Redefining organizational digitality: a relational-ontological approach inspired by new materialism

Organizations, as central actors in societal structure, undergo significant transformations due to the impact of digitalization, often resulting in disruptive changes. Consequently, organizations increasingly view digitalization as an ongoing process of negotiation, which has led to the emergence of new operational modes and organizational norms. In this context, the interaction between organizations and digital technologies is characterized by recursive dynamics, which blur conventional boundaries. This presents a challenge in defining the distinct domains of the digital and the organizational within the framework of recursivity. This article draws upon new materialism and agential realism to propose an ontological-relational approach to understanding organizational digitality. This approach suggests a reconceptualization of organizational digitality as a mechanism that generates relational entities, thereby reshaping their inherent meanings. By transcending traditional boundaries between organizations and digital, this perspective provides a nuanced understanding of digital phenomena within organizational contexts.

Use of Artificial Intelligence tools in supporting decision-making in hospital management

BACKGROUND

The use of Artificial Intelligence (AI) tools in hospital management holds potential for enhancing decision-making processes. This study investigates the current state of decision-making in hospital management, explores the potential benefits of AI integration, and examines hospital managers' perceptions of AI as a decision-support tool.

METHODS

A descriptive and exploratory study was conducted using a qualitative approach. Data were collected through semi-structured interviews with 15 hospital managers from various departments and institutions. The interviews were transcribed, anonymized, and analyzed using thematic coding to identify key themes and patterns in the responses.

RESULTS

Hospital managers highlighted the current inefficiencies in decision-making processes, often characterized by poor communication, isolated decision-making, and limited data access. The use of traditional tools like spreadsheet applications and business intelligence systems remains prevalent, but there is a clear need for more advanced, integrated solutions. Managers expressed both optimism and skepticism about AI, acknowledging its potential to improve efficiency and decision-making while raising concerns about data privacy, ethical issues, and the loss of human empathy. The study identified key challenges, including the variability in technical skills, data fragmentation, and resistance to change. Managers emphasized the importance of robust data infrastructure and adequate training to ensure successful AI integration.

CONCLUSIONS

The study reveals a complex landscape where the potential benefits of AI in hospital management are balanced with significant challenges and concerns. Effective integration of AI requires addressing technical, ethical, and cultural issues, with a focus on maintaining human elements in decision-making. AI is seen as a powerful tool to support, not replace, human judgment in hospital management, promising improvements in efficiency, data accessibility, and analytical capacity. Preparing healthcare institutions with the necessary infrastructure and providing specialized training for managers are crucial for maximizing the benefits of AI while mitigating associated risks.

Navigating workplace conflicts and fostering innovative behaviors: the role of job commitment and socio-instrumental ESM utilization

This study explores the dynamics of intersection between workplace conflicts, job commitment, and socio-instrumental enterprise social media (ESM) utilization for improving innovation. This study proposes job commitment as a pivotal mediator that influences employees' attitudinal responses to the array of conflicts encountered in the workplace. Additionally, it introduce socio-instrumental ESM use as a potent moderator, influencing employees' appraisals of workplace conflicts. To illuminate the intricate tapestry of these interactions, we present a moderated mediation model that delineates the complex nomological network governing the interplay among workplace conflicts, job commitment, and the cultivation of innovative behaviors. Based on empirical data encompassing 447 employees, our findings illuminate the distinctive moderating roles played by these socio-instrumental ESM usage. These patterns differentially moderate the connections between workplace conflicts and job commitment, as well as the indirect connections between workplace conflicts and the stimulation of employee innovation through job commitment. This research significantly advances our theoretical understanding of the multifaceted interplay among workplace conflicts, job commitment, socio-instrumental ESM utilization, and employee innovation. Moreover, it offers implications that can faciliate organizational strategies aimed at fostering innovation. By recognizing the pivotal roles of job commitment and socio-instrumental ESM, organizations can strategically harness these factors to cultivate a culture of innovation, positioning themselves for success in an increasingly competitive and dynamic business environment.

Smart Home Technologies for Enhancing Independence of Living and Reducing Care Dependence in Older Adults: A Systematic Review

AIM

To systematically review the potential of smart home technology to enhance the independence of older adults and reduce their dependence on care. Additionally, it sought to examine the positive impacts of such technology on their golden years.

DESIGN

A systematic review based on Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA).

DATA SOURCES

The search was conducted on 8 April 2024. Peer-reviewed studies in PubMed, Embase, Web of Science, IEEE Xplore, Scopus, The Cochrane Library, CINAHL, CNKI, WANFANG DATA and VIP from 1 January 2000 to 8 April 2024 were searched.

METHODS

The methodological quality assessment used the Mixed Methods Appraisal Tool (MMAT). Positive findings relevant to this study were extracted from the literature and analysed using thematic synthesis.

RESULTS

After meticulously examining 3404 studies, we identified 21 relevant sources for in-depth analysis, including qualitative studies (n = 10), experimental studies (n = 9) and mixed method studies (n = 2). These sources were grouped into five core themes based on the pivotal role of smart home technologies in enabling ageing in place: daily monitoring, assisted living activities, life reminders, functional improvement and emotional companionship. The study found that smart home technology offers numerous benefits to the lives of older adults, including increased independence, psychological support, improved cognitive functioning, enhanced self-management, increased mobility, support for caregivers, promoted social engagement and enhanced quality of life.

CONCLUSION

Smart home technology can enhance the independence of older adults' lives, reduce their dependence on care, alleviate the burden on caregivers and promote home-based elderly care.

IMPACT

This systematic review contributes to understanding the capability of smart home technology to promote elderly care at home and help better utilise smart home technology to benefit older adults. Older adults and their caregivers should be encouraged to adopt this technology to improve older adults' quality of life.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Wearable neurofeedback acceptance model for students' stress and anxiety management in academic settings

This study investigates the technology acceptance of a proposed multimodal wearable sensing framework, named mSense, within the context of non-invasive real-time neurofeedback for student stress and anxiety management. The COVID-19 pandemic has intensified mental health challenges, particularly for students. Non-invasive techniques, such as wearable biofeedback and neurofeedback devices, are suggested as potential solutions. To explore the acceptance and intention to use such innovative devices, this research applies the Technology Acceptance Model (TAM), based on the co-creation approach. An online survey was conducted with 106 participants, including higher education students, health researchers, medical professionals, and software developers. The TAM key constructs (usage attitude, perceived usefulness, perceived ease of use, and intention to use) were validated through statistical analysis, including Partial Least Square-Structural Equation Modeling. Additionally, qualitative analysis of open-ended survey responses was performed. Results confirm the acceptance of the mSense framework for neurofeedback-based stress and anxiety management. The study contributes valuable insights into factors influencing user intention to use multimodal wearable devices in educational settings. The findings have theoretical implications for technology acceptance and practical implications for extending the usage of innovative sensors in clinical and educational environments, thereby supporting both physical and mental health.

Tendencies and characteristics of public fitness behavior in the digital era: an Internet ethnography study based on the K Community in China

Introduction

The deep integration of media technologies into fitness activities in the era of digital intelligence has created a new and evolving landscape for public fitness. This transformation significantly impacts the practices and experiences of fitness.

Methods

This study employs Internet ethnography as a qualitative research methodology, focusing on the daily activities of participants in a digital fitness community known as the K-community. Through immersive observation and analysis, the research seeks to uncover the evolving patterns and characteristics of fitness practices in China during the digital era.

Results

As media technology and network culture advance, participants in digital fitness increasingly display fragmented, digitized, entertaining, ritualized, and highly socialized behaviors. These traits reflect the community's desire for varied and complex exercise experiences within the context of modern technology.

Discussion

The evolution of fitness behavior not only reflects the operational principles of contemporary media technologies but also encapsulates the essence of popular culture in the digital age. This study enhances our comprehension of fitness practices in digital environments and their wider cultural ramifications.

Model of driving factors for success in public health project management using structural equation modeling

In a context where pandemic crises and chronic conditions are a constant and increasing threat, the success of public health projects is absolutely critical. However, little is known about the factors that influence the success of projects that aim to provide conditions for people to be healthy and prolong the life of the population as a whole. A mixed-method study was carried out to fill the literature gap, resulting in a new model of success factors for public health projects. The research work theorizes the success factors that impact public health project success, providing relevant knowledge for project managers and contributing to the successful management of public health projects.

