COVID again? Health workers' burnout and turnover intentions: possible impacts of coronavirus-induced anxiety and first-level servant leaders

PURPOSE

Building on social exchange and leader-member exchange theories, this paper aims to propose a model of the impact of coronavirus-induced anxiety on health-care professionals' burnout and turnover intention through the mediation role of servant leadership.

DESIGN/METHODOLOGY/APPROACH

This model was examined by adopting partial least square-based structural equation modeling using data collected from 271 health professionals (doctors, nurses, midwives and analysts) from Turkey.

FINDINGS

The findings of the research illustrate that coronavirus-induced anxiety is positively associated with burnout and turnover intention. Furthermore, servant leadership mediates the relationship between coronavirus-induced anxiety, burnout and turnover intention. Yet, according to factor loadings, the mediating role of servant leadership is not strong (β : 0.035 and 0.053, respectively).

RESEARCH LIMITATIONS/IMPLICATIONS

First, this study targeted the health-care professionals from Turkey. Therefore, this population may not be able to provide general information on the topic. Thus, this study suggests that the subject be addressed in other populations as well. Second, the data were self-reported by the participants. Although common method bias and social desirability bias were not an issue in this study, it should be known that the results are based on the subjective judgments of the participants. Third, this study was limited to investigating the mediating role of servant leadership only.

PRACTICAL IMPLICATIONS

This study gives much beneficial information to both administrators and organizations by mirroring highly stressed workers' inside throughout statistically results. Hence, it is assumed that the findings will help leaders to cope with several difficult situations, especially in crisis moments. As the chaotic circumstances occurred, achieving organizational goals became more and more difficult. To do this, some leaders play critical roles for members like servant leaders by contributing uniquely spiritual dimensions.

SOCIAL IMPLICATIONS

Struggling with the COVID-19 pandemic has aggravated the health-care professionals' existing mental health and has loaded more agitation on them. According to Mozes (2021), suicide cases among nurses have doubled the number of women in the general population. Thus, leaders should do something to lower those ratios. This study points out that servant leaders could break down those unwanted issues by decreasing burnout and turnover intention rates of health workers. Barbuto and Wheeler (2006) highlighted this situation by creating a dimension called "The Natural Desire to Serve Others."

ORIGINALITY/VALUE

To the best of the authors' knowledge, to date, this study is the first to examine the mediating role of servant leadership in the effect of coronavirus-induced anxiety on burnout and turnover intention. Furthermore, this research reveals that servant leadership may play a role in avoiding burnout and turnover intention in the health sector.

Can digital economy foster synergistic increases in green innovation and corporate value? Evidence from China

The rapid evolution of the digital economy has significantly accelerated progress towards achieving green and sustainable processes, particularly in the field of green production. While existing research has delved into the effects of the digital economy on Green Innovation (GI) and the consequences of digital transformation on Corporate Value (CV), there remains a notable gap in the literature regarding the potential for synergistic enhancements in firms' GI&CV through the ongoing digital revolution. This study utilizes an evolutionary game model and employs system dynamics methods to simulate the dynamic evolution trajectory of the influence of the digital economy on the synergy between GI&CV. Subsequently, it empirically assesses the interconnected synergies between GI&CV using a dataset comprising information from Chinese listed firms spanning from 2011 to 2020, examining the impact of the digital economy on these synergies. Moreover, the study delves into the analysis of the transmission mechanism and conducts an extended investigation to further explore this phenomenon. The findings of this paper including: (1) The digital economy acts as a driving force behind the synergistic enhancement of firm GI&CV. Moreover, this effect is further augmented by governmental environmental regulation and green subsidy policies. (2) Drawing upon the information asymmetry theory and the resource-based theory, the regional marketization level and firms' digital transformation play intermediary roles. (3) The heterogeneity test indicate that firms situated in eastern regions and those classified as non-heavily polluted benefitted to a greater extent. This study sheds light on the incentive implications of digital economy for the synergistic upgrading of GI&CV, thereby extending the breadth of study on the consequences of digital economy. Moreover, it offers actionable suggestions for enterprises to leverage digital economy development towards achieving a synergistic improvement of GI&CV.

The indirect impact of the technostress subfactors on the satisfaction and desire to work from home

Introduction

Organizational digitalization is a phenomenon that is becoming more widespread and holistic; that is responsible for more employees being affected by digital work and working from home. While introducing remote work offers numerous economic benefits for organizations, this transition must be aligned with employees' needs rather than in an authoritarian manner. Our research aimed to investigate how sub-factors of technostress, directly and indirectly, influence the satisfaction and desire to work from home.

Methods

We conducted a cross-sectional survey with a sample of 361 office workers with at least two years of experience who have spent some time working from home. We checked our hypotheses with a path model.

Results

Our research found that techno-insecurity and techno-complexity have a minimal direct influence on the desire to work from home. However, the desire to work from home significantly decreases through various mediation pathways via the status sub-factor (which can be seen as one of the latent benefits of remote work) and through satisfaction with working from home. Our model explains 33.7% of the variance in the desire to work from home.

Discussion

This suggests that leaders have a task of great significance: to decrease the technostress employees are exposed to and to draw the attention of researchers to the fact that technostress has more complex indirect effects than previously assumed.

Dynamic modulation of the processing of unpredicted technical errors by the posterior cingulate and the default mode network

The pervasive use of information technologies (IT) has tremendously benefited our daily lives. However, unpredicted technical breakdowns and errors can lead to the experience of stress, which has been termed technostress. It remains poorly understood how people dynamically respond to unpredicted system runtime errors occurring while interacting with the IT systems on a behavioral and neuronal level. To elucidate the mechanisms underlying such processes, we conducted a functional magnetic resonance imaging (fMRI) study in which 15 young adults solved arithmetic problems of three difficulty levels (easy, medium and hard) while two types of system runtime errors (problem errors and feedback errors) occurred in an unexpected manner. The problem error condition consisted of apparently defective displays of the arithmetic problem and the feedback error condition involved erroneous feedback. We found that the problem errors positively influenced participants' problem-solving performance at the high difficulty level (i.e., hard tasks) at the initial stage of the session, while feedback errors disturbed their performance. These dynamic behavioral changes are mainly associated with brain activation changes in the posterior cingulate and the default mode network, including the posterior cingulate cortex, the mPFC, the retrosplenial cortex and the parahippocampal gyrus. Our study illustrates the regulatory role of the posterior cingulate in coping with unpredicted errors as well as with dynamic changes in the environment.

Mitigating Job Burnout in Jordanian Public Healthcare: The Interplay between Ethical Leadership, Organizational Climate, and Role Overload

In today's dynamic organizational landscape, characterized by rapid technological advancements and evolving workplace dynamics, understanding the factors influencing employee well-being is paramount. This study investigates the interplay between ethical leadership, organizational climate, role overload, and job burnout in public healthcare organizations across northern Jordan. By focusing on ethical leadership, organizational climate, and role overload as determinants of job burnout, this research provides insights into strategies for enhancing employee well-being. Drawing on ethical leadership theory, social exchange theory, and the job demands-resources model, this study employs PLS-SEM to analyze data collected from 260 employees working in Jordanian government hospitals. The findings reveal negative associations between ethical leadership and job burnout, highlighting the importance of ethical leadership behaviors in mitigating employee burnout. Additionally, a positive organizational climate is associated with lower levels of burnout, underscoring the impact of the broader organizational context on employee well-being. The study also explores the mediating role of organizational climate and the moderating effect of role overload in the relationship between ethical leadership and job burnout, providing insights into the complex dynamics at play in healthcare organizations. These findings enrich our understanding of the factors influencing employee well-being in healthcare contexts and underscore the importance of fostering ethical leadership and supportive organizational climates to mitigate job burnout.

