Framing doctor-managers' resilience during Covid-19 pandemic: A descriptive analysis from the Italian NHS

With the aim of providing evidence about doctor-managers' resilience during the Covid-19 pandemic, this study analyzes the characteristics of 114 doctor-managers operating within the Italian National Health Service (NHS). During the emergency, doctor-managers had to show adaptive capacities to deal with unexpected situations and develop new paradigms, procedures, and quick responses to patients' needs. This is in line with resilience, and in this perspective, it is crucial to investigate resilience determinants. The paper, therefore, provides an identikit of the resilient doctor-manager. The research was conducted between November and December 2020. Primary data were collected through an online questionnaire consisting of six sections. Participation was voluntary and anonymous. Data were analyzed using quantitative techniques and employing Stata 16. Confirmatory Factor Analysis was employed to test construct validity and scale reliability. Results show that increasing levels of individual resilience are related to increasing levels of managerial identity. Moreover, physicians' individual resilience has a positive association with commitment, knowledge diffusion, and Evidence-Based Medicine adoption. Finally, physicians' individual resilience has a negative association with their role in the university, their specialty, and their gender. The study suggests some practical implications for healtcare organizations. In general, career paths are decided primarily on competency assessment, while an important role should be devoted to behavioral characteristics. Furthermore, organizations should take care of the levels of individual commitment and encourage professional networking because both help doctor-managers cope with uncertainty. The originality of the study relies on a fresh look at all previous work. There are currently few contributions in the literature to explore and investigate resilience elements in doctor-managers during the pandemic era.

Social influence in the darknet market: The impact of product descriptions on cocaine sales

BACKGROUND

The rise of the darknet market, supported by technologies such as the Tor Browser and cryptocurrencies, has created a secure environment in which illicit transactions can occur. However, due to the lack of government oversight in this hidden online domain, darknet markets face significant challenges in upholding social order. Hence, this study explores the social dynamics that promote social order in a darknet market, focusing on the impact of item descriptions on sales. In particular, the study examines how text contained in product listings can influence sales and contribute to social order.

METHOD

To conduct this analysis, we examined 4160 cocaine listings on AlphaBay, which was active from December 2014 to July 2017 and is one of the largest darknet markets in history. Using generalised additive models (GAMs), we assessed the impact of various listing description features, including content and semantic structure, on cocaine sales.

RESULTS

The results showed that sales increased by 61.6 % when listings included delivery information in their description, compared to offers that did not. In addition, the standardised sentiment score (ranging 0,1) of the product description increased positively, and estimated sales increased by 260.5 %. We also found that international shipping reduced sales by 28.3 %. Finally, we found that listings stating the product origin increased sales for all continents except Asia.

CONCLUSION

The study sheds light on the characteristics of product advertising that facilitate social order within a darknet market. Listings that include delivery details in the description reduce uncertainty about a critical stage of the transaction process while using positive language increases trust. This study makes both an empirical and a theoretical contribution by demonstrating the influence of ad descriptions on sales and the intricate role of social influences in shaping market order.

Evaluation in design science: A framework to support project studies in the context of University Research Centres

This paper proposes a discussion of the evaluation of an artefact developed under the Design Science paradigm using the Delphi method. It evaluates the Ecosystem framework of University Research Centres in Project Studies, considering a set of criteria pre-established in the literature. The Delphi method is an evaluation implemented in an electronic platform involving twenty-one participants, among whom were academics, practitioners, and PhD candidates in the field of project management. It reached consensus and stability in two rounds: the results indicate a consensus among the participants in the applicability, novelty, simplicity, completeness, fidelity to modelled phenomena, consistency and internal coherence, scalability, flexibility, interest, elegance, and reusability criteria. Usability was the only criterion that did not attain the predefined percentage of consensus among the participants (70%). Given the framework's characteristics, Delphi participants indicated the need to produce complementary guidelines for its implementation.

Beyond Intrinsic Motivation: Why Researchers Should Consider the Full Motivation Continuum in Games for Health Research

Research within the domain of games for health has predominantly focused on individuals' intrinsic motivation characterized by an inherent enjoyment of the activity. Despite the apparent benefits of intrinsic motivation, we argue that it is imperative to adopt a more nuanced and refined perspective on motivation. Relying on the motivation continuum as outlined within Self-Determination Theory, research within this domain needs to distinguish between both intrinsic and extrinsic (i.e., external, introjected, identified, and integrated regulation) types of motivation. Researchers should, therefore, embrace instruments that assess a broader continuum of motivation rather than just intrinsic motivation alone. By doing so, future research can yield more insight into what fosters autonomous forms of motivation in the field of health-related games, including intrinsic and identified and integrated regulation.

Deep learning-aided decision support for diagnosis of skin disease across skin tones

Although advances in deep learning systems for image-based medical diagnosis demonstrate their potential to augment clinical decision-making, the effectiveness of physician-machine partnerships remains an open question, in part because physicians and algorithms are both susceptible to systematic errors, especially for diagnosis of underrepresented populations. Here we present results from a large-scale digital experiment involving board-certified dermatologists (n = 389) and primary-care physicians (n = 459) from 39 countries to evaluate the accuracy of diagnoses submitted by physicians in a store-and-forward teledermatology simulation. In this experiment, physicians were presented with 364 images spanning 46 skin diseases and asked to submit up to four differential diagnoses. Specialists and generalists achieved diagnostic accuracies of 38% and 19%, respectively, but both specialists and generalists were four percentage points less accurate for the diagnosis of images of dark skin as compared to light skin. Fair deep learning system decision support improved the diagnostic accuracy of both specialists and generalists by more than 33%, but exacerbated the gap in the diagnostic accuracy of generalists across skin tones. These results demonstrate that well-designed physician-machine partnerships can enhance the diagnostic accuracy of physicians, illustrating that success in improving overall diagnostic accuracy does not necessarily address bias.

'Is your accuser me, or is it the software?' Ambiguity and contested expertise in probabilistic DNA profiling

What happens when an algorithm is added to the work of an expert group? This study explores how algorithms pose a practical problem for experts. We study the introduction of a Probabilistic DNA Profiling (PDP) software into a forensics lab through interviews and court admissibility hearings. While meant to support experts' decision-making, in practice it has destabilized their authority. They respond to this destabilization by producing alternating and often conflicting accounts of the agency and significance of the software. The algorithm gets constructed alternately either as merely a tool or as indispensable statistical backing; the analysts' authority as either independent of the algorithm or reliant upon it to resolve conflict and create a final decision; and forensic expertise as resting either with the analysts or with the software. These tensions reflect the forensic 'culture of anticipation', specifically the experts' anticipation of ongoing litigation that destabilizes their control over the deployment and interpretation of expertise in the courtroom. The software highlights tensions between the analysts' supposed impartiality and their role in the courtroom, exposing legal and narrative implications of the changing nature of expertise and technology in the criminal legal system.

Telemedicine experiences and perspectives of healthcare providers in long-term care: A scoping review

OBJECTIVE

To consolidate existing evidence on experiences and perspectives of healthcare providers involved in telemedicine services in long-term residential care.

METHODS

A scoping review was conducted. A systematic search for articles published in 2000-2021 was performed in CINAHL, Web of Science, PubMed, EMBASE and Scopus; further, relevant journals and grey literature websites were hand searched. Key search terms included 'telemedicine', 'telehealth' and 'nursing homes'.

RESULTS

Twenty-six articles were included. A narrative synthesis of evidence was conducted. The review identified four themes: (1) Presence of multidisciplinary care, (2) perceived usefulness of telemedicine, (3) perceived ease of use and (4) expanded role of nursing home staff. The presence of multidisciplinary care providers provided a wide range of telemedicine services to residents and promoted interprofessional collaboration between acute and long-term care. Telemedicine was perceived to increase timely onsite management by remote specialists, which enabled care quality improvement. However, technical problems associated with equipment usage reduced the ease of use of telemedicine. Concerns emerged from the expanded role of nursing home staff, which could negatively affect clinical decision-making and create medico-legal risks.

