New Technologies in the Workplace: Can Personal and Organizational Variables Affect the Employees' Intention to Use a Work-Stress Management App?

Modelling the mass consumption potential of Plant Based Meat: Evidence from an emerging economy

The rising demand for plant-based meat (PBM) has the potential to minimize environmental degradation and save the lives of numerous animals. Furthermore, the intention to consume eco-friendly products triggers people to consume PBM. However, it is essential to understand the factors that influence consumer intentions and actual PBM consumption to enhance its adoption. By incorporating the Theory of Consumption Value, this study examines the impact of health consciousness, health motivation, personal innovativeness, perceived critical mass, perceived cost, and perceived product value on the intention to consume PBM. The impact of intention to consume PBM on actual consumption is also analyzed. Furthermore, the mediating role of the intention to consume PBM in the relationship between these factors and actual consumption behavior is investigated. Using a cross-sectional research design, 978 responses were obtained from Indonesia. The data were analyzed using partial least squares structural equation modelling (PLS-SEM). The results showed that health motivation, perceived critical mass perceived cost, and perceived product value were significant predictors of the intention to consume PBM. However, health motivation and personal innovation had insignificant effects on the intention to consume PBM. Moreover, the intention to consume PBM translated into actual consumption behavior. Furthermore, the intention to consume PBM significantly mediated the relationship between actual consumption behavior and factors other than health motivation, personal innovation, and perceived product value. The findings offer valuable insights for industry, policymakers, and producers interested in PBMA markets in developing focused marketing strategies, improving consumer perceptions, and addressing barriers, such as perceived costs to promote PBM consumption, particularly in emerging markets. Integrating the theory of consumption value and PLS-SEM provides a comprehensive understanding of the underlying dynamics and sheds light on the unique factors driving PBM consumption behavior.

Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology

Addressing the growing popularity of mobile health (m-Health) technology in the health industry, the current study examined consumers' intention and behaviour related to the usage of digital applications based on the unified theory of acceptance and use of technology (UTAUT). In particular, this study quantitatively assessed the moderating role of perceived product value and mediating role of intention to use m-Health application among Indonesians. This study adopted a cross-sectional design and collected quantitative data from conveniently selected respondents through an online survey, which involved 2068 Telegram users in Indonesia. All data were subjected to the analysis of partial least square- structural equation modeling (PLS-SEM). The obtained results demonstrated the moderating effect of perceived product value on the relationship between intention to use m-Health application (m-health app) and actual usage of m-Health app and the mediating effects of intention to use m-Health app on the relationships of perceived critical mass, perceived usefulness, perceived convenience, perceived technology accuracy, and perceived privacy protection on actual usage of m-Health app. However, the intention to use m-Health app did not mediate the influence of health consciousness and health motivation on the actual usage of m-Health app. Overall, this study's findings on the significance of intention to use m-Health app and perceived product value based on the UTAUT framework serve as insightful guideline to expand the usage of m-Health app among consumers.

Preliminary effectiveness of an evidence-based mobile application to promote resilience among working adults in Singapore and Hong Kong: Intensive longitudinal study

Evidence-based mobile health (mHealth) applications on smartphones are a cost-effective way for employees to take proactive steps to improve well-being and performance. However, little is known about what sustains engagement on these applications and whether they could dynamically improve occupational outcomes such as resilience and mood. Using real-world data, this intensive longitudinal study examines (a) which employees would continually engage with a cognitive behavioural therapy-informed mHealth application ('Intellect'); and (b) if daily engagement of 'Intellect' would relate to better occupational outcomes on the following day. A total of 515 working adults in Singapore and Hong Kong (Mage = 32.4, SDage = 8.17) completed daily in-app items on mood and resilience components (i.e. sleep hours, sleep quality, physical activity, and stress levels). Our results revealed that employees with lower baseline resilience (β = -0.048, odds ratio (OR) = 0.953, p < 0.01), specifically poorer sleep quality (β = -0.212, OR = 0.809, p = 0.001) and/or higher stress levels (β = -0.255, OR = 0.775, p = 0.05), were more likely to resume engagement on the application. Among the 150 active users (i.e. ≥3 consecutive days of engagement) (Mage = 32.2, SDage = 8.17), daily engagement predicted higher resilience (β = 0.122; 95% confidence interval (CI) 0.039-0.206), specifically lower stress levels (β = 0.018; 95% CI 0.004-0.032), higher physical activity (β = 0.079; 95% CI 0.032-0.126), and mood levels (β = 0.020; 95% CI 0.012-0.029) on the following day even after controlling for same-day outcomes. Our preliminary findings suggest that engaging with a mHealth application was associated with higher dynamic resilience and emotional well-being in employees.

