Design and development of a Telemedicine Assessment Toolkit (TAT) for the assessment of audiovisual telemedicine encounters

Although the use of audiovisual telemedicine has grown in recent years especially during recent COVID-19-related lockdowns, evidence shows there is still a lack of tools that can be used for the assessment of telemedicine encounters. The few validated questionnaires that are available for assessing telemedicine encounters are not often used. Non-validated questionnaires dominate research, leading to results that cannot be compared or extrapolated to other research or medical sites. Development of standard measures for the assessment of telemedicine encounters has been advocated by stakeholders. The objective of this study is to provide a comprehensive set of measures by developing a conceptual approach and a preliminary Telemedicine Assessment Toolkit (TAT) for the assessment of audiovisual telemedicine encounters. A two-step conceptual approach was used to identify potential domains and sub-domains by qualitative analysis of a pool of questions from studies published from 2016 to 2021. Questions were adopted from validated questionnaires or generated to represent the underlying concept of each sub-domain, resulting in a core block of comprehensive questions. A toolkit is proposed with question-measures that cover the sub-domains relevant to the assessment of telemedicine encounters. This study recommended 11 domains to be used for the assessment of telemedicine encounters: "usability," "patient satisfaction," "patient-provider interaction," "patient perspectives," "telemedicine readiness," "qualitative feedback," "comparison to standard (in-person) care," "privacy," "technology," "patient feeling," and "patient costs." Of the 11 domains, 26 underlying sub-domains were created. From the subdomains, a 30-question core block was proposed. The core-block together with a precursor block aimed to retrieve demographic/patient characteristics and, together with a customizable clinical outcomes block, complete the comprehensive toolkit. The toolkit, upon testing and validation, would enable researchers and system owners to assess patient-oriented aspects of audiovisual telemedicine encounters more accurately and accelerate the adoption of common audiovisual telemedicine assessment measures.

How good are large language models at product risk assessment?

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

Has digital technology innovation improved urban total factor energy efficiency? - Evidence from 282 prefecture-level cities in China

Enhancing total factor energy efficiency is a critical issue that needs to be addressed in the context of accelerating transformation in digital technologies and advancing sustainable development. This paper selects panel data from 282 prefecture-level cities in China from 2011 to 2021 to empirically analyze the impacts, mechanisms, and characteristics of digital technology innovation on urban total factor energy efficiency. The research findings indicate that digital technology innovation significantly enhances urban total factor energy efficiency. Specifically, a 1% increase in digital technology innovation leads to an approximate 0.035% improvement in energy efficiency. The mechanism tests reveal that financial support, represented by digital finance and green finance, plays a progressively increasing mediating role in enhancing urban total factor energy efficiency through digital technology innovation. When financial support surpasses a certain threshold, the effect of the mediating mechanism increases by over 20%. Discussions on the heterogeneity of the effects demonstrate that in cities with stronger regional innovation capabilities, higher proportions of traditional energy consumption, and more pronounced biases in innovation policies, energy policies, and financial support policies, the impact of digital technology innovation on total factor energy efficiency is more pronounced, generally 1 to 2 times higher. Particularly in cities with stronger innovation capabilities, the impact effect is about 7 times greater.

The impact of electronic health records on the ordering of medical tests

BACKGROUND

Healthcare facilities often encounter patients with incomplete records from previous visits, leading to duplicated tests. Recent Electronic Health Records (EHR) investments aim to address this issue. This study examines how viewing patient information via OFEK EHR affects the frequency of tests ordered by the physician. The OFEK system, developed in Clalit Health Services, is an advanced online medical records system used in hospitals. It was expanded to all hospitals and HMOs starting in 2013, allowing medical information to be shared and accessed in the Israeli healthcare system.

METHODS

The study was conducted at the Israel Center for Medical Simulation (MSR), with 26 physicians engaged in encounters with simulated patients (SP). The SPs provided relevant clinical histories and signs for two abdominal pain cases. The physicians ordered diagnostic tests, and after receiving the tests' results they set a final diagnosis and could order additional tests. They had randomized access to the OFEK system to vary test-ordering patterns. In both scenarios, we examined three key variables to see if access to the OFEK system influenced the decision to order diagnostic tests ("QTestsBefore" - the number of tests ordered by the physician after the patient visit; "QTestsAfters" - the number of tests ordered by the physician after receiving the results of the first round; "QSumTests" - The total number of tests).