Impact of Concurrent Media Exposure on Professional Identity: Cross-Sectional Study of 1087 Medical Students During Long COVID

BACKGROUND

Long COVID has widened the health gap across society and highlighted the vulnerabilities and risks faced by health care systems. For instance, the global trend of medical workers resigning has become a prominent topic on social media. In response to this severe social problem in global public health within the digital society, it is urgent to investigate how the professional identity of medical students, who are digital natives and the future workforce of medical practitioners, is affected by the media environment.

OBJECTIVE

This study aims to examine how media exposure relates to medical students' perceptions of informational and emotional support, and how these perceptions further influence the development of their professional identity.

METHODS

Building on the Stimulus-Organism-Response (SOR) framework, this study develops a theoretical model to illustrate how media exposure affects medical students' professional identity through the mediation of social support. Specifically, media exposure was assessed through online news media and social media exposure; social support was evaluated in terms of informational and emotional support; and professional identity was measured through medical students' sense of belonging and professional commitment. A survey was conducted at a medical school in China, yielding 1087 valid responses that were analyzed using SmartPLS 4.0.

RESULTS

Consistent with our expectations, online news media exposure was positively associated with both informational support (β=.163; P<.001) and emotional support (β=.084; P=.007). Similarly, social media exposure showed positive associations with informational support (β=.122; P<.001) and emotional support (β=.235; P<.001). Thereafter, informational support (β=.228; P<.001) and emotional support (β=.344; P<.001) were positively associated with students' sense of belonging. Meanwhile, both informational support (β=.245; P<.001) and emotional support (β=.412; P<.001) positively impacted medical students' professional commitment. In addition, a mediation test was conducted. The results confirmed that informational support and emotional support partially mediated the effect of online news media, while fully mediating the effect of social media on medical students' sense of belonging and professional commitment.

CONCLUSIONS

This study finds that exposure to online news media and social media can enhance medical students' sense of belonging and professional commitment through the formation of informational and emotional support. It expands the discussion on the role of media in providing social support and facilitating the development of medical students' professional identity. This is a valuable contribution to addressing complex public health crises through effective media governance in the network era.

Exploring the Moderating Effect of Musculoskeletal Pain on Technostress-Induced Burnout: A Cross-Sectional Study of Bank Employees

BACKGROUND/OBJECTIVES

Information and Communications Technology (ICT) advancements and high customer expectations are boosting the use of digital transformation and tech tools in business processes in a competitive environment. This trend enhances business effectiveness and efficiency but also introduces technostress as a new workplace stress factor. Technostress, defined as stress induced by using ICT in the workplace, has become increasingly prevalent in modern work environments, especially in sectors such as banking, due to digital transformation. As technology use intensifies, it raises concerns about potential adverse psychological and physiological effects on employees, particularly in relation to burnout. From a physiological perspective, musculoskeletal disorders (MSDs) are quite common among employees who use ICT for extended periods. MSDs can play a significant moderating role in the relationship between technostress and burnout. In this context, this study aimed to examine the moderating role of MSDs in the effect of technostress on burnout.

METHODS

This quantitative study surveyed a convenience sample of 220 bank employees, drawing on COR theory, the JD-R model, the P-E fit approach, and transactional stress theory. Data were analyzed using Structural Equation Modeling with SmartPLS 4.0 software, enabling examination of relationships between variables derived from these frameworks.

RESULTS

The results reveal that technostress increases bank employees' burnout experience. Additionally, bank employees with MSDs experience higher burnout levels than those without MSDs.

CONCLUSIONS

The study's findings provide valuable insights into managing workplace stress, addressing mental health problems, and promoting employee well-being in the digital age. These results have potential implications for academic understanding and practical applications in sustainable management.

More similarity than difference: comparison of within- and between-sex variance in early adolescent brain structure

Background

Adolescent neuroimaging studies of sex differences in the human brain predominantly examine mean differences between males and females. This focus on between-groups differences without probing relative distributions and similarities may contribute to both conflation and overestimation of sex differences and sexual dimorphism in the developing human brain.

Methods

We aimed to characterize the variance in brain macro- and micro-structure in early adolescence as it pertains to sex at birth using a large sample of 9-11 year-olds from the Adolescent Brain Cognitive Development (ABCD) Study (N=7,723). Specifically, for global and regional estimates of gray and white matter volume, cortical thickness, and white matter microstructure (i.e., fractional anisotropy and mean diffusivity), we examined: within- and between-sex variance, overlap between male and female distributions, inhomogeneity of variance via the Fligner-Killeen test, and an analysis of similarities (ANOSIM). For completeness, we examined these sex differences using both uncorrected (raw) brain estimates and residualized brain estimates after using mixed-effects modeling to account for age, pubertal development, socioeconomic status, race, ethnicity, MRI scanner manufacturer, and total brain volume, where applicable.

Results

The overlap between male and female distributions was universally greater than the difference (overlap coefficient range: 0.585 - 0.985) and the ratio of within-sex and between-sex differences was similar (ANOSIM R range: -0.001 - 0.117). All cortical and subcortical volumes showed significant inhomogeneity of variance, whereas a minority of brain regions showed significant sex differences in variance for cortical thickness, white matter volume, fractional anisotropy, and mean diffusivity. Inhomogeneity of variance was reduced after accounting for other sources of variance. Overlap coefficients were larger and ANOSIM R values were smaller for residualized outcomes, indicating greater within- and smaller between-sex differences once accounting for other covariates.

Conclusions

Reported sex differences in early adolescent human brain structure may be driven by disparities in variance, rather than binary, sex-based phenotypes. Contrary to the popular view of the brain as sexually dimorphic, we found more similarity than difference between sexes in all global and regional measurements of brain structure examined. This study builds upon previous findings illustrating the importance of considering variance when examining sex differences in brain structure.

Digital technology application on corporate internationalization: Co-moderating effect of centralizing decision power and internationalization experience

Digital technologies are a significant additional powerhouse for corporate internationalization and competitiveness. The existing research has not effectively distinguished the breadth and depth of internationalization, and there are also inadequate context considerations of how much digital technology applications influence enterprise internationalization. To bridge this gap, this paper has selected 203 valid questionnaires from manufacturing enterprises in Zhejiang Province, China, then elaborates and constructs a theoretical model based on existing studies, and using multiple linear regression analysis, finally to empirically assess and further explain the mechanisms of digital technologies' influence on corporate internationalization. The results reveal that utilizing digital technologies has positive influence on both internationalization breadth and depth. Moreover, centralizing decision power negatively moderates the relationship between enterprises' digital applications and their internationalization breadth (or depth), while internationalization experience has opposite influence, with these two factors jointly moderating such relationship. Finally, this research can contribute to better understanding of leveraging digital technologies to upgrade corporate internationalization and provides reasonable theoretical insights for enhancing deeper and more diversified enterprise internationalization.

Identifying Marijuana Use Behaviors Among Youth Experiencing Homelessness Using a Machine Learning-Based Framework: Development and Evaluation Study

BACKGROUND

Youth experiencing homelessness face substance use problems disproportionately compared to other youth. A study found that 69% of youth experiencing homelessness meet the criteria for dependence on at least 1 substance, compared to 1.8% for all US adolescents. In addition, they experience major structural and social inequalities, which further undermine their ability to receive the care they need.

OBJECTIVE

The goal of this study was to develop a machine learning-based framework that uses the social media content (posts and interactions) of youth experiencing homelessness to predict their substance use behaviors (ie, the probability of using marijuana). With this framework, social workers and care providers can identify and reach out to youth experiencing homelessness who are at a higher risk of substance use.

METHODS

We recruited 133 young people experiencing homelessness at a nonprofit organization located in a city in the western United States. After obtaining their consent, we collected the participants' social media conversations for the past year before they were recruited, and we asked the participants to complete a survey on their demographic information, health conditions, sexual behaviors, and substance use behaviors. Building on the social sharing of emotions theory and social support theory, we identified important features that can potentially predict substance use. Then, we used natural language processing techniques to extract such features from social media conversations and reactions and built a series of machine learning models to predict participants' marijuana use.

RESULTS

We evaluated our models based on their predictive performance as well as their conformity with measures of fairness. Without predictive features from survey information, which may introduce sex and racial biases, our machine learning models can reach an area under the curve of 0.72 and an accuracy of 0.81 using only social media data when predicting marijuana use. We also evaluated the false-positive rate for each sex and age segment.