The necessary, albeit belated, transition to computerized cognitive assessment

Cognitive assessment is a common and daily process in educational, clinical, or research settings, among others. Currently, most professionals use classic pencil-and-paper screenings, tests, and assessment batteries. However, as the SARS-CoV-2 health crisis has shown, the pencil-and-paper format is becoming increasingly outdated and it is necessary to transition to new technologies, using computerized cognitive assessments (CCA). This article discusses the advantages, disadvantages, and implications of this necessary transition that professionals should face in the immediate future, and encourages careful adoption of this change to ensure a smooth transition.

Introducing mobile apps to promote the well-being of German and Italian university students. A cross-national application of the Technology Acceptance Model

Stress represents a significant risk factor for several psychophysical diseases among college students, such as depression and anxiety, which may undermine their academic functioning, resulting in high drop rates from college. Nevertheless, university services for mental health promotion are typically underutilized. As a result, professionals and authorities strive to find new ways to address students' mental health needs. In this view, mobile apps seem appropriate for well-being promotion interventions. Drawing on the Technology Acceptance Model (TAM), which is the most widely used theory on users' intention to use technologies, we assumed that perceived usefulness (PU) and perceived ease of use (PEOU) would be positively related to intention to use (INT), and PEOU would be positively related to PU among both Italian and German university students. To test our hypotheses, we replicated the same cross-sectional study in Italy (n = 255) and Germany (n = 228) with university students. Although we found partial scalar invariance of the TAM dimensions across the two nations, our predictions were only partially confirmed: PEOU was positively related to PU in the Italian sample only. Overall, this study is one of the first empirical attempts to compare TAM cross-nationally within the European context and it contributes to the small but increasing body of research investigating students' acceptance of smartphone-based interventions for stress management and well-being promotion. Understanding mobile health acceptance could help universities increase students' chances of adopting the proposed services, considering the factors influencing this choice.

A Cluster Analysis of the Acceptance of a Contact Tracing App—The Identification of Profiles for the Italian Immuni Contact Tracing App

Digital contact tracing apps have been introduced by governments as a strategy to limit the spread of the COVID-19 pandemic. Digital contact tracking is an alternative to traditional contact tracing performed by human tracers who have to reconstruct each contact an infected person had in the recent past by means of interviews. The Italian government proposed the Immuni digital contact tracking app as a solution. Immuni uses Bluetooth technology to anonymously register all close contacts a person had: if she tests positive for COVID-19 then all registered contacts are notified. The main aim of the paper is to propose a cluster analysis of some factors concerning the possible acceptance of the Immuni app to build behaviour profiles that explain and predict the possible behaviours of the respondents. The factors considered referred to three different pillars: the technological pillar, investigated by considering factors from the technology acceptance models family; the health pillar, where variables of the health belief model were used; and the sociopolitical pillar, where some values of the respondents were considered as possible barriers to or facilitators of the acceptance of this technology. As a result of the cluster analysis, three behavioural profiles were built: the ProApp profile, the Hesitant profile, and the AntiApp profile. The first is the profile grouping the respondents who intend to use the contact tracing app; the second is more about people who are favourable of the use of the app, but some issues such as privacy reduce the strength of their intention; the last profile is about people who are less favourable to use the app. We are confident that the behaviour profiles found would be useful to build more tailored communication campaigns to help promote the use of the app by managing factors that could either be facilitators or barriers.