The Persuasive Systems Design (PSD) model identifies software features that enhance mHealth app persuasiveness through behavioural reinforcement. Despite its potential, research remains limited in measuring users' perceptions of these persuasive features. This study validated an instrument for measuring user perceptions of persuasive features in a mHealth app, explored user experiences, and identified areas for improvement. This study used a descriptive cross-sectional online survey to collect quantitative and qualitative data. Construct validity was evaluated through Exploratory Factor Analysis (EFA), with data suitability confirmed by Bartlett's test and Kaiser-Meyer-Olkin measures. Cronbach's alpha assessed internal consistency, and an independent sample t-test examined demographic-response relationships (significance at 0.05, two-tailed).A total of 168 participants completed the survey. EFA revealed a four-factor solution with 23 items explaining 62.71% of total variance. The instrument demonstrated good discriminant validity and excellent internal consistency (Cronbach's alpha > 0.8). No significant demographic variations influenced responses.One-sample t-test results showed significant above-neutral PSD features perception scores (t(167) = −21.7, p < .001), indicating participants perceived all features as persuasive. Thematic analysis of 288 qualitative inputs identified three main themes.Findings confirmed the instrument's validity and reliability for assessing user perceptions of persuasive features in mHealth apps. Practical design recommendations based on the findings are provided.

Women are increasingly turning to mHealth apps as primary sources for breastfeeding education and support. The rising prevalence of mHealth apps presents a unique opportunity to explore their impact on women’s breastfeeding experiences. Understanding user perspectives of these apps, especially focusing on their persuasive design aspects, can offer valuable insights for enhancing maternal and child health outcomes. These insights can optimize these technologies to align with user values and promote sustained healthy behaviors. This study aimed to undertake an empirical exploration of users’ experiences with the persuasive design features employed in the Milky Way mHealth app and align the findings with human values within the value-sensitive design (VSD) framework. Semi-structured interviews were conducted with a group of women who had used the Milky Way app. Interview data were analyzed using an inductive thematic approach. To provide insight into users’ values mediated by the app, a deductive analysis complemented by a data-driven inductive approach was performed. Data analysis was supported by NVivo data-management software. Findings from the study demonstrate that the persuasive design elements in the Milky Way app significantly influence users’ experiences. The analysis provided four primary themes: Informative, Easy to use, Credible, and Social connection. Overall, participants praised the app’s trustworthy educational content and support features as valuable resources for addressing breastfeeding challenges and obtaining reliable support. Participants expressed concerns about information overload and emphasized the importance of personalized support and evidence-based tailored recommendations. The results demonstrated that users’ values were expressed and embedded within the app. The analysis indicated an alignment between the app design features and the values and opinions of the users within the VSD framework. This study interprets women’s perspectives utilizing the Milky Way app and highlights the significance of its evidenced-based educational and support features. Further investigation into potential user values like privacy, remains crucial for a comprehensive user-centered app design. The empirical insights gained from this study contribute to future research, informing the development and design of ethically considerate persuasive mHealth apps to maintain their relevance in promoting positive user experiences and facilitating meaningful behavior change.

Recently, task allocation in multi-agent systems has been investigated by many researchers. Some researchers suggested to have a central controller which has a global view about the environment to allocate tasks. Although centralized control brings convenience during task allocation processes, it also has some obvious weaknesses. Firstly, a central controller plays an important role in a multi-agent system, but task allocation procedures will break down if the central controller of a system cannot work properly. Secondly, centralized multi-agent architecture is not suitable for distributed working environments. In order to overcome some limitations caused by centralized control, some researchers proposed distributed task allocation protocols. They supposed that each agent has a limited local view about its direct linked neighbors, and can allocate tasks to its neighbors. However, only involving direct linked neighbors could limit resource origins, so that the task allocation efficiency will be greatly reduced. In this paper, we propose an efficient task allocation protocol for P2P multi-agent systems. This protocol allows not only neighboring agents but also indirect linked agents in the system to help with a task if needed. Through this way, agents can achieve more efficient and robust task allocations in loosely coupled distributed environments (e.g. P2P multi-agent systems). A set of experiments are presented in this paper to evaluate the efficiency and adaptability of the protocol. The experiment result shows that the protocol can work efficiently in different situations.

A systematic review of how the personal digital assistants (PDAs) have been used in healthcare professions and medical education has been conducted in order to identify current usage of PDAs in both areas. The major aim of this research is to study the feasibility of incorporating PDAs into problem-based learning (PBL) medical education. A systematic review was conducted by exploring various databases on the use of PDAs in two major areas: the healthcare professions and medical education during the period 2000-2006. Results: The needs, patterns and functionalities of using PDAs in the medical profession have been identified and categorized into different areas. What remains is to how to best incorporate PDAs into a PBL approach to medical education at the University of Wollongong.