RESULTS

In the study group with access to the OFEK EHR, an average of 5.5 tests were ordered, compared to 6.85 in the control group (p-value = 0.01). Ordinary Least Squares regressions confirmed that the overall number of tests, particularly the second round ordered after receiving initial results, was significantly lower with OFEK. Additionally, years of clinical practice also correlated with fewer ordered tests.

CONCLUSIONS

The findings show that the OFEK EHR system reduces the number of medical examinations by allowing physicians to access medical histories and past tests, which supports efficient decision-making. This leads to fewer ordered medical tests and, thus, reduces the time procedures patients spend in EDs or hospitals. Efficient decision-making and fewer redundant medical tests can improve patient flow, free up resources, and reduce overcrowding in emergency departments.

Ecosystem benefits of urban woody plants for sustainable green space planning: a case study from Wroclaw

City residents benefit daily of urban green spaces, often unaware of their true value. We transformed biometric indicators of woody plants into ecosystem equivalents for evaluating ecosystem services (ES) by the I-tree eco tool estimate of boulevards with a different ratio of bushes, trees, and urban canopy cover (UCC). The results showed that the studied green spaces annually retain 111.24 metric tonnes of carbon in their biomass, estimated at 17,846 thousand €, and are capable of producing 1928 thousand € by different ES. It includes 4.01 metric tonnes/year of gross carbon sequestration worth €636.15, 76.01 m3/year of avoided runoff worth €139.28, and 60.95 metric tonnes/year of pollution removal (ozone, carbon monoxide, nitrogen dioxide, and particulate matter) worth €1152.16. For objects where shrubs are the primary producers of ES, it is important to model crown development along the horizontal axis. Quantitative and qualitative assessment of different types of woody plants of different ages allows for effective selection of urban plants to create a well-being environment for citizens. The practical value of the results can improve the spatial planning of urban green infrastructure by considering the ES indices of trees and shrubs and expanding opportunities to inform the public about their value.

Effect of task nature during short digital deprivation on time perception and psychophysiological state

The technological advances in recent years are influencing and redefining our daily lives, communications, and social relationships. While these advances bring us many benefits, their negative effects may also cause concern. Although often studied, the potential benefits of digital deprivation are still disputed. This laboratory study investigates the impact of short digital deprivation (7 min and 30 s) on the psychophysiological state and time perception of 90 participants. Three experimental conditions were created for the task performed during the waiting period (30 subjects per condition). Participants had to either freely use their smartphone, perform a non-digital task (sudoku), or wait (i.e. passive digital deprivation). Indicators of electrodermal activity and heart rate variability were calculated for the baseline and waiting periods, along with measures of subjective affective state. Four measures of time perception were also collected after the waiting period. Regardless of their experimental condition, the participants underestimated the duration of the waiting period on average (5 min 44 vs. 7 min 30). Passive digitally deprived participants felt that the time passed more slowly and were more bored than participants engaged in a task, regardless of whether the task was digital or not. Sudoku induced more positive affect and was more cognitively engaging than the free use of a smartphone regarding heart rate variability measures. The results suggest that performing a digital task (free smartphone use) is less cognitively demanding than a non-digital task (sudoku) and alters time perception in the same way. The digital nature of a task might also impact one's affective reaction. A similar study in the field with longer or repetitive digital deprivation periods and a different non-digital task to perform (e.g., reading news) should be conducted to confirm the results obtained in this study.

Enhancing the Innovation Ecosystem: Overcoming Challenges to Introducing Information-Driven Technologies in Health Care

As health care demands rise and resources remain constrained, optimizing health care systems has become critical. Information-driven technologies, such as data analytics and artificial intelligence (AI), offer significant potential to inform and enhance health care delivery at various levels. However, a persistent gap exists between the promise of these technologies and their implementation in routine practice. In this paper, we propose that fragmentation of the innovation ecosystem is behind the failure of new information-driven technologies to be taken up into practice and that these goals can be achieved by increasing the cohesion of the ecosystem. Drawing on our experiences and published literature, we explore five challenges that underlie current ecosystem fragmentation: (1) technology developers often focus narrowly on perfecting the technical specifications of products without sufficiently considering the broader ecosystem in which these innovations will operate; (2) lessons from academic studies on technology implementation are underused, and existing knowledge is not being built upon; (3) the perspectives of healthcare professionals and organizations are frequently overlooked, resulting in misalignment between technology developments and health care needs; (4) ecosystem members lack incentives to collaborate, leading to strong individual efforts but collective ecosystem failure; and (5) investment in enhancing cohesion between ecosystem members is insufficient, with limited recognition of the time and effort required to build effective collaborations. To address these challenges, we propose a series of recommendations: adopting a wide-lens perspective on the ecosystem; developing a shared-value proposition; fostering ecosystem leadership; and promoting local ownership of ecosystem investigation and enhancement. We conclude by proposing practical steps for ecosystem members to self-assess, diagnose, and improve collaboration and knowledge sharing. The recommendations presented in this paper are intended to be broadly applicable across various types of innovation and improvement efforts in diverse ecosystems.

