The Effects of Technological Developments on Work and Their Implications for Continuous Vocational Education and Training: A Systematic Review

Changes in MRI Workflow of Multiple Sclerosis after Introduction of an AI-Software: A Qualitative Study

The purpose of this study was to explore the effects of the integration of machine learning into daily radiological diagnostics, using the example of the machine learning software mdbrain® (Mediaire GmbH, Germany) in the diagnostic MRI workflow of patients with multiple sclerosis at the University Medicine Greifswald. The data were assessed through expert interviews, a comparison of analysis times with and without the machine learning software, as well as a process analysis of MRI workflows. Our results indicate a reduction in the screen-reading workload, improved decision-making regarding contrast administration, an optimized workflow, reduced examination times, and facilitated report communication with colleagues and patients. Our results call for a broader and quantitative analysis.

Effects of ChatGPT's AI capabilities and human-like traits on spreading information in work environments

The rapid proliferation and integration of AI chatbots in office environments, specifically the advanced AI model ChatGPT, prompts an examination of how its features and updates impact knowledge processes, satisfaction, and word-of-mouth (WOM) among office workers. This study investigates the determinants of WOM among office workers who are users of ChatGPT. We adopted a quantitative approach, utilizing a stratified random sampling technique to collect data from a diverse group of office workers experienced in using ChatGPT. The hypotheses were rigorously tested through Structural Equation Modeling (SEM) using the SmartPLS 4. The results revealed that system updates, memorability, and non-language barrier attributes of ChatGPT significantly enhanced knowledge acquisition and application. Additionally, the human-like personality traits of ChatGPT significantly increased both utilitarian value and satisfaction. Furthermore, the study showed that knowledge acquisition and application led to a significant increase in utilitarian value and satisfaction, which subsequently increased WOM. Age had a positive influence on WOM, while gender had no significant impact. The findings provide theoretical contributions by expanding our understanding of AI chatbots' role in knowledge processes, satisfaction, and WOM, particularly among office workers.

Association between exposure to technological advances in the workplace and work engagement: a prospective cohort study

OBJECTIVES

The study objective was to measure the association between exposure to technological advances and work engagement, adjusting for personal and workplace factors.

METHODS

We conducted a nationwide online longitudinal survey study in Japan. The sample was stratified to represent Japanese workforce conditions. Work engagement was measured using the Japanese version of the Utrecht Work Engagement Scale-9. Exposure to technological advances was measured using a single question with Likert scale responses. Industry characteristics that were more/less likely to be replaced by automation were also measured. Linear regression was used for statistical analysis.

RESULTS

There were 16 629 participants. We found that exposure to technological advances was associated with work engagement after adjustment for age, sex, education, income, and industry characteristics. We observed a significant interaction between age and exposure to technological advances (coefficient 0.891, P < .001), and conducted an age-stratified linear regression analysis. The significant association between age and exposure to technological advances reduced as age increased, and disappeared after adjustment for baseline work engagement.

CONCLUSIONS

Longitudinal observations showed that exposure to technological advances was not significantly associated with work engagement.

A step toward autonomy in education: probing into the effects of practicing self-assessment, resilience, and creativity in task supported language learning

Self-assessment (SA) can provide students with opportunities to self-evaluate, or make judgments about their learning process and products of learning. Regarding the importance of SA, this survey pursued to examine the effects of practicing SA on Saudi Arabian EFL learners' resilience, creativity, and autonomy in task supported language learning. To fulfill these objectives, 60 intermediate EFL learners were chosen and separated accidentally into two groups of control and experimental. They were then pre-tested using three related questionnaires of resilience, creativity, and autonomy. Next, the treatment was practiced on the two groups. Eight lessons of Touchstone Book 3 were taught to the experimental group using SAvia applying different tasks. On the other hand, the lessons were trained to the control group without using SA and tasks. The aforementioned questionnaires were re-administered as the post-tests following the completion of all lessons. Independent and paired samples t-test findings displayed that the control and experimental groups performed differently on the three post-tests. In essence, the results showed that the experimental group's resilience, creativity, and autonomy were all improved by the treatment. The research's implications and conclusions were then outlined. The implications of the research can allow students to evaluate their own progress and skill development critically.

