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A synthesised framework for behaviour change and persuasive system design

A synthesised framework for behaviour change and persuasive system design

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eHealth interventions are widely used to support parents in managing children's health behaviours and could be beneficial in supporting physiotherapy home programmes for children with cerebral palsy. The use of technology in health crosses several disciplines, and a conceptual analysis of techniques and models used by these different disciplines co...

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Context 1
... targets (i.e. motivation, capability or opportunity) can therefore be linked to BCTs through these intervention functions (Figure 3). Assessing or designing a behavioural intervention based on these intervention functions and their behaviour targets assists in recognising the different components that can impact the success or failure of an intervention. ...
Context 2
... have synthesised these frameworks and models as illustrated in Figure 3. The synthesised framework enables a Notes: B:MAP, behavior, motivation, ability, trigger Table 1 provides an example of mapping part of an eHealth intervention using this framework. ...

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Article
Patient engagement is currently considered the cornerstone of a revolution in healthcare for its positive impact on health outcomes, health behaviors and healthcare costs. Patient engagement is focused on personalized care to consumers through providing knowledge, skills and confidence. Mobile health (mHealth) applications are an innovative means to facilitate patient engagement. Nevertheless, the extent to which the current mHealth applications are designed to engage patients in managing their chronic diseases is unclear. This paper aims to identify the Persuasive System Design (PSD) features present in current mHealth applications that increased the engagement of patients with chronic diseases. This review also aims to identify patient engagement-related outcomes of these features. This paper conducted a systematic literature review and meta-analysis to find relevant studies published from all years up to 2020 through six databases: PubMed, Scopus, Web of Science, Cinahl plus with full text, MEDLINE with full text, and Cochrane Library (Central register of controlled trials). The database search returned 4939 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 13. A qualitative content analysis was performed to identify PSD model features and their patient engagement-related outcomes. The quality assessment has been done through the Cochrane Risk of Bias tool for RCTs. The systematic literature review and meta-analysis identified eleven PSD features that can increase patient engagement through using mHealth applications. The identified PSD features have been shown to have various patient engagement-related outcomes. Behavior Change Techniques (BCTs) were combined with the identified PSD features. This paper identified persuasive features of mHealth application design that influence the engagement of patients with chronic diseases toward changing their behavior. The impact of these features is also analyzed in this review. The results show that an mHealth technology-mediated patient engagement model is needed.
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Background Persuasive technology is an umbrella term that encompasses software (eg, mobile apps) or hardware (eg, smartwatches) designed to influence users to perform preferable behavior once or on a long-term basis. Considering the ubiquitous nature of mobile devices across all socioeconomic groups, user behavior modification thrives under the personalized care that persuasive technology can offer. However, there is no guidance for developing personalized persuasive technologies based on the psychological characteristics of users. Objective This study examined the role that psychological characteristics play in interpreted mobile health (mHealth) screen perceived persuasiveness. In addition, this study aims to explore how users’ psychological characteristics drive the perceived persuasiveness of digital health technologies in an effort to assist developers and researchers of digital health technologies by creating more engaging solutions. Methods An experiment was designed to evaluate how psychological characteristics (self-efficacy, health consciousness, health motivation, and the Big Five personality traits) affect the perceived persuasiveness of digital health technologies, using the persuasive system design framework. Participants (n=262) were recruited by Qualtrics International, Inc, using the web-based survey system of the XM Research Service. This experiment involved a survey-based design with a series of 25 mHealth app screens that featured the use of persuasive principles, with a focus on physical activity. Exploratory factor analysis and linear regression were used to evaluate the multifaceted needs of digital health users based on their psychological characteristics. Results The results imply that an individual user’s psychological characteristics (self-efficacy, health consciousness, health motivation, and extraversion) affect interpreted mHealth screen perceived persuasiveness, and combinations of persuasive principles and psychological characteristics lead to greater perceived persuasiveness. The F test (ie, ANOVA) for model 1 was significant (F9,6540=191.806; P<.001), with an adjusted R2 of 0.208, indicating that the demographic variables explained 20.8% of the variance in perceived persuasiveness. Gender was a significant predictor, with women having higher perceived persuasiveness (P=.008) relative to men. Age was a significant predictor of perceived persuasiveness with individuals aged 40 to 59 years (P<.001) and ≥60 years (P<.001). Model 2 was significant (F13,6536=341.035; P<.001), with an adjusted R2 of 0.403, indicating that the demographic variables self-efficacy, health consciousness, health motivation, and extraversion together explained 40.3% of the variance in perceived persuasiveness. Conclusions This study evaluates the role that psychological characteristics play in interpreted mHealth screen perceived persuasiveness. Findings indicate that self-efficacy, health consciousness, health motivation, extraversion, gender, age, and education significantly influence the perceived persuasiveness of digital health technologies. Moreover, this study showed that varying combinations of psychological characteristics and demographic variables affected the perceived persuasiveness of the primary persuasive technology category.