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      Comparing usage of a web and app stress management intervention: An observational study

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          Abstract

          Choices in the design and delivery of digital health behaviour interventions may have a direct influence on subsequent usage and engagement. Few studies have been able to make direct, detailed comparisons of differences in usage between interventions that are delivered via web or app. This study compared the usage of two versions of a digital stress management intervention, one delivered via a website (Healthy Paths) and the other delivered via an app (Healthy Mind). Design modifications were introduced within Healthy Mind to take account of reported differences in how individuals engage with websites compared to apps and mobile phones. Data were collected as part of an observational study nested within a broader exploratory trial of Healthy Mind. Objective usage of Healthy Paths and Healthy Mind were automatically recorded, including frequency and duration of logins, access to specific components within the intervention and order of page/screen visits. Usage was compared for a two week period following initial registration. In total, 381 participants completed the registration process for Healthy Paths (web) and 162 participants completed the registration process for Healthy Mind (app). App users logged in twice as often ( Mdn = 2.00) as web users ( Mdn = 1.00), U = 13,059.50, p ≤ 0.001, but spent half as much time ( Mdn = 5.23 min) on the intervention compared to web users ( Mdn = 10.52 min), U = 19,740.00, p ≤ 0.001. Visual exploration of usage patterns over time revealed that a significantly higher proportion of app users ( n = 126, 82.35%) accessed both types of support available within the intervention (i.e. awareness and change-focused tools) compared to web users ( n = 92, 40.17%), χ 2(1, n = 382) = 66.60, p < 0.001. This study suggests that the digital platform used to deliver an intervention (i.e. web versus app) and specific design choices (e.g. navigation, length and volume of content) may be associated with differences in how the intervention content is used. Broad summative usage data (e.g. total time spent on the intervention) may mask important differences in how an intervention is used by different user groups if it is not complemented by more fine-grained analyses of usage patterns over time. Trial registration number: ISRCTN67177737.

          Highlights

          • Modifying the design and delivery of theoretical intervention content may alter how that content is used and received.

          • App users logged in twice as often but spent half as much time on the intervention compared to web users.

          • App users accessed more of the available intervention tools compared to web users.

          • Fine-grained individual-level data can enable comparison of how an intervention is used over time by different user groups.

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          Engagement in a Diabetes Self-management Website: Usage Patterns and Generalizability of Program Use

          Background Increased access to the Internet and the availability of efficacious eHealth interventions offer great promise for assisting adults with diabetes to change and maintain health behaviors. A key concern is whether levels of engagement in Internet programs are sufficient to promote and sustain behavior change. Objective This paper used automated data from an ongoing Internet-based diabetes self-management intervention study to calculate various indices of website engagement. The multimedia website involved goal setting, action planning, and self-monitoring as well as offering features such as “Ask an Expert” to enhance healthy eating, physical activity, and medication adherence. We also investigated participant characteristics associated with website engagement and the relationship between website use and 4-month behavioral and health outcomes. Methods We report on participants in a randomized controlled trial (RCT) who were randomized to receive (1) the website alone (n = 137) or (2) the website plus human support (n = 133) that included additional phone calls and group meetings. The website was available in English and Spanish and included features to enhance engagement and user experience. A number of engagement variables were calculated for each participant including number of log-ins, number of website components visited at least twice, number of days entering self-monitoring data, number of visits to the “Action Plan” section, and time on the website. Key outcomes included exercise, healthy eating, and medication adherence as well as body mass index (BMI) and biological variables related to cardiovascular disease risk. Results Of the 270 intervention participants, the average age was 60, the average BMI was 34.9 kg/m2, 130 (48%) were female, and 62 (23%) self-reported Latino ethnicity. The number of participant visits to the website over 4 months ranged from 1 to 119 (mean 28 visits, median 18). Usage decreased from 70% of participants visiting at least weekly during the first 6 weeks to 47% during weeks 7 to 16. There were no significant differences between website only and website plus support conditions on most of the engagement variables. In total, 75% of participants entered self-monitoring data at least once per week. Exercise action plan pages were visited more often than medication taking and healthy eating pages (mean of 4.3 visits vs 2.8 and 2.0 respectively, P < .001). Spearman nonparametric correlations indicated few significant associations between patient characteristics and summary website engagement variables, and key factors such as ethnicity, baseline computer use, age, health literacy, and education were not related to use. Partial correlations indicated that engagement, especially in self-monitoring, was most consistently related to improvement in healthy eating (r = .20, P = .04) and reduction of dietary fat (r = -.31, P = .001). There was also a significant correlation between self-monitoring and improvement in exercise (r = .20, P = .033) but not with medication taking. Conclusions Participants visited the website fairly often and used all of the theoretically important sections, but engagement decreased over 4 months. Usage rates and patterns were similar for a wide range of participants, which has encouraging implications for the potential reach of online interventions. Trial Registration NCT00987285; http://clinicaltrials.gov/show/NCT00987285 (Archived by WebCite at http://www.webcitation.org/5vpe4RHTV)
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            Characteristics of visitors and revisitors to an Internet-delivered computer-tailored lifestyle intervention implemented for use by the general public.