Barriers and facilitators to utilizing digital health technologies by healthcare professionals

Digital technologies change the healthcare environment, with several studies suggesting barriers and facilitators to using digital interventions by healthcare professionals (HPs). We consolidated the evidence from existing systematic reviews mentioning barriers and facilitators for the use of digital health technologies by HP. Electronic searches were performed in five databases (Cochrane Database of Systematic Reviews, Embase®, Epistemonikos, MEDLINE®, and Scopus) from inception to March 2023. We included reviews that reported barriers or facilitators factors to use technology solutions among HP. We performed data abstraction, methodological assessment, and certainty of the evidence appraisal by at least two authors. Overall, we included 108 reviews involving physicians, pharmacists, and nurses were included. High-quality evidence suggested that infrastructure and technical barriers (Relative Frequency Occurrence [RFO] 6.4% [95% CI 2.9-14.1]), psychological and personal issues (RFO 5.3% [95% CI 2.2-12.7]), and concerns of increasing working hours or workload (RFO 3.9% [95% CI 1.5-10.1]) were common concerns reported by HPs. Likewise, high-quality evidence supports that training/educational programs, multisector incentives, and the perception of technology effectiveness facilitate the adoption of digital technologies by HPs (RFO 3.8% [95% CI 1.8-7.9]). Our findings showed that infrastructure and technical issues, psychological barriers, and workload-related concerns are relevant barriers to comprehensively and holistically adopting digital health technologies by HPs. Conversely, deploying training, evaluating HP's perception of usefulness and willingness to use, and multi-stakeholders incentives are vital enablers to enhance the HP adoption of digital interventions.

Depression, anxiety and insomnia in Chinese older adults and their family caregivers during the COVID-19 pandemic: an actor-partner interdependence model approach

Aims

This study aimed to explore the dyadic effects of depression and anxiety on insomnia symptoms in Chinese older adults and their caregivers living in a community setting.

Methods

Data were collected from 1,507 pairs of older adults and their caregivers who were in the Guangdong Mental Health Survey in China. The 9-item Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder module 7 (GAD-7), and Insomnia Severity Index (ISI) were used to measure depression, anxiety, and insomnia symptoms. Actor-Partner Interdependence Models (APIM) were used to determine whether anxiety or depression symptoms predicted individual or dyadic insomnia.

Results

Older adults' and caregivers' depression and anxiety had significant positive correlations with their own and their caregivers' insomnia symptoms (all P < 0.001). Actor effects were found between depression and insomnia symptoms in both older adults and caregivers (B = 0.695, P < 0.001; B = 0.547, P < 0.001, respectively), with one significant partner effects (B = 0.080, P = 0.007). Actor effects were also found between anxiety and insomnia symptoms in both older adults and caregivers (B = 0.825, P < 0.001; B = 0.751, P < 0.001, respectively), with one significant partner effects (B = 0.097, P = 0.004). However, the caregivers' depression and anxiety were not associated with older adults' insomnia symptoms in the APIM analyses.

Conclusions

Older adults and their caregivers had an interrelationship between psychological distress and insomnia. Consequently, healthcare providers might consider involving dyads when designing programs to reduce insomnia and improve psychological distress for family caregivers.

The Job Perception Inventory: considering human factors and needs in the design of human-AI work

Introduction

Artificial intelligence (AI) is seen as a driver of change, especially in the context of business, due to its progressive development and increasing connectivity in operational practice. Although it changes businesses and organizations vastly, the impact of AI implementation on human workers with their needs, skills, and job identity is less considered in the development and implementation process. Focusing on humans, however, enables unlocking synergies as well as desirable individual and organizational outcomes.

