Phone-based Physical Activity Research Articles

Effect of a smartphone-based physical intervention on depression, fitness factors and movement characteristics in adults

BackgroundPhysical activity has been shown to correlate with mental health and a reduction in symptoms of depression. However, the majority of research has focused only on the effects of either aerobic or nonaerobic exercise on depressive symptoms, while the use of novel technological innovations such as mobile phone-based activity programs and their effects on movement characteristics are underrepresented. This study had two objectives: (1) to investigate how effectively 4 weeks of mobile phone-based physical activity can affect depressive scores (CES-10-D and PHQ) and fitness levels and (2) to investigate the whether 4 weeks of mobile phone-based physical activity affected participants’ movement characteristics.MethodsA total of 31 participants were included and divided into an exercise group (n = 21) and a control group (n = 10). The exercise group was instructed to use a mobile phone-based exercise program 5 times per week for 4 weeks. Pre- and post-exercise, the participants’ depression score (CES-10-D, PHQ9), fitness level (YMCA, grip strength) and movement characteristics (postural sway, movement ROM, movement speeds, etc.) for three Azure Kinect physical activity games based on different fitness factors (balance game, cardiovascular game, reaction game) were measured.ResultsMixed model ANOVA revealed significant differences between pre- and post-intervention depression scores on the PHQ9 (P = .001) and CES-10-D (P < .001) in both the exercise group and the control group, but not between groups. In terms of movement characteristics, there was an increase in body sway (P = .045) and vertical head movement (P = .02) in the cardiovascular game jogging condition for the exercise group. In the reaction game, the exercise group showed a significant reduction in the number of mistakes (P = .03). There were no other significant differences for the other variables.ConclusionThe results revealed no differences in the reduction in depression scores between the exercise group and the control group. However, this study showed that a mobile phone-based physical activity intervention affects in-game movement characteristics such as body sway and vertical head movement and therefore may show the potential of using activity-promoting mobile games for improving movement.

Effect of Phone-based Counseling on Physical Activity and Fatigue in Postpartum Women

Objectives: Research shows that physical activity during postpartum affects maternal physical and mental health. In this study, we examined the associations of a phone-based physical activity intervention on objectively measured physical activity and self-reported fatigue. Methods: Participants (N=450) were randomly assigned to either a phone-based physical activity group (N=150), a wellness group (N=150), or a control group (N=150). Participants were on average 4.35 weeks postpartum at the time of the study. Physical activity was measured via accelerometer, and fatigue was measured via self-reported survey. We used a series of one-way analyses of variance (ANOVAs) to examine differences between study groups at the 6-month timepoint. Results: The physical activity group was significantly more active than the control group at 6 months, F(2, 243) = 4.27, p &lt; .05. The control group had significantly higher levels of reduced motivation at 6 months F(2,372) = 3.534, p &lt; .05. Other subscales of the fatigue measure were not significantly different by group. Conclusions: Phone-based counseling may be a useful tool to increase physical activity among postpartum women, but more research is needed to see if those benefits are sustained.

The Relationship Between Barriers to Physical Activity and Depressive Symptoms in Community-Dwelling Women.

Women are less physically active, report greater perceived barriers for exercise, and show higher levels of depressive symptoms. This contributes to high global disability. The relationship between perceived barriers for physical activity and depressive symptoms in women remains largely unexplored. The aims of this cross-sectional analysis were to examine the association between physical activity barriers and depressive symptoms, and identify types of barriers in physically inactive community-dwelling women. Three hundred eighteen physically inactive women aged 25-65 years completed the Barriers to Being Active Quiz (BBAQ) developed by the Centers for Disease Control and Prevention, and the Center for Epidemiological Studies Depression Scale at the baseline visit of the mobile phone-based physical activity education trial. The BBAQ consists of six subscales (lack of time, social influence, lack of energy, lack of willpower, fear of injury, lack of skill, and lack of resources). We used multivariate regression analyses, correcting for sociodemographics. Higher physical activity barriers were associated with greater depressive symptoms scores (linear effect, estimate = 0.75, 95% confidence interval [CI]: 0.39-1.12, p < 0.001). This effect appeared to taper off for the higher barrier scores (quadratic effect, estimate: -0.02, 95% CI: -0.03 to -0.01, p = 0.002). Exploratory analyses indicated that these associations were most driven by the social influence (p = 0.027) and lack of energy subscales (p = 0.017). Higher depression scores were associated with higher physical activity barriers. Social influence and lack of energy were particularly important barriers. Addressing these barriers may improve the efficacy of physical activity interventions in women with higher depressive symptoms. Future research should assess this in a randomized controlled trial. NCTO1280812 registered January 21, 2011.