CONCLUSIONS

We showed that textual interactions among youth experiencing homelessness and their friends on social media can serve as a powerful resource to predict their substance use. The framework we developed allows care providers to allocate resources efficiently to youth experiencing homelessness in the greatest need while costing minimal overhead. It can be extended to analyze and predict other health-related behaviors and conditions observed in this vulnerable community.

How Algorithmic Management Influences Gig Workers' Job Crafting

Algorithmic management, as a digital management tool in the gig economy, has become a hotspot of concern at the intersection of theory and practice. However, there is a lack of research on the mechanisms and boundary conditions through which algorithmic management affects gig workers' job crafting. Based on the social information processing theory, this study constructed a dual-mediation model of how algorithmic management influences gig workers' job crafting through gameful experience and perceived job autonomy. Data from 687 valid samples were collected through a two-stage survey and statistically analyzed using structural equation modeling (SEM). The results demonstrate that algorithmic management increases gig workers' promotion-focused job crafting behaviors (increasing job resources and challenging job demands) by stimulating their gameful experiences and increases gig workers' prevention-focused job crafting behaviors (decreasing hindering job demands) by inhibiting their perceived job autonomy. In addition, the higher-order personality trait core self-evaluation moderates the relationship between algorithmic management and gameful experience and perceived job autonomy, as well as the indirect effects of algorithmic management on job crafting through gameful experiences and perceived job autonomy. This study advances empirical research on algorithmic management in the field of the gig economy and human resource management practices. Crucially, it provides practical insights for optimizing algorithmic systems in platform companies, potentially enhancing their efficiency and economic benefits.

A systematic mapping study on gamification within information security awareness programs

Information security awareness (ISA) has become a vital issue for organizations, as security breaches are usually attributed to human errors. ISP programs are effective ways to educate employees and enhance their information security knowledge. Gamification is a new concept in the area of ISA programs and it has been proven to be one of the most effective and proper ISA methods in both the private and public sectors. Despite a growing interest in employing gamification as an ISP program in recent years, there is a lack of study to provide a comprehensive overview of gamification within ISA programs and identify trends, patterns, and research gaps in this area in order to direct future research. To bridge this gap, a systematic mapping study is adopted as a research methodology. A total of 69 papers were selected and classified by document type, year of publication, research type, research contribution, gamification type, gamification in terms of adaptivity based on the target group, and gamification in terms of the use of artificial intelligence (AI) in order to make it user-tailored. The mapping study revealed that the published papers in this area were split between journals and conference papers with a higher proportion published in conference proceedings. Regarding the publication trend, from 2015 to 2022, gamification within ISA programs has come across to researchers' attention. The identified two main research types were evaluation research and validation research and the vast majority of the contribution type was tools. Moreover, content gamification has been used more commonly in ISA programs than structural gamification. Furthermore, the finding indicated that there were clear gaps in employing adaptive gamification, dynamic adaptive gamification and AI-based adaptive gamification, which makes these areas significant for future research.

Exploring linguistic features and user engagement in Chinese online mental health counseling

With the popularity of online mental health platforms, more individuals are seeking help and receiving social support by openly discussing their problems. Therefore, it's crucial to gain a deeper understanding of which problem disclosures and social support on these platforms can attract more user attention and engagement. Previous research has primarily focused on social media forums. Our work concentrates on the professional mental health platform, intending to understand the linguistic features present in posts that promote user engagement and interaction. We employ text mining and deep learning techniques to analyze posts consisting of 22,250 questions from help-seekers and 78,328 answers providing social support extracted from the Chinese online mental health counseling platform. Initially, we analyze the high-frequency words and topics of the questions and answers to gain insights into the primary focal points and the range of topics covered in these posts. The results indicate that work-related issues are the most concerning and troublesome for help-seekers, and the topics that users follow are approximately 8 types, including growth, family, in-love, marriage, emotions, human-relations, behavioral-therapy and career. Subsequently, we analyze the language usage in question-and-answer posts with different engagement from three aspects: vocabulary categories, linguistic style matching, and language modeling, aiming to identify which linguistic features can attract more user attention and engagement. The results reveal that high-engagement answer posts exhibit a higher degree of linguistic style matching with the corresponding questions, and the use of vocabulary categories also influences the attention and engagement of the posts. By exploring the linguistic features and patterns displayed in posts with different levels of engagement on the professional online mental health platform, this study offers deep insights into user behavior and the factors that impact counseling effectiveness on the platform and provides valuable knowledge for understanding effective user interactions and engagement.

Occupational therapists' perspectives on welfare technologies for dementia: exploring recommendation frequencies - a pilot study

BACKGROUND

Occupational therapists have long been recognized for their expertise in welfare technology use, particularly in the context of dementia care. Despite this advanced training, however, there is often a gap between their knowledge of available technologies and the frequency with which they recommend these tools to individuals with dementia.

AIMS/OBJECTIVES

This study explores the perspectives of occupational therapists on the recommendations of welfare technologies for individuals with dementia.

MATERIALS AND METHODS

A survey was created with the assistance of an expert group in a Swedish municipality. The survey consisted of 26 questions (demographics, background/workload, perceptions of welfare technologies, accessibility/information and knowledge on how and when to use, and initiation of contact and recommendation frequency) and was distributed to 60 occupational therapists within the selected municipality. We received a total of 29 responses. The responses were then analyzed qualitatively for meaningful insights across various themes. Using an encoding scheme, a statistical analysis of the responses was performed to uncover potential trends in the distribution of the responses.

RESULTS

Results indicate positive perceptions of welfare technologies by occupational therapists, but a low frequency of recommendations for individuals with dementia.

CONCLUSIONS AND SIGNIFICANCE

Based on the results, we find it important to advocate for more educational opportunities for occupational therapists regarding welfare technologies and improved organizational structures that promote their understanding and ultimately benefits of recommending welfare technologies to individuals with dementia.

A Dynamic System to Control the Entry of Non-Authorized Visitors and Detect Superspreader Farms in Strongly Interconnected Systems

This study explores the critical challenges the livestock sector faces, particularly those related to biosecurity, animal welfare, and antibiotic use restrictions. It highlights the need to implement advanced information and communication technologies to enhance operational sustainability and decision-making. We introduce the Biorisk® External platform, a cloud-based visit control system designed to optimize biosecurity management by accurately tracking visitor activity through QR codes and GPS geolocation. During a 6-month study period from July to December 2023, we analyzed visits to 142 different swine production sites and 30 vehicle movement patterns. The analysis revealed trends in visitation patterns and compliance with biosecurity SOPs. The software categorized visits as authorized (A), not authorized with access (NAWA), and not authorized without access (NAWOA), providing a framework to assess biosecurity risks. Additionally, network analysis identified interconnected farms, which were classified as 'superspreaders', highlighting their considerable risk of disease transmission. This study advocates for the integration of digital systems in livestock operations to improve biosecurity measures, facilitate real-time data input, and support informed decision-making. By enhancing biosecurity protocols through technology, the livestock industry can better safeguard animal health, increase operational efficiency, and reduce potential economic losses associated with disease outbreaks.

Automatic Enrollment in Patient Portal Systems Mitigates the Digital Divide in Healthcare: An Interrupted Time Series Analysis of an Autoenrollment Workflow Intervention

PURPOSE

Racial and ethnic healthcare disparities require innovative solutions. Patient portals enable online access to health records and clinician communication and are associated with improved health outcomes. Nevertheless, a digital divide in access to such portals persist, especially among people of minoritized race and non-English-speakers. This study assesses the impact of automatic enrollment (autoenrollment) on patient portal activation rates among adult patients at the University of California, San Francisco (UCSF), with a focus on disparities by race, ethnicity, and primary language.

MATERIALS AND METHODS

Starting March 2020, autoenrollment offers for patient portals were sent to UCSF adult patients aged 18 or older via text message. Analysis considered patient portal activation before and after the intervention, examining variations by race, ethnicity, and primary language. Descriptive statistics and an interrupted time series analysis were used to assess the intervention's impact.

