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  • Perceptions and Experiences of Women Participating in a Digital Technology-Based Physical Activity Intervention (the mPED Trial): Qualitative Study JMIR PUBLIC HEALTH AND SURVEILLANCE Lindgren, T., Hooper, J., Fukuoka, Y. 2019; 5 (4): 73?86

    Abstract

    Despite the benefits of regular physical activity, women in every age group have lower activity levels than men, and few women meet the recommended levels of physical activity. Digital technologies have been useful in increasing physical activity during the course of an interventional study. However, sustaining that activity once the clinical trial was complete was a major challenge.This study aimed to describe the experiences and perspectives of physically inactive women who completed the mobile phone-based physical activity education (mPED), a randomized controlled trial, at 12 months.Of 210 women who were enrolled in the mPED trial, 203 completed a 12-month open-ended exit interview and survey through phone. The participants were asked about their physical activity levels; their digital technology use; what they learned from, liked, and would change about the trial; their motivations to keep active post-trial; and their advice for other women. Interviews were transcribed verbatim and thematically analyzed using the brief survey qualitative description. Descriptive statistics were used to describe the survey data with the significance level set at P<.05.In the 12-month survey, a greater proportion of the participants in the intervention group, compared with the control group, reported that they regularly wore a pedometer or physical activity tracker (49.3%, 66/143 vs 26.1%, 18/69; P=.002) and engaged in brisk walking (54.5%, 73/134 vs 30.4%, 21/69; P=.001). The experiences and perceptions of physical activity of physically inactive women over time were embedded in a complex interplay of internal and external factors. A total of 6 interactive themes emerged as critical in supporting continued engagement in physical activity postintervention: tracking, technology versus personal touch, accountability, resources and environment, motivation, and habit formation. Technology allowed for self-tracking, which supported internal accountability. However, tracking by another person (personal touch) was needed for external accountability. Resources and environment underpinned the relationship among the themes of tracking, technology versus personal touch, accountability, motivation, and habit formation.Future research is needed to identify the best ways to harness this dynamic process in promoting and sustaining physical activity among inactive women. Digital technology is evolving at an exponential rate and provides new opportunities to transform research into new approaches to promote physical activity.ClinicalTrials.gov NCT01280812; https://clinicaltrials.gov/ct2/show/NCT01280812.RR2-10.1186/1471-2485-11-933.

    View details for DOI 10.2196/13570

    View details for Web of Science ID 000526816800006

    View details for PubMedID 31859677

    View details for PubMedCentralID PMC6942195

  • A weight loss intervention using a commercial mobile application in Latino Americans-Adelgaza Trial. Translational behavioral medicine Fukuoka, Y. n., Vittinghoff, E. n., Hooper, J. n. 2018; 8 (5): 714?23

    Abstract

    More than half of Latino adults living in the USA are expected to develop type 2 diabetes in their lifetime. Despite the growing interest in smartphone use for weight loss and diabetes prevention, relatively few clinical trials have evaluated the efficacy of mobile app-based interventions in Latino populations. The aim of this study was to evaluate the potential efficacy of an in-person weight loss intervention in conjunction with a commercially available Fitbit app in a Latino sample at risk for type 2 diabetes and explore significant predictors associated with weight loss. After the run-in period, 54 self-identified Latinos with body mass index (BMI) > 24.9 kg/m2 were enrolled in an 8-week uncontrolled pilot study, and received a Fitbit Zip, its app, and two in-person weight loss sessions adapted from the Diabetes Prevention Program. Mean age was 45.3 (SD ± 10.8) years, 61.1% were born in the USA, and mean BMI was 31.4 (SD ± 4.1) kg/m2. Participants lost an average of 3.3 (SD ± 3.4) % of their body weight (p < .0005). We also observed statistically significant reductions in hip and waist circumferences, and systolic and diastolic blood pressure (p < .001). After controlling for demographic factors, use of the mobile app weight diary at least twice a week (p = .01) and change in the International Physical Activity Questionnaire score (p = .03) were associated with change in percent body weight. The intervention showed the potential efficacy of this intervention, which should be formally evaluated in a randomized controlled trial.

    View details for DOI 10.1093/tbm/ibx039

    View details for PubMedID 29474702

    View details for PubMedCentralID PMC6128967

  • 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. JMIR mHealth and uHealth Fukuoka, Y. n., Lindgren, T. G., Mintz, Y. D., Hooper, J. n., Aswani, A. n. 2018; 6 (6): e10042

    Abstract

    Regular 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.The 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.In 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.Approximately 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).The 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.ClinicalTrials.gov NCT01280812; https://clinicaltrials.gov/ct2/show/NCT01280812 (Archived by WebCite at http://www.webcitation.org/70IkGagAJ).

    View details for DOI 10.2196/10042

    View details for PubMedID 29925491

    View details for PubMedCentralID PMC6031900

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