How good are large language models at product risk assessment?

Product safety professionals must assess the risks to consumers associated with the foreseeable uses and misuses of products. In this study, we investigate the utility of generative artificial intelligence (AI), specifically large language models (LLMs) such as ChatGPT, across a number of tasks involved in the product risk assessment process. For a set of six consumer products, prompts were developed related to failure mode identification, the construction and population of a failure mode and effects analysis (FMEA) table, risk mitigation identification, and guidance to product designers, users, and regulators. These prompts were input into ChatGPT and the outputs were recorded. A survey was administered to product safety professionals to ascertain the quality of the outputs. We found that ChatGPT generally performed better at divergent thinking tasks such as brainstorming potential failure modes and risk mitigations. However, there were errors and inconsistencies in some of the results, and the guidance provided was perceived as overly generic, occasionally outlandish, and not reflective of the depth of knowledge held by a subject matter expert. When tested against a sample of other LLMs, similar patterns in strengths and weaknesses were demonstrated. Despite these challenges, a role for LLMs may still exist in product risk assessment to assist in ideation, while experts may shift their focus to critical review of AI-generated content.

Foreign executives, digital transformation, and innovation performance: Evidence from Chinese-listed firms

This study investigates the effect of foreign executives on firms' innovation performance and the mediation role of digital transformation in Chinese-listed firms from 2011 to 2021. Our findings indicate that the presence of foreign executives in top management teams promotes firms' innovation performance by enhancing digital transformation. Further analyses show that foreign executives contribute significantly to improving firms' radical innovation performance rather than incremental innovation performance. We also examine the moderating effect of negative performance feedback and financing constraints between foreign executives and innovation performance, finding that foreign executives can promote innovation performance particularly in firms with negative performance feedback and weak financing constraints.

Heterogeneous peer effects of college roommates on academic performance

Understanding how student peers influence learning outcomes is crucial for effective education management in complex social systems. The complexities of peer selection and evolving peer relationships, however, pose challenges for identifying peer effects using static observational data. Here we use both null-model and regression approaches to examine peer effects using longitudinal data from 5,272 undergraduates, where roommate assignments are plausibly random upon enrollment and roommate relationships persist until graduation. Specifically, we construct a roommate null model by randomly shuffling students among dorm rooms and introduce an assimilation metric to quantify similarities in roommate academic performance. We find significantly larger assimilation in actual data than in the roommate null model, suggesting roommate peer effects, whereby roommates have more similar performance than expected by chance alone. Moreover, assimilation exhibits an overall increasing trend over time, suggesting that peer effects become stronger the longer roommates live together. Our regression analysis further reveals the moderating role of peer heterogeneity. In particular, when roommates perform similarly, the positive relationship between a student's future performance and their roommates' average prior performance is more pronounced, and their ordinal rank in the dorm room has an independent effect. Our findings contribute to understanding the role of college roommates in influencing student academic performance.

Integrating the ESM usage and work engagement for employee agility performance: based on regulatory focus theory

This present research aims to clarify the intricate conjunction of enterprise social media (ESM) utilization and employee agility with a main focus on uncovering the underlying mechanisms that work through the mediating influence of work engagement and the moderating influence of regulatory focus. Drawing upon regularity focus theory, 353 Chinese samples of ESM users in organizational contexts are analyzed using SPSS 23.0. The empirical findings substantiate a robust and significant positive linkage between ESM usage and worker agility. Further reinforcing the model, the mediating role of work engagement is established as it channels the impact of ESM usage on worker agility. Turning to the moderating effects, the study unveils the differential impact of prevention focus and promotion focus, wherein individuals with a lower prevention focus exhibit a more pronounced positive linkage between ESM usage and worker agility. Similarly, individuals with a higher promotion focus demonstrate a heightened positive association between ESM usage and worker agility. By comprehensively inspecting the intricate dynamics of ESM usage, work engagement, and regulatory focus, this study enhances our theoretical understanding of how these factors synergistically shape employee agility, ultimately furnishing organizations with invaluable insights to foster and cultivate an agile workforce.

Assessing the Impact of Recommendation Novelty on Older Consumers: Older Does Not Always Mean the Avoidance of Innovative Products

Personalized recommendations that use digital technologies to predict user interests and preferences and give guiding conclusions have become a widely used digital marketing tool on e-commerce platforms. Given that existing consumer behavior research has not reached a consensus on the relationship between age and the adoption of innovative products, whether recommendation novelty can stimulate older consumers' acceptance of innovative products remains uncertain. Grounded in the aging and social influence literature, this experimental study investigated the moderating role of individual cognitive age on the impact of recommendation novelty on consumer perceptions regarding stereotype threat and receptiveness to innovativeness. An experiment involving 239 online shoppers was conducted to investigate the experiences of cognitively younger and older adults while using low or high levels of recommendation novelty designed for this study. Results reveal the tension for older adults when using highly recommended novelty, as they perceive these to be more of a stereotype threat, but they also have a higher level of receptiveness to innovativeness. This finding is contrary to the common belief that "the older the consumer, the less receptive to innovativeness", providing novel insight into the information systems literature. Theoretically, this research shows how increasing the level of recommended novelty affects stereotype threat and receptiveness to innovativeness (of consumers of different cognitive ages). For practitioners, the results provide important guidelines on the kind of personalized recommendations that are appropriate for consumers with different cognitive ages.

Automated vehicles for older adults with cognitive impairment: a survey study

As the population is ageing, the number of older adults with cognitive impairment (CI) is increasing. Automated vehicles (AVs) can improve independence and enhance the mobility of these individuals. This study aimed to: (1) understand the perception of older adults (with and without CI) and stakeholders providing services and supports regarding care and transportation about AVs, and (2) suggest potential solutions to improve the perception of AVs for older adults with mild or moderate CI. A survey was conducted with 435 older adults with and without CI and 188 stakeholders (e.g. caregivers). The results were analysed using partial least square - structural equation modelling and multiple correspondence analysis. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided recommendations to improve older adults' perception of AVs including education and adaptive driving simulation-based training.Practitioner summary: This study investigated the perception of older adults and other stakeholders regarding AVs. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided guidelines to improve older adults' perception of AVs.

From "online brains" to "online lives": understanding the individualized impacts of Internet use across psychological, cognitive and social dimensions

In response to the mass adoption and extensive usage of Internet-enabled devices across the world, a major review published in this journal in 2019 examined the impact of Internet on human cognition, discussing the concepts and ideas behind the "online brain". Since then, the online world has become further entwined with the fabric of society, and the extent to which we use such technologies has continued to grow. Furthermore, the research evidence on the ways in which Internet usage affects the human mind has advanced considerably. In this paper, we sought to draw upon the latest data from large-scale epidemiological studies and systematic reviews, along with randomized controlled trials and qualitative research recently emerging on this topic, in order to now provide a multi-dimensional overview of the impacts of Internet usage across psychological, cognitive and societal outcomes. Within this, we detail the empirical evidence on how effects differ according to various factors such as age, gender, and usage types. We also draw from new research examining more experiential aspects of individuals' online lives, to understand how the specifics of their interactions with the Internet, and the impact on their lifestyle, determine the benefits or drawbacks of online time. Additionally, we explore how the nascent but intriguing areas of culturomics, artificial intelligence, virtual reality, and augmented reality are changing our understanding of how the Internet can interact with brain and behavior. Overall, the importance of taking an individualized and multi-dimensional approach to how the Internet affects mental health, cognition and social functioning is clear. Furthermore, we emphasize the need for guidelines, policies and initiatives around Internet usage to make full use of the evidence available from neuroscientific, behavioral and societal levels of research presented herein.