Digital Interventions for Patients With Juvenile Idiopathic Arthritis: Systematic Review and Meta-Analysis

Background

Juvenile idiopathic arthritis (JIA) is a chronic rheumatic condition requiring long-term, multidisciplinary treatment, which consumes significant health care resources and family energy. This study aims to analyze the effectiveness of digital interventions on patient outcomes in individuals with JIA.

Objective

This meta-analysis aimed to evaluate the impact of digital interventions on alleviating symptoms and improving overall well-being in children and adolescents with JIA.

Methods

A systematic search of 5 databases identified randomized controlled trials assessing the impact of digital interventions on physiological and psychological outcomes in adolescents and children (average age ≤19 y). Outcomes included pain, physical activity, health-related quality of life, self-efficacy, and disease-related issues. A total of 2 reviewers independently screened papers and extracted data on intervention functionalities and outcomes, assessing the risk of bias. A meta-analysis using a random-effects model synthesized the results.

Results

The review included 11 studies involving 885 patients with JIA. Digital interventions included educational (eg, self-management training), therapeutic (eg, pain management), and behavioral (eg, promoting physical activity) approaches. These were delivered through websites, telephone consultations, video conferences, apps, and interactive games, with durations ranging from 8 to 24 weeks and no clear link observed between intervention length and outcomes. Compared with conventional control groups, digital interventions were significantly effective in alleviating pain (standardized mean difference [SMD] -0.19, 95% CI -0.35 to -0.04) and enhancing physical activity levels (SMD 0.37, 95% CI 0.06-0.69). Marginal improvements in health-related quality of life, self-efficacy, and disease-related issues were observed, but these did not reach statistical significance (SMD -0.04, 95% CI -0.19 to 0.11; SMD 0.05, 95% CI -0.11 to 0.20; and SMD 0.09, 95% CI -0.11 to 0.29, respectively). The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach rated the quality of evidence for pain, health-related quality of life, self-efficacy, and disease-related issues as moderate, while the evidence quality for physical activity was assessed as low.

Conclusions

Digital interventions can alleviate pain and enhance physical activity in patients with JIA. However, given the limited sample size and high risk of bias in some studies, further high-quality research is needed to improve the treatment and management of JIA.

AI, How Much Shall I Tell You? Exchange and Communal Consumer-AI Relationships and the Willingness to Disclose Personal Information

Personal information is an important resource for the optimal functioning of AI and technology. Starting from the different theories that define human relationships and the way information is exchanged within them, we investigate the way in which communal and exchange relationships are formed between consumers and AI and the way they influence consumers' willingness to disclose personal information to AI. With the help of structural equation modeling, we prove empirically that attachment to AI rather develops communal relationships compared to exchange relationships between consumers and AI. Communal relationships have a stronger influence on both enjoyment and self-disclosing behavior, while exchange relationships do not trigger a self-disclosing behavior unless there is enjoyment. Furthermore, attachment to AI alone does not influence self-disclosing behavior unless a communal relationship is developed. Our structural equation model emphasized the complex nature of relationships between consumers and AI and has important implications for the way AI will be optimally integrated in business processes and society.