CONCLUSION AND IMPLICATIONS

Telemedicine is valuable in distance-based care, especially in the current 2019 coronavirus pandemic, for supporting continuity of care to nursing home residents. This review provided evidence from multiple healthcare providers' perspectives. Further research can elucidate their specific roles and responsibilities in telemedicine and challenges in work processes, which will facilitate developing evidence-based competencies and improving technical infrastructure, thus contributing to personal and organisational readiness for telemedicine integration.

Applying the Affective Events Theory to Explore the Effect of Daily Micro-Interruptions on Mental Health: The Mediating Role of Affect and the Moderating Role of Pets at Work

This study relied on the affective events theory and the social exchange theory to develop a framework that explains how situational factors (daily micro-interruptions) enhance affective reactions (negative affect) and, in turn, impair health conditions (mental health) at work. We further delineate theoretical arguments to propose the pet-human's health effect by demonstrating that pets are boundary conditions that attenuate this relation, and as such are protective conditions for employees' mental health. We conducted a 5-day diary study with two groups of participants, one with participants who owned pets (N = 82 x 5 = 410), and the other who did not own pets (N = 87 x 5 = 435). The multilevel results showed an indirect effect of daily micro-interruptions on individuals' mental health through negative affect, with a daily backdrop of poorer mental health for those who did not own a pet (compared to those who owned a pet). These results evidence the benefits of owning a pet for individuals' mental health, even at work, and as such provide recommendations for teleworking practices. Moreover, this study resorts to an innovative and robust data collection method to demonstrate the pet-human' health effect. This study expands knowledge on the role of pets in working daily routines and shows that pets may be a personal resource for individuals while working.

Digital transformation and corporate financialization in emerging markets: Evidence from China

Corporate financialization poses serious challenges to the development of the real economy. In the context of promoting the deep integration of the digital economy and the real economy, it is crucial to explore whether digital transformation can inhibit corporate financialization. Using data from Chinese listed companies from 2009 to 2021, we construct a fixed effects model and find that digital transformation significantly reduces the level of corporate financialization, a conclusion that still holds after a series of robustness tests such as propensity score matching and adding control variables. Channel analysis shows that that digital transformation inhibits corporate financialization by enhancing the information mobility and operational capability of corporations. In addition, this effect is more pronounced at higher levels of industry competition as well as marketization. Finally, we also find structural differences in the impact of digital transformation on corporate financialization. Our study explores the determinants of corporate financialization in terms of a firm's mode of operation and type of strategy, and the findings provide a theoretical basis for the active development of digital technologies in emerging markets that are undergoing economic transitions, as well as for guarding against the shift of the economy from the real to the virtual.

An Environmental Uncertainty Perception Framework for Misinformation Detection and Spread Prediction in the COVID-19 Pandemic: Artificial Intelligence Approach

BACKGROUND

Amidst the COVID-19 pandemic, misinformation on social media has posed significant threats to public health. Detecting and predicting the spread of misinformation are crucial for mitigating its adverse effects. However, prevailing frameworks for these tasks have predominantly focused on post-level signals of misinformation, neglecting features of the broader information environment where misinformation originates and proliferates.

OBJECTIVE

This study aims to create a novel framework that integrates the uncertainty of the information environment into misinformation features, with the goal of enhancing the model's accuracy in tasks such as misinformation detection and predicting the scale of dissemination. The objective is to provide better support for online governance efforts during health crises.

METHODS

In this study, we embraced uncertainty features within the information environment and introduced a novel Environmental Uncertainty Perception (EUP) framework for the detection of misinformation and the prediction of its spread on social media. The framework encompasses uncertainty at 4 scales of the information environment: physical environment, macro-media environment, micro-communicative environment, and message framing. We assessed the effectiveness of the EUP using real-world COVID-19 misinformation data sets.

RESULTS

The experimental results demonstrated that the EUP alone achieved notably good performance, with detection accuracy at 0.753 and prediction accuracy at 0.71. These results were comparable to state-of-the-art baseline models such as bidirectional long short-term memory (BiLSTM; detection accuracy 0.733 and prediction accuracy 0.707) and bidirectional encoder representations from transformers (BERT; detection accuracy 0.755 and prediction accuracy 0.728). Additionally, when the baseline models collaborated with the EUP, they exhibited improved accuracy by an average of 1.98% for the misinformation detection and 2.4% for spread-prediction tasks. On unbalanced data sets, the EUP yielded relative improvements of 21.5% and 5.7% in macro-F1-score and area under the curve, respectively.

CONCLUSIONS

This study makes a significant contribution to the literature by recognizing uncertainty features within information environments as a crucial factor for improving misinformation detection and spread-prediction algorithms during the pandemic. The research elaborates on the complexities of uncertain information environments for misinformation across 4 distinct scales, including the physical environment, macro-media environment, micro-communicative environment, and message framing. The findings underscore the effectiveness of incorporating uncertainty into misinformation detection and spread prediction, providing an interdisciplinary and easily implementable framework for the field.

A survey of deep learning applications in cryptocurrency

This study aims to comprehensively review a recently emerging multidisciplinary area related to the application of deep learning methods in cryptocurrency research. We first review popular deep learning models employed in multiple financial application scenarios, including convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning. We also give an overview of cryptocurrencies by outlining the cryptocurrency history and discussing primary representative currencies. Based on the reviewed deep learning methods and cryptocurrencies, we conduct a literature review on deep learning methods in cryptocurrency research across various modeling tasks, including price prediction, portfolio construction, bubble analysis, abnormal trading, trading regulations and initial coin offering in cryptocurrency. Moreover, we discuss and evaluate the reviewed studies from perspectives of modeling approaches, empirical data, experiment results and specific innovations. Finally, we conclude this literature review by informing future research directions and foci for deep learning in cryptocurrency.

Knowledge Transfer Within Organizations: Mechanisms, Motivation, and Consideration

Knowledge transfer-the extent to which one unit learns from or is affected by the experience of another-has the potential to improve the performance of organizations. Through knowledge transfer, developments made in one unit of an organization can benefit others. Studies have found, however, considerable variation in the extent to which knowledge transfers across organizational units. In some cases, knowledge transfers seamlessly, whereas in others, knowledge transfer is far from complete. This article reviews research with the aim of explaining the variation observed in knowledge transfer. Key factors identified as explaining the variation include knowledge transfer opportunities, knowledge characteristics, mechanisms for knowledge transfer, motivation for transfer, and the depth of consideration of knowledge. These factors are integrated into a theoretical framework that predicts when knowledge transfer will be successful. The article concludes with a discussion of directions for future research to increase our understanding of knowledge transfer in organizations.

The impact of environmental regulatory instruments on agribusiness technology innovation-A study of configuration effects based on fsQCA

This paper investigates the complex causal relationships between various types of environmental regulatory instruments (ERI) and agri-firms' technological innovation employing fuzzy set qualitative comparative analysis (fsQCA). The study finds a well-designed set of ERI can promote technological innovation in agribusiness; control-command ERI cannot promote technological innovation in agribusiness solely, market-incentivized ERI is indispensable in promoting firms' innovation performance, implicit ERI plays an important role in promoting firms' innovation and voluntary ERI does not play a significant role in promoting firms' technological innovation. The government should coordinate among various types of ERI and improve the design of ERI to achieve a win-win situation for both economic and environmental performance in the agriculture sector.

Systematic review using a spiral approach with machine learning

With the accelerating growth of the academic corpus, doubling every 9 years, machine learning is a promising avenue to make systematic review manageable. Though several notable advancements have already been made, the incorporation of machine learning is less than optimal, still relying on a sequential, staged process designed to accommodate a purely human approach, exemplified by PRISMA. Here, we test a spiral, alternating or oscillating approach, where full-text screening is done intermittently with title/abstract screening, which we examine in three datasets by simulation under 360 conditions comprised of different algorithmic classifiers, feature extractions, prioritization rules, data types, and information provided (e.g., title/abstract, full-text included). Overwhelmingly, the results favored a spiral processing approach with logistic regression, TF-IDF for vectorization, and maximum probability for prioritization. Results demonstrate up to a 90% improvement over traditional machine learning methodologies, especially for databases with fewer eligible articles. With these advancements, the screening component of most systematic reviews should remain functionally achievable for another one to two decades.