Sipping a sustainable life: Exploring drivers and barriers in consumer attitudes toward non or low alcoholic spirits

Alcohol consumption continues to be prevalent and is on the rise in many countries, posing a grave risk for the health and wellbeing of millions and creating a strain on health services worldwide. A hopeful trend has emerged, however, as consumers' growing preference for healthier, sustainable lifestyles has led traditional alcoholic brands to innovate, launching reduced or non-alcoholic (NoLo) options. This aligns with the SDGs and is reflected in NoLo spirits representing four of Spain's top ten disruptive innovations of 2022. This paper uses a mixed methodology in a qualitative-quantitative sequential approach to gain insight into this phenomenon. The study involved 13 in-depth interviews with HoReCa (an acronym for Hotels, Restaurants, and Caterings) professionals and four focus groups among consumers. Second, behavioral reasoning theory (BRT) was used in a quantitative study aiming to explore motivations for and against consuming NoLo spirits. Data from a survey of 620 participants was conducted and analyzed using SEM-PLS to measure the antecedents of consumer's behavioral intention towards NoLo spirits and to gauge the potential for marketing opportunities. The research reveals that the purchase intention of NoLo spirits is strongly related to health consciousness, while enjoying the effects of alcohol for fun and entertainment, and the social pressure to drink hinders its consumption. In addition, it was found that "reasons for" are more substantial than "reasons against" the consumption of those beverages, differing significantly by age group. Results offer implications for theory and practice, including recommendations for practitioners and regulators willing to improve sustainability in the industry. Further, this paper helps augment the innovation adoption literature by using BRT in the paradoxical context of consumers' increasing alcohol abuse despite their professed attempts to adopt healthier lifestyles.

Protocol for a randomised controlled field experiment on the effect of different gamification designs of physical activity

Gamification is finding growing application in the field of physical activity, promising engaging and motivating experiences that foster behavioural change. However, existing empirical work has insufficiently scrutinised whether the reported positive outcomes emerge because of gamification and what type of gamification design leads to optimal results. This protocol for a parallel four-arm randomised controlled field experiment was purposely designed to investigate the effect of different gamification designs on motivation, perceived usefulness, and the intended behavioural change in physical activity (increase in step counts). Participants were randomly assigned to either: 1) a competitive gamified group; 2) a cooperative gamified group; 3) a hybrid (competitive-cooperative) gamified group; or 4) a control group. The design of the gamified interventions was guided by gamification design frameworks identified in literature. The data gathered includes: 1) a longitudinal panel dataset of step counts to investigate the causal effect of gamification on physical activity behaviour; and 2) self-reported data to examine the effect of gamification on the users' intrinsic motivation and perceived usefulness of the experience. This protocol outlines the procedure and processes followed during this experiment to facilitate replicability for future studies.

The desirability bias in personality-related syllogistic reasoning

INTRODUCTION

The belief-bias effect is a tendency to evaluate syllogistic statements based on believability rather than on formal logic validity. Following this rationale, the study examines desirability bias as the tendency to evaluate syllogistic conclusions based on their desirability when reasoning is conducted on personality-relevant categorical syllogisms.

METHODS

For this purpose, 60 syllogisms were constructed based on the items of the Big Five questionnaire. Syllogisms were subsequently categorized as desirable (e.g., "I empathize with others") and undesirable (e.g., "I am passive") based on their conclusion. In each task, the second premise and the conclusion were formulated in the first person to increase a respondent's identification with the content. A total of 300 university students (Mage = 20.08, SD = 2.02) participated in the study.

RESULTS

A 2 (syllogism validity: valid, invalid) × 2 (syllogism desirability: desirable, undesirable) repeated measures ANOVA was employed. The analysis showed a greater tendency to accept desirable conclusions on valid syllogisms (valid desirable rather than valid undesirable) and reject undesirable conclusions on invalid syllogisms (invalid undesirable rather than invalid desirable).

CONCLUSION

These findings have implications for socially desirable responding in cognitive tasks, which may be further developed as a source of self-relevant content as well as for further extension of belief bias in the form of desirability bias.

Mixed Methods Illustration of Teachers' Trauma-Informed Attitudes and Practice

Traumatic events during childhood are crucial to consider when addressing children's social and emotional development, as childhood trauma is associated with negative impacts, including academic achievement. Additionally, positive classroom environments and teachers' trauma-informed attitudes and behavior play a role in supporting recovery from children's trauma-related experiences. Aspire, Connect, Thrive (ACT) is a trauma-informed school-based intervention that examined students' Social Emotional Competence (SEC) and resilience for K-8th grade students in a disadvantaged, urban elementary school in Connecticut contending with the effects of students' exposure to trauma. The present study examines the experience of ACT teachers who received professional development and subsequently implemented learned content in the classroom (N = 17; 70.6% female, mean age = 44 years; 47.1% racial/ethnic minority; mean years teaching = 15.6) through qualitative evidence of trauma sensitivity (observed and self-reported) and clinician-ratings of teachers' positive classroom environment. Quantitative results indicate significant change over time in teachers' attitudes and trauma-informed classroom responses. Interview themes suggest (1) teachers learned from and implemented the intervention content in their classrooms dependent upon the support the teacher was given, (2) teachers' perspectives on the connections between the student-teacher relationship and trauma-informed attitudes or practices influenced teacher behavior, and (3) teachers' own emotions and experiences implementing trauma-informed practices were key to classroom management.

Electronic medication administration record (eMAR) in Swedish home healthcare-Implications for Nurses' and nurse Assistants' Work environment: A qualitative study

BACKGROUND

The electronic medication administration record (eMAR) is an eHealth system that has replaced the traditional paper-based medication administration used in many healthcare settings. Research has highlighted that eHealth technologies can change working methods and professional roles in both expected and unexpected ways. To date, there is sparse research that has explored how nurses and nurse assistants (NA) in home healthcare experience eMAR in relation to their work environment.

AIM

The aim was to explore how nurses and nurse assistants experienced their work environment, in terms of job-demand, control, and support in a Swedish home healthcare setting where an electronic medication administration record had been implemented to facilitate delegation of medical administration.

METHOD

We took a qualitative approach, where focus groups were used as data collection method. The focus groups included 16 nurses and nine NAs employed in a Swedish municipality where an eMAR had been implemented 6 months before the first focus groups were performed. The analysis adapted the job-demand-control-support model, by condensing the professionals' experiences into the three categories of demand, control, and support, in alignment with the model.

RESULTS

NAs experienced high levels of job demand and low levels of job control. The use of the eMAR limited NAs' ability to control their work, in terms of priorities, content, and timing. In contrast, the nurses described demands as high but manageable, and described having a high level of control. Both professions found the eMar supportive.

CONCLUSION

Nurses and NAs in home healthcare experienced changes in their work environment regarding demand, control, and support when an eMAR was implemented to facilitate delegation of medical administration. In general, nurses were satisfied with the eMAR. However, NAs felt that the eMAR did not cover all aspects of their daily work. Healthcare organisations should be aware of the changes that digitalisation processes entail in the work environment of nurses and NAs in home healthcare.

Superior medical resources or geographic proximity? The joint effects of regional medical resource disparity, geographic distance, and cultural differences on online medical consultation

Online medical consultation platforms enable patients to seek health advice from physicians across geographic regions. In this study, we analyze patterns of online consultation between patients and physicians. We examine the joint effects of regional medical resource disparity, geographic distance, and cultural differences between patients and physicians on patients' decisions about which physicians they consult online. Using a unique dataset of city-to-city tuples based on 813,684 online consultation records and combining it with region-level data from multiple external sources, we find that while regional medical resource disparity drives patients from medically disadvantaged regions to seek online consultations with physicians from medically advantaged regions, geographic distance and cultural differences tend to constrain these consultations. We also find that cultural differences can amplify the impact of regional medical resource disparity, whereas geographic distance may lessen this effect. Further, we discover that the constraining effect of geographic distance is partly due to the online-to-offline nature of online medical consultations. Moreover, additional analyses suggest that physicians' online reputation and information about physicians' participation on the platform can help alleviate the negative effects of geographic distance and cultural differences. These findings hold significant implications for the allocation of medical resources and the formulation of healthcare policies.

