Research surveys and their evolution: Past, current and future uses in healthcare

Research surveys are believed to have originated in antiquity with evidence of them being performed in ancient Egypt and Greece. In the past century, their use has grown significantly and they are now one of the most frequently employed research methods including in the field of healthcare. Modern validation techniques and processes have allowed researchers to broaden the scope of qualitative data they can gather through these surveys such as an individual’s views on service quality to nationwide surveys that are undertaken regularly to follow healthcare trends. This article focuses on the evolution and current utility of research surveys, different methodologies employed in their creation, the advantages and disadvantages of different forms and their future use in healthcare research. We also review the role artificial intelligence and the importance of increased patient participation in the development of these surveys in order to obtain more accurate and clinically relevant data.

The association between internet addiction and sleep quality among medical students in Saudi Arabia

BACKGROUND

Sleep is one of the fundamental human needs, essential for maintaining a high quality of life and mental and physical well-being across all age groups. Poor sleep quality often stems from negative lifestyle habits, including excessive internet usage. Therefore, it is important to determine the prevalence of internet gaming disorder among youth in Saudi Arabia and to examine the relationship between internet addiction levels and sleep quality.

METHODS

Data were collected from 338 medical students in the southern region of Saudi Arabia (mean age = 21.2 years, standard deviation = 3.29 years). Participants completed an online questionnaire comprising the Internet Addiction Test (IAT) and the Pittsburgh Sleep Quality Index (PSQI). Data analysis employed iterations, chi-square tests, Pearson correlation coefficients, and ANOVA.

RESULTS

The results revealed that 21% of the participants exhibited severe internet addiction, while 31% displayed moderate internet addiction. Furthermore, the findings indicated a positive correlation between sleep quality and the severity of internet addiction. Sleep quality symptoms explained 75% of the variance in Internet addiction scores, even after controlling for demographic variables. Additional bivariate analyses revealed that individuals who spent six or more hours online daily were more likely to experience symptoms of poor sleep quality and exhibit a higher severity of internet addiction. Additionally, Men were more susceptible to developing internet addiction compared to women. Moreover, students with internet addiction tended to have lower academic achievements.

CONCLUSION

These findings, while exploratory, offer valuable insights into potential interventions, strategies, and programs for mitigating internet addiction and enhancing sleep quality among medical college students.

Quantifying the heterogeneity impact of risk factors on regional bicycle crash frequency: A hybrid approach of clustering and random parameter model

The existence of internal and external heterogeneity has been established by numerous studies across various fields, including transportation and safety analysis. The findings from these studies underscore the complexity of crash data and the multifaceted nature of risk factors involved in accidents. However, most studies consider the effects of unobserved heterogeneity from one perspective -- either within clusters (internal) or between clusters (external) -- and do not investigate the biases from both simultaneously on crash frequency analysis. To fill this gap, this study proposes a hybrid approach combining latent class cluster analysis with the random parameter negative binomial regression model (LCA-RPNB) to explore the association between risk factors and bicycle crash frequency. First, the bicycle crash data is categorized into three clusters using LCA based on crash features such as gender, trip purposes, weather, and light conditions. Then, the separated crash frequency models for different clusters and the overall model are developed based on RPNB using regional factors of crash locations as independent variables and the crash frequency of different clusters respectively as dependent variables. The hybrid approach enables a comprehensive examination of internal and external heterogeneities among bicycle crash frequency factors simultaneously. Results suggest that the proposed hybrid approach exhibits superior fitting and predictive performance compared to the model only considers the effects of unobserved heterogeneity from one perspective with the lower values of Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). This approach can help policymakers and urban planners to design more effective safety interventions by understanding the distinct needs of different bicyclist clusters and the specific factors that contribute to crash risk in each group.

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

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

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

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

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

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

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

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

Cultural values and digital gap: Overview of behavioral patterns

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

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

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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

PURPOSE

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

METHOD

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

RESULTS

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

CONCLUSION

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

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

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

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

INTRODUCTION

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

METHODS

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

RESULTS

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

DISCUSSION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

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

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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Flipping healthcare by including the patient perspective in integrated care pathway design: A scoping review

BACKGROUND

Despite the recognized benefits of integrating patient perspectives into healthcare design and clinical decision support, theoretical approaches and standardized methods are lacking. Various strategies, such as developing pathways, have evolved to address these challenges. Previous research emphasized the need for a framework for care pathways that includes theoretical principles, extensive user involvement, and data from electronic health records to bridge the gap between different fields and disciplines. Standardizing the representation of the patient perspective could facilitate its sharing across healthcare organizations and domains and its integration into journal systems, shifting the balance of power from the provider to the patient.