Intra- and Inter-Individual Associations of Family-to-Work Conflict, Psychological Distress, and Job Satisfaction: Gender Differences in Dual-Earner Parents during the COVID-19 Pandemic

The COVID-19 pandemic changed the work-family interface dynamics in some families. For couples who kept earning a double income during the pandemic, their family demands may entail a loss of psychological resources that affect the work domain. This study explored the intra-individual and inter-individual (crossover) direct and indirect effects of family-to-work conflict (FtoWC) on psychological distress and job satisfaction in a non-probabilistic sample of 860 different-sex dual-earner parents with adolescent children from Temuco and Rancagua, Chile. Mothers and fathers answered an online questionnaire measuring FtoWC, the Depression, Anxiety, and Stress Scale, and the Overall Job Satisfaction Scale. The data were analyzed using the actor-partner interdependence model with structural equation modeling. Results showed that a higher FtoWC is linked to greater psychological distress and lower job satisfaction in both parents. In contrast, psychological distress is directly linked to lower job satisfaction in fathers. In both fathers and mothers, they and their partners' FtoWC were indirectly linked to lower job satisfaction via the fathers' psychological distress. These findings indicate the need for gender-sensitive social and labor policies aimed at reducing the conflict between family and work to increase job satisfaction in both parents and reduce psychological distress, particularly in fathers.

Research on the evaluation and configuration path of China's rural common Prosperity-NCA and fsQCA based on provincial panel data

Based on 2013-2019 panel data covering 31 provinces and cities in China, this paper uses the entropy weight technique for order of preference by similarity to ideal solution (TOPSIS) method to measure rural common prosperity (CP). Based on the global and local Moran's I methods, we analyze the dynamic evolutionary characteristics of China's rural CP and the regional differences. Additionally, we use the necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) methods to explore how six antecedents at the technology-organization-environment (TOE) level interact to affect CP. This research finds that, first, China's rural CP showed a fluctuating upward trend, with the highest level of CP in rural areas in the eastern region, followed by the central and western regions. Additionally, the gap between the three gradually narrowed. Second, China's rural CP had "high-high" and "low-low" agglomeration characteristics, with positive spatial autocorrelation, no transition changes, and strong spatial stability. Third, individual digital economic elements and organizational and environmental elements were not necessary conditions for promoting rural CP. Fourth, the multiple concurrent factors of the digital economy, organizations and the environment constituted three diversified configurations of rural CP, showing that the driving path of rural CP was characterized by "different paths that lead to the same goal". Moreover, "perfect digital facilities" and "high entrepreneurial activity" had a universal role in promoting rural CP. The conclusions of this research hold important theoretical and practical significance for improving China's rural CP.

From atoms to bits: Resource mobilization of non-digital, hybrid, and digital cleantech startups

Climate change is one of the most critical challenges to tackle in this century, where innovations developed and commercialized by cleantech startups are crucial contributors to achieve emission reduction targets. Entrepreneurship scholars have long presumed that resource mobilization is essential for startups to transit successfully through the conception and commercialization life cycle stages. Yet, we have a limited understanding of how resource mobilization varies across the three startups types of non-digital, hybrid - an intermediate type of non-digital and digital startups -, and digital cleantech startups. Drawing on insights from 16 semi-structured interviews with startups, investors, and industry experts in the U.S. cleantech industry, as well as secondary data, this study provides a novel framework that identifies the resource mobilization approaches of cleantech startups disentangled by the three startup types. The findings indicate that non-digital cleantech startups face the most severe resource mobilization challenges, followed by hybrid and digital cleantech startups, respectively. The study contributes to the literature on resource mobilization of cleantech startups and digital entrepreneurship. It also outlines implications for startups and venture capital investors as practitioners as well as for policymakers.

Social media use and social capital: Social media usage habits and perceptions of school administrators

Social media allows people to spend time together online and interact and connect. The relationship between well-being and social media usage is being studied more and more because it affects many areas and is discussed from different aspects. In this study, a complete count was made, and an online questionnaire was applied to all 1282 school administrators working at Antalya Provincial National Education public schools. Results reveal how the social media usage habits and social media perceptions of school administrators are, and accordingly how social media may help fertilize their social capital and establishing a healthy work environment. In light of the findings, social media usage habits are gathered under four dimensions: research/information, entertainment, recognition, and development. These gratified needs are the key elements of building one's social capital.

Can Positive Emotions Predict Consumer Satisfaction in Adverse Services?

Background

Managing emotions during hospital visits is important to enhance patient satisfaction. The purpose of this paper is to explore the relationship between patients' happiness and satisfaction through patients' mood and perceived service quality at a healthcare setup.

Methods

This study was conducted in a tertiary care hospital located in coastal Karnataka during the period from November to December 2021. Primary data was collected through a structured questionnaire from 227 respondents. "Statistical Package for the Social Sciences (SPSS) 27.0" and "SmartPLS 3.0" software was used for data analysis.

Results

Hypotheses proposed in this study were examined by comparing the direct effect of patients' happiness level on perceived service quality and the indirect effect of the level of patients' happiness on patient satisfaction. The influence of all the exogenous latent variables namely, happiness, mood, perceived service quality, on the endogenous latent variable of patient satisfaction is estimated to be moderate (R 2=62.5%).

Conclusion

This study empowers hospital managers to recognize how patient satisfaction is dependent on patients' happiness. In order to enhance patient satisfaction, the quality of care provided by health services, human resources, and infrastructure must be improved. As a result, the entire service encounter can be made enjoyable to the customers by reducing the distress caused by adverse services. Managers can utilize the outcomes of the study to develop marketing strategies to influence patients' emotions in the healthcare setup by modifying the servicescape elements.

Predictive Model of the Relationship between Positive and Negative Affect, Self-Consciousness of Appearance, and Positive Body Image in Physical Exercise Practice

The biopsychosocial development of individuals is influenced by body image and physical exercise. This study aimed to evaluate seven hypotheses regarding the impact of positive affect, negative affect, self-consciousness of appearance, and positive body image on the practice of physical exercise. The data were processed using the statistical package SmartPLS 4.0.9.5. Using an exploratory methodology based on structural equation modeling (SEM) of structural equations applied to small sample sizes, a tentative model has been generated to define the drivers of physical activity. The survey used the Body Mass Index, Body Appreciation Scale-Revised, and Derriford Appearance Scale-14 items. The study involved 129 men and 279 women (N = 408). The model demonstrated a distinct internal consistency in that, out of the seven hypotheses analyzed, only one was rejected. The findings of the multigroup analysis indicate that there are no statistically significant discrepancies between the constructed measures and the practice of physical activity. The conclusions of this study showed that, although positive and negative affect, and self-consciousness influence positive body image, there were no statistically significant differences between those who exercise and those who do not exercise. Various factors influence biopsychosocial development. Future studies should explore the influence of psychological and social variables on understanding body image and physical exercise.

Privacy Concerns About Sharing General and Specific Health Information on Twitter: Quantitative Study

BACKGROUND

Twitter is a common platform for people to share opinions, discuss health-related topics, and engage in conversations with a wide audience. Twitter users frequently share health information related to chronic diseases, mental health, and general wellness topics. However, sharing health information on Twitter raises privacy concerns as it involves sharing personal and sensitive data on a web-based platform.

OBJECTIVE

This study aims to adopt an interactive approach and develop a model consisting of privacy concerns related to web-based vendors and web-based peers. The research model integrates the 4 dimensions of concern for information privacy that express concerns related to the practices of companies and the 4 dimensions of peer privacy concern that reflect concerns related to web-based interactions with peers. This study examined how this interaction may affect individuals' information-sharing behavior on Twitter.

METHODS

Data were collected from 329 Twitter users in the United States using a web-based survey.

