology and realistic and individualized goals should be considered in interventions for physical activity using smartphones. TRIAL REGISTRATION: Brazilian Registry of Clinical Trials RBR-8xtc9c; http://www.ensaiosclinicos.gov.br/rg/RBR-8xtc9c/.