Social media as a workplace panopticon: The development and validation of social media monitoring by workplace contacts scale

The monitoring of employees' private social network accounts by employers and colleagues has become increasingly prevalent, yet research in this area remains limited. To address this gap, the present study developed and validated a scale to measure social media monitoring by workplace contacts (SMMWC). The scale, comprising fifteen items, was developed using Hinkin's (1998) approach to scale development and has four dimensions based on the concept of panoptic effect by Foucault (1977) and Botan (1996). While Study 1, based on 334 employees, focused on scale development, Study 2, based on 302 employees, replicated the factor structure of the SMMWC scale and examined its impact on outcomes, using a time-lagged design. The SMMWC scale demonstrated strong psychometric properties, including factorial validity; discriminant validity with electronic performance monitoring and user perceptions of social media monitoring; and criterion-related validity with online disclosure, social capital, emotional exhaustion, and self-concept clarity. Notably, SMMWC was positively associated with online disclosure in both the studies and was significantly related to emotional exhaustion and self-concept clarity in Study 2, suggesting that SMMWC can influence employees' online behavior and psychological well-being.

Influence of digital transformation on employee innovative behavior: roles of challenging appraisal, organizational culture support, and transformational leadership style

Introduction

This study investigates the relationships between digital transformation (DT), challenging appraisal (CA), organizational culture support (OCS), transformational leadership style (TLS), and employee innovative behavior (EINB) in Brazzaville's banking sector. Grounded in Social Cognitive Theory and Self-Determination Theory, the research aims to provide insights into how these factors interact to influence innovation within organizations undergoing digital change.

Methods

Data were collected from 280 employees working in the top five banks in Brazzaville. Structural Equation Modeling (SEM) was applied using SPSS 26 and SmartPLS to analyze the relationships among DT, CA, OCS, TLS, and EINB.

Results

The findings reveal significant positive relationships between DT and CA, DT and EINB, and CA and EINB. Moreover, CA and OCS partially mediate the relationship between DT and EINB. While CA has a significant effect on EINB, TLS moderates the DT-EINB relationship by weakening its positive impact. Hypotheses regarding these relationships were largely confirmed, except for the interaction effect of DT and TLS on EINB.

Discussion

These results highlight the crucial role of CA and OCS in facilitating the impact of digital transformation on employee innovation. Additionally, they suggest that higher levels of transformational leadership may not always strengthen innovation in digitally transforming organizations. The study provides valuable managerial implications for fostering an innovative workforce in the banking sector.

Digital Wellness Programs in the Workplace: Meta-Review

BACKGROUND

Corporate wellness programs are increasingly using digital technologies to promote employee health. Digital wellness programs (DWPs) refer to initiatives that deliver health interventions through digital tools. Despite a growing body of evidence on DWPs, the literature remains fragmented across multiple health domains.

OBJECTIVE

This study aims to provide a comprehensive synthesis of existing research on the efficacy (eg, impact on employee's physical health, mental well-being, behavioral changes, and absenteeism) and acceptability (eg, engagement, perceived usefulness, and adoption) of employer-provided DWPs. Specifically, we aim to map the extent, range, and nature of research on this topic; summarize key findings; identify gaps; and facilitate knowledge dissemination.

METHODS

We conducted a meta-review of studies published between 2000 and 2023. We adopted a database-driven search approach, including the MEDLINE, PsycINFO, ProQuest Central, and Web of Science Core Collection databases. The inclusion criteria consisted of (1) review articles; (2) publications in English, French, or German; (3) studies reporting on digital health interventions implemented in organizations; (4) studies reporting on nonclinical or preclinical employee populations; and (5) studies assessing the efficacy and acceptability of employer-provided DWPs. We performed a descriptive numerical summary and thematic analysis of the included studies.

RESULTS

Out of 593 nonduplicate studies screened, 29 met the inclusion criteria. The most investigated health domains included mental health (n=19), physical activity (n=8), weight management (n=6), unhealthy behavior change (n=4), and sleep management (n=2). In total, 24 reviews focused on the efficacy of DWPs, primarily in relation to health-related outcomes (eg, stress and weight), while fewer reviews addressed organization-related outcomes (eg, burnout and absenteeism). Four reviews explored the mechanisms of action, and 3 assessed the acceptability of DWPs using various measures. Overall, the findings support the efficacy and acceptability of DWPs, although significant gaps persist, particularly regarding the durability of outcomes, the role of technology, and the causal mechanisms underlying behavioral change.

CONCLUSIONS

While DWPs show promise across a variety of health domains, several aspects of their effectiveness remain underexplored. Practitioners should capitalize on existing evidence of successful DWPs while acknowledging the limitations in the literature.

