Dataset Information

Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling.

ABSTRACT: BACKGROUND:Smartphones and wearable activity trackers present opportunities for large-scale physical activity (PA) surveillance that overcome some limitations of questionnaires or researcher-administered devices. However, it remains unknown whether current users of such technologies are representative of the UK population. OBJECTIVE:The objective of this study was to investigate potential sociodemographic biases in individuals using, or with the potential to use, smartphone apps or wearable activity trackers for PA surveillance in the United Kingdom. METHODS:We used data of adults (aged ?16 years) from two nationally representative surveys. Using the UK-wide 2018 Ofcom Technology Tracker (unweighted N=3688), we derived mutually adjusted odds ratios (ORs; 95% CI) of personal use or household ownership of a smartwatch or fitness tracker and personal use of a smartphone by age, sex, social grade, activity- or work-limiting disability, urban or rural, and home nation. Using the 2016 Health Survey for England (unweighted N=4539), we derived mutually adjusted ORs of the use of wearable trackers or websites or smartphone apps for weight management. The explanatory variables were age, sex, PA, deprivation, and body mass index (BMI). Furthermore, we stratified these analyses by BMI, as these questions were asked in the context of weight management. RESULTS:Smartphone use was the most prevalent of all technology outcomes, with 79.01% (weighted 2085/2639) of the Technology Tracker sample responding affirmatively. All other outcomes were <30% prevalent. Age ?65 years was the strongest inverse correlate of all outcomes (eg, OR 0.03, 95% CI 0.02-0.05 for smartphone use compared with those aged 16-44 years). In addition, lower social grade and activity- or work-limiting disability were inversely associated with all Technology Tracker outcomes. Physical inactivity and male sex were inversely associated with both outcomes assessed in the Health Survey for England; higher levels of deprivation were only inversely associated with websites or phone apps used for weight management. The conclusions did not differ meaningfully in the BMI-stratified analyses, except for deprivation that showed stronger inverse associations with website or phone app use in the obese. CONCLUSIONS:The sole use of PA data from wearable trackers or smartphone apps for UK national surveillance is premature, as those using these technologies are more active, younger, and more affluent than those who do not.

SUBMITTER: Strain T

PROVIDER: S-EPMC6371078 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling.

Strain Tessa T Wijndaele Katrien K Brage Søren S

JMIR mHealth and uHealth 20190129 1

<h4>Background</h4>Smartphones and wearable activity trackers present opportunities for large-scale physical activity (PA) surveillance that overcome some limitations of questionnaires or researcher-administered devices. However, it remains unknown whether current users of such technologies are representative of the UK population.<h4>Objective</h4>The objective of this study was to investigate potential sociodemographic biases in individuals using, or with the potential to use, smartphone apps o ...[more]

PMID: 30694198

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Project description:BACKGROUND:Studies have reported on the proportion of the population looking for potential sexual partners using internet sites and smartphone apps, but few have investigated those who have sex with these partners, arguably a more important target group for health promotion. OBJECTIVE:This study aimed to determine the proportion of people who have had sex with someone they met on an internet site or a smartphone app in the previous year. METHODS:We analyzed data from the 2012-2013 Second Australian Study of Health and Relationships, a nationally representative telephone survey of Australian residents aged 16-69 years (N=20,091). The participation rate for the telephone survey was 66.22%. The prevalence of looking for a potential partner, physically meeting, and having sex with someone first met through an internet site or a smartphone app was estimated. Multivariate logistic regression was used for men and women separately to determine demographic and behavioral factors associated with having had sex with someone met on an internet site or a smartphone app in the last year. RESULTS:Overall, 12.09% of respondents had looked for potential partners using these technologies and 5.40% had done so in the last year. In the last year, 2.98% had met someone in person and 1.95% reported having had sex with someone first met on an internet site or a smartphone app. The prevalence of all behaviors was greater in men than in women and in younger respondents than in older respondents. Among sexually active men, factors associated with having had sex with someone met using internet sites or smartphone apps included identifying as gay or bisexual (adjusted odds ratio, AOR: 15.37, 95% CI 8.34-28.35), having either 2-3 or >3 sexual partners in the last year (AOR: 9.20, 95% CI 9.20-34.68 and AOR: 35.77, 95% CI 18.04-70.94, respectively), having had a sexually transmissible infection (STI) test in the past year (AOR: 2.02, 95% CI 1.21-3.38), or an STI in the last year (AOR: 3.15, 95% CI 1.25-7.97). Among sexually active women, factors associated with having had sex with someone met on an internet site or a smartphone app were as follows: having either 2-3 or >3 sexual partners in the last year (AOR: 32.01, 95% CI 13.17-77.78 and AOR: 71:03, 95 % CI 27.48-183.57, respectively), very low and low income (vs very high AOR: 3.40, 95% CI 1.12-10.35), and identifying as lesbian or bisexual (AOR: 2.27, 95% CI 1.04-4.49). CONCLUSIONS:More than a third of adults who had looked for potential partners using websites and apps each year had sex with such partners, and those who had done so were more sexually active, suggesting that dating and hookup websites and applications are suitable settings for targeted sexual health interventions.