Domain-Specific Greed

Greed, the insatiable and excessive desire and striving for more even at the expense of others, may be directed toward various goods. In this article, we propose that greed may be conceptualized as a domain-specific construct. Based on a literature review and an expert survey, we identified 10 domains of greed which we operationalized with the DOmain-SPEcific Greed (DOSPEG) questionnaire. In Study 1 (N = 725), we found support for the proposed structure and convergent validity with related constructs. Bifactor-(S-1) models revealed that generic greed is differentially related to the greed domains, indicating that generic greed primarily captures a striving for money and material things. In the second study (N = 591), we found that greed domains had incremental validity beyond generic greed with regard to corresponding criteria assessed via self- and other-reports. We conclude that greed can be conceptualized as a domain-specific construct and propose an onion model reflecting this structure.

A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis

Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient's complete health history to make informed decisions about future events. However, previous work has mostly relied on so-called black-box models, which are unintelligible to humans, making it difficult for clinicians to apply such models. Our work introduces PatWay-Net, an ML framework designed for interpretable predictions of admission to the intensive care unit (ICU) for patients with symptoms of sepsis. We propose a novel type of recurrent neural network and combine it with multi-layer perceptrons to process the patient pathways and produce predictive yet interpretable results. We demonstrate its utility through a comprehensive dashboard that visualizes patient health trajectories, predictive outcomes, and associated risks. Our evaluation includes both predictive performance - where PatWay-Net outperforms standard models such as decision trees, random forests, and gradient-boosted decision trees - and clinical utility, validated through structured interviews with clinicians. By providing improved predictive accuracy along with interpretable and actionable insights, PatWay-Net serves as a valuable tool for healthcare decision support in the critical case of patients with symptoms of sepsis.

An optimised and validated surrogate analyte A-TEEM-PARAFAC-PLS technique for detecting and quantifying the biological oxygen demand in surface water

A 5-day test duration makes BOD5 measurement unsatisfactory and hinders the development of a quick technique. Protein-like fluorescence peaks show a strong correlation between the BOD characteristics and the fluorescence intensities. For identifying and measuring BOD in surface water, a simultaneous absorbance-transmittance and fluorescence excitation-emission matrices (A-TEEM) method combined with PARAFAC (parallel factor) and PLS (partial least squares) analyses was developed using a tyrosine and tryptophan (tyr-trpt) mix as a surrogate analyte for BOD. The use of a surrogate analyte was decided upon due to lack of fluorescent BOD standards. Tyr-trpt mix standard solutions were added to surface water samples to prepare calibration and validation samples. PARAFAC analysis of excitation-emission matrices detected the tyr-trpt mix in surface water. PLS modelling demonstrated significant linearity (R2 = 0.991) between the predicted and measured tyr-trypt mix concentrations, and accuracy and robustness were all acceptable per the ICH Q2 (R2) and ASTM multivariate calibration/validation procedures guidelines. Based on a suitable and workable surrogate analyte method, these results imply that BOD can be detected and quantified using the A-TEEM-PARAFAC-PLS method. Very positive comparability between tyr-trypt mix concentrations was found, suggesting that tyr-trypt mix might eventually take the place of a BOD-based sampling protocol. Overall, this approach offers a novel tool that can be quickly applied in water treatment plant settings and is a step in supporting the trend toward rapid BOD determination in waters. Further studies should demonstrate the wide application of the method using real wastewater samples from various water treatment facilities.

Physiotherapy services during the COVID-19 pandemic: A mediated model of physiotherapists' self-efficacy, tele-physiotherapy role stressors, and motivation to provide tele-physiotherapy

BACKGROUND

Occupational self-efficacy is a stable predictor for professionals' motivation to engage with new methods and tasks. Yet, the delivery of tele-physiotherapy (Tele-PT) by physiotherapists (PTs) during the coronavirus disease of 2019 (COVID-19) outbreak without advance training may have had the potential to increase work stress and damage their motivation, regardless of their occupational self-efficacy.

OBJECTIVES

The present study examined whether the relations between PTs' overall occupational self-efficacy and motivation to provide Tele-PT was mediated by role stress (i.e. role conflict and ambiguity).

DESIGN AND METHOD

Between February 4 and April 23, 2021, 150 Israeli PTs completed an online survey that measured their overall occupational self-efficacy, their role stress induced by the provision of Tele-PT, their motivation to provide Tele-PT, and their demographic characteristics.

RESULTS

PTs' overall occupational self-efficacy was positively associated with PTs' motivation to provide Tele-PT (r= 0.328, p < .01) and fully mediated by role conflict (0.1757, 95% CI = [0.0231, 0.3797]) and by role ambiguity (0.1845, 95% CI = [0.0196, 0.4184]) (components of role stress) caused by the provision of Tele-PT.

CONCLUSIONS

It is important to investigate the predictors and mediators of the motivation to provide Tele-PT because in the post-COVID-19 era health organizations are likely to adopt many tele-medicine services, and they need to find ways to mitigate perceived challenges.

Data on mathematics teacher educators' proficiency and willingness to use technology: A structural equation modelling analysis

The role of Mathematics Teacher Educators (MTEs) in preparing future teachers to effectively integrate technology into their mathematics instruction is of paramount importance yet remains an underexplored domain. Technology has the potential to enhance the development of 21st-century skills, such as problem-solving and critical thinking, which are essential for students in the era of the fourth industrial revolution. However, the rapid evolution of technology and the emergence of new trends like data analytics, the Internet of Things, machine learning, cloud computing, and artificial intelligence present new challenges in the realm of mathematics teaching and learning. Consequently, MTEs need to equip prospective teachers with the knowledge and skills to harness technology in innovative ways within their future mathematics classrooms. This paper presents and describes data from a survey of 104 MTEs in Zambia. The study focuses on MTEs' proficiency, perceived usefulness, perceived ease of use, and willingness to incorporate technology in their classrooms. This data-driven article aims to unveil patterns and trends within the dataset, with the objective of offering insights rather than drawing definitive conclusions. The article also highlights the data collection process and outlines the procedure for assessing the measurement model of the hypothesised relationships among variables through structural equation modelling analysis. The data described in this article not only sheds light on the current landscape but also serves as a valuable resource for mathematics teacher training institutions and other stakeholders seeking to understand the requisites for MTEs to foster technological skills among prospective teachers of mathematics.

Economic policy uncertainty and enterprise export resilience in China: Does the digital economy matter?

In the new era of international trade, escalating uncertainty and the swift development of the digital economy stand out as two pivotal transformations. These phenomena individually exert significant influences on enterprises' exports; however, their combined effects on export resilience remain underexplored. Hence, drawing on existing theories, this paper analyzes the weakening effect of economic policy uncertainty on export resilience and explores the influence of regional digital economic development on this attenuation effect. Furthermore, empirical tests are conducted using micro-level data from China. The study findings reveal: (1) Economic policy uncertainty weakens firms' export resilience by increasing transaction costs; (2) Digital economic development mitigates this weakening effect by reducing transaction costs, with a more pronounced effect observed among highly efficient firms. The findings suggest that amid escalating uncertainty, vigorously promoting digital economic development holds profound policy significance for the high-quality development of international trade.