Enterprise Digital Transformation Strategy: The Impact of Digital Platforms

The development of the digital economy is a strategic choice for seizing new opportunities in the latest wave of technological revolution and industrial transformation. As a critical tool for driving the digital transformation of enterprises, digital platforms play a pivotal role in this process. This study employs the evolutionary game theory of complex networks to develop a game model for the digital transformation of enterprises and utilizes the Fermi rule from sociophysics to characterize the evolution of enterprise strategies. Throughout this process, the interactive behaviors and strategic choices of enterprises embody the features of information flow and dynamic adjustment within the network. These features are crucial for elucidating the complexity and uncertainty inherent in strategic decision-making. The research findings indicate that digital platforms, through the provision of high-quality services and the implementation of effective pricing strategies, can significantly reduce the costs associated with digital transformation, thereby enhancing operational efficiency and innovation capacity. Moreover, the model reveals the competitive relationships between enterprises and their impact on transformation strategies, offering theoretical insights for policymakers. Based on these findings, the paper proposes policy recommendations such as strengthening infrastructure, implementing differentiated service strategies, and enhancing decision-making capability training, with the aim of supporting the digital transformation of enterprises across various industries and promoting sustainable development.

Study on the "digital divide" in the continuous utilization of Internet medical services for older adults: Combination with PLS-SEM and fsQCA analysis approach

BACKGROUND

With the rapid digitalization of healthcare and an aging population, understanding the factors influencing older adults' sustained adoption of Internet medical services is critical. However, existing research often oversimplifies these factors by relying on linear models. This study integrates Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to explore the complex pathways driving continued use.

METHODS

A survey of 1,920 older adults (60-75 years) in China assessed satisfaction, e-health literacy, self-efficacy, social support, social influence, social participation, and willingness to use Internet medical services. PLS-SEM examined the relationships between variables, while fsQCA identified multiple configurations leading to sustained use.

RESULTS

PLS-SEM identified satisfaction as the strongest predictor of sustained use (β = 0.281, p < 0.001), acting as both a direct determinant and a mediator for e-health literacy and social participation. Social influence (β = 0.189, p < 0.001) and social support (β = 0.172, p < 0.001) also contributed significantly. FsQCA revealed six distinct configurations, with satisfaction and e-health literacy as core conditions across most pathways.

CONCLUSIONS

By integrating linear and configurational approaches, this study provides a nuanced understanding of older adults' digital healthcare behaviors. Enhancing satisfaction, digital literacy, and social engagement is key to fostering sustained adoption. Tailored interventions based on distinct configurations can maximize the effectiveness of digital health programs.

IMPLICATIONS

This research bridges gaps in understanding complex behaviors and provides actionable insights for policymakers and healthcare providers, highlighting the critical role of digital literacy and social support.

A study on the causes of viewers' non-continuous following intention in tourism live streaming

With the advancement of digital technologies, tourism live streaming (TLS) has rapidly gained global popularity due to its real-time and interactive features, showcasing significant marketing potential. However, viewer retention remains a major challenge and a bottleneck for TLS development. This study first defined the concept and dimensions of alternative attractiveness in TLS through qualitative interviews. It then constructs an analytical framework based on the Push-Pull-Mooring (PPM) theory. It empirically tests how psychological contract breach, viewer-live streamer social distance, and alternative attractiveness influence viewers' non-continuous following intention (NCFI) in TLS. The findings reveal that these factors significantly impact NCFI. Customer complaining behavior mediates the relationship between psychological contract breach and NCFI, and perceived controllability positively moderates this relationship. This study provides a new theoretical perspective on understanding viewer attrition mechanisms and offers practical suggestions for TLS platforms and streamers to enhance viewer retention.

Applying Robotic Process Automation to Monitor Business Processes in Hospital Information Systems: Mixed Method Approach

BACKGROUND

Electronic medical records (EMRs) have undergone significant changes due to advancements in technology, including artificial intelligence, the Internet of Things, and cloud services. The increasing complexity within health care systems necessitates enhanced process reengineering and system monitoring approaches. Robotic process automation (RPA) provides a user-centric approach to monitoring system complexity by mimicking end user interactions, thus presenting potential improvements in system performance and monitoring.

OBJECTIVE

This study aimed to explore the application of RPA in monitoring the complexities of EMR systems within a hospital environment, focusing on RPA's ability to perform end-to-end performance monitoring that closely reflects real-time user experiences.

