Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Jun 27, 2022
Date Accepted: Aug 10, 2022
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Evaluating The Persuasiveness Of Mobile Health: The Intersection Of Persuasive System Design And Personalization
ABSTRACT
Background:
Persuasive technology is an umbrella term that encompasses any software (e.g., mobile app) or hardware (e.g., smartwatch) designed to influence users to perform a 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 user’s psychological characteristics.Persuasive technology is an umbrella term that encompasses any software (e.g., mobile app) or hardware (e.g., smartwatch) designed to influence users to perform a 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 user’s psychological characteristics.
Objective:
This research examines the role psychological characteristics play in interpreted mHealth screen perceived persuasiveness. In addition, this study aims to explore how a user’s psychological characteristics drives the perceived persuasiveness of digital health technologies in an effort to assist developers and researchers of digital health technologies with 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) impact the perceived persuasiveness of digital health technologies utilizing the Persuasive System Design (PSD) framework. Participants (n=262) were recruited by Qualtrics utilizing the XM Research Service’s online survey system. 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 (EFA) and linear regressions were used to evaluate the multifaceted needs of digital health users based on 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 (i.e., analysis of variance) for Model 1 was significant, F(9, 6540) = 191.806, P < .001, with an adjusted R2 of .208, indicating that the demographic variables explained 20.8% of the variance in perceived persuasiveness. Gender was a significant predictor, with females having higher perceived persuasiveness (p = .008) relative to males. Age was a significant predictor of perceived persuasiveness with individuals in the 40-59 age group (P < .001) and 60+ age group (P < .001). The F-test for Model 2 was significant, F(13, 6536) = 341.035, P < .001, with an adjusted R2 of .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 research evaluates the role psychological characteristics play in interpreted mHealth screen perceived persuasiveness. Findings indicate that self-efficacy, health consciousness, health motivation, extraversion, gender, age, and education have a significant influence on the perceived persuasiveness of digital health technologies. Moreover, this research showed varying combinations of the psychological characteristics and demographic variables impacted the perceived persuasiveness of the primary persuasive technology category.
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