Top of tide: Nexus between organization agility, digital capability and top management support in SME digital transformation

In the swiftly evolving business landscape, digital transformation (DT) has emerged as a crucial strategy for firms to gain a competitive edge. Despite the abundance of literature on DT in firms, there remains a dearth of empirical research that defines and analyzes crucial antecedents of small and medium-sized enterprises' (SMEs) DT from an internal perspective. To fill this research gap, this study examines the correlation between organizational agility and digital capability in cultivating SMEs' DT while also evaluating top management support as a moderating variable through the lens of internal factors of SMEs. The results indicate that both organizational agility and digital capability have a positive impact on SMEs' DT, with organizational agility significantly influencing digital capability. Furthermore, the findings highlight that digital capability serves as a mediator between organizational agility and SMEs' DT. In addition, top management support plays a moderating role in these relationships to a certain extent. Additionally, we explicate the concept of digital capabilities from the perspective of dynamic capability. Our study contributes to an enhanced understanding of the effect of organizational agility and digital capability on SMEs' DT, as well as the role of top management support. We provide recommendations for managers to enhance organizational agility and suggest that SMEs should improve their digital thinking to better perceive digital technology changes, enhance digital operation capabilities, and better integrate digital resources.

Ethnocentrism and place identity in the consumption of local products

Research on the consumption of local products is essential to promote sustainability, boost local economies, and preserve cultural identity. Although a positive relationship has been demonstrated between attitude towards local products and consumption determinants, the role of the former as a mediator has not been sufficiently explored. This study examines how the attitude towards local products mediates between consumer ethnocentrism and consumption intention, as well as between place identity and consumption intention. A total of 1325 wine and cheese consumers in the Canary Islands were surveyed using a moderated mediation model, applying PLS-SEM. The results indicate that attitude towards local products mediates the aforementioned relationships but does not moderate them according to the type of local product. Consequently, marketing strategies should focus on the emotional and cultural connection that consumers establish with local products, highlighting their value in terms of identity and belonging.

Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software

Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs) and neuritic plaques (NPs), without consideration of lesion heterogeneity in individual cases. We developed a deep learning workflow for automated annotation and segmentation of NPs and NFTs from AT8-immunostained whole slide images (WSIs) of AD brain sections. Fifteen WSIs of frontal cortex from 4 biobanks with varying tissue quality, staining intensity, and scanning formats were analyzed. We established an artificial intelligence (AI)-driven iterative procedure to improve the generation of expert-validated annotation datasets for NPs and NFTs thereby increasing annotation quality by >50%. This strategy yielded an expert-validated annotation database with 5013 NPs and 5143 NFTs. We next trained two U-Net convolutional neural networks for detection and segmentation of NPs or NFTs, achieving high accuracy and consistency (mean Dice similarity coefficient: NPs, 0.77; NFTs, 0.81). The workflow showed high generalization performance across different cases. This study serves as a proof-of-concept for the utilization of proprietary image analysis software (Visiopharm) in the automated deep learning segmentation of NPs and NFTs, demonstrating that AI can significantly improve the annotation quality of complex neuropathological features and enable the creation of highly precise models for identifying these markers in AD brain sections.

The Impact of Performance Expectancy, Workload, Risk, and Satisfaction on Trust in ChatGPT: Cross-Sectional Survey Analysis

BACKGROUND

ChatGPT (OpenAI) is a powerful tool for a wide range of tasks, from entertainment and creativity to health care queries. There are potential risks and benefits associated with this technology. In the discourse concerning the deployment of ChatGPT and similar large language models, it is sensible to recommend their use primarily for tasks a human user can execute accurately. As we transition into the subsequent phase of ChatGPT deployment, establishing realistic performance expectations and understanding users' perceptions of risk associated with its use are crucial in determining the successful integration of this artificial intelligence (AI) technology.

OBJECTIVE

The aim of the study is to explore how perceived workload, satisfaction, performance expectancy, and risk-benefit perception influence users' trust in ChatGPT.

METHODS

A semistructured, web-based survey was conducted with 607 adults in the United States who actively use ChatGPT. The survey questions were adapted from constructs used in various models and theories such as the technology acceptance model, the theory of planned behavior, the unified theory of acceptance and use of technology, and research on trust and security in digital environments. To test our hypotheses and structural model, we used the partial least squares structural equation modeling method, a widely used approach for multivariate analysis.

RESULTS

A total of 607 people responded to our survey. A significant portion of the participants held at least a high school diploma (n=204, 33.6%), and the majority had a bachelor's degree (n=262, 43.1%). The primary motivations for participants to use ChatGPT were for acquiring information (n=219, 36.1%), amusement (n=203, 33.4%), and addressing problems (n=135, 22.2%). Some participants used it for health-related inquiries (n=44, 7.2%), while a few others (n=6, 1%) used it for miscellaneous activities such as brainstorming, grammar verification, and blog content creation. Our model explained 64.6% of the variance in trust. Our analysis indicated a significant relationship between (1) workload and satisfaction, (2) trust and satisfaction, (3) performance expectations and trust, and (4) risk-benefit perception and trust.

CONCLUSIONS

The findings underscore the importance of ensuring user-friendly design and functionality in AI-based applications to reduce workload and enhance user satisfaction, thereby increasing user trust. Future research should further explore the relationship between risk-benefit perception and trust in the context of AI chatbots.

Human-annotated rationales and explainable text classification: a survey

Asking annotators to explain "why" they labeled an instance yields annotator rationales: natural language explanations that provide reasons for classifications. In this work, we survey the collection and use of annotator rationales. Human-annotated rationales can improve data quality and form a valuable resource for improving machine learning models. Moreover, human-annotated rationales can inspire the construction and evaluation of model-annotated rationales, which can play an important role in explainable artificial intelligence.

Navigating board dynamics: Configuration analysis of corporate governance's factors and their impact on bank performance

This research utilizes the fsQCA technique to investigate how a combination of corporate governance conditions or factors collectively influences the performance of banks. Examining key elements such as board size, busy directors, independent directors, CEO duality, and women on the board, the research employs data collected from the annual reports of 30 banks spanning from 2010 to 2020. The necessary condition analysis (NCA) underscores that no individual condition or factor is indispensable for the ultimate outcome. Nevertheless, the sufficiency analysis reveals distinct solutions, each representing a unique set of conditions or factors sufficient to generate the outcome. The study concludes that the relationship between corporate governance characteristics and bank performance is complex and multifaceted, with neither ROA nor ROE reliant on a singular input condition or factor. The theoretical contributions of the findings align with or partially support various theories and propositions within the realm of corporate governance. Notably, the application of fsQCA contributes to enhance the methodological understanding of corporate governance studies in existing literature.

Navigating the decision-making landscape of AI in risk finance: Techno-accountability unveiled

The integration of artificial intelligence (AI) systems has ushered in a profound transformation. This conversion is marked by revolutionary extrapolative capabilities, a shift toward data-centric decision-making processes, and the enhancement of tools for managing risks. However, the adoption of these AI innovations has sparked controversy due to their unpredictable and opaque disposition. This study employs the transactional stress model to empirically investigate how six technological stressors (techno-stressors) impact both techno-eustress (positive stress) and techno-distress (negative stress) experienced by finance professionals and experts. To collect data for this research, an e-survey was distributed to a diverse group of 251 participants from various sources. The findings, particularly the identification and development of techno-accountability as a significant factor, contribute to the risk analysis domain by improving the failure mode and effect analysis framework to better fit the rapidly evolving landscape of AI-driven innovations.