OBJECTIVES

This study aims to 1) Identify research approaches taken to develop patient-centred, integrated, care pathways supported by electronic health records 2) Propose a socio-technical framework for designing patient-centred care pathways across multiple healthcare levels that integrates the voice of the patient with the knowledge of the care provider and technological perspectives.

METHODS

This study conducted a scoping review following the Joanna Briggs Institute guidelines and PRISMA-ScR protocol. The databases PubMed, Scopus, Web of Science, ProQuest, IEEE, and Google Scholar were searched using a key term search strategy including variations of patient-centred, integrated care, pathway, framework and model to identify relevant studies. Eligible articles included peer-reviewed literature documenting methodologies for mapping patient-centred, integrated care pathways in healthcare service design.

RESULTS

This review summarizes the application of care pathway modelling practices across various areas of healthcare innovation. The search resulted in 410 studies, with 16 articles included after the full review and grey literature search.

CONCLUSIONS

Our research illustrated incorporating patient perspectives into modelling care pathways and healthcare service design. Regardless of the medical domain, our methodology proposes an approach for modelling patient-centred, integrated care pathways across the care continuum, including using electronic health records to support the pathways.

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

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

Digital transformation and corporate tax avoidance: An analysis based on multiple perspectives and mechanisms

Promoting the seamless integration of the digital economy with the real economy, mitigating the adverse impacts of widespread corporate tax avoidance, and optimizing tax governance are critical imperatives in the era of digital economy. This study examines all A-share listed companies from 2007 to 2022 as research samples. It utilizes multiple perspectives including signal theory, information asymmetry theory, and the T-O-E (Technology-Organisation-Environment) framework to investigate the primary impacts of digital transformation on corporate tax avoidance, along with the intermediate mechanisms and foundational conditions that influence its effectiveness. After conducting both theoretical and empirical analyses, this paper presents the following conclusions. (1) The implementation of digital transformation significantly reduces corporate tax avoidance, a conclusion supported by rigorous robustness tests. Moreover, digital transformation enhances corporate productivity through the suppression of tax avoidance. (2) Digital transformation diminishes corporate tax avoidance through enhanced innovation and efficiency in resource allocation (technology level), improved quality of internal controls (organization level), and decreased industry competition (environment level). (3) The impact of digital transformation in reducing tax avoidance is significantly greater for enterprises in their growth phase, experiencing lower financing constraints, particularly those situated in the central and western regions. (4) Lower business risk is essential for maximizing the effectiveness of digital transformation and reducing corporate tax avoidance. This is crucial for governments seeking to improve tax administration, guide market and regional development, and enhance the impact of corporate digital transformation on mitigating tax avoidance.

Mediation effect of knowledge management on the impact of IT capability on firm performance: exploring the moderating role of organization culture management

Introduction

With the development of the digital economy, a multitude of firms have embarked on the path of digital transformation through information technology (IT). Scholars have called for attention to the mediating or moderating mechanisms of IT capability on firm performance. This study argues that further exploration is needed regarding the relationship between IT capability and firm performance.

Methods

This study obtained questionnaire data from 152 IT senior managers of randomly selected manufacturing firms. The data was used to empirically test the proposed hypotheses using hierarchical regression analysis.

Results

The results showed that IT capability has a positive effect on firm performance directly and indirectly via knowledge stock and knowledge process. Moreover, organizational culture management moderates the relationship between knowledge stock/knowledge process, and firm performance.

Discussion

This study proposes the "resources-knowledge-performance" mechanism, which sheds light on the "black box" of how IT capability affects firm performance. This enriches the research on knowledge from different perspectives and the the research on organizational culture by discussing the moderating role of organizational culture management in the relationship between knowledge stock/process and firm performance. Our research also has important managerial implications to firm.

Factors influencing user's health information discernment abilities in online health communities: based on SEM and fsQCA

Introduction

Online health communities have become the main source for people to obtain health information. However, the existence of poor-quality health information, misinformation, and rumors in online health communities increases the challenges in governing information quality. It not only affects users' health decisions but also undermines social stability. It is of great significance to explore the factors that affect users' ability to discern information in online health communities.

Methods

This study integrated the Stimulus-Organism-Response Theory, Information Ecology Theory and the Mindsponge Theory to constructed a model of factors influencing users' health information discernment abilities in online health communities. A questionnaire was designed based on the variables in the model, and data was collected. Utilizing Structural Equation Modeling (SEM) in conjunction with fuzzy-set Qualitative Comparative Analysis (fsQCA), the study analyzed the complex causal relationships among stimulus factors, user perception, and the health information discernment abilities.

Results

The results revealed that the dimensions of information, information environment, information technology, and information people all positively influenced health information discernment abilities. Four distinct configurations were identified as triggers for users' health information discernment abilities. The core conditions included information source, informational support, technological security, technological facilitation, and perceived risk. It was also observed that information quality and emotional support can act as substitutes for one another, as can informational support and emotional support.