Applying machine learning to predict future adherence to physical activity programs

BackgroundIdentifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction models using objectively measured physical activity data in the Mobile Phone-Based Physical Activity Education program (mPED) trial. To the best of our knowledge, this is the first to apply Machine Learning methods to predict exercise relapse using accelerometer-recorded physical activity data.MethodsWe use logistic regression and support vector machine methods to design two versions of a Discontinuation Prediction Score (DiPS), which uses objectively measured past data (e.g., steps and goal achievement) to provide a numerical quantity indicating the likelihood of exercise relapse in the upcoming week. The respective prediction accuracy of these two versions of DiPS are compared, and then numerical simulation is performed to explore the potential of using DiPS to selectively allocate financial incentives to participants to encourage them to increase physical activity.Resultswe had access to a physical activity trial data that were continuously collected every 60 sec every day for 9 months in 210 participants. By using the first 15 weeks of data as training and test on weeks 16–30, we show that both versions of DiPS have a test AUC of 0.9 with high sensitivity and specificity in predicting the probability of exercise adherence. Simulation results assuming different intervention regimes suggest the potential benefit of using DiPS as a score to allocate resources in physical activity intervention programs in reducing costs over other allocation schemes.ConclusionsDiPS is capable of making accurate and robust predictions for future weeks. The most predictive features are steps and physical activity intensity. Furthermore, the use of DiPS scores can be a promising approach to determine when or if to provide just-in-time messages and step goal adjustments to improve compliance. Further studies on the use of DiPS in the design of physical activity promotion programs are warranted.Trial registrationClinicalTrials.gov NCT01280812 Registered on January 21, 2011.

Short- and Long-term Effects of a Mobile Phone App in Conjunction With Brief In-Person Counseling on Physical Activity Among Physically Inactive Women

Mobile phone applications (apps) and activity trackers allow researchers to remotely deliver an intervention and monitor physical activity but have not been rigorously evaluated for longer periods. To determine whether a mobile phone-based physical activity education app, in conjunction with brief in-person counseling, increases and then maintains levels of physical activity. In this parallel randomized clinical trial, community-dwelling physically inactive women recruited between May 2011 and April 2014 were randomized in equal proportions into the control (n = 69), regular (n = 71), and plus (n = 70) groups. Data were analyzed using intention to treat from September 16, 2016, through June 30, 2018. The regular and plus groups were instructed to use the app on their mobile phone and an accelerometer every day for 3 months and attend brief in-person counseling. During the 6-month maintenance period, the plus group continued to use the app and accelerometer, while the regular group stopped using the app but continued using the accelerometer. The control group used the accelerometer throughout. The primary and secondary outcomes were daily accelerometer-measured total steps and time spent in moderate to vigorous physical activity (MVPA). The 210 participants had a mean (SD) age of 52.4 (11.0) years. At baseline, the mean (SD) daily total steps by accelerometer in the control, regular, and plus groups were 5384 (2920), 5063 (2526), and 5837 (3235), respectively. During the 3-month intervention period, daily steps and MVPA increased in the combined regular and plus groups compared with the control group (between-group differences, 2060 steps per day; 95% CI, 1296-2825 steps per day; P < .001 and 18.2 min/d MVPA; 95% CI, 10.9-25.4 min/d MVPA; P < .001). During the subsequent 6-month maintenance period, mean activity level remained higher in the combined plus and regular groups than among controls (between-group difference, 1360 steps per day; 95% CI, 694-2026 steps per day; P <. 001), but trends in total daily steps and MVPA were similar in the plus and regular groups. In this trial, the intervention groups substantially increased their physical activity. However, use of both the app and accelerometer for an additional 6 months after the initial 3-month intervention did not help to maintain increases in physical activity compared with continued use of the accelerometer alone. ClinicalTrials.gov identifier: NCT01280812.