RESULTS

Results suggest that privacy concerns related to company practices might not significantly influence the sharing of general health information, such as details about hospitals and medications. However, privacy concerns related to companies and third parties can negatively shape the disclosure of specific health information, such as personal medical issues (β=-.43; P<.001). Findings show that peer-related privacy concerns significantly predict sharing patterns associated with general (β=-.38; P<.001) and specific health information (β=-.72; P<.001). In addition, results suggest that people may disclose more general health information than specific health information owing to peer-related privacy concerns (t165=4.72; P<.001). The model explains 41% of the variance in general health information disclosure and 67% in specific health information sharing on Twitter.

CONCLUSIONS

The results can contribute to privacy research and propose some practical implications. The findings provide insights for developers, policy makers, and health communication professionals about mitigating privacy concerns in web-based health information sharing. It particularly underlines the importance of addressing peer-related privacy concerns. The study underscores the need to build a secure and trustworthy web-based environment, emphasizing the significance of peer interactions and highlighting the need for improved regulations, clear data handling policies, and users' control over their own data.

Motivation crowding effects on the intention for continued use of gamified fitness apps: a mixed-methods approach

It has become an emerging idea for fitness apps to be gamified to intrinsically and extrinsically motivate user's usage intention or behavior. For the long-term success of gamified fitness apps, understanding what and how various motivations affect continued use is critical. A combination of qualitative and quantitative methodologies was used to explore two research questions concerning gamified fitness applications. Specifically, the research questions focused on understanding the impacts of intrinsic and extrinsic motivations on continued usage. Additionally, the study aimed to investigate whether extrinsic motivations enhance or diminish the influence of intrinsic motivations. Results from qualitative study identified three intrinsic motivations (self-development, self-control and hedonic motivation) and two extrinsic motivations (social recognition and financial reward) in gamified fitness apps. Results from quantitative study indicated that intrinsic motivations (formed by self-development, self-control and hedonic motivation), financial reward and social recognition could significantly improve intention for continued use; and further, both financial reward and social recognition could crowd-in intrinsic motivations. This research offers insights into the phenomenon of motivation crowding effects on the intention to continue using gamified fitness apps.

A Sustainable Model for Healthcare Systems: The Innovative Approach of ESG and Digital Transformation

In recent years, the globe has faced a series of topics of growing concern, such as the COVID-19 pandemic, the international financial crisis, rising socio-economic inequalities, the negative outcomes of greenhouse gas emissions, which resulted in climate change, and many others. Organizations worldwide have confronted these new challenges of sustainable finance by incorporating environmental, social, and corporate governance (ESG) factors and digital transformation (DT) in their innovation business strategies. The healthcare sector represents a large share of the global economy (about 10% of global economic output), employs a large number of workers, and needs to rely more on an open innovation model where interested parties, especially patients, are going to have a say in their own well-being. Thus, it is imperative that healthcare providers be efficient, effective, resilient, and sustainable in the face of significant challenges and risks. At the same time, they must offer sustainable development goals and digital transformation to healthcare users through limited governmental resources. This study investigates the role, importance, and correlation of ESG factors and digital transformation to the sustainable finance of healthcare systems through an innovative model. The main purpose of the paper is to present the already implemented ESG and DT factors in the healthcare sector and to propose a mutual and combined implementation strategy based on common evaluation tools, methods, and actions. A set of proposed actions and strategies are presented for the sustainability and resilience of the healthcare sector.

How article category in Wikipedia determines the heterogeneity of its editors

Collaboration is essential to advancing knowledge and, ultimately, entire societies. With the development of Web 2.0, the possibilities have risen to unprecedented levels and allowed for the collaborative creation of the world's largest compendium of knowledge that ever existed - Wikipedia. Collaboration is not a safeguard of quality per se, however. Rather, the quality of Wikipedia articles rises with the number of editors per article as well as a greater diversity among them. Here, we address a not yet documented potential threat to those preconditions: self-selection of Wikipedia editors to articles. Specifically, we expected articles with a clear-cut link to a specific country (e.g., about its highest mountain, "national" article category) to attract a larger proportion of editors of that nationality when compared to articles without any specific link to that country (e.g., "gravity", "universal" article category), whereas articles with a link to several countries (e.g., "United Nations", "international" article category) should fall in between. Across several language versions, hundreds of different articles, and hundreds of thousands of editors, we find the expected effect within Wikipedia: The more exclusively an article topic is linked to a particular nation, the higher the proportion of editors from that country is among the contributors.

The willingness and influencing factors to choose institutional elder care among rural elderly: an empirical analysis based on the survey data of Shandong Province

BACKGROUND

The ageing of the population has become an escalating problem in China, which has led to an increasing demand for healthcare throughout society. The care services of elderly institutions, as a more mature way of aging, can alleviate various social problems brought about by ageing to a certain extent. The aim of this paper is to explore the degree of acceptance of institutional care by rural elderly people in Shandong Province and the factors that influence whether rural elderly people accept institutional care services.

METHODOLOGY

Based on the theory of planned behavior, an analytical framework was constructed for the willingness of rural elderly people to receive nursing services from elderly care institutions. Using survey data from 192 rural elderly people in Shandong Province, descriptive statistics, binary logistic regression, and horizontal comparative analysis methods were used to analyze the willingness of rural elderly people to provide for the elderly and its influencing factors.

RESULT

Only 17.71% of respondents expressed willingness to receive services from elderly care institutions. Among them, education level, trust in elderly care institutions, and support from adult children have a significant positive impact on whether rural elderly people receive nursing services from elderly care institutions; The number of children, the level of understanding of elderly care institutions, neighbors' choices of elderly care methods, and their ability to contribute to the family have a significant negative impact on whether rural elderly people receive nursing services from elderly care institutions. There are significant differences in the willingness and influencing factors of rural elderly people to provide for the elderly among different regions.

CONCLUSION

The non-acceptance of institutional care by rural older people is a general phenomenon rather than a sample characteristic, thus justifying the supplementary status of institutional care services. The pension intention of the rural elderly in Shandong Province is obviously affected by personal will factors, and the influencing factors are various. The traditional concept of old-age care in Shandong province has a strong path-dependent effect on the choice of the rural elderly. There is heterogeneity in the willingness and influencing factors of the rural elderly in different regions and countries. Based on this, this paper puts forward the following suggestions: strengthen the spiritual and cultural construction of residents; The government should pay attention to the correct guidance of public opinion; And increase pension subsidies. It is hoped that reduce the burden of national elderly care through these suggestions.

The Effect of Characteristics of Patient Communication on Physician Feedback in Online Health Communities: An Observational Cross-Sectional Study

With the rapid development of e-health and telemedicine, previous studies have explored the relationship between physician-patient communication and patient satisfaction; however, there is a paucity of research on the influence of the characteristics of patient communication on the characteristics of physician feedback. Based on the communication accommodation theory, as well as the computer-mediated communication theory and media richness theory, this study aimed to explore how characteristics of patient communication influence characteristics of physician feedback in online health communities. We employed a crawler software to download the communication data between 1652 physicians and 105,325 patients from the Good Doctor platform, the biggest online health community in China. We built an empirical model using this data and employed a multilevel model to test our hypotheses using Stata and Python software. The results indicate that the amount of patients' rendered information positively influences the physicians' text (α = 0.123, t = 33.147, P < .001) and voice feedback (β = 0.201, t = 40.011, P < .001). Patients' hope for help signals and the provision of their electronic health records weaken the effect of the amount of patients' rendered information on physicians' text feedback (α = -0.040, t = -24.857, P < .001; α = -0.048, t = -15.784, P < .001), whereas, it strengthened the effect of the amount of patients' rendered information on physicians' voice feedback (β = 0.033, t = 14.789, P < .001; β = 0.017, t = 4.208, P < .001). Moreover, the occurrence of high-privacy diseases strengthened the effect of the amount of patients' presented information on physicians' text and voice feedback (α = 0.023, t = 4.870, P < .001; β = 0.028, t = 4.282, P < .001). This research contributes to the development of computer-mediated communication theories and sheds light on service delivery in the online health community.