Online Medical Consultation Service-Oriented Recommendations: Systematic Review

BACKGROUND

Online health communities (OHCs) have given rise to a new e-service known as online medical consultation (OMC), enabling remote interactions between physicians and patients. To address challenges such as patient information overload and uneven distribution of physician visits, OHCs should develop OMC-oriented recommenders.

OBJECTIVE

We aimed to comprehensively investigate what paradigms lead to the success of OMC-oriented recommendations.

METHODS

A literature search conducted through e-databases, including PubMed, ACM Digital Library, Springer, and ScienceDirect from January 2011 to December 2023. This review included all papers directly and indirectly related to the topic of healthcare-related recommendations for online services.

RESULTS

The search identified 313 articles, of which 26 met the inclusion criteria. Despite the growing academic interest in OMC recommendations, there remains a lack of consensus of e-service-oriented recommenders on their definition among researchers. The discussion highlights three key factors influencing recommender success: features, algorithms, and metrics. It advocates for moving beyond traditional e-commerce-oriented recommenders to establish an innovative theoretical framework for e-service-oriented recommenders and addresses critical technical issues in two-sided personalized recommendations.

CONCLUSIONS

The review underscores the essence of e-services, particularly in knowledge-intensive and labor-intensive domains like OMC, where patients seek interpretable recommendations due to their lack of domain knowledge, and physicians must balance their energy levels to avoid overworking. Our study's findings shed light on the importance of customizing e-service-oriented personalized recommendations to meet the distinct expectations of two-sided users, considering their cognitive abilities, decision-making perspectives, and preferences. To achieve this, a paradigm shift is essential to develop unique attributes and explore distinct content tailored for both parties involved.

CLINICALTRIAL

Green innovation and enterprise digital transformation: Escape from the "dilemma" of development and governance choices

The digital economy is now the expected norm for economic development, warranting strategic importance for enterprise digital transformation. Nonetheless, enterprises have a lengthy journey to embark upon for digital transformation. On the one hand, resource-based demands pose a significant challenge due to the development characteristics of the initiative; on the other hand, excessive emphasis on economic gains may result in severe environmental issues. Therefore, this paper examines whether green innovation, which combines environmental and economic benefits, can effectively address the above dilemma. The study includes all A-share listed companies from 2010 to 2020 as the research sample, and empirically investigates the impact of green innovation on enterprise digital transformation and its mechanism based on resource-based view. The study concluded that (i) green innovation has a significant positive impact on corporate digital transformation performance, exhibiting asymmetric effects. The robustness tests confirmed the validity of the findings. (ii) Enterprises that actively engage in green innovation can effectively reduce their financial constraints, enhance their operational capacity, and enable the efficient allocation of resources, thereby promoting digital transformation within the enterprise. (iii) There is a regional imbalance in the conversion of green innovation performance into economic performance. The aforementioned results offer fresh insights for investigating the connection between green innovation and digital transformation. Additionally, these findings hold significant implications for the discourse on the synergistic advancement of the environment and economy.

Unlocking future learning: Exploring higher education students' intention to adopt meta-education

Despite the potential of meta-education to transform higher education, there remains a scarcity of research investigating students' adoption intentions. This study aimed to identify factors influencing students' intentions to adopt meta-education using an extended Decomposed Theory of Planned Behavior model (DTPB). Data was collected via an online survey of 596 higher education students from Jordan who were purposefully selected. Structural equation modeling using partial least squares analysis revealed attitude, social influence, and perceived behavioral control as key antecedents of adoption intention. Furthermore, newly added variables including perceived enjoyment, herd behavior, student autonomy, and student innovativeness showed efficiency in explaining variance in attitude, social influence, and perceived behavioral control. Overall, the extended model provided meaningful insights on factors driving students' willingness to adopt meta-education. The study contributes to theory by extending the decomposed TPB model in the context of emerging educational technologies. It also provides practical implications for policymakers and educators aiming to encourage meta-education adoption.

Research on the impact of digital transformation on innovative high-quality development in the context of environmental regulation in agricultural enterprises

Digital transformation is an important strategic choice for agricultural enterprises to adapt to economic development in the new era. The innovation quality of patents with core technology and high commercial value is significantly higher than that of low-quality patents such as weak patents developed through technological imitation. This study investigates the impact of digital transformation on innovative high-quality development in the context of environmental regulation in agricultural enterprises for the timeframe from 2012 to 2020. The purpose of this study is to examine whether the goal of improving innovation quality can be achieved through digital transformation in agricultural companies. The results show that digital transformation can effectively promote the improvement of innovation quality in companies, and environmental regulation has a significant positive moderating effect on the relationship between them. "Violating agricultural operation" is a specific appellation for the diversified management of listed agricultural companies, and it is one of the management modes of agricultural enterprises. For listed agricultural companies, the greater the degree of enterprise diversification, the greater the degree of "violating agricultural operation". The influence mechanism test shows that "violating agricultural operation" plays a part in mediating effect in the process of digital transformation promoting innovation quality improvement.

SNS citizenship behavior based on D&M information system success model and social capital theory: Mediating role of subjective well-being

Social media has become integral to contemporary society, with online behaviors impacting individual experiences and the wider community. In Bangladesh, a developing country, SNS have played a pivotal role in the nation's digitalization efforts. This study explores the relationship between social capital theory, D&M Information System Model, subjective well-being, and SNS Citizenship Behavior (SCB) among active social media users in Bangladesh. Data was collected from 418 participants through an online survey, and hypotheses were tested using structural equation modeling. The findings indicate that the items of the D&M model positively influenced the aspects of social capital theory, excluding service quality. In contrast, social interaction ties and shared values were positively associated with SCB, although social trust did not exhibit a significant relationship. Additionally, subjective well-being mediated the connection between social capital and SCB. This research offers valuable insights into the factors influencing online prosocial behavior and provides practical implications for cultivating a positive communication culture in the digital era. The model proposed in this study holds significant implications for Bangladesh's policymakers and social networking site authorities, guiding their efforts in implementing technology-based initiatives.

The study of female college students' consumer psychology mechanism toward male celebrity endorsed products: Tempted or coerced?

The trend of male celebrities endorsing female products is increasing. However, research is lacking on whether this influence is due to the positive emotions generated by the male celebrity's attractiveness or the peer pressure due to mass purchases by the celebrity's fans, and how these effects differ across products with different attributes. This study aims to fill the gap in the existing literature by investigating the influence of male endorsers on female consumers purchase intention, and to deepen the understanding of the mechanisms by which attractiveness and conformity jointly influence purchase decisions. This study used a mixed-design text experiment to investigate the impact of male endorsers' attractiveness and conformity on female college students' positive product attitude and purchase intention for gender-neutral product, female skincare product, and female intimate product, based on the Theory of Planned Behaviour (TPB). The data collected from 456 female college students were analyzed using bootstrap analysis. The study found that both male endorsers' attractiveness and conformity can enhance female college students' positive product attitude and promote their purchase intention for gender-neutral product. However, for female skincare product, male endorsers' attractiveness affects their positive product attitude and purchase intention. Nevertheless, when conformity was present, attractiveness no longer had an effect. Furthermore, for individuals with high levels of loneliness, attractiveness had a detrimental effect on their positive product attitude. On the other hand, conformity had a positive effect by promoting positive product attitude and increasing purchase intention. For female's intimate product, attractiveness did not affect positive product attitude and purchase intention, but the positive effect of conformity remained significant, and both relationships were not moderated by loneliness. It enhances our comprehension of the intricate dynamics underlying the influence of male celebrity endorsements on consumer purchasing decisions, and also offers theoretical justification for the selection of male endorsers for diverse female product.