Discussion

This study provides a new perspective to study the influencing factors of health information discernment abilities of online health community users. It can provide experiences and references for online health community information services, information resource construction and the development of users' health information discernment abilities.

The three pillars of tomorrow: How Marketing 5.0 builds on Industry 5.0 and impacts Society 5.0?

In today's environment, the connections between Marketing 5.0, Industry 5.0, and Society 5.0 are gaining increasing attention. Governments and businesses are eager to explore how they can boost both economic competitiveness and societal well-being through strategic initiatives. It is important to ensure that technology adoption, ethical governance, and human capital development all align and are in-sync. This review dives into this challenge, aiming to create a theoretical model that provides significant insight on how Marketing 5.0 influences Society 5.0 through Industry 5.0. By analyzing a broad range of literature, the aim was to offer practical suggestions and guidelines for enhancing competitiveness and societal welfare. 48 studies were analyzed studies to discuss the complexities of the relationships between these three domains. The findings suggest actionable steps and strategies for both businesses and policymakers. Finally, the paper serves as a foundation for future research in this area, exploring the synergy between Marketing 5.0, Industry 5.0, and Society 5.0.

CEO regulatory focus on digital transformation: Evidence from China

Digital transformationsw has become crucial for business to stay competitive in today's technology-driven world. Research shows CEOs' characteristics can influence firms' digital transformation, however, this work has not considered the role of CEO regulatory focus. In this paper, we build a framework to understand the relationship between CEO regulatory focus and firm's digital transformation. Build on regulatory focus theory, we argue that CEO promotion focus is positively associated with enterprise digital transformation, whereas CEO prevention focus is negatively associated with enterprise digital transformation. We further identify two contextual factors that moderating the relationship between CEO regulatory focus and digital transformation. Specifically, we find CEO power and economic policy uncertainty strengthen the relationship between CEO regulatory focus and enterprise digital transformation. We find strong support for our hypotheses in a sample of 2696 Chinese publicly listed firms between 2008 and 2023. Our findings have significant implications for understanding the role of CEO regulatory focus on digital transformation.

Does digital-industrial technology integration reduce corporate carbon emissions?

The integration of digital technology and industrial technology emerges as a pivotal avenue for enterprises to attain Sustainable Development Goals (SDGs), promoting the transition towards a sustainable and green trajectory of development. The panel data utilized in this paper encompasses financial, operational, and carbon emission metrics of publicly listed companies in China from 2008 to 2019. This longitudinal dataset enables us to perform robust statistical analyses to evaluate the impacts of Digital-Industrial technology integration on carbon emission intensity over time. The results indicate that: (i) Digital-Industrial technology integration significantly reduces the carbon emission intensity of enterprises, the conclusion remains robust when subjected to endogeneity and sensitivity analyses. (ii) Digital-Industrial technology integration mainly reduces the marginal cost of production and enhances the accumulation of knowledge to reduce the carbon emission intensity of enterprises. (iii) Digital-Industrial Technology Integration manifests more pronounced effects in curbing carbon emissions in regions characterized by robust property rights protection and well-developed digital infrastructure. (iv) Further research finds that Digital-Industrial technology integration increases the green technology innovation and ESG (Environmental, Social, and Governance) performance of enterprises. The results of this study provide empirical evidence for the carbon emission reduction function of the Digital-Industrial technology integration, and also verify the positive externality impact of the Digital-Industrial technology integration on the enterprise green innovation and SDGs.

Which Receives More Attention, Online Review Sentiment or Online Review Rating? Spillover Effect Analysis from JD.com

Studies have found that competitive products' online review ratings (ORRs) have a spillover effect on the focal product's sales. However, the spillover effect of online review sentiment (ORS) as an essential component of online review analysis has yet to be studied. In this study, we analyze online review content from JD.com using the latent Dirichlet allocation to identify the product attribute topics that consumers are most concerned about. We then construct a baseline regression model of ORS and ORRs to explore the effects of online competitive product reviews on focal product sales. Moreover, we examine how the interaction between ORS and critical factors of online reviews affect sales. Our results indicate that the ORS of competitive products has a negative effect on focal product sales, and the effect is greater than the ORS and ORRs of focal products, respectively. In addition, the ORS of competitive products inhibits the sale of focal products as evaluations of product attributes become more positive or online review usefulness increases. We also find that the effect of ORRs of competitive products is not significant, which may be because clothing, as an experiential product, requires consumers to gain more information about specific usage scenarios before making a decision. This study provides a more accurate basis for consumer decision-making and offers retailers a novel approach to developing marketing strategies.

