The Evaluation of Online Persuasion Criteria on E-Commerce Website using Persuasive System Design (PSD) Model

Persuasive technology in online shopping is proven to assist people while purchasing online. It is crucial to study how was the implementation of such successful persuasive technology in the e-commerce domain. Also, there are certain marketing strategies against consumers from different generational cohorts. Each generation has unique lifestyles, generational history, demographics, experiences, expectations and values that influence their buying behaviours. The persuasive design of e-commerce websites is related to the website conversion rate and is shown to support people throughout the online purchasing process. The objective of this research study is to evaluate the online persuasion criteria on two largest e-commerce websites in Malaysia; Lazada and Shopee through Persuasive System Design (PSD) principles. The four main categories of design technique applied in PSD are primary task support, dialogue support, credibility support and social support. The result shows that both selected e-commerce websites have applied 71.43% of the PSD principles. The most emphasize design technique in Lazada and Shopee is primary task support, followed by dialogue support. Most of the persuasive features in this model has implemented in both e-commerce websites. However, this research proved that the success of the e-commerce websites is related with the implemented persuasive feature which can be manipulated and implemented by other e-commerce websites.

Automatic Evaluation of Piano Performances for STEAM Education

Music plays an important part in the lives of people from an early age. Many parents invest in music education of various types for their children as arts and music are of economic importance. This leads to a new trend that the STEAM education system draws more and more attention from the STEM education system that has been developed over several years. For example, parents let their children listen to music since they were in the womb and invest their money in studying music at an early age, especially for playing and learning musical instruments. As far as education is concerned, assessment for music performances should be standardized, not based on the individual teacher’s standard. Thus, in this study, automatic assessment methods for piano performances were developed. Two types of piano articulation were taken into account, namely “Legato” with vibration notes using sustain pedals and “Staccato” with detached notes without the use of sustain pedals. For each type, piano sounds were analyzed and classified into “Good”, “Normal”, and “Bad” categories. The study investigated four approaches for this task: Support Vector Machine (SVM), Naive Bayes (NB), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM). The experiments were conducted using 4680 test samples, including isolated scale notes and kids’ songs, produced by 13 performers. The results show that the CNN approach is superior to the other approaches, with a classification accuracy of more than eighty percent.

Persuasive Apps for Sustainable Waste Management: A Comparative Systematic Evaluation of Behavior Change Strategies and State-of-the-Art

With the proliferation of ubiquitous computing and mobile technologies, mobile apps are tailored to support users to perform target behaviors in various domains, including a sustainable future. This article provides a systematic evaluation of mobile apps for sustainable waste management to deconstruct and compare the persuasive strategies employed and their implementations. Specifically, it targeted apps that support various sustainable waste management activities such as personal tracking, recycling, conference management, data collection, food waste management, do-it-yourself (DIY) projects, games, etc. The authors who are persuasive technology researchers retrieved a total of 244 apps from App Store and Google Play, out of which 148 apps were evaluated. Two researchers independently analyzed and coded the apps and a third researcher was involved to resolve any disagreement. They coded the apps based on the persuasive strategies of the persuasive system design framework. Overall, the findings uncover that out of the 148 sustainable waste management apps evaluated, primary task support was the most employed category by 89% (n = 131) apps, followed by system credibility support implemented by 76% (n = 112) apps. The dialogue support was implemented by 71% (n = 105) apps and social support was the least utilized strategy by 34% (n = 51) apps. Specifically, Reduction (n = 97), personalization (n = 90), real-world feel (n = 83), surface credibility (n = 83), reminder (n = 73), and self-monitoring (n = 50) were the most commonly employed persuasive strategies. The findings established that there is a significant association between the number of persuasive strategies employed and the apps’ effectiveness as indicated by user ratings of the apps. How the apps are implemented differs depending on the kind of sustainable waste management activities it was developed for. Based on the findings, this paper offers design implications for personalizing sustainable waste management apps to improve their persuasiveness and effectiveness.

Starting ambulance care professionals and critical incidents: a qualitative study on experiences, consequences and coping strategies

Background Ambulance care professionals are regularly confronted with critical incidents that increase risks for mental health disorders. To minimize these risks, it is important that ambulance care professionals adequately cope with critical incidents. Especially from the perspective of starting ambulance care professionals it is unknown which coping styles they use when experiencing a critical incident and how they are trained to cope with critical incidents. The aim of this study was to gain insight in (a) what starting ambulance care professionals describe as critical incidents, (b) how they experience these critical incidents and their consequences, (c) how they cope with these incidents, and (d) how they are trained and guided to cope with these incidents. Methods A qualitative design with individual, semi-structured interviews was used. The data was analyzed by using inductive thematic analysis. Results Twenty-two starting ambulance care professionals were interviewed of which, 11 were male. The age ranged from 23 to 31 years, with 11 participants being 27 years or younger. Three key-themes emerged that make an incident critical: (1) emotional connection versus emotional detachment, (2) feeling loss of control, and (3) incomprehension. All participants experienced several short to middle term physical, psychological and social consequences after encountering a critical incident. Starting ambulance care professionals applied different coping strategies during different phases of the ambulance care process: a mix of depersonification, focus on the medical task, support from colleagues and their own network, seeking confirmation, and distraction. Most starting ambulance care professionals don’t actively remember they received education about coping with critical incidents during their initial educational program. During and after traineeships, the workplace preceptor has a crucial role for starting ambulance care professionals to learn them how to cope with critical incidents. Conclusions Three key-themes interact to make an incident more critical for starting ambulance care professionals. To cope with these critical incidents, starting ambulance care professionals use a variety of coping strategies. These results can be used to develop training and coaching for starting ambulance care professionals so they can adequately cope with critical incidents.