RESULTS

Autoenrollment increased patient portal activation rates among all adult patients and patients of minoritized races saw greater increases in activation rates than White patients. While initially not statistically significant, by the end of the surveillance period, we observed statistically significant increases in activation rates in Latinx (3.5-fold, p = < 0.001), Black (3.2-fold, p = 0.003), and Asian (3.1-fold, p = 0.002) patient populations when compared with White patients. Increased activation rates over time in patients with a preferred language other than English (13-fold) were also statistically significant (p = < 0.001) when compared with the increase in English preferred language patients.

CONCLUSION

An organization-based workflow intervention that provided autoenrollment in patient portals via text message was associated with statistically significant mitigation of racial, ethnic, and language-based disparities in patient portal activation rates. Although promising, the autoenrollment intervention did not eliminate disparities in portal enrollment. More work must be done to close the digital divide in access to healthcare technology.

Drowning in emails: investigating email classes and work stressors as antecedents of high email load and implications for well-being

Introduction

High email load has been associated with impaired well-being because emails impose specific demands, disturb the workflow, and thereby overtax individuals' action regulation toward prioritized goals. However, the causes and well-being-related consequences of email load are not yet well understood, as previous studies have neglected the interaction type and function of emails as well as co-occurring stressors as antecedents of high email load and have relied predominantly on cross-sectional designs.

Methods

In two studies, we aimed to clarify the nature of email load through the lens of action regulation theory. The first study, a two-wave investigation with a fortnightly interval, examined the lagged relationships among email load, work stressors, strain, and affective well-being. The sample included 444 individuals across various occupations and organizations, with 196 of them working from home or remotely at least part of the time. In the second cross-sectional study, we surveyed 257 individuals using a convenience sampling approach, 108 of whom worked from home or remotely at least partially. This study focused on evaluating how different email classes-distinguished by email interaction type (received vs. processed) and email function (communication vs. task)-serve as predictors of high email load.

Results

In Study 1, we found a positive lagged effect of high email load on strain, even when controlling for the co-occurring stressors time pressure and work interruptions. In addition, lagged effects of email load on time pressure and interruptions were identified, while no evidence was found for the reverse direction. The results of Study 2 suggest that only the number of communication-related emails received, but not the number of task-related emails received, or the number of all emails processed contribute to high email load.

Conclusion

Findings suggest that email load can be considered a unique stressor and that different classes of email need to be distinguished to understand its nature. Clarifying the sources of email load can help develop effective strategies to address it.

Exploring the determinants of online health service usage intentions under the threat of air pollution

Introduction

The rapid evolution of online health services (OHS) has significantly improved healthcare accessibility. However, the impact of air pollution on individuals' willingness to engage with OHS remains underexplored in the existing literature. This study addresses this gap by investigating how air pollution threats influence the intention to use OHS, grounded in Protection Motivation Theory (PMT) and Rational Choice Theory (RCT).

Methods

Using cross-sectional survey data, a theoretical model was developed and tested to examine the relationships between threat appraisal, coping appraisal, perceived benefits, perceived costs, and OHS usage intentions.

Results

The findings indicate that threat appraisal, coping appraisal, and perceived benefits positively affect the intention to use OHS, while perceived costs negatively impact usage intention. Additionally, age significantly moderates the relationship between coping appraisal and the intention to use OHS.

Discussion

This study extends the application of PMT and RCT in the context of OHS. It provides valuable insights into the factors influencing users' intentions to utilize these services, with implications for improving OHS adoption in environments affected by air pollution.

Patient Burden of Atopic Dermatitis and Opportunities for Real-World Self-Monitoring

Atopic dermatitis (AD) is a complex, chronic disease with multiple negative impacts to patients' health, lives, and overall well-being. The lived experience of AD is multidimensional, heterogeneous, and ever-changing, yet an essential contributor to a holistic understanding of disease burden. Real-world self-monitoring of disease burden by patients has potential as a valuable adjunct to clinical and patient-reported assessments in health care settings. Newer digital tools are available to support these activities, providing opportunity for patients and health care providers to identify aspects of self-monitoring that can best support AD care and management goals, treatment outcomes, and minimize patient burden.

The role of Contact-Tracing Mobile Apps in pandemic prevention: A multidisciplinary perspective on health beliefs, social, and technological factors

During the recent COVID-19 pandemic, governments implemented mobile applications for contact tracing as a rapid and effective solution to mitigate the spread of the virus. However, these seemingly straightforward solutions did not achieve their intended objectives. In line with previous research, this paper aims to investigate the factors that influence the acceptance and usage of contact-tracing mobile apps (CTMAs) in the context of disease control. The research model in this paper integrates the Unified Theory of Acceptance and Use of Technology and the Health Belief Model (HBM). The present study involved a diverse sample of 770 French participants of all genders, ages, occupations, and regions. Critical elements from the Health Belief Model, technological factors related to the app, and social factors, including the centrality of religiosity, were assessed using well-established measurement scales. The research's findings demonstrate that several factors, such as perceived benefits and perceived severity, social influence, health motivation, and centrality of religiosity, significantly impact the intention to use a CTMA. These findings suggest that CTMAs hold promise as valuable tools for managing future epidemics. However, addressing challenges, revising implementation strategies, and potentially collaborating with specialized industry partners under regulatory frameworks are crucial. This practical insight can guide policymakers and public health officials in their decision-making.

Emotional exhaustion weakens the relationship between social media use and knowledge sharing behavior

PURPOSE

Knowledge sharing behavior is crucial for ensuring organizational success, fueling innovation, solving problems, and informing decision-making. While social media platforms offer powerful tools for employees to share knowledge, the intricate relationship between social media use and knowledge sharing behavior remains unclear. Few studies have examined the influencing mechanisms of emotional exhaustion on the above relationships, especially through self-determination perspective.

DESIGN/METHODOLOGY/APPROACH

As knowledge is inherently private to the individual, grounded in self-determination theory, this study employed a moderated mediation analysis to explore the internal mechanisms of social media use on employee knowledge sharing behavior. The survey of 356 full-time employees was collected from a large environmental protection group in China. Hypotheses are tested using hierarchical regression analysis and bootstrap tests.

FINDINGS

The results show that social media use positively affects employee knowledge sharing behavior; knowledge sharing intention partially positively mediates the influence of social media use on knowledge sharing behavior; emotional exhaustion negatively moderates the relationship between social media use and knowledge sharing intention.

CONTRIBUTION OF RESEARCH

The study identifies how two styles of social media use - work-related purpose and social-related purpose - affect knowledge sharing behavior. It significantly advances the understanding of social media use on knowledge sharing behavior from self-determination perspective.

PRACTICAL IMPLICATIONS

This study has several important practical implications for organizations seeking to facilitate employee knowledge sharing behavior through social media use. Organizations should improve employees' knowledge sharing intention and avoid emotional exhaustion.

Exploring the determinants of patients' continuance intentions in online health communities from the network effects perspective

Objectives: Online health communities (OHCs) facilitate patient-physician interaction and the adoption of online health services. However, few studies explored the impact of network effects on patients' continuance intentions in OHCs. This study aims to explore the determinants affecting OHC patients' continuance intentions based on the network effects theory and expectation confirmation model (ECM). Methods: An integrated research model and relative hypotheses are proposed. A total of 420 valid responses are collected through an online questionnaire survey to test the research framework using structural equation modeling. Results: The results reveal that direct network effect, cross network effect, and indirect network effect all positively affect perceived ease of use, and the latter two also positively affect perceived usefulness that further affect continuance intention. In addition, other results are consistent with the ECM-based hypotheses and the positive impact of perceived e-health literacy on continuance intention is also explained. Conclusion: Patients' continuance intention to use OHCs can be improved by network effects through direct, cross, and indirect formats. ECM-based determinants, including confirmation, perceived usefulness, and satisfaction, provide valuable insights for OHC patients' continuous use. Enhancing e-health literacy helps maintain patients' intention to continue using OHCs.