Understanding the rationales and information environments for early, late, and nonadopters of the COVID-19 vaccine

Anti-vaccine sentiment during the COVID-19 pandemic grew at an alarming rate, leaving much to understand about the relationship between people's vaccination status and the information they were exposed to. This study investigated the relationship between vaccine behavior, decision rationales, and information exposure on social media over time. Using a cohort study that consisted of a nationally representative survey of American adults, three subpopulations (early adopters, late adopters, and nonadopters) were analyzed through a combination of statistical analysis, network analysis, and semi-supervised topic modeling. The main reasons Americans reported choosing to get vaccinated were safety and health. However, work requirements and travel were more important for late adopters than early adopters (95% CI on OR of [0.121, 0.453]). While late adopters' and nonadopters' primary reason for not getting vaccinated was it being too early, late adopters also mentioned safety issues more often and nonadopters mentioned government distrust (95% CI on OR of [0.125, 0.763]). Among those who shared Twitter/X accounts, early adopters and nonadopters followed a larger fraction of highly partisan political accounts compared to late adopters, and late adopters were exposed to more neutral and pro-vaccine messaging than nonadopters. Together, these findings suggest that the decision-making process and the information environments of these subpopulations have notable differences, and any online vaccination campaigns need to consider these differences when attempting to provide accurate vaccine information to all three subpopulations.

Factors associated with self-management in older adults with multiple chronic conditions: a qualitative study

Background and purpose

Recognizing the importance of self-management in older adults with multiple chronic conditions (MCCs) is crucial for their quality of life. This qualitative study explored the factors linked to self-management among older adults with MCCs.

Materials and methods

The present study was conducted in three stages: an integrated review, qualitative interviews, and Delphi. The search used electronic databases including Web of Science, PubMed, Scopus, Magiran, SID, and Iranmedex. The results of 33 studies that met the inclusion criteria were analyzed using conventional content analysis. A data matrix was formed; and purposeful sampling was conducted among older adults with MCCs, family caregivers, and specialists. The data were collected through semi-structured interviews. Data analysis of 29 interviews was conducted simultaneously with data collection using oriented qualitative content analysis and the Elo and Kyngäs approach. Three rounds of Delphi were conducted via email correspondence with a group of 30 experts to develop and validate the proposed variables.

Results

The factors that influence self-management can be categorized into various categories. Biological factors, cognitive factors, co-morbidities, socio-economic factors, health-related behaviors, mental health, interactions with healthcare teams, Family relationships, medical facility resources, employee empowerment, health policy development, and cultural influences.

Conclusion

Self-management in older Iranian adults with MCCs is a complex and multidimensional phenomenon. By identifying the relevant factors, it is possible to design operational plans that promote self-management among the older adult population and are tailored to fit the specific needs of Iranian society.

Social media ostracism and creativity: moderating role of emotional intelligence

The goal of this study is to learn more about social media ostracism, a stressor associated with online social networks, defined by feelings of rejection, exclusion, or ignoring. We investigate the connection between social media ostracism and worker creativity. We suggest that psychological safety and psychological rumination serve as intermediaries in this relationship. Furthermore, we investigate emotional intelligence as a relationship regulator. To verify our hypothesis, we gathered data with the help of the HR department from 244 workers of nine Chinese organizations. Our research shows that psychological rumination and social media exclusion are significantly correlated, but only in workers with low emotional intelligence. Furthermore, for individuals with strong emotional intelligence, we did not discover a statistically negative association between psychological safety and social media exclusion. Findings suggest that psychological safety and psychological rumination serve as mediating factors in the relationship between employee creativity and social media exclusion. This study illuminates the negative aspects of social media ostracism and reveals how it might hinder creativity. It also emphasizes how emotional intelligence functions as a moderator. Organizations may learn a lot from this study on how to lessen the negative impacts of social media exclusion on employee creativity.

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

PURPOSE

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

DESIGN/METHODOLOGY/APPROACH

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

FINDINGS

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

CONTRIBUTION OF RESEARCH

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

PRACTICAL IMPLICATIONS

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

Mobile Patient-Provider Communication and Lifestyle Improvement: Examining the Role of Mobile Technology Identity and Health Empowerment

In the span of a decade, smartphones have gained popularity and acceptance among both patients and physicians thanks to their advantages in health care delivery. However, research investigating mobile patient-provider communication (MPPC) and its impact on patients' lifestyles is only just beginning. Drawing on the pathway model of health communication and mobile technology (MTI) theory, we developed a research model to explore the effect of MPPC on lifestyle improvement, using health empowerment as a mediator and MTI as a moderator. The findings from 432 participants (Mage = 32.5 years old, female = 212) suggested that after controlling for respondents' age, gender, education, income, and general health status, having greater communication with healthcare providers through mobile devices was positively related to lifestyle improvement and that health empowerment mediated this relationship. Moreover, MTI-emotional energy (MTIE) moderated the direct relationship between MPPC and lifestyle improvement, while MTI-dependency (MTID) moderated the indirect impact of MPPC. Individuals who hold a greater MTIE/MTID were more likely to benefit from MPPC such that they are more likely to be empowered for self-care and maintain healthy lifestyles. This study not only contributes to the growing literature on mobile health communication but also plays a reference role for interventions in patient empowerment and health promotion. Theoretical and practical implications were discussed.

