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While the phenomenon of technostress has received significant attention from researchers in recent years, empirical findings concerning the consequences of specific forms of techno-stressors have remained scattered and contradictory. The authors aim to integrate the conclusions of previous studies to understand the effects of specific techno-stressors on strain and job performance.

This study employs meta-analytic techniques to calibrate the findings of 67 studies investigating more than 63,100 employees.

In general, not all techno-stressors have adverse effects. In particular, techno-uncertainty does not impact job performance. In addition, relative weight analyses reveal the relative importance of techno-complexity and techno-insecurity as predictors of both strain and job performance. Finally, this study finds that the effects of specific techno-stressors on job performance vary depending on research participants' gender, educational attainment and employment status.

First, this study provides a more nuanced view of the effects of specific techno-stressors. Second, this research clarifies the relative importance of specific techno-stressors as predictors of strain and job performance. Finally, this study reveals the moderating effects of demographic variables on the relationships between specific techno-stressors and job performance.

In this study, we investigated the positive and negative effects of stress that is driven by responsible artificial intelligence (RAI) principles on employee job outcomes by adapting the challenge–hindrance stressors model.

The study design involved empirically validating the proposed model on 299 respondents who use AI for work-related tasks.

The results revealed several RAI-driven challenge and hindrance stressors related to employees’ positive and negative psychological responses and task performance in a digital workplace. Practitioners could use the RAI characteristics to improve employees’ RAI-driven task performance.

This study contributes to the ongoing discussion on technostress and awareness in the context of RAI in the AI literature. By extending the C-HS model to the RAI context, it complements the context-specific technostress literature by conceptualizing different characteristics of RAI as RAI-driven stressors.

Adoption and use of technologies like RAI are not automatically translated into expected job outcomes. Instead, practitioners and academicians also need to know whether the RAI characteristics actually help employees show positive or negative behavior. Furthermore, relying on the challenge–hindrance stressor (C-HS) model, we try to reveal the beneficial and detrimental effects of different RAI characteristics on employees’ job outcomes.

The authors investigate the relationship between instant messenger (IM) use and work performance, mediated by interruptions and two key indicators of the stress associated with technology use: overload and complexity.

The authors validate this research model using partial least squares structural equation modelling (PLS-SEM) with data collected through a survey of 416 working professionals.

The data reveal that while IM use contributes minimally to work interruptions and to a greater extent to technological complexity, these two constructs fully mediate the direct influence of IM use at work on technology overload, and meanwhile significantly and directly contribute to work performance.

This research provides theoretical insights into the deployment of IM and its actual impacts in the workplace. To improve the generalisation of the findings, the authors call for more IM-related research in other countries, with more native theories and various methodologies in this domain.

The level of stress generated through IM use is moderate, considering IM is not a significant contributor to work interruptions. Thus, despite the potential negative effects of IM communication, the positive effects of using IM at work prevail. As a result, the technology can be promoted as long as employees, their managers and the organisation as a whole are well prepared. Employees can transfer skills and behaviour from the personal setting to their work environment and thus may find an intrinsic motivation to make better use of the IM technology at work.

The authors argue that this research model is novel for its perspective on evaluating the actual impacts of IM use at work instead of the reasons of using it. The authors conceptualise the process to explain how IM contributes to interruptions and other technostress indicators in the working context, and the impact on performance. Contrary to some prior research, the authors find that overall IM applications do not have a negative impact on work performance, and instead may enhance it.

The construction industry has more propensity to negatively affect employees’ physical–mental well-being due to the inherently intense and demanding nature of the work involved. Digitalization can streamline the construction processes, and reduce stress, overtime and overall job-related pressure generated due to the nature of employment, contributing to the well-being of employees. Hence, the authors examined how digitalization, technostress and individual resilience could contribute to construction professionals’ physical–mental well-being using the transaction model of stress, self-determination theory and job-demand resources theory.

Data were collected from 86 young professionals using a structured survey. The professionals were working in Indian construction organizations where digitalization is implemented extensively. The survey consists of 21 items to measure four latent variables namely digitalization, technostress, physical–mental well-being and individual resilience. The study employs a partial least squares structural equation modeling (PLS-SEM) approach to examine the theoretical model empirically.

The results revealed that digitalization was positively associated with physical–mental well-being and negatively associated with technostress. Further, individual resilience was a moderating variable in the relationship between digitalization and technostress. Finally, technostress partially mediated the relationship between digitalization and physical–mental well-being.

Digitalization has emerged as a valuable tool to tackle these challenges and improve the overall well-being of construction personnel. In the present study, digitalization is found to augment the physical–mental well-being of young construction professionals. Also, digitalization helps to significantly reduce technostress, thereby improving the physical–mental well-being of young professionals.

The recent pandemic (COVID-19) and the continuous ICT advancements have resulted in increased levels of technostress. On this basis, the present work tried to explore how technostress influences employees’ turnover intention with the mediation of work-exhaustion. Deploying the theoretical lens of job demands-resources theory, the authors also aim to investigate the part that positive psychological capital (PsyCap) has to play as a moderator in between technostress and work-exhaustion.