The acceptance and attitudes towards using assistive technology for people with stroke in Jordan: caregivers' perspectives

The aim of this study is to evaluate the acceptance and attitudes toward assistive technology (AT) for people with stroke from their caregivers' perspectives in Jordan. Also, this study further validates the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire. This is a cross-sectional study that includes a three-sections survey: the first section contains demographic data, the second section includes the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire, and the third section consists of two optional open-ended questions. Among 123 caregivers of people with stroke over 18 years of age who participated in this study, 23% were male. The findings indicate a moderate to high acceptance of using AT for stroke survivors, confirm the validity and reliability of the UTAUT questionnaire, and clarify novel issues regarding AT based on the caregivers' perspectives.

Academics' continuance intention to use learning technologies during COVID-19 and beyond

The COVID-19 pandemic has revolutionized the teaching pedagogy in higher education as universities are forecasted to increase investments in learning technology infrastructure to transition away from traditional teaching methods. Therefore, it is crucial to investigate whether academics intend to continually integrate learning technologies as part of a permanent pedagogical change beyond the COVID-19 pandemic. Drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT), and Expectation Confirmation Model (ECM), this study examines the salient determinants influencing the continuance intention of academics to use learning technologies in their teaching pedagogy during and after COVID-19. Primary data collected from a private university was analyzed using the partial least squares structural equation modelling technique (PLS-SEM). The findings revealed two sequential mediating relationships which serve as the mechanism linking the relationship between facilitating conditions and their continuance intention to use learning technologies during and beyond the COVID-19 pandemic.

Sorting Insiders From Co-Workers: Remote Synchronous Computer-Mediated Triage for Investigating Insider Attacks

OBJECTIVE

Develop and investigate the potential of a remote, computer-mediated and synchronous text-based triage, which we refer to as InSort, for quickly highlighting persons of interest after an insider attack.

BACKGROUND

Insiders maliciously exploit legitimate access to impair the confidentiality and integrity of organizations. The globalisation of organisations and advancement of information technology means employees are often dispersed across national and international sites, working around the clock, often remotely. Hence, investigating insider attacks is challenging. However, the cognitive demands associated with masking insider activity offer opportunities. Drawing on cognitive approaches to deception and understanding of deception-conveying features in textual responses, we developed InSort, a remote computer-mediated triage.

METHOD

During a 6-hour immersive simulation, participants worked in teams, examining password protected, security sensitive databases and exchanging information during an organized crime investigation. Twenty-five percent were covertly incentivized to act as an 'insider' by providing information to a provocateur.

RESULTS

Responses to InSort questioning revealed insiders took longer to answer investigation relevant questions, provided impoverished responses, and their answers were less consistent with known evidence about their behaviours than co-workers.

CONCLUSION

Findings demonstrate InSort has potential to expedite information gathering and investigative processes following an insider attack.

APPLICATION

InSort is appropriate for application by non-specialist investigators and can be quickly altered as a function of both environment and event. InSort offers a clearly defined, well specified, approach for use across insider incidents, and highlights the potential of technology for supporting complex time critical investigations.

Exploring nationwide policy interventions to control COVID-19 from the perspective of the rapid learning health system approach

Introduction

The health systems needed to improve their learning capacities during the COVID-19 pandemic. Iran is one of the countries massively struck by the pandemic. This study aimed to explore whether and how the policy interventions made by Iran's policymakers at the national level to control COVID-19, could improve the rapid learning characteristics of the health system.

Methods

A guide to clarify rapid learning health system (RLHS) characteristics was developed. The guide was used by two independent authors to select the policy interventions that could improve RLHS characteristics, then, to analyze the content of the selected policy interventions. In each stage, results were compared and discussed by all three authors. Final results were presented based on different RLHS characteristics and the potential mechanisms of contribution.

Results

Five hundred policy interventions were developed during the first 7 months of the outbreak. Thirty-one policy interventions could potentially improve RLHS characteristics (6.2%). Two characteristics, such as the timely production of research evidence and the appropriate decision support were addressed by selected policy interventions. Policies, that could improve learning capacities, focused on decision-maker groups more than user groups or researcher groups.

Conclusions

Most of the developed policy interventions during the first months of the epidemic did not address the learning capacities of the health system. To improve health system functions, improving RLHS characteristics of the health system, especially in patient-centered and data linkage characteristics, is recommended.

Empirical Evidence of Internal and External Factors Influencing Users' Motivation Toward Teleconsultation Use

Introduction: The use of teleconsultation systems has increased in recent years, which has improved patients' access to health care providers and enabled seamless interaction between them. The literature points out several factors that either facilitate or impede the use of teleconsultation. However, there is a lack of studies that provide empirical evidence of factors that influence consumers' motivation toward the use of teleconsultation systems. Aim and Objective: This study aimed to provide empirical evidence of the internal and external factors that influence consumers' motivation toward the use of teleconsultation systems. Methods: A cross-sectional survey was used to collect data from consumers who used a real-time teleconsultation system called the Sehha application in Saudi Arabia between March 13 and June 14, 2021. SPSS 27.0.1 was used for descriptive analysis. Results: Four hundred eighty-five participants completed the survey, 471 of whom were included in the analysis. The findings confirmed that internal and external factors exert an influence on consumers' motivation toward the use of teleconsultation systems. The findings indicated that the presence of factors such as saving time, saving cost, accessibility to health care, ease-of-use, reliable internet access, availability of devices, and appropriate places during the online connection would increase consumers' motivation toward teleconsultation systems use. Also, the findings indicated that users' familiarity with systems similar to teleconsultation systems, users' perception of teleconsultation convenience, the influence of others on users' decision to use teleconsultation, and user's skills and confidence in using teleconsultation easily, and their trust in the teleconsultation system would also increase their motivation to use it. Furthermore, the findings showed that demographic factors, including age, gender, level of education, and employment status, did not influence users' motivation toward the use of teleconsultation Conclusions: This study provided empirical evidence of a variety of internal and external factors that exert an influence on consumers' motivation toward the use of teleconsultation systems.

Examining information systems use to facilitate the workplace accommodation process

BACKGROUND

The workplace accommodation process is often affected by ineffective and inefficient communications and information exchanges among disabled employees and other stakeholders. Information systems (IS) can play a key role in facilitating a more effective and efficient accommodation process since IS has been shown to facilitate business processes and effect positive organizational changes.

OBJECTIVE

Since there is little to no research that exists on IS use to facilitate the workplace accommodation process, this paper, as a critical first step, examines how IS have been used in the accommodation process.

METHODS

Thirty-six interviews were conducted with disabled employees from various organizations. Open, axial, and selective coding were part of the analysis. Fuzzy set qualitative comparative analysis was used to identify different levels of IS use based on participants' descriptions.

RESULTS

An IS used in the workplace accommodation process consists of electronic request form, accommodation checklist, special budget, specific role, ancillary service, formal policy and procedure. There are different levels of IS use in the current accommodation process. The high-level IS use often results in a better accommodation performance than the low-level IS use, including high efficiency, high effectiveness, and low emotional tolls. Nevertheless, the high-level IS use often uses a specific, inflexible template as well as disregards human elements in the accommodation process.

CONCLUSION

This work provides implications that future IS design should raise awareness of disability and accommodation, account for individual differences, involve multiple stakeholder inputs, as well as address the fundamental social issues in the accommodation process.

Association between digital engagement and urban-rural disparities in Chinese women's depressive symptoms: A national-level cross-sectional study

Objectives

This study aims to investigate the impact of digital engagement on urban-rural disparities in depressive symptoms among Chinese women.

Methods

Using a dataset from the China Family Panel Studies (CFPS) wave 2020, this study analyzes the impact of digital engagement on the urban-rural disparity in women's depressive symptoms using multiple linear regression and recentered influence function (RIF) models. Furthermore, the extent to which digital engagement affects the urban-rural disparity in women's depressive symptoms was calculated using the RIF decomposition method.

Results

Analysis showed that rural women had significantly higher levels of depressive symptoms compared to urban women; digital engagement significantly reduced women's depressive symptoms levels and mitigated the urban-rural disparity for women with moderate to high levels of depressive symptoms, and the mitigating effect was stronger for the highly depressed sample, but still widened the urban-rural disparity in women's depressive symptoms overall. In addition, the results of the RIF decomposition showed that digital engagement explained 28.28% of the urban-rural disparity in women's depressive symptoms.

