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dc.contributor.authorMurphy, J-
dc.contributor.authorUttamlal, T-
dc.contributor.authorSchmidtke, KA-
dc.contributor.authorVlaev, I-
dc.contributor.authorTaylor, D-
dc.contributor.authorAhmad, M-
dc.contributor.authorAlsters, S-
dc.contributor.authorPurkayastha, P-
dc.contributor.authorScholtz, S-
dc.contributor.authorRamezani, R-
dc.contributor.authorAhmed, AR-
dc.contributor.authorChahal, H-
dc.contributor.authorDarzi, A-
dc.contributor.authorBlakemore, AIF-
dc.identifier.citationBMC Medical Informatics and Decision Making, 2020, 20 (17), pp. 1 - 11 (11)en_US
dc.description.abstractBackground Within the United Kingdom’s National Health System (NHS), patients suffering from obesity may be provided with bariatric surgery. After receiving surgery many of these patients require further support to continue to lose more weight or to maintain a healthy weight. Remotely monitoring such patients’ physical activity and other health-related variables could provide healthworkers with a more ‘ecologically valid’ picture of these patients’ behaviours to then provide more personalised support. The current study assesses the feasibility of two smartphone apps to do so. In addition, the study looks at the barriers and facilitators patients experience to using these apps effectively. Methods Participants with a BMI > 35 kg/m2 being considered for and who had previously undergone bariatric surgery were recruited. Participants were asked to install two mobile phone apps. The ‘Moves’ app automatically tracked participants’ physical activity and the ‘WLCompanion’ app prompted participants to set goals and input other health-related information. Then, to learn about participants’ facilitators and barriers to using the apps, some participants were asked to complete a survey informed by the Theoretical Domains Framework. The data were analysed using regressions and descriptive statistics. Results Of the 494 participants originally enrolled, 274 participants data were included in the analyses about their activity pre- and/or post-bariatric surgery (ages 18–65, M = 44.02, SD ± 11.29). Further analyses were performed on those 36 participants whose activity was tracked both pre- and post-surgery. Participants’ activity levels pre- and post-surgery did not differ. In addition, 54 participants’ survey responses suggested that the main facilitator to their continued use of the Moves app was its automatic nature, and the main barrier was its battery drain. Conclusions The current study tracked physical activity in patients considered for and who had previously undergone bariatric surgery. The results should be interpreted with caution because of the small number of participants whose data meet the inclusion criteria and the barriers participants encountered to using the apps. Future studies should take note of the barriers to develop more user-friendly apps.en_US
dc.description.sponsorshipEngineering and Physical Sciences Research Council; National Institute for Health Research; Applied Research Centre West Midlandsen_US
dc.format.extent1 - 11 (11)-
dc.subjectPhysical activity monitoringen_US
dc.subjectSmartphone appen_US
dc.titleTracking physical activity using smart phone apps: assessing the ability of a current app and systematically collecting patient recommendations for future developmenten_US
dc.relation.isPartOfBMC Medical Informatics and Decision Making-
pubs.publication-statusPublished online-
Appears in Collections:Dept of Life Sciences Research Papers

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