A text messaging-based intervention to increase physical activity among persons living in permanent supportive housing: Feasibility and acceptability findings from a pilot study.

ObjectivePersons who have experienced homelessness and are living in permanent supportive housing experience high rates of health and mental health problems. Given that physical activity is associated with improved health outcomes and persons with homelessness histories report high rates of cell phone use, phone-based interventions to increase physical activity may be effective for improving health and wellbeing among persons in permanent supportive housing.MethodsTo understand the acceptability and feasibility of a cell phone-based physical activity intervention in this population, this 6-week pilot study enrolled 13 persons living in permanent supportive housing. Participants were eligible if they had completed their final, 12-month follow-up interview in a larger, longitudinal study of persons moving into permanent supportive housing in the Los Angeles area, spoke English, and reported comorbid chronic physical and mental health conditions. For the study duration, participants wore a pedometer, received multiple weekly motivational text messages on set days (at times selected by the participant), and responded via text to weekly depression screeners and requests to report their weekly step totals, as recorded by their pedometers. Follow-up interviews asked open-ended questions about study participation and satisfaction.ResultsParticipants were 53 years old on average, most were female (54%), and most were African-American (62%). Changes to people’s physical activity levels were limited, but participants reported increased quality of life during the intervention period. Interviews revealed that the intervention was well received and enjoyable for participants.ConclusionsThe efficacy of utilizing cell phones to improve health and wellbeing among adults living in permanent supportive housing requires further research, but these pilot findings suggest that such interventions are feasible and acceptable.

Applying Natural Language Processing to Understand Motivational Profiles for Maintaining Physical Activity After a Mobile App and Accelerometer-Based Intervention: The mPED Randomized Controlled Trial.

BackgroundRegular physical activity is associated with reduced risk of chronic illnesses. Despite various types of successful physical activity interventions, maintenance of activity over the long term is extremely challenging.ObjectiveThe aims of this original paper are to 1) describe physical activity engagement post intervention, 2) identify motivational profiles using natural language processing (NLP) and clustering techniques in a sample of women who completed the physical activity intervention, and 3) compare sociodemographic and clinical data among these identified cluster groups.MethodsIn this cross-sectional analysis of 203 women completing a 12-month study exit (telephone) interview in the mobile phone-based physical activity education study were examined. The mobile phone-based physical activity education study was a randomized, controlled trial to test the efficacy of the app and accelerometer intervention and its sustainability over a 9-month period. All subjects returned the accelerometer and stopped accessing the app at the last 9-month research office visit. Physical engagement and motivational profiles were assessed by both closed and open-ended questions, such as “Since your 9-month study visit, has your physical activity been more, less, or about the same (compared to the first 9 months of the study)?” and, “What motivates you the most to be physically active?” NLP and cluster analysis were used to classify motivational profiles. Descriptive statistics were used to compare participants’ baseline characteristics among identified groups.ResultsApproximately half of the 2 intervention groups (Regular and Plus) reported that they were still wearing an accelerometer and engaging in brisk walking as they were directed during the intervention phases. These numbers in the 2 intervention groups were much higher than the control group (overall P=.01 and P=.003, respectively). Three clusters were identified through NLP and named as the Weight Loss group (n=19), the Illness Prevention group (n=138), and the Health Promotion group (n=46). The Weight Loss group was significantly younger than the Illness Prevention and Health Promotion groups (overall P<.001). The Illness Prevention group had a larger number of Caucasians as compared to the Weight Loss group (P=.001), which was composed mostly of those who identified as African American, Hispanic, or mixed race. Additionally, the Health Promotion group tended to have lower BMI scores compared to the Illness Prevention group (overall P=.02). However, no difference was noted in the baseline moderate-to-vigorous intensity activity level among the 3 groups (overall P>.05).ConclusionsThe findings could be relevant to tailoring a physical activity maintenance intervention. Furthermore, the findings from NLP and cluster analysis are useful methods to analyze short free text to differentiate motivational profiles. As more sophisticated NL tools are developed in the future, the potential of NLP application in behavioral research will broaden.Trial RegistrationClinicalTrials.gov NCT01280812; https://clinicaltrials.gov/ct2/show/NCT01280812 (Archived by WebCite at http://www.webcitation.org/70IkGagAJ)

Comparing Asian American Women's Knowledge, Self-Efficacy, and Perceived Risk of Heart Attack to Other Racial and Ethnic Groups: The mPED Trial.