The study utilizes a time-lagged methodological design; data was gathered from 544 Indian IT employees. Additionally, PLS-SEM was used to carry out the aforementioned moderation-mediation analysis.

All the hypotheses proposed were confirmed. It was found that technostress significantly impacts employees’ turnover intention. Additionally, work-exhaustion does mediate the relationship between technostress and employees’ turnover intention. Furthermore, PsyCap did play the role of a moderator between Technostress and work-exhaustion.

This paper provides an augmented understanding of technostress in IT organizations and highlights the role of personal resources in aiding employees’ to deal with technostress.

This study is one of the early studies to highlight the role of positive psychological capital in mitigating the impact of technology-induced exhaustion and employees’ turnover intention.

This paper aims to explore the underlying mechanism whereby information-induced stress, resulting from the burdensome nature, questionable information reliability, misleading content and diffuse characteristics of infodemic pressure, impacts individuals’ online information-related behavior and health-related preventive behavior.

We conducted a cross-sectional survey organized with social media users during the post-pandemic period. Based on the 342 valid responses, structural equation modeling was employed to validate the research model.

The results substantiate our multidimensional view of infodemic stress, which encompasses dimensions including information overload, uncertainty, diffusivity and insecurity. We found that the infodemic stress contributes to pandemic fatigue, then engenders both negative information behavior and reduced engagement in preventive behavior. Furthermore, infodemic stress has also been found to have a direct positive effect on individuals’ engagement in preventive behavior.

This study introduces the concept of “infodemic stress” and presents a comprehensive framework to capture its various dimensions. This study offers novel insights into the psychological and behavioral repercussions of the infodemic stress transmitted through social media.

Social media is now regularly used by employees for both personal and professional reasons. Its potential significance in industry 5.0 cannot be denied. Social media usage can stress out employees, despite its benefits. Numerous adverse outcomes have been associated with using social media for work-related purposes. The current study too aimed at understanding how using social media for job related activities affect technostress amongst employees at IT sector in India before and during COVID-19.

In order to determine whether the data were reliable and valid, confirmatory factor analysis and Cronbach’s alpha were used. After that, using a structural equation model, the impact of social media usage intensity for job related activities on techostress through social media is measured.

The study’s findings confirmed that using social media for work-related purposes had a positive relationship with technological stress both during and before COVID-19 situation.

The study is an original piece of work by the authors with no conflict of interest with any party, person or organization.

This study examined whether job and personal resources could buffer the negative effects of technostrain and information and communication technology (ICT) availability demands on employee well-being.

The data were collected among Finnish comprehensive school teachers (n = 323) between December 2020 and February 2021 through an online questionnaire. Hierarchical multiple regression analyses were employed to analyse the main and moderating effects.

The results indicated that technostrain was positively associated with burnout and negatively associated with work engagement. These associations were stronger than those of ICT availability demands. The moderated regression analyses revealed that psychological detachment buffered the negative effects of technostrain on cynicism and a sense of inadequacy. School support acted as a moderator by buffering the negative impact of technostrain on emotional exhaustion and cynicism. Furthermore, school support was found to be an important job resource in terms of boosting work engagement when ICT availability demands were high.

This study provides insights into the role of resources in buffering possible burdening effects of technology on teacher well-being when adopting online teaching in the context of the Covid-19 pandemic.

As workplaces increasingly integrate digital technologies, understanding their impact on employee burnout has become imperative. This paper introduces the Technological Work Burnout Scale (TWBS), an innovative tool developed to measure the influence of technology on workplace burnout.

To bridge the existing gap in this area of study, our research employed Hinkin’s (1998) psychometric methodologies, creating a structured process for developing the TWBS, which included initial item generation, item reduction with reliability estimation, confirmatory factor analysis and tests for both convergent and discriminant validity. By applying these procedures, we validated the scale across various professional settings (in three different samples), ensuring its robustness and applicability in diverse technological work environments.

The TWBS demonstrates a consistent unidimensional structure, effectively capturing the multifaceted nature of burnout in the digital age.

Through this scale, we provide insights into how technology influences employee well-being and organizational health, offering a valuable tool for organizations to assess and manage the growing issue of technological work burnout. Our study not only enriches the academic understanding of burnout in the context of technological integration in workplaces but also offers practical implications for addressing this critical concern.

The purpose of this study is to propose and test a model to explain users’ intention to adopt m-health devices and divide the importance of antecedents for users to adopt m-health devices based on the stimulus-organism-response (S-O-R) framework.

This research conducted an online survey with m-health app users and collected 562 valid responses. A hybrid SEM-ANN approach was employed to evaluate the research model and hypotheses.

The results show that motivation (M), opportunity (O), and ability (A) affect users’ flow experience and loyalty and further affect their adoption intention of m-health technology. Opportunity plays a more critical role in m-health adoption intention than ability.

This study comprehensively examined the factors that affect users’ deep engagement and m-health adoption from the perspective of MOA. It used the hybrid SEM-ANN method to divide the critical role of motivation, opportunity and ability, providing a new analysis approach for studying information technology (IT) behavior.