Conclusion

There is a significant disparity in depressive symptoms levels between urban and rural women in China. Digital engagement reduces women's depressive symptoms, but it also widens the depressive symptoms disparity between urban and rural women overall. Digital engagement is potentially positive for reducing women's depressive symptoms.

Strategy development to increase consumer intention of purchasing prescription drugs through e-pharmacy in Indonesia

BACKGROUND

The global COVID-19 pandemic has forced people to obtain health products and services from home. Similar to other e-commerce, medicines are bought online and delivered using a courier service.

OBJECTIVE

By being fully concerned to patient safety, this study aims to determine development strategies to increase intention in purchasing prescription drugs through e-pharmacy.

METHODS

Two stages of measurement are employed in this study, namely confirmatory factor analyis using PLS-SEM and pairwise comparison using AHP method. To discover consumer perception in using e-pharmacy, the basic model of Theory of Planned Behavior (TPB) is employed with several extensions.

RESULTS

The results of PLS-SEM express that Trust has a major role as an intervening variable to enhance the indirect effect of Subjective Norms and Perceived Values on Purchase Intention. In general, PLS-SEM structural model is declared "fit" (GFI = 0.93 ≥ 0.90; RMSEA = 0.045 ≤ 0.08; SRMR = 0.033 ≤ 0.05). Measurement model test proves that all selected indicators are valid to represent their related constructs (Loading Factor ≥ 0.50), and all selected constructs are reliable to build the whole path model (CR ≥ 0.7; AVE ≥ 05). Meanwhile, the results of AHP indicate that strengthening government policies and regulations is prioritized to increase consumer intention of purchasing prescription drugs through e-pharmacy, followed by protection of user confidential data in the second place. Those two eigenvectors are 0.236 and 0.185 respectively.

CONCLUSION

Future research is suggested to add perceived risk as latent variable in the study of consumer behavior for any high-risk products.

Use of Social Media in Orthopaedic Surgery Training and Practice: A Systematic Review

Background

Social media use has grown across healthcare delivery and practice, with dramatic changes occurring in response to the coronavirus (COVID-19) pandemic. The purpose of this study was to conduct a comprehensive systematic review to determine the current landscape of social media use by (1) orthopaedic surgery residencies/fellowship training programs and (2) individual orthopaedic surgeons and the change in use over time.

Methods

We searched 3 electronic databases (PubMed, MEDLINE, and Embase) from their inception to April 2022 for all studies that analyzed the use of social media in orthopaedic surgery. Two reviewers independently determined study eligibility, rated study quality, and extracted data. Methodology was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Results

Twenty-eight studies were included, of which 11 analyzed social media use by orthopaedic surgery residency and fellowship training programs and 17 examined its use by individual orthopaedic surgeons. Among residency and fellowship programs, Instagram was identified as the most common platform used, with 42% to 88% of programs reporting program-specific Instagram accounts, followed by Twitter/X (20%-52%) and Facebook (10%-38%). Social media was most commonly used by programs for recruitment and information dissemination to prospective residency applicants (82% and 73% of included studies, respectively). After the start of the COVID-19 pandemic, there was a 620% and 177% increase in the number of training programs with Instagram and Twitter/X accounts, respectively. Individual use of social media ranged from 1.7% to 76% (Twitter/X), 10% to 73% (Facebook), 0% to 61% (Instagram), 22% to 61% (LinkedIn), and 6.5% to 56% (YouTube).

Conclusions

Instagram, Twitter/X, and Facebook are the premier platforms that patients, residency applicants, and institutions frequent. With the continued growth of social media use anticipated, it will be critical for institutions and individuals to create and abide by guidelines outlining respectful and professional integration of social media into practice.

Level of Evidence

Level IV.

The Store-and-Forward Telemedicine Service User-satisfaction Questionnaire: Development and validation of a questionnaire to monitor and assess health care providers' experiences

INTRODUCTION

With wider adoption of store-and-forward telemedicine accelerating, particularly post-coronavirus disease 2019, it is essential to understand health care providers' (HCPs) satisfaction with digital solutions offered by telemedicine organizations to (continuously) guarantee service quality. We developed the Store-and-Forward Telemedicine Service User-satisfaction Questionnaire to monitor and assess HCPs' experiences with contracted telemedicine organizations.

METHODS

Questionnaire construction (phase 1) consisted of exploratory literature search on validated telemedicine satisfaction questionnaires, a telemedicine domain and human factors expert focus group, stakeholder focus group (customer service employee and telemedicine account managers), and two pre-testing rounds among 18 HCPs. The pilot questionnaire (phase 2) was sent to 2179 HCPs for validity and reliability assessment.

RESULTS

Phase 1: Two validated questionnaires (73 items overall) were used as input for Store-and-Forward Telemedicine Service User-satisfaction Questionnaire. Revisions resulted in 61 items. Phase 2: the pilot 61-item Store-and-Forward Telemedicine Service User-satisfaction Questionnaire instrument was completed by 181 of 2179 invited HCPs. Forty-one mandatory items of the pilot Store-and-Forward Telemedicine Service User-satisfaction Questionnaire rated on a 5-point Likert scale were included in psychometric analyses and resulted in six reliable scales: training, communication, organization policy and strategy, interaction platform, usage platform, and working conditions.

DISCUSSION

The Store-and-Forward Telemedicine Service User-satisfaction Questionnaire is a reliable and valid questionnaire for measuring HCPs' satisfaction with store-and-forward telemedicine services as part of a continuous quality improvement cycle. Reimbursement questions were excluded due to low response. As adoption of telemedicine may be impeded by financial compensation issues, this requires consideration in future telemedicine questionnaires. Store-and-Forward Telemedicine Service User-satisfaction Questionnaire including video consultation items is needed to monitor also synchronous services as these expanded in the coronavirus disease 2019 pandemic.

Review of the Factors Affecting Acceptance of AI-Infused Systems

OBJECTIVE

The study aimed to provide a comprehensive overview of the factors impacting technology adoption, to predict the acceptance of artificial intelligence (AI)-based technologies.

BACKGROUND

Although the acceptance of AI devices is usually defined by behavioural factors in theories of user acceptance, the effects of technical and human factors are often overlooked. However, research shows that user behaviour can vary depending on a system's technical characteristics and differences in users.

METHOD

A systematic review was conducted. A total of 85 peer-reviewed journal articles that met the inclusion criteria and provided information on the factors influencing the adoption of AI devices were selected for the analysis.

RESULTS

Research on the adoption of AI devices shows that users' attitudes, trust and perceptions about the technology can be improved by increasing transparency, compatibility, and reliability, and simplifying tasks. Moreover, technological factors are also important for reducing issues related to human factors (e.g. distrust, scepticism, inexperience) and supporting users with lower intention to use and lower trust in AI-infused systems.

CONCLUSION

As prior research has confirmed the interrelationship among factors with and without behaviour theories, this review suggests extending the technology acceptance model that integrates the factors studied in this review to define the acceptance of AI devices across different application areas. However, further research is needed to collect more data and validate the study's findings.

APPLICATION

A comprehensive overview of factors influencing the acceptance of AI devices could help researchers and practitioners evaluate user behaviour when adopting new technologies.

Convolutional neural network-based program to predict lymph node metastasis of non-small cell lung cancer using 18F-FDG PET

PURPOSE

To develop a convolutional neural network (CNN)-based program to analyze maximum intensity projection (MIP) images of 2-deoxy-2-[F-18]fluoro-D-glucose (FDG) positron emission tomography (PET) scans, aimed at predicting lymph node metastasis of non-small cell lung cancer (NSCLC), and to evaluate its effectiveness in providing diagnostic assistance to radiologists.