            The Internet has become important for the delivery of behavior change interventions. This observational study examines how many people visited, registered and revisited a web-based computer-tailored intervention promoting heart-healthy behaviors when it is implemented for use by the general public. Among registered visitors, the association between visitors' characteristics and initiating, completing and revisiting the website and/or its behavior-specific modules was analyzed. Server statistics showed that 285 146 visitors from unique IP addresses landed on the home page in a 36-month period; of these, >50% left the intervention website within 30 s. In total, 81 574 (28.6%) visitors completed the registration procedure and gained access to the intervention; 99% of registered visitors initiated one module, 91% completed at least one module and 6% revisited the intervention. The majority of the registered visitors were women, medium to highly educated, with a body mass index (BMI) <25. Women, visitors aged 40-50 years, visitors with a medium educational level and visitors with a BMI <25 were more likely to initiate and finish the modules. It is concluded that a heart-healthy computer-tailored Internet program can reach substantial numbers of people, but additional research is needed to develop promotional strategies that reach the high-risk population, i.e. men, older and lower educated persons.
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              Investigating Predictors of Visiting, Using, and Revisiting an Online Health-Communication Program: A Longitudinal Study

              Background Online health communication has the potential to reach large audiences, with the additional advantages that it can be operational at all times and that the costs per visitor are low. Furthermore, research shows that Internet-delivered interventions can be effective in changing health behaviors. However, exposure to Internet-delivered health-communication programs is generally low. Research investigating predictors of exposure is needed to be able to effectively disseminate online interventions. Objective In the present study, the authors used a longitudinal design with the aim of identifying demographic, psychological, and behavioral predictors of visiting, using, and revisiting an online program promoting physical activity in the general population. Methods A webpage was created providing the public with information about health and healthy behavior. The website included a “physical activity check,” which consisted of a physical activity computer-tailoring expert system where visitors could check whether their physical activity levels were in line with recommendations. Visitors who consented to participate in the present study (n = 489) filled in a questionnaire that assessed demographics, mode of recruitment, current physical activity levels, and health motivation. Immediately after, participants received tailored feedback concerning their current physical activity levels and completed a questionnaire assessing affective and cognitive user experience, attitude toward being sufficiently physically active, and intention to be sufficiently physically active. Three months later, participants received an email inviting them once more to check whether their physical activity level had changed. Results Analyses of visiting showed that more women (67.5%) than men (32.5%) visited the program. With regard to continued use, native Dutch participants (odds ratio [OR] = 2.81, 95% confidence interval [CI] = 1.16-6.81, P = .02) and participants with a strong motivation to be healthy (OR = 1.46, CI = 1.03-2.07, P = .03) were most likely to continue usage of the program. With regard to revisiting, older participants (OR = 1.04, CI = 1.01-1.06, P = .01) and highly educated participants (OR = 4.69, CI = 1.44-15.22, P = .01) were more likely to revisit the program after three months. In addition, positive affective user experience predicted revisiting (OR = 1.64, CI = 1.12-2.39, P = .01). Conclusions The results suggest that online interventions could specifically target men, young people, immigrant groups, people with a low education, and people with a weak health motivation to increase exposure to these interventions. Furthermore, eliciting positive feelings in visitors may contribute to higher usage rates.
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                Author and article information

                Contributors
                Journal
                Internet Interv
                Internet Interv
                Internet Interventions
                Elsevier
                2214-7829
                21 April 2018
                June 2018
                21 April 2018
                : 12
                : 74-82
                Affiliations
                [a ]Department of Psychology, Faculty of Social, Human, and Mathematical Sciences, University of Southampton, Southampton, Hampshire, UK
                [b ]Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, Hampshire, UK
                [c ]Redcar & Cleveland Borough Council, Redcar, Yorkshire, UK
                [d ]Health and Social Care Institute, School of Health and Social Care, Teesside University, Middlesbrough, Tees Valley, UK
                [e ]Fuse, Centre for Translational Research in Public Health, Newcastle University, Newcastle upon Tyne, Tyne and Wear, UK
                [f ]Centre for Public Policy and Health, School of Medicine, Pharmacy and Health, Durham University, Stockton on Tees, UK
                [g ]Gateshead Council, Gateshead, Tyne and Wear, UK
                [h ]Electronics and Computer Science, University of Southampton, Southampton, Hampshire, UK
                [i ]Nuffield Department of Primary Care Health Sciences, Medical Sciences Division, University of Oxford, Oxford, UK
                Author notes
                [* ]Corresponding author at: Department of Psychology, University of Southampton, University Road, Highfield, Southampton SO17 1BJ, UK. A.W.Geraghty@ 123456soton.ac.uk
                [1]

                Present address: Newcastle City Council, Newcastle Upon Tyne, UK.

                [2]

                Present address: Department of Creative Technology, Faculty of Science and Technology, Bournemouth University, Poole, Dorset, UK.

                Article
                S2214-7829(18)30006-X
                10.1016/j.invent.2018.03.006
                6096327
                30135771
                c66f0d1a-3a55-4eae-af3c-a17ce4dfd65d
                © 2018 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 18 January 2018
                : 19 March 2018
                Categories
                Full length Article

                internet,mobile applications,data analysis,health,behavioural research,usage

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