The aim of the study was to compare knowledge and awareness of heart attacks/heart disease and perceived risk for future heart attack in Asian/Pacific Islander women, compared to other racial and ethnic groups. In this cross-sectional study, 318 women enrolled in a mobile phone-based physical activity education trial were analyzed. Heart attack knowledge, self-efficacy for recognizing and responding to heart attack symptoms, and perceived risk for a future heart attack were measured. Analyses were conducted using logistic, proportional odds, and linear regression models, depending on the outcome and adjusting for age. Pairwise differences between Asian/Pacific Islanders and the other four groups were assessed using a Bonferroni correction (p < 0.0125). Asian/Pacific Islander women had significantly lower total scores for knowledge of heart attack and self-efficacy for heart attack recognition and care seeking behavior compared to the Caucasian women (p = 0.001 and p = 0.002, respectively). However, perceived risk did not differ among the groups. Forty-six percent of the Asian American women, compared to 25% of Caucasian women, falsely believed "breast cancer is the number one cause of death for women (p = 0.002)." In addition, Asian/Pacific Islander women were less likely to report "arm pain, numbness, tingling, or radiating" as one of the heart attack symptoms compared to the Caucasian and the multiracial group (34%, 63% [p < 0.001], and 66% [p = 0.004], respectively). These findings highlight the urgent need to develop effective, tailored campaigns to close the knowledge gap between Asian/Pacific Islander women and Caucasian women.

Identifying Factors Associated With Dropout During Prerandomization Run-in Period From an mHealth Physical Activity Education Study: The mPED Trial.

BackgroundThe mobile phone-based physical activity education (mPED) trial is a randomized controlled trial (RCT) evaluating a mobile phone-delivered physical activity intervention for women. The study includes a run-in period to maximize the internal validity of the intervention trial, but little is known about factors related to successful run-in completion, and thus about potential threats to external validity.ObjectiveObjectives of this study are (1) to determine the timing of dropout during the run-in period, reasons for dropout, optimum run-in duration, and relevant run-in components, and (2) to identify predictors of failure to complete the run-in period.MethodsA total of 318 physically inactive women met preliminary eligibility criteria and were enrolled in the study between May 2011 and April 2014. A 3-week run-in period was required prior to randomization and included using a mobile phone app and wearing a pedometer. Cross-sectional analysis identified predictors of dropout.ResultsOut of 318 participants, 108 (34.0%) dropped out prior to randomization, with poor adherence using the study equipment being the most common reason. Median failure time was 17 days into the run-in period. In univariate analyses, nonrandomized participants were younger, had lower income, were less likely to drive regularly, were less likely to have used a pedometer prior to the study, were generally less healthy, had less self-efficacy for physical activity, and reported more depressive symptoms than randomized participants. In multivariate competing risks models, not driving regularly in the past month and not having used a pedometer prior to the study were significantly associated with failure to be randomized (P=.04 and .006, respectively), controlling for age, race/ethnicity, education, shift work, and use of a study-provided mobile phone.ConclusionsRegular driving and past pedometer use were associated with reduced dropout during the prerandomization run-in period. Understanding these characteristics is important for identifying higher-risk participants, and implementing additional help strategies may be useful for reducing dropout.Trial RegistrationClinicalTrials.gov NCT01280812; https://clinicaltrials.gov/ct2/show/NCT01280812 (Archived by WebCite at http://www.webcitation.org/6XFC5wvrP).