METHODS

We obtained PET images of NSCLC from public datasets, including those of 435 patients with available N-stage information, which were divided into a training set (n = 304) and a test set (n = 131). We generated 36 maximum intensity projection (MIP) images for each patient. A residual network (ResNet-50)-based CNN was trained using the MIP images of the training set to predict lymph node metastasis. Lymph node metastasis in the test set was predicted by the trained CNN as well as by seven radiologists twice: first without and second with CNN assistance. Diagnostic performance metrics, including accuracy and prediction error (the difference between the truth and the predictions), were calculated, and reading times were recorded.

RESULTS

In the test set, 67 (51%) patients exhibited lymph node metastases and the CNN yielded 0.748 predictive accuracy. With the assistance of the CNN, the prediction error was significantly reduced for six of the seven radiologists although the accuracy did not change significantly. The prediction time was significantly reduced for five of the seven radiologists with the median reduction ratio 38.0%.

CONCLUSION

The CNN-based program could potentially assist radiologists in predicting lymph node metastasis by increasing diagnostic confidence and reducing reading time without affecting diagnostic accuracy, at least in the limited situations using MIP images.

First test of the theory of reasoned goal pursuit: predicting physical activity

OBJECTIVE

This study applied the theory of reasoned goal pursuit (TRGP) in predicting physical activity among Australian undergraduate students, providing the first empirical test of the model.Methods: The research comprised an elicitation study (N = 25; MAge= 25.76, SDAge= 11.33, 20 female, 5 male) to identify readily accessible procurement and approval goal beliefs and behavioural, normative, and control beliefs; and, a two-wave prospective online survey study (N = 109; MAge = 21.88, SDAge = 7.04, 63 female, 46 male) to test the tenets of the TRGP in relation to meeting World Health Organization physical activity guidelines during the COVID-19 pandemic among first year university students.Results: A linear PLS-SEM model displayed good fit-to-data, predicting 38%, 74%, and 48% of the variance in motivation, intention, and physical activity, respectively. The model supported the majority of hypothesised pattern of effects among theory constructs; in particular, the proposition that beliefs corresponding to procurement and approval goals would be more consequential to people's motivation and, thus, their intentions and behaviour, than other behavioural and normative beliefs, respectively.Conclusions: Results lend support for the TRGP and sets the agenda for future research to systematically test the proposed direct, indirect, and moderation effects for different health behaviours, populations, and contexts.

Supplemental data for this article is available online at https://doi.org/10.1080/08870446.2022.2026946 .

Visual and steering behaviours during lane departures: a longitudinal study of interactions between lane departure warning system, driving task and driving experience

Lane Departure Warning Systems (LDWS) generate a warning in case of imminent lane departure. LDWS have proven to be effective and associated human-machine cooperation modelled. In this study, LDWS acceptance and its impact on visual and steering behaviour have been investigated over 6 weeks for novice and experienced drivers. Unprovoked lane departures were analysed along three driving tasks gradually more demanding. These observations were compared to a baseline condition without automation. The number of lane departures and their duration were dramatically reduced by LDWS, and a narrower visual spread of search during lane departure events was recorded. The findings confirmed LDWS effectiveness and suggested that these benefits are supported by visuo-attentional guidance. No specific influence of driving experience on LDWS was found, suggesting that similar cognitive processes are engaged with or without driving experience. Drivers' acceptance of LDWS lowered after automation use, but LDWS effectiveness remained stable during prolonged use.Practitioner summary: Lane Departure Warning Systems (LDWS) have been designed to prevent lane departure crashes. Here, LDWS assessment over a 6-week period showed a major drop in the number of lane departure events increasing over time. LDWS effectiveness is supported by the guidance of drivers' visual attention during lane departure events.

Doctoral Contribution to Nursing Science in Sub-Saharan Africa: A Document Review

Nursing science is at serious risk of extinction. The lack of funding for research, absence of healthcare policies underpinned by nursing science, and general lack of understanding of nursing metaparadigms all contribute to the stunted growth in nursing science. Doctoral research is a platform for the development and refinement of nursing science. The purpose of this qualitative retrospective document review was to describe the doctoral contribution to nursing in sub-Saharan Africa (SSA). Electronic dissertations for doctoral degrees in nursing within a 5-year period from universities in SSA were included. The extracted data comprising the purpose of the studies, the models used in the studies, and the studies' contributions to nursing science were analyzed against a knowledge contribution framework. In total, 166 documents were included, mostly from South African universities, with a predominant focus on developing models, frameworks, and strategies within nursing practice. Only 17% of the studies applied grand nursing theories or models, with the rest of the studies applying theories from other disciplines. The contribution to nursing science from the doctoral studies was poor. The low uptake of nursing models in doctoral research in SSA may significantly contribute to the lack of refinement of nursing science within SSA. Structured approaches focused on integrating the nursing metaparadigms, theories, and models and fundamental underpins for doctoral education in Africa are essential to influencing the refinement of nursing science.

Work interruptions of office workers: The influence of the complexity of primary work tasks on the perception of interruptions

BACKGROUND

Research demonstrates that work interruptions are considered one of the most common work stressors. Understanding the mechanisms of work interruptions is therefore vital to reducing worker stress and maintaining performance.

OBJECTIVE

The aim of this research is to investigate the influence of the frequency of work interruptions on subjective workload in the context of office work. Specifically, the mediating influence of interruption perception as well as the moderating influence of the complexity of the primary task are examined.

METHOD

The work interruptions of 492 office workers in Germany were collected by means of a one-day diary study. A mediation model and a conditional indirect effect model were calculated to examine the influence of interruption frequency on subjective workload, mediated by the individual perception of these interruptions as well as moderated by the complexity of the primary work tasks.

RESULTS

The analyses indicated a significant mediation and moderation. This implies that, on the one hand, the perception of work interruptions significantly mediates the relationship between the frequency of work interruptions and subjective workload. On the other hand, more complex primary work tasks seem to strengthen the positive relationship between interruption frequency and perceived interruption overload.

CONCLUSION

The study underlines that work interruptions need to be considered in a much more differentiated way than is currently the case. Both in research and in terms of intervention measures in the work context, the various influencing factors need to be identified for an assessment of the effects on the working person to be possible.

Factors influencing telemedicine adoption among physicians in the Malaysian healthcare system: A revisit

Background

The Malaysian healthcare system is under strain due to an aging population, the rising prevalence of chronic diseases, and heavy workloads among physicians. As costs and requirements continue to rise, telemedicine is critical for bridging gaps in supply and demand. However, there are limited studies on telemedicine adoption among Malaysian physicians. Furthermore, the existing literature on telemedicine adoption does not contain a comprehensive framework that integrates the multidimensional social influence, and technological, clinical, and individual factors.

Objective

This research investigates the adoption of telemedicine among Malaysian physicians. It draws from the Technology Acceptance Model (TAM) and Kelman's Social Influence Theory.

Methods

A survey was conducted among 230 participants in hospitals located in Kuala Lumpur and Selangor. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Results

The study identified crucial factors influencing telemedicine adoption, including informational influences, rewards, perceived ease of use, and usefulness. Meanwhile, the Importance-performance Map Analysis (IPMA) identified perceived ease of use as the most important factor for physicians, but the highest performance was patient's records.

Conclusions

The proposed integrated model enhances the understanding of telemedicine adoption and highlights the differential effects of individual, technological, clinical, and multidimensional social influence factors from the physicians' perspective. The findings can guide future studies and influence implementation strategies for telemedicine promotion in the Malaysian healthcare context. Hospitals should prioritize user-friendly technology and information provision, while telemedicine providers should enhance the accessibility of patient records to facilitate telemedicine adoption. Policymakers should consider supporting training programs that will boost physicians' confidence in effectively utilizing telemedicine.

Is information evaluated subjectively? Social media has changed the way users search for medical information

Objective

In recent years, social media platforms, such as TikTok and RedBook, have emerged as important channels through which users access and share medical information. Additionally, an increasing number of healthcare professionals have created social media accounts through which to disseminate medical knowledge. This paper explores why users obtain their medical information from social media and how the signals transmitted by social platforms affect use behaviours.