User Experiences of Transitioning From a Homegrown Electronic Health Record to a Vendor-Based Product in the Department of Veterans Affairs: Qualitative Findings From a Mixed Methods Evaluation

BACKGROUND

The Department of Veterans Affairs (VA), the largest nationally integrated health system in the United States, is transitioning from its homegrown electronic health record (EHR) to a new vendor-based EHR, Oracle Cerner. Experiences of the first VA site to transition have been widely discussed in the media, but in-depth accounts based on rigorous research are lacking.

OBJECTIVE

We sought to explore employee perspectives on the rationale for, and value of, transitioning from a VA-tailored EHR to a vendor-based product.

METHODS

As part of a larger mixed methods, multisite, formative evaluation of VA clinician and staff experiences with the EHR transition, we conducted semistructured interviews at the Mann-Grandstaff VA Medical Center before, during, and after going live in October 2020. In total, we completed 122 interviews with 26 participants across multiple departments.

RESULTS

Before the new vendor-based EHR went live, participants initially expressed cautious optimism about the transition. However, in subsequent interviews following the go-live, participants increasingly critiqued the vendor's understanding of VA's needs, values, and workflows, as well as what they perceived as an inadequate fit between the functionalities of the new vendor-based EHR system and VA's characteristic approach to care. As much as a year after going live, participants reiterated these concerns while also expressing a desire for substantive changes to the transition process, with some questioning the value of continuing with the transition.

CONCLUSIONS

VA's transition from a homegrown EHR to a vendor-based EHR system has presented substantial challenges, both practical and cultural in nature. Consequently, it is a valuable case study for understanding the sociotechnical dimension of EHR-to-EHR transitions. These findings have implications for both VA leadership and the broader community of policy makers, vendors, informaticists, and others involved in large-scale health information technology implementations.

You cannot spell risk without "I-S": The disclosure of information systems risks by Fortune 1000 firms

Cybersecurity events can cause business disruptions, health and safety repercussions, financial costs, and negative publicity for large firms, and executives rank cybersecurity as a top operational concern. Although cybersecurity may be the most publicized information systems (IS) risk, large firms face a range of IS risks. Over the past three decades, researchers developed frameworks to categorize and evaluate IS risks. However, there have been few updates to these frameworks despite numerous technological advances, and we are not aware of any research that uses empirical data to map actual IS risks cited by large firms to these frameworks. To address this gap, we coded and analyzed text data from Item 1A (Risk Factors) of the fiscal year 2020 Securities and Exchange Commission Forms 10-K for all Fortune 1000 firms. We build on prior research to develop a framework that places 25 IS risks into four quadrants and 10 categories, and we record the number and type of IS risks cited by each firm. The risk of cyberattack is cited by virtually all Fortune 1000 firms, and the risk of software/hardware failure is cited by 90% of Fortune 1000 firms. Risks associated with data privacy law compliance are cited by 70% of Fortune 1000 firms, and risks associated with internet/telecommunications/power outage, human error, and natural disasters/terrorism are cited by 60% of Fortune 1000 firms. We perform additional analysis to identify differences in risk citation based on industry and financial measures.

Time in hand: Temporal focus in risk discourse and audience emotions on knowledge-sharing platforms

Online knowledge-sharing platforms construct risk knowledge and provide the audience with risk-related scientific facts. We study how speakers organize narratives in past, present, and future foci to influence the audience's emotions through the audience's appraisal of motive congruency and coping potential. Empirical evidence from 210 Technology, Entertainment, Design talks about disasters from 2002 to 2018 demonstrates that emphasizing the past, present, and future in risk narrative leads to the audience's comments with more negative, less positive, and more positive emotions, respectively. Concrete (vs. abstract) portrayal of the risk narrative improves the audience's situational awareness, enhances their risk appraisal, and intensifies the impact of temporal focus on emotions, providing evidence of how temporal focus impacts. These findings demonstrate that temporal focus can effectively reduce risk overreaction or ignorance and facilitate emotion regulation in risk communication.

Can digital technology innovation contribute to firms' market value?