Unveiling the shadows: Beyond the hype of AI in education

Despite the wave of enthusiasm for the role of Artificial Intelligence (AI) in reshaping education, critical voices urge a more tempered approach. This study investigates the less-discussed 'shadows' of AI implementation in educational settings, focusing on potential negatives that may accompany its integration. Through a multi-phased exploration consisting of content analysis and survey research, the study develops and validates a theoretical model that pinpoints several areas of concern. The initial phase, a systematic literature review, yielded 56 relevant studies from which the model was crafted. The subsequent survey with 260 participants from a Saudi Arabian university aimed to validate the model. Findings confirm concerns about human connection, data privacy and security, algorithmic bias, transparency, critical thinking, access equity, ethical issues, teacher development, reliability, and the consequences of AI-generated content. They also highlight correlations between various AI-associated concerns, suggesting intertwined consequences rather than isolated issues. For instance, enhancements in AI transparency could simultaneously support teacher professional development and foster better student outcomes. Furthermore, the study acknowledges the transformative potential of AI but cautions against its unexamined adoption in education. It advocates for comprehensive strategies to maintain human connections, ensure data privacy and security, mitigate biases, enhance system transparency, foster creativity, reduce access disparities, emphasize ethics, prepare teachers, ensure system reliability, and regulate AI-generated content. Such strategies underscore the need for holistic policymaking to leverage AI's benefits while safeguarding against its disadvantages.

Competition of multiplatform firms: Implications for the Internet of Things

The Internet of Things (IoT) technology trend is transforming business and society. This creates a need to understand strategic behavior in the consumer IoT, where firms tend to offer multiple platform devices, and new generations of devices are introduced frequently. We propose a novel analytical model that formalizes the concept of a multiplatform firm that offers a system of platforms, such as a smartphone, and a new platform device, such as a smartwatch, and orchestrates a multiplatform ecosystem. The analysis shows how a platform design decision, like offering a new standalone device, affects consumer choices and market outcomes. We identify two classes of new devices that matter, and show when a new platform device may disrupt the smartphone market. Moreover, we characterize conditions under which it is profitable for a vendor to make its new platform device look and feel more like its smartphone. Overall, we provide insights into how multiplatform firms differ from platform firms. We identify future research opportunities on the economics of consumer IoT and multiplatform ecosystems.

Information Seeking and Receiving of Older Adults with Diabetes in the Online Health Community: An Information Need Contextualization Perspective

Online health communities (OHCs) are important online health communication channels for older adults with diabetes to access health information. When seeking health information, they often disclose a variety of contextual information (e.g., socio-economic situations) in their questions. Selective contextual information disclosure is a type of communication strategy for users in OHCs to elicit replies from others. In this study, we adopted text analysis to investigate what contextual information older adults with diabetes disclose to articulate their information needs and used the fixed-effect Poisson model to examine the relationships between different types of contextual information disclosure and informational support receipt. Our analyses were based on a dataset of 4,505 questions and corresponding replies from an online diabetes community. The results showed that cognitive information is the most frequently disclosed contextual information, while older adults tend to disclose demographic information in their questions less. Providing demographic and situational details in questions can enhance informational support receiving, resulting in an increased number of informational supports. However, disclosing cognitive, affective, informational channels, or support information does not significantly affect the informational support receiving. These findings can contribute to extending our existing understanding of information seekers' communication strategies in OHCs.

Empowering pro-environmental behavior in tourists through digital media: the influence of eco-guilt and empathy with nature

In the digital economy era, leveraging digital media to foster tourists' pro-environmental behavioral intention (TPEBI) has become crucial in the field of sustainable tourism. While existing studies have mainly focused on the driving mechanism of TPEBI within physical tourism contexts, the correlation between digital media information sharing and TPEBI remains unclear. Our study employs the cognitive-affective-conative framework to construct a theoretical model, considering eco-guilt and empathy with nature as mediating variables. It aims to explore the influencing mechanism of destination environmental information sharing through digital media on TPEBI from a presence perspective. Thereby, two scenario experiments were designed: Study 1 examined the impact of different formats of destination environmental threat information presentation on digital media on the sense of presence, while Study 2 explored the influencing mechanism of presence on TPEBI based on the conclusions of Study 1. Results indicate that (1) vivid and visible presentation formats of destination environmental threat information on digital media enhance individuals' sense of presence; (2) sense of presence positively influences TPEBI; and (3) eco-guilt and empathy with nature mediate between presence and TPEBI. These findings not only contribute to theoretical and empirical research on digital media information sharing in sustainable tourism but also offer guidance for governments and tourism destinations to effectively stimulate TPEBI through digital media, achieve the sustainable development of destinations.

The digital transformation in pharmacy: embracing online platforms and the cosmeceutical paradigm shift

In the face of rapid technological advancement, the pharmacy sector is undergoing a significant digital transformation. This review explores the transformative impact of digitalization in the global pharmacy sector. We illustrated how advancements in technologies like artificial intelligence, blockchain, and online platforms are reshaping pharmacy services and education. The paper provides a comprehensive overview of the growth of online pharmacy platforms and the pivotal role of telepharmacy and telehealth during the COVID-19 pandemic. Additionally, it discusses the burgeoning cosmeceutical market within online pharmacies, the regulatory challenges faced globally, and the private sector's influence on healthcare technology. Conclusively, the paper highlights future trends and technological innovations, underscoring the dynamic evolution of the pharmacy landscape in response to digital transformation.

A comparative analysis of risk factors in taxi-related crashes using XGBoost and SHAP

Taxis play a crucial role in urban public transportation, but the traffic safety situation of taxi drivers is far from optimistic, especially considering the introduction of ride-hailing services into the taxi industry. This study conducted a comparative analysis of risk factors in crashes between traditional taxi drivers and ride-hailing taxi drivers in China, including their demographic characteristics, working conditions, and risky driving behaviors. The data was collected from 2,039 traditional taxi drivers and 2,182 ride-hailing taxi drivers via self-reported questionnaires. Four XGBoost models were established, taking into account different types of taxi drivers and crash types. All models showed acceptable performance, and SHAP explainer was used to analyze the model results. The results showed that for both taxi drivers, risk factors related to risky driving behaviors are more important in predicting property damage (PD) crashes, while risk factors related to working conditions are more important in predicting person injury (PI) crashes. However, the relative importance of each risk factor varied depending on the type of crashes and the type of taxi drivers involved. Furthermore, the results also validated certain interactions among the risk factors, indicating that the combination of certain factors generated a greater impact on crashes compared to individual factors alone. These findings can provide valuable insights for formulating appropriate measures to enhance road safety for taxi driver.

Required data elements for interprofessional rounds through the lens of multiple professions

The lack of a proper system for ongoing open interprofessional communication among care providers increases miscommunications and medical errors. Seamless access to patient information is important for care providers to prevent miscommunication and improve patient safety. A shared understanding of the information needs of different care providers in an interprofessional team is lacking. Our purpose is to identify care providers' information needs from the perspective of different professions for communication, shared understanding about the patient, and decision-making. We conducted semi-structured interviews with 10 subject matter experts representing eight professions, including dentistry, dietetics, medicine, nursing, occupational therapy, pharmacy, physical therapy, and social work in a 465-bed academic hospital at a large urban Midwestern city. We used an in-house rounding tool presenting physicians' information needs and a hypothetical patient scenario to collect participants' feedback. Interview notes were coded using direct content analysis. We identified 22 additional essential data elements for an interprofessional rounding tool. We categorized those into six domains: discharge-related, social determinants of health, hospital safety, nutrition, interprofessional situation awareness, and patient history. A well-designed validated rounding tool that includes an interprofessional team of care providers' information needs could improve communication, care planning, and decision-making among them.