Methods

The objective of the present study is (a) to develop a survey-based inventory from the literature on work research and b) a first validation with employees encountering an AI application. The Job Perception Inventory (JOPI) functions as a work-analytical tool to support the human-centered implementation and application of intelligent technologies. It is composed of established and self-developed scales, measuring four sections of work characteristics, job identity, perception of the workplace, and the evaluation of the introduced AI.

Results

Overall, the results from the first study from a series of studies presented in this article indicate a coherent survey inventory with reliable scales that can now be used for AI implementation projects.

Discussion

Finally, the need and relevance of the JOPI are discussed against the background of the manufacturing industry.

HRM models of online labor platforms: Strategies of market and corporate logics

Studies on online labor platforms (OLPs) have revealed that OLPs can have extensive managerial control over independent workers, which affects their autonomy and precariousness. The permeability of the management makes some OLPs' roles as neutral intermediaries in labor exchanges questionable. While there are several platform work studies on the effects of human resource management (HRM) activities, earlier studies have focused more on certain types of OLP companies. Earlier OLP classifications did not make systematic distinctions between HRM activities either. This paper offers a classification to view how HRM activities manifest in OLPs. The study utilizes terms of service and webpage data from 46 multinational and Finland-based OLPs. Based on these data, OLPs have been classified into six models with five governance principles and institutional logic. The study uses the idea of institutional complexity and claims that OLPs balance their operations between the complexity of two institutional logics, market, and corporation, by using varying strategies with their HRM activities. Differently managed OLPs are also often marketed to different worker groups. This indicates that workers' levels and quality of autonomy differ between OLPs. Hence, could be expected that platform workers' expectations toward OLPs, perceptions of fairness, and experiences of wellbeing may be influenced by the HRM activities in which they engage. The results contribute to the ongoing discussions of power asymmetries between OLPs and platform workers, and thus OLPs' roles as either marketplaces or hierarchical corporations. Formed models can be utilized to enrich studies on key issues of platform workers' autonomy, precariousness, and experiences in different types of OLPs.

The Mediating Role of Selfitis in the Associations between Self-Esteem, Problematic Social Media Use, Problematic Smartphone Use, Body-Self Appearance, and Psychological Distress among Young Ghanaian Adults

Selfie-related activities have become pervasive to the point that they may affect the mental health of people who engage in them. To ascertain this mechanism, this study examined the mediating role of selfitis in the associations between self-esteem, problematic social media use, problematic smartphone use, body-self appearance, and psychological distress among young Ghanaian adults. A total of 651 participants completed a questionnaire with measures on self-esteem, body-self appearance, problematic social media use, problematic smartphone use, depression, anxiety, stress, coping skills, and selfitis. There were direct associations between all the variables except between self-esteem and selfitis. In addition, selfitis mediated the associations between problematic social media use, problematic smartphone use, body-self appearance, and psychological distress except between self-esteem and psychological distress. These findings suggest that selfitis can serve as a pathway by which people who overly engage in problematic social media use, problematic smartphone use, and have poor body-self appearance may experience psychological distress. Hence, there is a need for health communicators, school authorities, and opinion leaders to educate young adults on the consequences of the problematic use of technology, especially for selfitis behaviour. Future studies can examine the factors that predict selfitis behaviour among adults.