A mobile phone‐based physical activity recall using daily activity pictures: helping to recall intensity and duration of physical activity (1021.7)

The goals of this study were to develop a mobile phone‐based physical activity (PA) recall using periodic photographs and to compare reported minutes of moderate‐intensity PA (MPA) per day using the International Physical Activity Questionnaire (IPAQ). Participants used their cell phone to take 3 pictures (in the morning, afternoon, and evening) per day of their daily activities for 3 days per week. Participants were given the IPAQ within a week, and a PA recall (their minutes and intensity level of PA) was then conducted by researcher using their 9 pictures saved in their cell phone. The difference between the IPAQ reported minutes and the MPA by PA recall at each of four time intervals: baseline, 8‐week, 3‐months and 6‐months were obtained. To determine whether the difference in reported minutes between IPAQ and PA recall varied over time or with BMI, generalized estimating equations were used to account for the repeated measurements. Forty‐four females and 13 males, age 23.1 ± 5.74(SD) years, baseline BMI 26.2 ± 6.36(SD) participated in the study. The mean differences in the minutes at each of the time points were 16.3, 14.4, 3.4, and 10.7 minutes, respectively. Neither BMI nor time was significantly associated with the difference between minutes reported in PA recall and the minutes reported in the IPAQ. The first generation of cell phone‐based PA recall using activity pictures is well accepted and may help to predict better estimates of PA.

Validity and reliability of a smart phone-based physical activity monitoring application

Background: Accelerometers are accurate and useful for monitoring Physical Activity in healthy people as well as chronic disease patients (e.g. Diabetics, Coronary Heart Disease and Chronic Obstructive Pulmonary Disease patients) and may help motivate patients to comply with rehabilitation. However, they are expensive and not always user-friendly. Similar motion sensors are embedded within the majority of newer mobile phones, which are widely accessible.

New Insights Into Compliance With a Mobile Phone Diary and Pedometer Use in Sedentary Women

The purposes of this study were 1) to determine compliance with a pedometer and mobile phone- based physical activity diary, and 2) to assess concordance between self-reported daily steps recorded and transmitted by a mobile phone and pedometer-measured daily steps in sedentary women. In this 3-week pilot clinical study, 41 sedentary women who met all inclusion criteria were recruited from local communities. We asked the participants to wear a pedometer every day and to report their daily steps using a mobile phone diary each night before retiring. In the first week, women were asked to monitor their daily steps (baseline steps). In the second and third weeks, they were asked to increase their steps by 20% from the previous week. Although the pedometer can automatically store the most recent 41 days' performance, the participants were not informed of this function of the pedometer. Overall compliance was 93.8% with pedometer use and 88.3% with the mobile phone physical activity diary. Bland Altman plots showed that the agreement between self-reported daily steps by mobile phone diary and pedometer-recorded daily steps from week 1 to week 3 was high. The combination of a pedometer and a mobile phone diary may enhance the quality of self-reported data in clinical studies.

Comparison of Paper-Based and Cell Phone-Based Physical Activity Records

Comparison of Paper-Based and Cell Phone-Based Physical Activity Records

Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial.

Background The Internet has potential as a medium for health behavior change programs, but no controlled studies have yet evaluated the impact of a fully automated physical activity intervention over several months with real-time objective feedback from a monitor.Objective The aim was to evaluate the impact of a physical activity program based on the Internet and mobile phone technology provided to individuals for 9 weeks.Methods A single-center, randomized, stratified controlled trial was conducted from September to December 2005 in Bedfordshire, United Kingdom, with 77 healthy adults whose mean age was 40.4 years (SD = 7.6) and mean body mass index was 26.3 (SD = 3.4). Participants were randomized to a test group that had access to an Internet and mobile phone–based physical activity program (n = 47) or to a control group (n = 30) that received no support. The test group received tailored solutions for perceived barriers, a schedule to plan weekly exercise sessions with mobile phone and email reminders, a message board to share their experiences with others, and feedback on their level of physical activity. Both groups were issued a wrist-worn accelerometer to monitor their level of physical activity; only the test group received real-time feedback via the Internet. The main outcome measures were accelerometer data and self-report of physical activity.Results At the end of the study period, the test group reported a significantly greater increase over baseline than did the control group for perceived control (P < .001) and intention/expectation to exercise (P < .001). Intent-to-treat analyses of both the accelerometer data (P = .02) and leisure time self-report data (P = .03) found a higher level of moderate physical activity in the test group. The average increase (over the control group) in accelerometer-measured moderate physical activity was 2 h 18 min per week. The test group also lost more percent body fat than the control group (test group: −2.18, SD = 0.59; control group: −0.17, SD = 0.81; P = .04).Conclusions A fully automated Internet and mobile phone–based motivation and action support system can significantly increase and maintain the level of physical activity in healthy adults.