With the rapid development of digital technology, digital technology innovation has become a core driver of China's economic development. Thus, this study uses A-share listed companies from 2003 to 2021 as the research sample. The digital patents of firms are identified to portray the level of digital technology innovation by matching the digital economy industry classification code, national economy industry classification code, and IPC number. Considers the economic effect of digital technology innovation from the perspective of firm market value. It is found that digital technology innovation significantly contributes to the increase in firm market value, and this finding still holds when robustness tests are performed. Mechanistic tests have shown that digital technology innovation affects firm market value by driving digital transformation, promoting productivity, and enhancing market profitability. Further analysis reveals that digital technology innovation has a more significant effect on increasing firm market value for large, non-state, capital-intensive, technology-intensive and low internal control costs firms. This study verifies the enabling effect of digital technology innovation on the development of the real economy at the micro level, and provides insights for the optimization of China's digital technology innovation policies and the formulation of firms' digital development strategies.

Beyond the Screen: A Comprehensive Analysis of Emotional Skills and Social Networking in French Young Adults

(1) Background: This study investigates the influence of social networks on young adults, focusing on both positive and negative impacts. It considers problematic social networking site use (PSNSU), emotional intelligence, empathy, and the phenomenon of Fear of Missing Out (FoMO). (2) Methods: A comprehensive online survey was conducted with 442 participants aged 18 to 30 years that used various psychometric tools to assess emotional intelligence, empathy, internet and social media use, and FoMO. (3) Results: The study revealed that young adults display low competencies in emotional intelligence and empathy, with a tendency towards problematic internet and social media use. High FoMO scores were observed, correlating with negative internet use outcomes. Gender differences in these aspects were also explored. (4) Conclusions: The findings suggest a complex interaction between social network use, emotional skills, and FoMO that impacts young adults' mental health and social behaviors. This study highlights the need for a nuanced understanding of these relationships and their implications for well-being and social interaction in the digital age.

Antecedents and consequents of circular economy adoption: A meta-Analytic Investigation

This paper aims to integrate and empirically assess the antecedents and consequents of circular economy (CE) adoption to remove ambiguity existing in the literature and clarify divergent views. This study uses meta-analysis methodology to validate the research framework, considering 106 empirical studies with 210 effect sizes. Based on these studies, we establish twelve antecedents and three consequents related to CE. Antecedents are categorized in a technological-organizational-environmental framework and consequents in the sustainability outcomes. The result suggests that organisational factors are more prominent in driving CE practices, followed by environmental and technological factors. In the organisational category, the three most influencing factors are managing product returns, green manufacturing, and environmental strategy. In the environmental category, coercive pressure is the most influential factor, followed by mimetic and social pressures. Emerging I4.0 technologies are the most prominent factor in the technological category. Our study suggests that CE helps to achieve sustainable performance by significantly enabling economic, environmental, and social outcomes. This study further analyses how contextual factors such as national culture (masculinity) and economic regions influence the various relationships with CE using subgroup analysis. The moderation results show that low masculine culture and developing economies are more effectively using the I4.0 technologies to drive CE adoption than high masculine culture and developed economies. Additionally, different dimensions of sustainability are also influenced by the variations in masculinity and economic regions.

Therapeutic use of the humanoid robot, Telenoid, with older adults: A critical interpretive synthesis review

This review sought to critically evaluate the use of the teleoperated humanoid robotic communications device, Telenoid, for therapeutic purposes with older adults, and identify and highlight key considerations for future research and clinical practice within gerontechnology. A critical interpretive synthesis was conducted, with nine electronic databases and online sources searched using the keyword "Telenoid." Studies were included in the review if they were: written in English; reported primary research; employed a qualitative, quantitative, or mixed-method design; and described or measured effects, experiences, or perceptions of using Telenoid for therapeutic purposes with older adults. Critical engagement with the studies identified key themes, as well as opportunities to advance future research. Ten studies involving Telenoid were identified, with eight focused on older adults living with dementia. Study findings centered around two themes: effects (including positive effects and negative reactions), and challenges and considerations (including technical issues, operator training, acceptability, and dosage). Although several issues currently challenge the use of Telenoid, available studies show some therapeutic potential of using Telenoid with older adults, including those living with dementia, particularly for communication and mood. Higher-quality studies are required to advance understanding, and considerations for the field are outlined to aid development.

For-profit versus non-profit cybersecurity posture: breach types and locations in healthcare organisations

BACKGROUND

The implementation of emerging technologies has resulted in an increase of data breaches in healthcare organisations, especially during the COVID-19 pandemic. Health information and cybersecurity managers need to understand if, and to what extent, breach types and locations are associated with their organisation's business type.