Project description:BackgroundSocial class is frequently used as a means of ranking the population to expose inequalities in health, but less often as a means of understanding the social processes of causation. We explored how effectively different social class mechanisms could be measured by longitudinal cohort data and whether those measures were able to explain health outcomes.MethodsUsing a theoretically informed approach, we sought to map variables within the National Child Development Study (NCDS) to five different social class mechanisms: social background and early life circumstances; habitus and distinction; exploitation and domination; location within market relations; and power relations. Associations between the SF-36 physical, emotional and general health outcomes at age 50 years and the social class measures within NCDS were then assessed through separate multiple linear regression models. R2 values were used to quantify the proportion of variance in outcomes explained by the independent variables.ResultsWe were able to map the NCDS variables to the each of the social class mechanisms except 'Power relations'. However, the success of the mapping varied across mechanisms. Furthermore, although relevant associations between exposures and outcomes were observed, the mapped NCDS variables explained little of the variation in health outcomes: for example, for physical functioning, the R2 values ranged from 0.04 to 0.10 across the four mechanisms we could map.ConclusionsThis study has demonstrated both the potential and the limitations of available cohort studies in measuring aspects of social class theory. The relatively small amount of variation explained in the outcome variables in this study suggests that these are imperfect measures of the different social class mechanisms. However, the study lays an important foundation for further research to understand the complex interactions, at various life stages, between different aspects of social class and subsequent health outcomes.

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Project description:BackgroundDiabetes is one of the leading noncommunicable chronic diseases globally. In people with diabetes, blood glucose levels need to be monitored regularly and managed adequately through healthy lifestyles and medications. However, various factors contribute to poor medication adherence. Smartphone apps can improve medication adherence in people with diabetes, but it is not clear which app features are most beneficial.ObjectiveThis study aims to systematically review and evaluate high-quality apps for diabetes medication adherence, which are freely available to the public in Android and Apple app stores and present the technical features of the apps.MethodsWe systematically searched Apple App Store and Google Play for apps that assist in diabetes medication adherence, using predefined selection criteria. We assessed apps using the Mobile App Rating Scale (MARS) and calculated the mean app-specific score (MASS) by taking the average of app-specific scores on 6 dimensions, namely, awareness, knowledge, attitudes, intention to change, help-seeking, and behavior change rated on a 5-point scale (1=strongly disagree and 5=strongly agree). We used the mean of the app's performance on these 6 dimensions to calculate the MASS. Apps that achieved a total MASS mean quality score greater than 4 out of 5 were considered to be of high quality in our study. We formulated a task-technology fit matrix to evaluate the apps for diabetes medication adherence.ResultsWe identified 8 high-quality apps (MASS score≥4) and presented the findings under 3 main categories: characteristics of the included apps, app features, and diabetes medication adherence. Our framework to evaluate smartphone apps in promoting diabetes medication adherence considered physiological factors influencing diabetes and app features. On evaluation, we observed that 25% of the apps promoted high adherence and another 25% of the apps promoted moderate adherence. Finally, we found that 50% of the apps provided low adherence to diabetes medication.ConclusionsOur findings show that almost half of the high-quality apps publicly available for free did not achieve high to moderate medication adherence. Our framework could have positive implications for the future design and development of apps for patients with diabetes. Additionally, apps need to be evaluated using a standardized framework, and only those promoting higher medication adherence should be prescribed for better health outcomes.

Dataset Information

Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling.

Publications

Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling.

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