Postgraduate students' perception of plagiarism, awareness, and use of Turnitin text-matching software

Plagiarism is a highly discussed issue in higher education institutions in recent times. Turnitin text-matching software has widely been adopted by many academic institutions in Ghana as one of the solutions to improving students' and faculty academic writing and a solution for detecting incidences of plagiarism. There has been little empirical research into what students actually know about plagiarism and their lived experiences of text-matching technology, despite the fact that a lot of research has looked at attitudes, motivations, and demographic characteristics related to academic dishonesty. This study used an online Google form for data collection. We enrolled 1054 postgraduate students of the University of Cape Coast. The data collected was analyzed using SPSS version 21.0, and the proposed hypothesis was tested using Structural Equation Modeling. Findings show that there was no statistically significant relationship between postgraduate students' academic levels and their perception of plagiarism. However, there is significant relationship between postgraduate students' perception of plagiarism and their use of Turnitin. There is also statistically significant relationship between postgraduate students' awareness of Turnitin and its use. This calls for increased awareness creation and sensitization, which can be accomplished through scientific writing workshops, focused on inculcating ethical research practices into students.

Do spirituality and emotional intelligence improve the perception of the ability to provide care at the end of life? The role of knowledge and self-efficacy

OBJECTIVES

Spirituality, emotional intelligence, and palliative care (PC) knowledge have a positive and direct influence on self-efficacy and on perception of preparation and ability to provide end-of-life (EOL) care. The aim of this work is to propose a conceptual model that relates spirituality, emotional intelligence, PC knowledge, self-efficacy, and the preparation and ability to provide EOL care by doctors and nurses.

METHODS

Quantitative, exploratory, descriptive, and inferential study applied to doctors and nurses in a hospital in the north of Portugal, between May and July 2022. The data collection instrument includes a questionnaire. The relationships between latent variables were evaluated using structural equation models by the partial least squares method using the Smart PLS 3.0 software. It was obtained the previous authorization of the ethics committee.

RESULTS

The results (n = 380) indicate that self-efficacy, spirituality, and PC knowledge have a positive influence on the ability to provide EOL care. Emotional intelligence and spirituality have a direct and positive effect on self-efficacy. There is no direct influence of emotional intelligence on the ability to provide EOL care, but emotional intelligence has an indirect effect mediated by self-efficacy.

SIGNIFICANCE OF RESULTS

Spirituality, self-efficacy, and emotional intelligence are very important for the ability of doctors and nurses to provide EOL care. The identification of predictive factors of the ability to provide EOL care and the determination of the relationship between them can improve the provision of EOL care, reduction of health costs, timely and early referral of people to PC, and increase life quality.

Multi-task learning with multi-gate mixture of transformer-based experts for predictive process monitoring in manufacturing

Manufacturing industries involve both business processes and complex manufacturing processes. Predictive process monitoring techniques are effective for managing process executions by making multi-perspective real-time predictions, preventing issues such as delivery delays. Conventional predictive process monitoring for business processes focuses on predicting the next activity, next event time, and remaining time using single-task learning, which is costly and complex. For complex manufacturing processes, predictive process monitoring primarily aims to predict the remaining time, that is, product cycle time. However, single-task learning methods fail to capture all the variations within the historical process executions. To address them, we propose the multi-gate mixture of transformer-based experts framework, which leverages a transformer network within the multi-gate mixture-of-experts multi-task learning architecture to extract sequential features and employs gated expert networks to model task commonalities and differences. Empirical results demonstrate that multi-gate mixture of transformer-based experts outperforms three alternative architectures across five real-life event logs, highlighting its generalization, effectiveness, and efficiency in predictive process monitoring.

The Safe Environment for Every Kid Model in the Swedish Child Health Services: Adoption and Introduction in a Healthcare Region

BACKGROUND

Early support for children and families in need can improve children's health and development. In a Swedish region, a new working model called Safe Environment for Every Kid (SEEK) was introduced in the Child Health Services to facilitate the early identification of psychosocial risk factors.

OBJECTIVE

The aim of this study was to describe the adoption and introduction of the SEEK model in the Child Health Services of Region Jönköping County.

METHODS

Quantitative data were analysed using descriptive statistics, whereas qualitative data were analysed separately by a thematic approach. The results were then interpreted together with documents (including CHS management meeting notes and documents describing planning and training sessions) using an exploratory mixed-methods approach to give a comprehensive description of the adoption and introduction of the SEEK model.

RESULTS

The results show that the SEEK model improved coordination and collaboration, which led to better integrated care for children and families. The structure was regarded as supportive when introducing the SEEK model in Child Health Services. The questionnaire, as part of the SEEK model, was used in 88% of possible health visits. The most reported reason for not using it was a lack of time.

CONCLUSIONS

The desire to make a difference and thereby promote better health and development for children was a crucial factor for the nurses in adopting the SEEK model in their clinical practice. The design using coaches was also appreciated and supported the adoption and introduction of the SEEK model.

PATIENT OR PUBLIC CONTRIBUTION

Parents and healthcare professionals did not contribute to the research process. The results are based on dialogues between CHS nurses and parents after the parents filled in the SEEK questionnaire, providing an understanding of professional relationships when dealing with challenging issues.

Hybrid Teamwork: What We Know and Where We Can Go From Here

Hybrid teamwork, which describes any combination of one's work time spent across organizational and other (typically domestic) work settings, has become a critical aspect of modern work environments. However, despite the rising prevalence and technological support for hybrid teamwork, there is limited understanding of its impact at the team level. Although we still lack research that addresses the dynamic geographic configurations inherent to hybrid teamwork, we believe that much of the extant literature on virtual teamwork can inform our understanding and guide future research. Accordingly, this paper aims to advance knowledge on hybrid teamwork by defining its unique characteristics and critically reviewing three broad classes of theory from the virtual teams literature and their implications for understanding hybrid teamwork. Based on both contributions and limitations of these three theory classes, we conclude this paper by mapping out pressing questions to guide future research.

The Googling Effect on patient co-creation in physiotherapy service exchange

We study the process of value co-creation in physiotherapist-patient relationships and the underlying mechanisms of this process. We present the Googling Effect Model outlining the relationship between patients' pre-encounter online information search and their commitment to compliance in physiotherapy service exchange. We tested the model on a sample of physiotherapy service patients (n = 446) in the United States. We analyzed the collected responses using the partial least squares method, using SmartPLS 4.0. Our study contributes to the existing body of knowledge in several ways. We developed and tested the Googling Effect Model. Doing so adds to the healthcare literature on value co-creation in physiotherapy. The Googling Effect Model increases the predictive value of the Service-Dominant Logic as it outlines the mechanism underlying value co-creation in healthcare, including the role and importance of pre-encounter online information search in collaborative healthcare. Moreover, the findings illustrate how the underlying mechanism through which pre-encounter online information search affects commitment to compliance differs between men and women and different ethnic groups. These findings can be used to create an environment that increases service engagement and commitment to compliance by accounting for patients' gender and ethnicity.

How are companies going to business digitalization? An explanation based on the implementation of e-commerce with data of SMEs

The data presented in this article is based on a questionnaire survey regarding e-commerce and business digitalization of SMEs in Mexico answered by the CEOs of the companies. A valid sample of 4121 Mexican SMEs was collected covering many industries, such as primary sector, extractive industries, manufacturing industries, energy, water, recycling, construction, trade, services, and others. The data includes information about the implementation of e-commerce, business digitalization, operational efficiency, corporate performance, and other demographic indicators of the sampling firms. The link between e-commerce and corporate performance is still underexplored in SMEs, even more so between companies from Latin America, being Mexico a perfect example to explore how different SMEs adapt and thrive due to the rapid growth of their e-commerce and the diversity of their business sectors (Santos-Jaén et al., 2023 [2]). Data analysis was conducted using SPSS and Smart PLS. The data are useful as the data can be reproduced, reused and reanalyzed paying special attention to group-specific effects. This data article also opens up better research opportunities going forward through collaboration with other researchers.

Cultural values and digital gap: Overview of behavioral patterns

The study uses different statistical techniques to understand the relationship between variables explaining the digital divide and classification based on The Inglehart-Welzel Cultural Map for 2023. To achieve this purpose variables focusing on Digital Penetration (the percentage of internet and social media users and mobile cellular connections), Operating Systems share (iOS and Android), Device Traffic (laptop/mobile phone-based web traffic) as well as Mobile Commerce variables (bills and payments using mobile internet) were included in the analysis. To minimize any effects arithmetic means of data was calculated.: The results from one-way ANOVA tests indicate significant differences among groups classified by cultural values for almost all measured variables of digitalization. The mean squares and F-values across variables like cellular mobile connections, internet users, and active social media users are significant indicating a shift towards more secular and self-expressive cultural values. The results of the GLM procedure show that significant portions of the total variance in digitalization variables are associated with membership in groups based on the cultural map. This suggests that cultural classifications can explain substantial differences in digital behavior and preferences across populations. Spearman's correlation coefficients showed strong positive correlations between Traditional/Secular values and several digitalization metrics, such as the use of mobile phones or the internet for payments, and negative correlations with others like share of web traffic by device type (mobile vs. laptop/computer). These correlations suggest that cultural values play a substantial role in influencing digital habits and accessibility.