Connecting Artificial Intelligence and Primary Care Challenges: Findings from a Multi-Stakeholder Collaborative Consultation

Despite widespread advancements in and envisioned uses for artificial intelligence (AI), few examples of successfully implemented AI innovations exist in primary care (PC) settings. Objectives: To identify priority areas for AI and PC in Ontario, Canada. Methods: A collaborative consultation event engaged multiple stakeholders in a nominal group technique process to generate, discuss, and rank ideas for how AI can support Ontario PC. Results: The consultation process produced nine ranked priorities: 1) preventative care and risk profiling, 2) patient self-management of condition(s), 3) management and synthesis of information, 4) improved communication between PC and AI stakeholders, 5) data sharing and interoperability, 6-tie) clinical decision support, 6-tie) administrative staff support, 8) practitioner clerical and routine task support, and 9) increased mental health care capacity and support. Themes emerging from small group discussions about barriers, implementation issues, and resources needed to support the priorities included: equity and the digital divide; system capacity and culture; data availability and quality; legal and ethical issues; user-centered design; patient-centredness; and proper evaluation of AI-driven tool implementation. Discussion: Findings provide guidance for future work on AI and PC. There are immediate opportunities to use existing resources to develop and test AI for priority areas at the patient, provider, and system level. For larger-scale, sustainable innovations, there is a need for longer-term projects that lay foundations around data and interdisciplinary work. Conclusion: Study findings can be used to inform future research and development of AI for PC, and to guide resource planning and allocation.

ECMO During a Pandemic: A COVID-19 Quality Improvement Process

Extracorporeal membrane oxygenation is a modified form of cardiopulmonary bypass and a complex adult critical care therapy. No evidence appears to exist on sustaining relevant quality nursing standards during a pandemic. The aim for this quality improvement process was to address nursing provision in real time related to extracorporeal membrane oxygenation in a pandemic, providing fundamentals for future readiness. The Ishikawa fishbone diagram and a Plan-Do-Study-Act cycle were methods used. Process changes included implementation of a communication algorithm, an alternative nursing care model, increased nursing staffing and leadership visibility, use of perfusion services for nursing task support, and minimized nursing documentation. Changes applied were successful. We recommend increasing nursing staffing volume and support resources, applying a communication algorithm, and minimizing documentation requirements. These strategies are generalizable to other clinical nursing areas in similar pandemics or disasters.

The ideal mHealth-application for rheumatoid arthritis: qualitative findings from stakeholder focus groups

Background Shifts in treatment strategies for rheumatoid arthritis (RA) have made ambulatory care more labour-intensive. These developments have prompted innovative care models, including mobile health (mHealth) applications. This study aimed to explore the perceptions of mHealth-inexperienced stakeholders concerning these applications in RA care. Methods We performed a qualitative study by focus group interviews of stakeholders including RA patients, nurses specialised in RA care and rheumatologists. The qualitative analysis guide of Leuven (QUAGOL), which is based on grounded theory principles, was used to thematically analyse the data. In addition, the Persuasive Systems Design (PSD) model was used to structure recommended app-features. Results In total, 2 focus groups with nurses (total n = 16), 2 with patients (n = 17) and 2 with rheumatologists (n = 25) took place. Six overarching themes emerged from the analysis. Efficiency of care and enabling patient empowerment were the two themes considered as expected benefits of mHealth-use in practice by the stakeholders. In contrast, 4 themes emerged as possible barriers of mHealth-use: the burden of chronic app-use, motivational aspects, target group aspects, and legal and organisational requirements. Additionally, recommendations for an ideal mHealth-app could be structured into 4 domains (Primary Task Support, Dialogue Support, Social Support and System Credibility) according to the PSD-framework. Most recommended features were related to improving ease of use (Task Support) and System Credibility. Conclusions Although mHealth-apps were expected to improve care efficiency and stimulate patient empowerment, stakeholders were concerned that mHealth-app use could reinforce negative illness behaviour. For mHealth-apps to be successful in practice, challenges according to stakeholders were avoiding long-term poor compliance, finding the target audience and tailoring a legal and organisational framework. Finally, the ideal mHealth-application should above all be trustworthy and easy to use.