Exploring the status of the human operator in Industry 4.0: A systematic review

Industry 4.0 (I4.0) promises to transform jobs and working conditions through the implementation of unprecedented human-machine interaction modes. As the operator working in these new settings, known as the Operator 4.0, is a relatively recent concept, and although technological developments are expected to support workers and require higher labor skills, the risks and health impacts resulting from these changes remain underexplored. This systematic review aims to (i) systematize literature findings on how workers are perceived and participate in I4.0 work systems; (ii) identify the main technological changes driven by I4.0; and (iii) instigate discussion regarding the impacts these changes may have for workers and the sustainability of work systems. Following a systematic review approach using the PRISMA protocol, the articles were organized into two main analysis axes: the technical changes brought about by I4.0, and the representation of the human worker within these new work settings. The findings reveal that a techno-centered approach still seems to be dominant in guiding the implementation of I4.0 models; secondly, as a consequence, the social dimensions of work tend to remain as residual issues, overshadowed by the promises related with technology (e.g., productivity, efficiency); finally, the representation of the Operator 4.0 remains blurry, as he/she is perceived as gender neutral, skillful, and perfectly fit for work, assuring the functioning (and compensating for the limits) of these systems. While I4.0 promises safer and more productive workplaces, issues related to employment conditions, emerging risks and health impacts become more prominent when analyzed from an activity-centered perspective. In terms of future research, a more heuristic analysis could be achieved through a participatory and work-centered approach and following a gender perspective. This way, visibility could be conferred to another side of I4.0, thus guaranteeing conditions for the sustainable development of these work situations.

Bibliometric analysis and science mapping of global scientific publications on technical vocational education training (TVET)

Purpose

While technical vocational education training (TVET) has been studied in-depth, the evolution and performance patterns of the subject remain unknown and limited. A bibliometric analysis was performed to examine the global scientific literature to assess the state of the art in TVET research over the past 23 years.

Design/methodology/approach

The Web of Science (WoS) database was searched to explore TVET-related research from 1999 to 2021, resulting in the identification of 7,512 articles. The VOSviewer software was used to investigate the network of collaboration between authors, institutions, countries and author keywords.

Findings

The results reveal that the subject categories of “education” and “educational research” are the most prolific contributors to TVET-related research, with 3,314 articles. Most of the previous studies in Phase I (1999–2006) focussed on human capital resources development in the TVET sector. Phase II (2007–2014) follows with the centralisation of TVET, focussing on technology transition in education. However, in Phase III (2015–2021), researchers appear to focus on vocational studies in higher education towards increasing the productivity of human resources via the implementation of technology transition.

Originality/value

The valuable findings of this study can facilitate better understanding among scholars on the trends of TVET research developments and on the direction of future research.

Prevalence and correlates of depressive and anxiety symptoms among adults in Guangdong Province of China: A population-based study

AIMS

To examine the prevalence and health correlates of depressive and anxiety symptoms among adults living in Guangdong province of China with a large population and rapid urbanization.

METHODS

The Guangdong Sleep and Psychosomatic Health Survey was conducted from September to November in 2019, which was a population-based study with a representative sample of adults aged 18-85 years. Multistage stratified cluster sampling was used. A total of 13,768 inhabitants were included and face-to-face interviewed using standardized assessment tools. Depressive and anxiety symptoms were evaluated using the Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder Scale (GAD-7), respectively.

RESULTS

The weighted prevalence rates of depressive and anxiety symptoms were 8.6% (95% confidence interval [CI]: 8.0%-9.3%) and 6.0% (95%CI, 5.4%-6.5%) respectively. People who have never married, irregular diet rhythm, hardly exercise, poorer sleep, alcohol consumption, chronic diseases and being unemployment and retirement were more likely to suffer depressive and anxiety symptoms. Moreover, the prevalence of depressive symptoms was significantly higher in those suffering from cardiovascular disease (Odds ratio[OR]:3.89, 95%CI: 1.77-8.54), chronic nephrosis (OR:3.89, 95%CI: 1.52-9.94), hyperlipidemia (OR:2.68, 95%CI: 1.57-4.59), anemia (OR:1.96, 95%CI: 1.33-2.89) and arthritis (OR:1.93, 95%CI: 1.17-3.16). The prevalence of anxiety symptoms was evidently greater within patients with cardiovascular disease (OR:3.15, 95%CI: 1.39-7.14), chronic nephrosis (OR: 2.89, 95%CI: 1.22-6.83), hyperlipidemia (OR:2.27, 95%CI: 1.20-4.29) and diabetes (OR:1.99, 95%CI: 1.15-3.44).