Meaning, trust, and belonging: Exploring the factors that foster elite forced migrant athletes' growth

BACKGROUND AND PURPOSE

Researchers have highlighted elite refugee athletes' acculturation and sport-related challenges upon transitioning into host country sports systems. Using a strength-based approach, we aimed to broaden this view through exploring the internal and external factors that have fostered refugee athletes' abilities to find meaning and growth following their transitions into a national sports system.

METHODOLOGY

Data collection began with an arts-based drawing activity which was then discussed in a conversational interview. Fourteen (n = 11 male, 3 female) national and international refugee athletes participated. The interviews were analyzed using a reflexive thematic analysis, a form of qualitative analysis used to derive commonalities that connect athletes' experiences. The data is represented through polyphonic vignettes (narrative featuring multiple perspectives) to safeguard athletes' anonymity whilst showcasing varying perspectives.

RESULTS

Athletes were at various phases of growth at the time of the interviews. The primary internal factor that facilitated growth was responsibility to find and pursue meaning. External factors of trust and belonging, actualized through supporting elite athletes' personal differences, were external factors that fostered their abilities to find meaning.

CONCLUSION

Elite refugee athletes' growth occurred at the nexus of individual responsibility, trusting relationships, and inclusive sport environments. The findings inform individual and environmental growth-based interventions for current and future elite athletes who face varying adversities within their sports contexts.

Users' unverified information-sharing behavior on social media: The role of reasoned and social reactive pathways

Unverified or false information spread by irresponsible users can amplify the dissemination of fake news or misinformation. This phenomenon may not only undermine the credibility of social media platforms but also pose severe consequences for individuals and society. This study applies and extends the prototypical willingness model with the aim of comprehending the reasons, and decision-making process driving users' unverified information-sharing behavior a reasoned and intended pathway or an impulsive and unconscious one. Data from a sample of 646 users were analyzed using Structural Equation Modeling to assess the determinative effect of both the reasoned pathway (attitude toward unverified information-sharing, subjective norm, and perceived behavioral control) and the social-reaction pathway (prototype favorability and similarity). Findings highlight the substantial role of the social-reaction pathway in forecasting users' unverified information-sharing behavior, with prototype similarity and attitude being the dominant predictors. Meanwhile, components of the reasoned pathway, specifically perceived behavior control, and attitude, also exhibited significant contributions toward predicting the behavior. In summary, while a deliberate, reasoned process has some influence, the sharing of unverified information on social media by users is primarily an intuitive, spontaneous response to specific online circumstances. This study therefore offers valuable insights that could aid relevant stakeholders in effectively regulating the spread of misinformation. Against this backdrop, highlighting potential risks associated with sharing unverified information and the negative portrayal of users propagating misinformation may contribute to the development of a more critical perspective toward online information sharing by users themselves.

SALUS-A Study on Self-Tonometry for Glaucoma Patients: Design and Implementation of the Electronic Case File

BACKGROUND

 In times of omnipresent digitization and big data, telemedicine and electronic case files (ECFs) are gaining ground for networking between players in the health care sector. In the context of the SALUS study, this approach is applied in practice in the form of electronic platforms to display and process disease-relevant data of glaucoma patients.

OBJECTIVES

 The SALUS ECF is designed and implemented to support data acquisition and presentation, monitoring, and outcome control for patients suffering from glaucoma in a clinical setting. Its main aim is to provide a means for out- and inpatient exchange of information between various stakeholders with an intuitive user interface in ophthalmologic care. Instrument data, anamnestic data, and diagnostic assessments need to be accessible and historic data stored for patient monitoring. Quality control of the data is ensured by a reading center.

METHODS

 Based on an intensive requirement analysis, we implemented the ECF as a web-based application in React with a Datomic back-end exposing REST and GraphQL APIs for data access and import. A flexible role management was developed, which addresses the various tasks of multiple stakeholders in the SALUS study. Data security is ensured by a comprehensive encryption concept. We evaluated the usability and efficiency of the ECF by measuring the durations medical doctors need to enter and work with the data.

RESULTS

 The evaluation showed that the ECF is time-saving in comparison to paper-based assessments and offers supportive monitoring and outcome control for numerical and imaging-related data. By allowing patients and physicians to access the digital ECF, data connectivity as well as patient autonomy were enhanced.

CONCLUSION

 ECFs have a great potential to efficiently support all patients and stakeholders involved in the care of glaucoma patients. They benefit from the efficient management and view of the data tailored to their specific role.

Interruption Value Type and Source Matter in Different Phases of an Interruption Process: Emotional/Cognitive Impact and Neural Evidence

OBJECTIVE

To examine the effect of interruption value type (utilitarian, hedonic) and source (external, internal) in different phases of an interruption process.

BACKGROUND

Prior studies on interruption mostly focused on the cognitive outcomes of utilitarian interruptions. Hedonic interruptions are common in life; however, they are not sufficiently explored through research. Hedonic value is closely associated with emotional experiences, and, in turn, influences behaviors. Moreover, the way the effect of values is moderated by interruptions initiated by intrinsic motives is worth exploring.

METHOD

A 2 × 2 mixed design experiment was conducted with 48 participants who were asked to respond to instant messages during the writing task. The interruption value was induced by work or non-work tasks. The interruption source was manipulated by providing an alert. Functional near-infrared spectroscopy, behavioral data, and subjective measurements were collected and analyzed.

RESULTS

Hedonic interruptions increased emotional valence, while utilitarian interruptions decreased it. These effects were strengthened by internal interruptions. The effect of interruption value type on work exhaustion was also moderated by the source. Interruption value type and source influenced the attention allocation before an interruption occurred. Hedonic interruptions led to longer resumption lags, whereas utilitarian interruptions required longer interruption durations. Internal interruptions led to improved performance in the resumed task.

CONCLUSION

Interruption source modulate the effect of interruption value type, especially on emotional experience and attention allocation before an interruption occurs.

APPLICATION

Self-initiated hedonic interruptions have emotional benefits, while alerts for utilitarian interruptions will improve attention on the main task before interruptions.

Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy

Circulating hybrid cells (CHCs) are a newly discovered, tumor-derived cell population found in the peripheral blood of cancer patients and are thought to contribute to tumor metastasis. However, identifying CHCs by immunofluorescence (IF) imaging of patient peripheral blood mononuclear cells (PBMCs) is a time-consuming and subjective process that currently relies on manual annotation by laboratory technicians. Additionally, while IF is relatively easy to apply to tissue sections, its application to PBMC smears presents challenges due to the presence of biological and technical artifacts. To address these challenges, we present a robust image analysis pipeline to automate the detection and analysis of CHCs in IF images. The pipeline incorporates quality control to optimize specimen preparation protocols and remove unwanted artifacts, leverages a β-variational autoencoder (VAE) to learn meaningful latent representations of single-cell images, and employs a support vector machine (SVM) classifier to achieve human-level CHC detection. We created a rigorously labeled IF CHC data set including nine patients and two disease sites with the assistance of 10 annotators to evaluate the pipeline. We examined annotator variation and bias in CHC detection and provided guidelines to optimize the accuracy of CHC annotation. We found that all annotators agreed on CHC identification for only 65% of the cells in the data set and had a tendency to underestimate CHC counts for regions of interest (ROIs) containing relatively large amounts of cells (>50,000) when using the conventional enumeration method. On the other hand, our proposed approach is unbiased to ROI size. The SVM classifier trained on the β-VAE embeddings achieved an F1 score of 0.80, matching the average performance of human annotators. Our pipeline enables researchers to explore the role of CHCs in cancer progression and assess their potential as a clinical biomarker for metastasis. Further, we demonstrate that the pipeline can identify discrete cellular phenotypes among PBMCs, highlighting its utility beyond CHCs.