An Analysis of the Persuasive Technology Design Features that Support Behavioural Change

Asmah, Alexander Ekow; Ofoeda, Joshua; Agbozo, Ebenezer

doi:10.1007/978-3-030-89912-7_56

Cited by 4 publications

(4 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The findings of this study disagree with those of previous researchers such as Chatterjee [ 21 ] and Pourmand et al [ 62 ], who found culture to be a significant factor in the use of mHealth. In contrast, this study’s findings agree with those of Asmah et al [ 63 ], who argued that well-sensitized patients with chronic disease will use mHealth without cultural bias and misconceptions of the causes of the diseases and with no fear of treatment.…”

Section: Discussionsupporting

confidence: 89%

mHealth Self-Monitoring Model for Medicine Adherence of Patients With Diabetes in Resource-Limited Countries: Structural Equation Modeling Approach

Kgasi¹,

Chimbo²,

Motsi³

2023

JMIR Form Res

View full text Add to dashboard Cite

Background The COVID-19 pandemic has led to serious challenges and emphasized the importance of using technology for health care operational transformation. Consequently, the need for technological innovations has increased, thus empowering patients with chronic conditions to tighten their adherence to medical prescriptions. Objective This study aimed to develop a model for a mobile health (mHealth) self-monitoring system for patients with diabetes in rural communities within resource-limited countries. The developed model could be based on the implementation of a system for the self-monitoring of patients with diabetes to increase medical adherence. Methods This study followed a quantitative approach, in which data were collected from health care providers using a questionnaire with close-ended questions. Data were collected from district hospitals in 3 South African provinces that were selected based on the prevalence rates of diabetes and the number of patients with diabetes treated. The collected data were analyzed using smart partial least squares to validate the model and test the suggested hypotheses. Results Using variance-based structural equation modeling that leverages smart partial least squares, the analysis indicated that environmental factors significantly influence all the independent constructs that inform patients’ change of behavior toward the use of mHealth for self-monitoring of medication adherence. Technology characteristics such as effort expectancy, self-efficacy, and performance expectancy were equally significant; hence, their hypotheses were accepted. In contrast, the contributions of culture and social aspects were found to be insignificant, and their hypotheses were rejected. In addition, an analysis was conducted to determine the interaction effects of the moderating variables on the independent constructs. The results indicated that with the exception of cultural and social influences, there were significant interacting effects on other independent constructs influencing mHealth use for self-monitoring. Conclusions On the basis of the findings of this study, we conclude that behavioral changes are essential for the self-monitoring of chronic diseases. Therefore, it is important to enhance those effects that stimulate the behavior to change toward the use of mHealth for self-monitoring. Motivational aspects were also found to be highly significant as they triggered changes in behavior. The developed model can be used to extend the research on the self-monitoring of patients with chronic conditions. Moreover, the model will be used as a basic architecture for the implementation of fully fledged systems for self-monitoring of patients with diabetes.

show abstract

Section: Discussionsupporting

confidence: 89%

mHealth Self-Monitoring Model for Medicine Adherence of Patients With Diabetes in Resource-Limited Countries: Structural Equation Modeling Approach

Kgasi¹,

Chimbo²,

Motsi³

2023

JMIR Form Res

View full text Add to dashboard Cite

show abstract

“…For example, healthcare apps may be designed to encourage people to engage in healthy behavior to prevent health problems [43]. Persuasive dialogue refers to the extent to which an application reassures, motivates, and supports users to have continuous interaction with the system through employing seven features: reminders, suggestions, social role, liking, similarity, rewards, and praise [23].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Reminders have a positive impact on the efficacy and adherence of web-based interventions that affect users' attitudinal loyalty to technology [47,50]. By employing PDS features, the application reassures, motivates, and supports users to have continuous interaction [23]. Therefore, PDS features facilitate AL.…”

Section: Persuasive Dialogue Support (Pds) and Altitudinal Loyalty (Al)mentioning

confidence: 99%

“…In pursuit of this objective, app designers are increasingly exploring the principles of persuasive dialogue design, a vital facet in captivating and retaining users, especially in the context of social networking applications [22]. Persuasive dialogue technology, often abbreviated as PDS, encompasses the extent to which an application reassures, motivates, and supports users to interact with the system continuously [13,[23][24][25][26]. PDS finds its roots in the work of B.J.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Why Millennials Continue to Use WhatsApp? A Focus on Culture and Computer–Human Dialogue

Allil,

Faisal,

Zia

2024

Human Behavior and Emerging Technologies

View full text Add to dashboard Cite

Continuous usage behavior among millennials is crucial, yet factors influencing this behavior are not well understood. This study integrates human-computer interaction and marketing research to investigate the relationship between persuasive dialogue support (PDS), attitudinal loyalty (AL), and continuous-use intention (CI) in the context of WhatsApp. The study also examines the moderating role of four cultural dimensions: uncertainty avoidance (UA), power distance (PD), masculinity (MAS), and individualism (IND) in these relationships. Data was collected from 287 WhatsApp users in four countries, and the proposed theoretical model was tested using structural equation modelling (SEM-PLS). The results indicate that PDS has a direct positive impact on AL, which in turn leads to CI. The study also found that cultural differences can moderate the relationship between PDS and AL and between AL and CI. Therefore, app developers need to consider cultural differences when designing their products and implement persuasive design aspects to boost user loyalty and intention to use. To ensure optimal app performance in diverse cultural settings, developers should strike an appropriate balance between universal design principles and culturally sensitive adaptation. However, the study’s limitations, such as reliance on self-reported data and a relatively small sample size, suggest the need for future research to expand its scope to include participants from a broader range of cultural backgrounds.

show abstract

Evaluating user perceptions of the persuasive system design in a breastfeeding mHealth app: a cross-sectional study

Almohanna,

Vlahu-Gjorgievska,

Meedya

et al. 2024

Behaviour & Information Technology

View full text Add to dashboard Cite

An Analysis of the Persuasive Technology Design Features that Support Behavioural Change

Cited by 4 publications

References 24 publications

mHealth Self-Monitoring Model for Medicine Adherence of Patients With Diabetes in Resource-Limited Countries: Structural Equation Modeling Approach

mHealth Self-Monitoring Model for Medicine Adherence of Patients With Diabetes in Resource-Limited Countries: Structural Equation Modeling Approach

Why Millennials Continue to Use WhatsApp? A Focus on Culture and Computer–Human Dialogue

Evaluating user perceptions of the persuasive system design in a breastfeeding mHealth app: a cross-sectional study

Contact Info

Product

Resources

About