OBJECTIVE

To investigate if breach type and breach location are associated with business type, and if so, investigate how these factors affect information systems and protected health information in for-profit versus non-profit organisations.

METHOD

The quantitative study was performed using chi-square tests for association and post-hoc comparison of column proportions analysis on an archival data set of reported healthcare data breaches from 2020 to 2022. Data from the Department of Health and Human Services website was retrieved and each organisation classified as for-profit or non-profit.

RESULTS

For-profit organisations experienced a significantly higher number of breaches due to theft, and non-profit organisations experienced a significantly higher number of breaches due to unauthorised access. Furthermore, the number of breaches that occurred on laptops and paper/films was significantly higher in for-profit organisations.

CONCLUSION

While the threat level of hacking techniques is the same in for-profit and non-profit organisations, certain breach types are more likely to occur within specific breach locations based on the organisation's business type. To protect the privacy and security of medical information, health information and cybersecurity managers need to align with industry-leading frameworks and controls to prevent specific breach types that occur in specific locations within their environments.

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.

Assessing inclusion and representativeness on digital platforms for health education: Evidence from YouTube

BACKGROUND

Studies confirm that significant biases exist in online recommendation platforms, exacerbating pre-existing disparities and leading to less-than-optimal outcomes for underrepresented demographics. We study issues of bias in inclusion and representativeness in the context of healthcare information disseminated via videos on the YouTube social media platform, a widely used online channel for multi-media rich information. With one in three US adults using the Internet to learn about a health concern, it is critical to assess inclusivity and representativeness regarding how health information is disseminated by digital platforms such as YouTube.

METHODS

Leveraging methods from fair machine learning (ML), natural language processing and voice and facial recognition methods, we examine inclusivity and representativeness of video content presenters using a large corpus of videos and their metadata on a chronic condition (diabetes) extracted from the YouTube platform. Regression models are used to determine whether presenter demographics impact video popularity, measured by the video's average daily view count. A video that generates a higher view count is considered to be more popular.

RESULTS

The voice and facial recognition methods predicted the gender and race of the presenter with reasonable success. Gender is predicted through voice recognition (accuracy = 78%, AUC = 76%), while the gender and race predictions use facial recognition (accuracy = 93%, AUC = 92% and accuracy = 82%, AUC = 80%, respectively). The gender of the presenter is more significant for video views only when the face of the presenter is not visible while videos with male presenters with no face visibility have a positive relationship with view counts. Furthermore, videos with white and male presenters have a positive influence on view counts while videos with female and non - white group have high view counts.

CONCLUSION

Presenters' demographics do have an influence on average daily view count of videos viewed on social media platforms as shown by advanced voice and facial recognition algorithms used for assessing inclusion and representativeness of the video content. Future research can explore short videos and those at the channel level because popularity of the channel name and the number of videos associated with that channel do have an influence on view counts.

Mitigating the influence of message features on health misinformation sharing intention in social media: Experimental evidence for accuracy-nudge intervention

RATIONALE

The escalating dissemination of health misinformation on social media platforms poses a significant threat to users' well-being. It is imperative to identify the types of health misinformation that are more susceptible to widespread dissemination and to explore strategies to curb its spread.

METHOD

This study designed a 2 (emotional appeal type: positive vs. negative) × 2 (fabricated source type: pseudo-common vs. pseudo-authoritative) × 2 (accuracy-nudge label: No vs. Yes) online between-subjects experiment controlling for factors such as e-health literacy, prior sharing experience, and personal involvement. A snowball sampling approach was used to recruit 1952 participants through social media, resulting in a final sample of 1393 valid responses.

RESULTS

Compared to positive emotional appeal and pseudo-common sources, negative emotional appeal and pseudo-authoritative sources resulted in higher levels of sharing intention. Under the condition of negative emotional appeal, the promotion effect of pseudo-authoritative sources on sharing intention was intensified. The accuracy-nudge intervention could significantly mitigate this tendency. The underlying mechanisms revealed more details: both negative emotional appeals and pseudo-authoritative sources increased the perceived credibility of health misinformation, thereby increasing users' sharing intention. However, in contrast to pseudo-authoritative sources, excessive negative emotional appeal induced vigilant verification behavior among users, which reduced sharing to some extent. Adding an accuracy-nudge label to health misinformation reduced users' misguided trust in health misinformation features and stimulated information verification, ultimately reducing health misinformation sharing intention.

CONCLUSIONS

Negative emotional appeal and pseudo-authoritative sources can enhance the perceived credibility of health misinformation, thereby strengthening the sharing intention of social media users. Therefore, health misinformation with negative emotional appeal and pseudo-authoritative sources is more likely to be widely shared. The accuracy nudge intervention can trigger users' information verification behavior, suppress the persuasive effects of the misinformation features mentioned above, and help prevent the spread of health misinformation on social media.