METHODS

The research was conducted at Seoul National University Bundang Hospital using a mixed methods approach. It included the iterative development and integration of RPA bots programmed to simulate and monitor typical user interactions with the hospital's EMR system. Quantitative data from RPA process outputs and qualitative insights from interviews with system engineers and managers were used to evaluate the effectiveness of RPA in system monitoring.

RESULTS

RPA bots effectively identified and reported system inefficiencies and failures, providing a bridge between end user experiences and engineering assessments. The bots were particularly useful in detecting delays and errors immediately following system updates or interactions with external services. Over 3 years, RPA monitoring highlighted discrepancies between user-reported experiences and traditional engineering metrics, with the bots frequently identifying critical system issues that were not evident from standard component-level monitoring.

CONCLUSIONS

RPA enhances system monitoring by providing insights that reflect true end user experiences, which are often overlooked by traditional monitoring methods. The study confirms the potential of RPA to act as a comprehensive monitoring tool within complex health care systems, suggesting that RPA can significantly contribute to the maintenance and improvement of EMR systems by providing a more accurate and timely reflection of system performance and user satisfaction.

Offline visit intention of online patients: the Grice's maxims and patient involvement

Online Healthcare Consulting Services (OHCS) can benefit physicians and patients. However, it is unclear how OHCS and what types of persuasive content enhance patients' intentions to visit offline. Based on the Elaboration Likelihood Model (ELM) and Grice's maxims of the Cooperative Principle, we formulated hypotheses related to factors in the central route, peripheral route, and patient involvement that influence patients' offline visit intentions. We used the amount of information, reliability, relevance, and understandability to measure information quality. By collecting data from an online healthcare site, we employed a regression model to evaluate our hypotheses. The results revealed that central route factors (amount of information, reliability, relevance, and understandability) and peripheral cues positively affect patients' offline visits. We also verified that patient involvement increases the impact of central route factors. This study extended the application of ELM and Grice's maxims in the field of OHCS, offering insights into how patients form intentions to visit offline through persuasive online content and providing valuable practical guidance for online physicians.

Promoting elderly wellbeing through indigenous music and choral performance

This paper explores the impact of indigenous instrumental music and choir performances on the wellbeing of elderly individuals who perform their music at the Hlanganani Malamulele Society for the Aged centre in Giyani, Limpopo Province, South Africa. It examines how these musical activities provide emotional nourishment and promote happiness and wellbeing among the elderly. Through interviews, performances, music transcription, participation, and observation, the study finds that engagement in music activities, such as choir singing, performing and listening to indigenous instruments, significantly promotes the wellbeing and health of the elderly. The findings suggest that these musical activities contribute to the reduction of stress and depression while encouraging a fulfilling lifestyle for the elderly participants. This paper argues that indigenous instrumental and choral music play a crucial role in fostering a healthy, wellbeing and happy life for the elderly members.

A pilot study protocol of a relational coordination training intervention among healthcare professionals in an Army medical center

BACKGROUND

As patient care becomes more complex, high-quality communication and relationships among healthcare professionals are critical to coordinating care. Relational coordination (RC), a process of high-quality communication supported by shared goals, shared knowledge, and mutual respect, is positively associated with better patient (e.g., quality of care) and staff (e.g., job satisfaction, and retention) outcomes. A few researchers have found that communication skills training improves RC in civilian hospitals. However, researchers have not tested the feasibility of conducting communication skills training based on the RC framework among healthcare professionals in military hospitals. To address this gap, we propose conducting an RC training intervention in a military hospital. The primary aim of the proposed pilot study is to determine the feasibility (e.g., recruitment, retention, and completion rates) of conducting an RC training intervention in an Army medical center. The secondary aim is to explore the acceptability and usability of the RC training intervention. We will also explore changes in RC, quality of care, job satisfaction, and intent to stay among participants following the RC training intervention.

METHODS

A single-group feasibility study will be conducted among nurses and physicians from three units (intensive care unit, medical-surgical, and labor and delivery unit). A convenience sample of licensed practical nurses (LPNs), registered nurses (RNs), resident physicians, and physicians from the participating units will be invited to complete a 1-h RC training intervention once a month for 3 months. Participants will complete RC, quality of care, job satisfaction, and intent to stay measures at baseline and 2 weeks after each RC training intervention session. To assess the feasibility of conducting an RC training intervention, we will examine recruitment/retention rates, intervention session completion rates, and survey measure completion rates. Acceptability will be assessed qualitatively through focus group interviews, and results will be used to refine the intervention and determine if the selected measures align with participant experiences. For our secondary aim, we will explore the acceptability of the RC training intervention through focus group interviews. We will also explore changes in outcome measures using descriptive statistics with 95% confidence intervals.