Methods

We combined the elaboration likelihood model and signal theories to construct a comprehensive model for this study. We used simple random sampling to investigate users' behaviours related to social media usage. A total of 351 valid questionnaires were completed by people in Mainland China. The participants were enthusiastic about social media platforms and had searched for health-related information on social media in the past three months. We analysed the data using partial least squares structural equation modelling to investigate the influence of two pathways and two signals (objective and subjective judgement pathways and positive and negative signals) on social media use behaviours.

Results

When seeking medical information on social media, users tend to rely on subjective judgment rather than objective judgment, although both are influential. Furthermore, in the current era, in which marketing methods involving big data algorithms and artificial intelligence prevail, negative signals, such as information overload, have a more pronounced impact than positive signals.

Conclusions

This study demonstrates that the subjective judgment path has a greater impact on users than the objective judgment path. Platforms are encouraged to focus more on users' emotional needs. The paper also discusses the negative impact of information overload on users, sounding an alarm for enterprises to control their use of homogeneous information resulting from the excessive use of big data algorithms.

What drives the vaccination intention against COVID-19? Application of EPPM, TAM, and theories of risk assessment

Vaccines are widely used to fight against COVID-19. However, COVID-19 vaccine hesitancy appears as some individuals are concerned with COVID-19 vaccines. This study investigates the vaccination intention against COVID-19 in China with the Extended Parallel Process Model (EPPM), Technology Acceptance Model (TAM), and theories of risk information assessment. Results showed that the formation mechanism of vaccination intention could be considered a psychological process, as subjective knowledge was a primary influence on correspondents' weighting of both the potentially positive (usefulness) and negative effects (threat) of vaccination. This unequal consideration then resulted in different levels of fear arousal between subjects. Driven by usefulness/threat perception and fear, people conducted different decision strategies, so-called analytical assessment, and experiential assessment to make vaccination decision. In addition to the direct effects of experiential assessment on vaccination intention, two decision strategies and fear arousal also affected people's vaccination intention through the mediation role of vaccination attitude. For policymakers and stakeholders, this study provides a knowledge base for confidence-building, and emotional guidance concerning against COVID-19 vaccination.

I Do Not Want to Miss a Thing! Consequences of Employees' Workplace Fear of Missing Out for ICT Use, Well-Being, and Recovery Experiences

As more and more employees have access to work-related information and communication technologies (ICTs) anywhere and anytime, new challenges arise in terms of well-being and recovery experiences. Feelings of workplace fear of missing Out (wFoMO) and workplace telepressure may be personal demands that add to the literature of the job demands-resources (JD-R) theory. In this study, we proposed a model in which wFoMO and workplace telepressure were associated with employee well-being variables via the use of ICTs during leisure time. Therefore, we analyzed the data of N = 130 employees who answered two questionnaires in the interval of one work week. The results revealed negative indirect effects between wFoMO/workplace telepressure and psychological detachment/perceived stress via ICT use. The results were more ambivalent regarding the dependent variables burnout, relaxation, and control. This strengthens the literature that categorized ICT use as a job demand. However, we also found positive indirect effects on perceived informational benefits, which supports the idea of ICTs being both a job demand and a job resource in light of the JD-R theory. This study contributes to past research on work-related ICT use during leisure time and demonstrates the relevance of personal demands such as wFoMO for employees' well-being.

Omnichannel integration strategy based on BOPS

Technological innovation and the upgrading of consumer preferences have greatly accelerated the rapid development of the "new retail" omnichannel model. Meeting the personalized and seamless interactive experience expected by consumers requires integrating the advantages of both offline and online channels and expanding the integrated and intelligent omnichannel layout. This has emerged as a complex problem that the industry urgently needs to address. In order to tackle this issue, we conducted a study on a Buy-Online-and-Pick-up-in-Store (BOPS) pricing game between offline stores and e-commerce departments, considering factors such as match probability and network cost of return. Furthermore, we proposed the Buy-Online-and-Pick-up-in-Store-and-Return-Online (BORO) strategy and conducted an analysis on the variation in market share and revenue levels for both offline stores and e-commerce departments under this strategy. The results demonstrate that: (i) the omnichannel strategy of BOPS can increase the revenues of both offline stores and e-commerce departments only when the distance costs are moderate; (ii) the BORO strategy provides greater benefits to offline stores compared to e-commerce departments; and (iii) the effectiveness of the BORO strategy is influenced by factors such as match probability, distance cost, and product return. This research not only provides a theoretical foundation but also practical insights for the strategic channel management of omnichannel brand merchants.

Effects of Internal and External Factors on Hospital Data Breaches: Quantitative Study

BACKGROUND

Health care data breaches are the most rapidly increasing type of cybercrime; however, the predictors of health care data breaches are uncertain.

OBJECTIVE

This quantitative study aims to develop a predictive model to explain the number of hospital data breaches at the county level.

METHODS

This study evaluated data consolidated at the county level from 1032 short-term acute care hospitals. We considered the association between data breach occurrence (a dichotomous variable), predictors based on county demographics, and socioeconomics, average hospital workload, facility type, and average performance on several hospital financial metrics using 3 model types: logistic regression, perceptron, and support vector machine.

RESULTS

The model coefficient performance metrics indicated convergent validity across the 3 model types for all variables except bad debt and the factor level accounting for counties with >20% and up to 40% Hispanic populations, both of which had mixed coefficient directionality. The support vector machine model performed the classification task best based on all metrics (accuracy, precision, recall, F1-score). All the 3 models performed the classification task well with directional congruence of weights. From the logistic regression model, the top 5 odds ratios (indicating a higher risk of breach) included inpatient workload, medical center status, pediatric trauma center status, accounts receivable, and the number of outpatient visits, in high to low order. The bottom 5 odds ratios (indicating the lowest odds of experiencing a data breach) occurred for counties with Black populations of >20% and <40%, >80% and <100%, and >40% but <60%, as well as counties with ≤20% Asian or between 80% and 100% Hispanic individuals. Our results are in line with those of other studies that determined that patient workload, facility type, and financial outcomes were associated with the likelihood of health care data breach occurrence.

CONCLUSIONS

The results of this study provide a predictive model for health care data breaches that may guide health care managers to reduce the risk of data breaches by raising awareness of the risk factors.

Optimal strategy of in-game items with conspicuous consumption: whether to provide the grinding version?

In the virtual world, whether or not to spend money on in-game items distinguishes paying players from non-paying players. Due to the existence of conspicuous psychology, paying players will greatly increase their conspicuous utility after purchasing an item in addition to the utility of the item itself. In this case, whether providing different versions of items can bring greater revenue to the game company is a question worth investigating. In this study, two analytical models considering conspicuous intensity are developed to compare the optimal pricing strategy of the game company providing the single-version item or dual-version items. The single-version item can only be purchased, while a relatively low-quality version that can be obtained by grinding is provided in the dual-version strategy. Grinding means using time in games to get items instead of spending in games. The results suggest that it is more profitable for companies to offer dual-version items when conspicuous intensity is strong. Game companies can also adjust the time needed to acquire the grinding version item and the quality gap between the two versions to achieve greater revenue. The research contributes to providing a theoretical basis and decision support for game companies to decide whether to provide different versions of in-game items.

Can digital transformation reduce corporate stock price crashes?

PURPOSE

The purpose of this paper is to study the impact of enterprises' digital transformation on the risk of stock price crashes, but also to study the mediating role of enterprises' financialization and accounting conservatism in the enterprises' digital transformation on stock price crash risk.

DESIGN/METHODOLOGY/APPROACH

Based on the data of 2,599 listed companies in China from 2010 to 2019, this paper constructs indicators of enterprise digital transformation through word frequency analysis method, and uses fixed-effects model and mediated-effects model to explore the impact and mechanism of enterprise digital transformation on the stock price crash risk.

FINDINGS

This study shows that firms' digital transformation reduces the risk of stock price crashes and that financialization of firms and accounting conservatism play a significant mediating effect between enterprises' digital transformation and the risk of stock price crashes.

ORIGINALITY/VALUE

This study enriches the study of stock price crash risk by including digital transformation in the field of stock price crash research, and it examines the mediating roles of financialization of enterprises and accounting conservatism, which provides a new explanatory mechanism to the study of the correlation between digital transformation of enterprises and the risk of stock price crash.