Analysing the public's beliefs, emotions and sentiments towards Metaverse workplace: A big-data qualitative inquiry

The Metaverse is gaining attention as a potential future workplace, and advancements in VR/AR technologies are set to revolutionise how we work and collaborate. Extensive research using big data is still needed to fully comprehend the public's perception of this emerging field. Grounded in the Technology Acceptance Model (TAM), the Diffusion of Innovations Theory (DIT), and Social Presence Theory (SPT), this study seeks to fill this knowledge gap. Using a methodology that involved machine learning and qualitative analysis of big data, the research gathered comments from social media users on widely viewed YouTube videos discussing the Metaverse workplace. The initial dataset, which contained 6982 comments, underwent thorough cleaning processes, resulting in the analysis of 2804 comments through thematic, emotion, and sentiment analyses. The process of the thematic analysis revealed that out of the total comments, 472 were unclassified, while the remaining 2332 helped structure the public's beliefs about the Metaverse workplace into four overarching themes: 1- benefits of flexibility and accessibility (37 %), highlighting VR's potential to transform workspaces, especially for creative fields and efficient space use; 2- Health concerns (26 %), including eye strain and physical discomfort from prolonged headset use; 3- data privacy and corporate control fears (20 %), reflecting worries over pervasive data collection and potential misuse of power; 4- scepticism over readiness and practicality (17 %), noting visual clarity challenges and ergonomic issues. The overall vibes about working in the Metaverse are mixed. While more than half the sentiments were positive, expressing contentment, curiosity and enthusiasm, there were also concerns about health effects, data privacy, and integration issues. The public recognises Metaverse's potential for remote work, desiring improvements in areas like visual clarity, ergonomics and productivity support before widespread adoption. This study is a pioneering effort in the field, providing a first-of-its-kind structure of the public's beliefs about the Metaverse workplace, drawing upon naturally occurring data. The findings not only contribute to the academic understanding of the Metaverse workplace but also have significant implications for society and practitioners for optimising the positive aspects to enhance overall acceptance in this relatively understudied field.

Enhancing the energy level of regional digital innovation ecosystems: A configuration perspective

This study introduces the concept of "energy level" into the analysis of innovation ecosystems. Drawing on the theory of "architects", we have identified the key architects of regional digital innovation ecosystems. By integrating Necessary Condition Analysis (NCA) and Fuzzy-set Qualitative Comparative Analysis (fsQCA), we examined the configuration effects of internal architects, external architects, and digital innovation habitats on the energy level of these ecosystems, utilizing data from 30 provinces in China as case studies. The results indicate that the contribution of a single architect to achieving a high energy level in a regional digital innovation ecosystem is limited and cannot be regarded as a necessary condition for driving a high energy level. However, core innovation actors and digital infrastructures emerge as more significant core conditions. The architects of regional digital innovation ecosystems exhibit multiple concurrent causal relationships. The configuration paths of high and non-high energy levels of ecosystems display a causally asymmetric "multiple paths to the same outcome" relationship. The three identified paths for driving high energy levels are categorized as "core actor-infrastructure"-driven paths. The findings of this paper hold substantial theoretical and practical significance for fostering the healthy development of regional digital innovation ecosystems.

Harnessing the Power of Complementarity Between Smart Tracking Technology and Associated Health Information Technologies: Longitudinal Study

BACKGROUND

Smart tracking technology (STT) that was applied for clinical use has the potential to reduce 30-day all-cause readmission risk through streamlining clinical workflows with improved accuracy, mobility, and efficiency. However, previously published literature has inadequately addressed the joint effects of STT for clinical use and its complementary health ITs (HITs) in this context. Furthermore, while previous studies have discussed the symbiotic and pooled complementarity effects among different HITs, there is a lack of evidence-based research specifically examining the complementarity effects between STT for clinical use and other relevant HITs.

OBJECTIVE

Through a complementarity theory lens, this study aims to examine the joint effects of STT for clinical use and 3 relevant HITs on 30-day all-cause readmission risk. These HITs are STT for supply chain management, mobile IT, and health information exchange (HIE). Specifically, this study examines whether the pooled complementarity effect exists between STT for clinical use and STT for supply chain management, and whether symbiotic complementarity effects exist between STT for clinical use and mobile IT and between STT for clinical use and HIE.

METHODS

This study uses a longitudinal in-patient dataset, including 879,122 in-patient hospital admissions for 347,949 patients in 61 hospitals located in Florida and New York in the United States, from 2014 to 2015. Logistic regression was applied to assess the effect of HITs on readmission risks. Time and hospital fixed effects were controlled in the regression model. Robust standard errors (SEs) were used to account for potential heteroskedasticity. These errors were further clustered at the patient level to consider possible correlations within the patient groups.

RESULTS

The interaction between STT for clinical use and STT for supply chain management, mobile IT, and HIE was negatively associated with 30-day readmission risk, with coefficients of -0.0352 (P=.003), -0.0520 (P<.001), and -0.0216 (P=.04), respectively. These results indicate that the pooled complementarity effect exists between STT for clinical use and STT for supply chain management, and symbiotic complementarity effects exist between STT for clinical use and mobile IT and between STT for clinical use and HIE. Furthermore, the joint effects of these HITs varied depending on the hospital affiliation and patients' disease types.

CONCLUSIONS

Our results reveal that while individual HIT implementations have varying impacts on 30-day readmission risk, their joint effects are often associated with a reduction in 30-day readmission risk. This study substantially contributes to HIT value literature by quantifying the complementarity effects among 4 different types of HITs: STT for clinical use, STT for supply chain management, mobile IT, and HIE. It further offers practical implications for hospitals to maximize the benefits of their complementary HITs in reducing the 30-day readmission risk in their respective care scenarios.

Hospital Unit Type and Professional Roles as a Predictor of Relational Coordination in an Army Medical Center

BACKGROUND AND OBJECTIVES

High-quality communication and relationships are associated with quality of care. Workflow differences across hospital units can impede communication and relationships among health care professionals. Relational coordination (RC) is a process of communication supported by shared goals, shared knowledge, and mutual respect and is associated with quality of care and better performance outcomes in civilian hospitals. However, RC has not been explored in military hospitals. The objective of our study was to determine whether RC differs between hospital units and professional roles. Specifically, we examined RC differences by unit type for nurses, resident physicians, and physicians working in an Army Medical Center.

METHODS

We conducted an exploratory analysis of a secondary question from a cross-sectional study using a convenience sample of active-duty and civilian licensed practical nurses (LPNs), registered nurses (RNs), physician residents, and physicians (n = 289). We received institutional review board approval from the study site. Data were collected from January 2020 to March 2020, and participants completed a 47-item survey regarding their experiences of RC in various hospital units. We used t tests and one-way analyses of variance to explore bivariate relationships between RC and other study variables, as well as multiple regression to explore whether RC varied by unit type. We controlled for education and experience by including them in the model because these variables may influence perceptions of nurse-physician RC and their interactions with each other.

RESULTS

Seventy percent of participants were civilian (n = 203), 75% RNs (n = 217), and 78% female (n = 216). The mean age of respondents was 40 years (SD = 11.7), and the mean experience level was 11.9 years (SD = 9.5). RC was not associated with unit type. Total RC and between-role RC were associated with professional role. Physicians reported higher RC (β = .45, P = .01), and LPNs reported lower RC (β = -.06, P = .01). Education and experience were associated with RC. Participants with less experience reported higher RC (β = -.01, P = .00), and participants with graduate degrees reported lower RC (β = -.62, P = .00).

CONCLUSIONS

We recommend hospital leaders consider interventions to build interprofessional relationships, including interdisciplinary meetings, huddles, and structured communication tools. Improving RC among health care professionals is a cost-effective and unique way to enhance communication and collaboration among health care professionals across hospital units.