Targeted communication and race: explicating perceived message relevance

Objectives: Targeting is a communication strategy in which a message is designed to address a particular group. It has been postulated that targeting increases message relevance; however, researchers are still explicating relevance and its impact on downline cognitive processes (e.g. message quality, cognitive cost). The current study addresses both gaps by evaluating the impact of targeted materials for White and African American audiences. Design: Adult women (N = 266) aged 18-74 (Mage = 47.12, SD = 1.40) were recruited to participate in a 2 (targeting: multiracial, African American) × 2 (race: White participants, African American participants) × 2 (topic: Hypertension, Environmental Breast Cancer) message experiment. Results: Across both topics, African American participants in the African American condition had reduced cognitive costs, increased message clarity, and increased message relevance. An indirect serial mediation model was supported wherein the relationship between targeting and behavioral intention was mediated by perceived relevance and perceived message quality. Conclusion: Targeting enhances perceived message relevance which, in turn, impacts behavioral intentions via perceived message quality. This model is consistent with the postulates of relevance theory and informs both intervention design and evaluation.

Punishing "Privilege": Antisemitic Hate Crime in Canada

Both federal government and civil society organization data point to consistently rising incidents of antisemitic narratives and acts across Canada. In spite of this, antisemitic hate crime has not been the focus of any academic research here, some would argue because Jews are not typically thought to be an at-risk community. Rather, the Jewish community is thought to occupy a relatively privileged place in society which shields them from bias motivated attacks. Countering this narrative, our study, based in Ontario and Quebec, reveals that Jewish individuals and institutions are highly vulnerable to discursive, physical, and property violations. Many of those we spoke with felt embattled by the narrative attacks that rendered the community vulnerable to corollary physical attacks. Of particular significance are the enabling images of Jews that equate "Jewish privilege" with excessive power and control. We explore these themes, concluding with calls for strategies intended to counter hateful narratives.

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.

Large language models and generative AI in telehealth: a responsible use lens

OBJECTIVE

This scoping review aims to assess the current research landscape of the application and use of large language models (LLMs) and generative Artificial Intelligence (AI), through tools such as ChatGPT in telehealth. Additionally, the review seeks to identify key areas for future research, with a particular focus on AI ethics considerations for responsible use and ensuring trustworthy AI.

MATERIALS AND METHODS

Following the scoping review methodological framework, a search strategy was conducted across 6 databases. To structure our review, we employed AI ethics guidelines and principles, constructing a concept matrix for investigating the responsible use of AI in telehealth. Using the concept matrix in our review enabled the identification of gaps in the literature and informed future research directions.

RESULTS

Twenty studies were included in the review. Among the included studies, 5 were empirical, and 15 were reviews and perspectives focusing on different telehealth applications and healthcare contexts. Benefit and reliability concepts were frequently discussed in these studies. Privacy, security, and accountability were peripheral themes, with transparency, explainability, human agency, and contestability lacking conceptual or empirical exploration.

CONCLUSION

The findings emphasized the potential of LLMs, especially ChatGPT, in telehealth. They provide insights into understanding the use of LLMs, enhancing telehealth services, and taking ethical considerations into account. By proposing three future research directions with a focus on responsible use, this review further contributes to the advancement of this emerging phenomenon of healthcare AI.

Risk factors for technology addiction in young children ages 2-5 years

PURPOSE

This study was conducted to determine the factors predictive of technology addiction in young children (aged 2-5 years). The study examined the effects of digital parenting awareness, parental stress, family demographic characteristics and parents' technology use habits on technology addiction in young children.

DESIGN AND METHODS

This cross-sectional study was conducted between October 2023 and February 2024 with 401 volunteer parents of children aged 2-5 years in a province in the Western Mediterranean region of Turkey. Data were collected using the Technology Addiction Scale for Ages 2-5, the Digital Parental Awareness Scale, and the Parental Stress Scale.

RESULTS

Digital parenting awareness, negative modeling and digital neglect, and parental stress positively and directly affect technology addiction in young children (β1 = 0.166, β2 = 0.443, β3 = 0.087, all p < 0.05). Additionally, parental gender (β = 0.095), parental marital status (β = 0.092), and household income (β = 0.088) were significant predictors of technology addiction in young children (p < 0.05). The level of technology addiction is significantly higher in children who use devices without parental controls (Z = -6.187, p < 0.001).

CONCLUSIONS

Low digital parenting awareness, high parental stress, male caregivers, low household income and single-parent families in digital tools increase the risk of technology addiction in young children (2-5 years). Multidisciplinary, family-oriented intervention programs, incorporating consideration of parental risk factors, should be developed to prevent and reduce technology addiction in this group.