CONCLUSIONS

Depressive and anxiety symptoms are commonly found in patients with chronic diseases. Given these adverse outcomes on health, health professionals should pay more attention to depressive and anxiety problems in health care for high-risk population.

Overcoming the "Dark Side" of Technology-A Scoping Review on Preventing and Coping with Work-Related Technostress

In the course of the digitalisation of work, the phenomenon of technostress is increasingly being examined. While there is a plethora of research on its causes and consequences, a growing body of research on mitigating work-related technostress is emerging. In order to identify opportunities to overcome this "dark side" of technology, this scoping review aims to provide a comprehensive overview of the current state of research on how to prevent and cope with work-related technostress. The databases PubMed, MEDLINE, PsycInfo, PSYNDEX, and Web of Science were searched in the time period between 2008 and 2021. The studies were screened independently by two authors and selected based on predefined inclusion and exclusion criteria. Sixty-two studies were included and their methodological quality was assessed using standardised checklists. Resources were identified at the technical, organisational, social and personal level, including, e.g., leadership, organisational and technical support as well as self-efficacy and IT mindfulness. Problem- and emotion-focused coping strategies were, e.g., seeking support or distancing from IT. None of the included studies investigated prevention measures, emphasising a dearth of research that needs to be addressed in the future. Nevertheless, the identified resources and coping strategies provide starting points to address adverse work- and health-related consequences and reduce work-related technostress.

Working With Robots: Human Resource Development Considerations in Human–Robot Interaction

Advancements in robotic technology have accelerated the adoption of collaborative robots in the workplace. The role of humans is not reduced, but robotic technology requires different high-level responsibilities in human–robot interaction (HRI). Based on a human-centered perspective, this literature review is to explore current knowledge on HRI through the lens of HRD and propose the roles of HRD in this realm. The review identifies HRD considerations that help implement effective HRI in three human-centered domains: human capabilities, collaboration configuration, and attributes related to contact. The eight HRD considerations include employees’ attitudes toward robots, their readiness for robot technology, communication with robots, human–robot team building, leading multiple robots, systemwide collaboration, safety interventions, and ethical issues. Theoretical implications, practical implications, and limitations are discussed. This paper contributes to HRD by introducing potential areas of multidisciplinary collaborations to help organizations implement robotic systems.

Preparing Workplaces for Digital Transformation: An Integrative Review and Framework of Multi-Level Factors

The rapid advancement of new digital technologies, such as smart technology, artificial intelligence (AI) and automation, robotics, cloud computing, and the Internet of Things (IoT), is fundamentally changing the nature of work and increasing concerns about the future of jobs and organizations. To keep pace with rapid disruption, companies need to update and transform business models to remain competitive. Meanwhile, the growth of advanced technologies is changing the types of skills and competencies needed in the workplace and demanded a shift in mindset among individuals, teams and organizations. The recent COVID-19 pandemic has accelerated digitalization trends, while heightening the importance of employee resilience and well-being in adapting to widespread job and technological disruption. Although digital transformation is a new and urgent imperative, there is a long trajectory of rigorous research that can readily be applied to grasp these emerging trends. Recent studies and reviews of digital transformation have primarily focused on the business and strategic levels, with only modest integration of employee-related factors. Our review article seeks to fill these critical gaps by identifying and consolidating key factors important for an organization’s overarching digital transformation. We reviewed studies across multiple disciplines and integrated the findings into a multi-level framework. At the individual level, we propose five overarching factors related to effective digital transformation among employees: technology adoption; perceptions and attitudes toward technological change; skills and training; workplace resilience and adaptability, and work-related wellbeing. At the group-level, we identified three factors necessary for digital transformation: team communication and collaboration; workplace relationships and team identification, and team adaptability and resilience. Finally, at the organizational-level, we proposed three factors for digital transformation: leadership; human resources, and organizational culture/climate. Our review of the literature confirms that multi-level factors are important when planning for and embarking on digital transformation, thereby providing a framework for future research and practice.