Technostress in Nuclear Medicine: A Qualitative Study of Causes, Mitigators, and Resolution Levels

BACKGROUND

In contemporary healthcare, information and communication technology enables specialized treatment and efficient information sharing. However, it also causes stress and frustration, so-called technostress, among healthcare staff.

PURPOSE

To investigate the day-to-day occurrence of technostress, we ask the research question: What causes the stressful situations with technology, how are they mitigated, and to what extent are they resolved?

METHOD

We interviewed 15 healthcare providers in the department of nuclear medicine at a Danish hospital about their experiences with technology-induced stress in their daily work.

RESULTS

The interviewees described 185 stressful situations with technology, mostly technology indispensable to their work. The two most frequent causes of stressful situations are system performance (46%) and technology-related organizational procedures (18%). To mitigate the situations, the most frequent strategies are accommodating (51%), consulting others for help (18%), and repeating previous task steps (13%). The mitigation strategies indicate that the stressful situations involve adapting work practices to the technology to a much larger extent than succeeding in adapting the technology to the work. Regarding the level of resolution, as much as 66% of the stressful situations are merely solved for now, that is, the concrete situation is resolved but the underlying issue remains unsolved. The underlying issue is resolved in only 10% of the situations, thereby indicating that the vast majority of the stressful situations are likely to recur later.

CONCLUSION

The staff at the studied hospital department repeatedly experience stressful situations with the technology they rely on in their work. This technostress is an extra stressor on top of those induced by the staff's responsibility for providing quality patient treatment. At the individual level, technostress leads to frustration and possibly burnout; at the organizational level, it calls for preventive action.

Exploring user usability perceptions and acceptance of chording-enabled keyboards: A perspective between human-computer interaction

In recent years, a variety of alternative keyboard designs have emerged with the primary goal of enhancing user comfort and productivity compared to conventional keyboards. The objective of this study was to determine the variables affecting the acceptance and perceptions of people towards chording-enabled keyboards. A holistic analysis was done with the use of an extended framework of unified theory of acceptance and use of technology (UTAUT2), analyzed through partial least square structural equation modeling. Gathering a total of 430 valid respondent through purposive sampling, perceived usability, behavioral intention, usage behavior, habit, performance expectancy, social influence, and hedonic motivation were seen to be important factors in adopting chord-enabled keyboards. From the output, it was posited that the attributes of the keyboards' functionality, ease of use, adaptability, and people's willingness to use it, significantly affected their intention of using the keyboard. The findings and suggestions included in this study will benefit not only users but also the developers by providing insights into user preferences. Efficiently improving and marketing chording enabled keyboards could be considered as suggested in the implications. Moreover, the study's model construct could also be utilized in other studies related to user acceptance of technology in different countries.

Use of research evidence in U.S. federal policymaking: A reflexive report on intra-stage mixed methods

The policymaking process is largely opaque, especially regarding the actual writing of the policy. To attempt to better understand this complex process, we utilized mixed methods in our evaluation of an intervention. However, the process of mixing methods can be messy, and thus may require recalibration during the evaluation itself. Yet, in comparison to reporting results, relatively little attention is paid to the effects of mixing methods on the evaluation process. In this article, we take a reflexive approach to reporting a mixed methods evaluation of an intervention on the use of research evidence in U.S. federal policymaking. We focus on the research process in a qualitative coding team, and the effects of mixing methods on that process. Additionally, we report in general terms how to interpret multinomial logistic regressions, an underused analysis type applicable to many evaluations. Thus, this reflexive piece contributes (1) findings from evaluation of the intervention on the policymaking process, (2) an example of mixing methods leading to unexpected findings and future directions, (3) a report about the evaluation process itself, and (4) a tutorial for those new to multinomial logistic regressions.

'Without support CALD patients will be left behind': A mixed-methods exploration of culturally and linguistically diverse (CALD) client perspectives of telehealth and those of their healthcare providers

INTRODUCTION

The rapid adoption of telehealth during the global pandemic has the potential to widen disparities for culturally and linguistically diverse (CALD) consumers. We explored the perspectives and experiences of CALD consumers accessing telehealth during the global pandemic and those of their healthcare providers.

METHODS

A multistakeholder mixed-methods study involving two parallel samples comprising consumer-participants (n = 56) and healthcare provider-participants (n = 81). Multicultural consumer-participants, recruited from consecutive referrals to Health Language Services for telehealth support, were assisted to complete two surveys (before and after their clinical telehealth appointment) in their preferred language. A purposive sample of consumer-participants was interviewed to understand their perceived barriers and enablers of successful telehealth consultations. Simultaneously, all healthcare providers within the local health district were eligible to participate in an online survey if they had provided telehealth care to a consumer during the recruitment period. Closed-ended responses were descriptively summarised, while open-ended responses and interview transcripts were analysed thematically.

RESULTS

Despite 86% of consumer-participants inexperienced with telehealth, 80% achieved a successful appointment with a healthcare provider. Consumer perceptions were shaped by cultural and diagnostic concepts of legitimacy, in the context of known accessibility and technology literacy challenges. Healthcare provider perspectives were less favourable towards telehealth, with equity of healthcare delivery a major concern.

DISCUSSION

Our findings highlight unintended consequences arising from a rapid transition to telehealth. Adopting collaborative approaches to the design and implementation of telehealth is imperative to mitigate health inequities faced by CALD communities and maximise their opportunity to realise potential health benefits associated with telehealth.

Strengths, weaknesses, opportunities, and threats (SWOT) of the electronic prescribing systems executed in Iran from the physician's viewpoint: a qualitative study

BACKGROUND

Electronic prescribing (e-prescribing) is an essential technology in the modern health system. This technology has made many changes in the prescription process, which have advantages and disadvantages and have created opportunities for transforming the health system. This study aimed to investigate the strengths, weaknesses, opportunities, and threats of the e-prescribing system implemented in Iran from the physician's viewpoint.

METHODS

This phenomenological qualitative study was conducted in 2022. The participants were 15 Iranian specialist physicians working at Urmia University of Medical Sciences, selected purposively and deliberately. Data was collected through in-depth semi-structured interviews using an interview guide comprising 16 questions. Interviews were conducted until data saturation was reached. The audio data was transcribed into text and analyzed using the thematic analysis. To ensure the validity and reliability of the findings, the criteria introduced by Lincoln and Guba were employed.

RESULTS

The results of this study showed that the e-prescribing system executed in Iran has diverse and multidimensional strengths, weaknesses, opportunities, and threats. In the strengths section, the analysis of the interviews led to the extraction of semantic units in the categories of prescription process, prescriber, patient, technical, economic, communication, and insurance. Also, the weaknesses in the three categories of the prescriber, patient, and technical were debatable. The opportunities extracted from the narratives of the interviewees were placed in four categories including technical, national macro policies, Ministry of Health macro-policies, and socio-cultural issues. Finally, the discussed threats are classified into two technical and macro policies of the Ministry of Health categories. On the other hand, technical issues played an effective role in all aspects of the SWOT model.

CONCLUSION

The e-prescribing system in Iran has strengths, weaknesses, opportunities, and threats. An overarching factor across all aspects of the SWOT model was technical infrastructure. A robust technical infrastructure is considered a strength and an opportunity for the growth of the electronic prescribing system in Iran. Conversely, any shortcomings in these systems are viewed as weaknesses and pose a threat to the system's sustainability.

The dark side of enterprise social media and employee digital creativity: Communication visibility perspective

The primary objective of this study is to evaluate the significances of excessive usage of enterprise social media (ESM) on individuals' digital creativity through ESM exhaustion. In addition, we intend to investigate the significance of ESM visibility as a moderator in the connection between excessive usage of ESM, ESM exhaustion, and digital creativity. The results presented in this study are derived from primary data collected from 718 Chinese workers who utilize ESM. The data analysis were conducted using SPSS version 23.0. Findings revealed that excessive usage of ESM is negatively linked to employee digital creativity and has a significant impact on ESM exhaustion. ESM exhaustion is negatively related to employee digital creativity. ESM visibility is further found to play a significant moderating role in strengthening the connection between excessive use of ESM and ESM exhaustion. Additionally, ESM visibility reinforces the negative association between excessive use of ESM and employee digital creativity. This study encompasses ESM users' perceptions of the connection between excessive ESM usage and its exhaustion, providing evidence for organizations to develop and manage ESM usage policies to mitigate the negative impact of ESM usage for employees.

