47 research outputs found

    sj-docx-1-dhj-10.1177_20552076221110534 - Supplemental material for Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA)

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    Supplemental material, sj-docx-1-dhj-10.1177_20552076221110534 for Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA) by Sarah Martine Edney, Su Hyun Park, Linda Tan, Xin Hui Chua, Borame Sue Lee Dickens, Salome A Rebello, Nick Petrunoff, Andre Matthias Müller, Cheun Seng Tan, Falk Müller-Riemenschneider and Rob M van Dam in Digital Health</p

    Co-design of a digital dietary intervention for adults at risk of type 2 diabetes

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    Abstract Background Co-design has the potential to create interventions that lead to sustainable health behaviour change. Evidence suggests application of co-design in various health domains has been growing; however, few public-facing digital interventions have been co-designed to specifically address the needs of adults at risk of Type 2 diabetes (T2D). This study aims to: (1) co-design, with key stakeholders, a digital dietary intervention to promote health behaviour change among adults at risk of T2D, and (2) evaluate the co-design process involved in developing the intervention prototype. Methods The co-design study was based on a partnership between nutrition researchers and designers experienced in co-design for health. Potential end-users (patients and health professionals) were recruited from an earlier stage of the study. Three online workshops were conducted to develop and review prototypes of an app for people at risk of T2D. Themes were inductively defined and aligned with persuasive design (PD) principles used to inform ideal app features and characteristics. Results Participants were predominantly female (range 58–100%), aged 38 to 63 years (median age = 59 years), consisting of a total of 20 end-users and four experts. Participants expressed the need for information from credible sources and to provide effective strategies to overcome social and environmental influences on eating behaviours. Preferred app features included tailoring to the individual’s unique characteristics, ability to track and monitor dietary behaviour, and tools to facilitate controlled social connectivity. Relevant persuasive design principles included social support, reduction (reducing effort needed to reach target behaviour), tunnelling (guiding users through a process that leads to target behaviour), praise, rewards, and self-monitoring. The most preferred prototype was the Choices concept, which focusses on the users’ journey of health behaviour change and recognises progress, successes, and failures in a supportive and encouraging manner. The workshops were rated successful, and feedback was positive. Conclusions The study’s co-design methods were successful in developing a functionally appealing and relevant digital health promotion intervention. Continuous engagement with stakeholders such as designers and end-users is needed to further develop a working prototype for testing

    User engagement and attrition in an app-based physical activity intervention: Secondary analysis of a randomized controlled trial

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    Vandelanotte, CL ORCiD: 0000-0002-4445-8094Background: The success of a mobile phone app in changing health behavior is thought to be contingent on engagement, commonly operationalized as frequency of use. Objective: This subgroup analysis of the 2 intervention arms from a 3-group randomized controlled trial aimed to examine user engagement with a 100-day physical activity intervention delivered via an app. Rates of engagement, associations between user characteristics and engagement, and whether engagement was related to intervention efficacy were examined. Methods: Engagement was captured in a real-time log of interactions by users randomized to either a gamified (n=141) or nongamified version of the same app (n=160). Physical activity was assessed via accelerometry and self-report at baseline and 3-month follow-up. Survival analysis was used to assess time to nonuse attrition. Mixed models examined associations between user characteristics and engagement (total app use). Characteristics of super users (top quartile of users) and regular users (lowest 3 quartiles) were compared using t tests and a chi-square analysis. Linear mixed models were used to assess whether being a super user was related to change in physical activity over time. Results: Engagement was high. Attrition (30 days of nonuse) occurred in 32% and 39% of the gamified and basic groups, respectively, with no significant between-group differences in time to attrition (P=.17). Users with a body mass index (BMI) in the healthy range had higher total app use (mean 230.5, 95% CI 190.6-270.5; F2=8.67; P<.001), compared with users whose BMI was overweight or obese (mean 170.6, 95% CI 139.5-201.6; mean 132.9, 95% CI 104.8-161.0). Older users had higher total app use (mean 200.4, 95% CI 171.9-228.9; F1=6.385; P=.01) than younger users (mean 155.6, 95% CI 128.5-182.6). Super users were 4.6 years older (t297=3.6; P<.001) and less likely to have a BMI in the obese range (χ22=15.1; P<.001). At the 3-month follow-up, super users were completing 28.2 (95% CI 9.4-46.9) more minutes of objectively measured physical activity than regular users (F1,272=4.76; P=.03). Conclusions: Total app use was high across the 100-day intervention period, and the inclusion of gamified features enhanced engagement. Participants who engaged the most saw significantly greater increases to their objectively measured physical activity over time, supporting the theory that intervention exposure is linked to efficacy. Further research is needed to determine whether these findings are replicated in other app-based interventions, including those experimentally evaluating engagement and those conducted in real-world settings. © Sarah Martine Edney, Jillian C Ryan, Tim Olds, Courtney Monroe, François Fraysse, Corneel Vandelanotte, Ronald Plotnikoff, Rachel Curtis, Carol Maher. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.11.2019. This is an open-access article distributed under the terms of the Creative Commons Attribution Licens

    E-learning in industry: Case studies from New Zealand

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    In an increasingly Information and Communication Technology (ICT) dependent world, industry leaders are recognising the critical need to investigate the potential of ICT in developing workplace competencies. It is considered a strategic imperative to be aware of effective processes, procedures and plans to improve workforce capability through the implementation of e-learning applications, strategies and techniques. The aim of the “Using e-learning to build workforce capability: A review of activitie
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