Low-carbon information quality dimensions and random forest algorithm evaluation model in digital marketing

The growing urgency for low-carbon lifestyles necessitates developing effective strategies to promote sustainable consumer choices. This study investigates key dimensions of information quality that shape consumer behavior within digital marketing to achieve this goal. Employing a mixed-methods approach that integrates grounded theory and machine learning, this study identifies three core dimensions of low-carbon information quality: matching quality, presentation quality, and interpretability quality. These dimensions underscore the importance of aligning information with consumer needs, ensuring clear and accurate presentation, and fostering transparency for trustworthiness. A Random Forest algorithm-based evaluation model is constructed to assess low-carbon information quality, demonstrating its effectiveness in identifying high-quality, sustainable content. This research provides a practical tool for digital marketers to enhance their strategies, raise consumer awareness of sustainable options, and ultimately contribute to the growth of the low-carbon consumption market.

Continuous adoption of online healthcare platforms: an extension to the expectation confirmation model and network externalities

BACKGROUND

Online healthcare platforms (OHPs) promote the accessibility of health services while integrating online and offline service delivery. Continuous adoption of these platforms can reduce the information asymmetry between patients and healthcare providers. However, existing study has rarely focused on how the network externalities of these platforms influence patients' continuous adoption. Expectation Confirmation Model (ECM) explains the continuous behavior after initial adoption and reveal the factors influencing satisfaction and continuous adoption intention. Few studies have integrated network externalities with the ECM to understand patients' continuous adoption of OHPs.

OBJECTIVE

This study aims to explore what factors affect the continuous adoption of OHPs based on an extension to the ECM and network externalities. We propose a comprehensive model for the continuous adoption of OHPs by patients with chronic diseases. We extend the conceptual framework by incorporating constructs related to perceived value, habits, and switching costs.

METHODS

This study utilized a web-based survey to collect data from participants in China. We selected a sample of individuals who had experience with OHPs using a random sampling method. This method ensured that participants was randomly chosen from a pool of patients without any regional bias. A total of 568 questionnaires were collected and 518 valid questionnaires were obtained. Structural equation modeling was applied to assess the relationships among the constructs. Hierarchical regression analysis was utilized to examine the moderating effects, while the mediating effects were investigated using the bootstrapping approach.

RESULTS

Direct network externality had significant positive impacts on the confirmation (β = 0.232, p < 0.001) and perceived value (β = 0.167, p < 0.010). Cross network externality had significant positive impacts on confirmation (β = 0.307, p < 0.001) and perceived value (β = 0.120, p < 0.05). Indirect network externality had significant positive impacts on confirmation (β = 0.169, p < 0.010) and perceived value (β = 0.270, p < 0.001). Confirmation had a significant positive impact on perceived value (β = 0.205, p < 0.001) and satisfaction (β = 0.508, p < 0.001). In addition, satisfaction had a significant positive impact on continuous adoption intention (β = 0.579, p < 0.001). Continuous adoption intention had a significant positive impact on continuous adoption behavior (β = 0.547, p < 0.001). Confirmation and perceived value significantly mediate the relationship between network externalities and satisfaction. Moreover, both confirmation and perceived value enhance continuous adoption intention by positively influencing satisfaction, which serves as a mediator. Additionally, confirmation directly influences satisfaction through the mediating role of perceived value. Habits and switching costs positively moderate the relationship between continuous adoption intention and behavior.

CONCLUSIONS

This study contributes by expanding the incorporation of network externalities into the ECM. Results enrich the existing literature on the continuous adoption of professional online platforms.

Designing A Blockchain-Empowered Telehealth Artifact for Decentralized Identity Management and Trustworthy Communication: Interdisciplinary Approach

BACKGROUND

Telehealth played a critical role during the COVID-19 pandemic and continues to function as an essential component of health care. Existing platforms cannot ensure privacy and prevent cyberattacks.

OBJECTIVE

The main objectives of this study are to understand existing cybersecurity issues in identity management and trustworthy communication processes in telehealth platforms and to design a software architecture integrated with blockchain to improve security and trustworthiness with acceptable performance.

METHODS

We improved personal information security in existing telehealth platforms by adopting an innovative interdisciplinary approach combining design science, social science, and computer science in the health care domain, with prototype implementation. We used the design science research methodology to implement our overall design. We innovated over existing telehealth platforms with blockchain integration that improves health care delivery services in terms of security, privacy, and efficiency. We adopted a user-centric design approach and started with user requirement collection, followed by system functionality development. Overall system implementation facilitates user requirements, thus promoting user behavior for the adoption of the telehealth platform with decentralized identity management and an access control mechanism.

RESULTS

Our investigation identified key challenges to identity management and trustworthy communication processes in telehealth platforms used in the current health care domain. By adopting distributed ledger technology, we proposed a decentralized telehealth platform to support identity management and a trustworthy communication process. Our design and prototype implementation using a smart contract-driven telehealth platform to provide decentralized identity management and trustworthy communication with token-based access control addressed several security challenges. This was substantiated by testing with 10,000 simulated transactions across 5 peers in the Rahasak blockchain network. The proposed design provides resistance to common attacks while maintaining a linear time overhead, demonstrating improved security and efficiency in telehealth services. We evaluated the performance in terms of transaction throughput, smart contract execution time, and block generation time. To create a block with 10,000 transactions, it takes 8 seconds on average, which is an acceptable overhead for blockchain-based applications.

CONCLUSIONS

We identified technical limitations in current telehealth platforms. We presented several design innovations using blockchain to prototype a system. We also presented the implementation details of a unique distributed architecture for a trustworthy communication system. We illustrated how this design can overcome privacy, security, and scalability limitations. Moreover, we illustrated how improving these factors sets the stage for improving and standardizing the application and for the wide adoption of blockchain-enabled telehealth platforms.

Algorithmic management and human-centered task design: a conceptual synthesis from the perspective of action regulation and sociomaterial systems theory

This paper aims to explain potential psychological effects of algorithmic management (AM) on human-centered task design and with that also workers' mental well-being. For this, we link research on algorithmic management (AM) with Sociomaterial System Theory and Action Regulation Theory (ART). Our main assumption is that psychological effects of sociomaterial systems, such as AM, can be explained by their impact on human action. From the synthesis of the theories, mixed effects on human-centered task design can be derived: It can be expected that AM contributes to fewer action regulation opportunities (i.e., job resources like job autonomy, transparency, predictability), and to lower intellectual demands (i.e., challenge demands like task complexity, problem solving). Moreover, it can be concluded that AM is related with more regulation problems (i.e., hindrance demands like overtaxing regulations) but also fewer regulation problems (like regulation obstacles, uncertainty). Based on these considerations and in line with the majority of current research, it can be assumed that the use of AM is indirectly associated with higher risks to workers' mental well-being. However, we also identify potential positive effects of AM as some stressful and demotivating obstacles at work are often mitigated. Based on these considerations, the main question of future research is not whether AM is good or bad for workers, but rather how work under AM can be designed to be humane. Our proposed model can guide and support researchers and practitioners in improving the understanding of the next generation of AM systems.

Is AI Food a Gimmick or the Future Direction of Food Production?-Predicting Consumers' Willingness to Buy AI Food Based on Cognitive Trust and Affective Trust

In recent years, artificial intelligence (AI) has been developing rapidly and has had a broad impact on the food industry, with food produced from AI-generated recipes already appearing to actually go on sale. However, people's trust and willingness to purchase AI food are still unclear. This study builds an integrated theoretical model based on cognitive trust and affective trust, taking into account consumers' quality value orientations, social norms, and perceived risks of AI food, with the aim of predicting and exploring consumers' trust and acceptance of AI food. This study utilized the questionnaire method and 315 questionnaires were collected. The results of structural equation modeling (PLS-SEM) indicated that food quality orientation, subjective norms, perceived trust, and affective trust all had a significant positive effect on consumers' purchase intentions. Perceived risk had a negative effect on affective trust and consequently on consumers' purchase intention, but the effect on cognitive trust was not significant. The results also suggest that cognitive trust is the basis of affective trust and that consumer trust and acceptance of AI food can be enhanced by augmenting two antecedents of cognitive trust (food quality orientation and subjective norms). Possible practical implications and insights from the current findings are discussed.