DISCUSSION

Findings will establish the feasibility and acceptability of conducting an RC intervention in a military hospital and inform refinement of the intervention and study procedures prior to conducting a larger randomized controlled trial to establish efficacy.

Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model

In the rapidly evolving field of healthcare, Artificial Intelligence (AI) is increasingly driving the promotion of the transformation of traditional healthcare and improving medical diagnostic decisions. The overall goal is to uncover emerging trends and potential future paths of AI in healthcare by applying text mining to collect scientific papers and patent information. This study, using advanced text mining and multiple deep learning algorithms, utilized the Web of Science for scientific papers (1587) and the Derwent innovations index for patents (1314) from 2018 to 2022 to study future trends of emerging AI in healthcare. A novel self-supervised text mining approach, leveraging bidirectional encoder representations from transformers (BERT), is introduced to explore AI trends in healthcare. The findings point out the market trends of the Internet of Things, data security and image processing. This study not only reveals current research hotspots and technological trends in AI for healthcare but also proposes an advanced research method. Moreover, by analysing patent data, this study provides an empirical basis for exploring the commercialisation of AI technology, indicating the potential transformation directions for future healthcare services. Early technology trend analysis relied heavily on expert judgment. This study is the first to introduce a deep learning self-supervised model to the field of AI in healthcare, effectively improving the accuracy and efficiency of the analysis. These findings provide valuable guidance for researchers, policymakers and industry professionals, enabling more informed decisions.

The relationship between specific problematic internet use and hope: academic exhaustion as mediator and mattering as moderator among Chinese university students

Problematic social media use (PSMU) and problematic gaming (PG) among university students as specific types of problematic internet use (PIU) have become a growing concern. PSMU and PG may lead to negative outcomes such as academic exhaustion and diminished hope. However, previous studies have not simultaneously considered the associations among these variables from the perspective of Stressor-Strain-Outcome model. Furthermore, the concept of 'mattering'-the feeling of being valued and important to others and 'fear of not mattering' in this dynamic is notably under-investigated. The present study aimed to examine the associations among these variables and evaluated whether mattering profiles moderated the associations involving PIU among university students.A survey was conducted among 3,035 university students in China, with an average age of 19.24 years (SD = 1.83). The sample included 52% males and 48% females from 19 different universities. The Bergen Social Media Addiction Scale, the Internet Gaming Disorder Scale-Short Form, the General Mattering Scale, the Fear of Not Mattering Inventory, the Maslach Burnout Inventory-Student Survey, and the Dispositional Hope Scale were utilized to evaluate PSMU, PG, general mattering, fear of not mattering, academic exhaustion, and hope, respectively. Furthermore, latent profile analysis was used to categorize students into distinct mattering profiles based on measures of general mattering and fear of not mattering to others.Correlational analyses indicated that PSMU and PG were associated with greater academic exhaustion, reduced hope, and higher levels of fear of not mattering. Mediation analysis identified academic exhaustion as a mediator in the relationships between PSMU and hope, as well as between PG and hope. Profile analyses identified a group of students distinguished by exceptionally low levels of general mattering. Mattering profiles acted as moderators of the associations between PG and academic exhaustion, and between academic exhaustion and hope.PG negatively affected students' hope through academic exhaustion, while different mattering profiles had diverse associations. Customized intervention strategies focused on boosting hope and feelings of mattering, and reducing fears of not mattering are needed to reduce vulnerability to PG and PSMU.

Doctor-patient-family collaboration in community-based chronic disease management to enhance multidimensional value

The United Nations Sustainable Development Goal (SDG 3) aims to strengthen healthcare systems, combat chronic and infectious diseases, and improve global health. However, chronic diseases pose significant public health challenges, straining healthcare resources and escalating economic burdens. In China, they affect 180 million people, account for over 90 % of the national disease burden, and are the leading cause of mortality. Community chronic disease management faces challenges such as limited capacity, uneven resource allocation, and weak information systems. Despite policies to improve primary healthcare, outcomes remain modest due to implementation gaps. Addressing these issues requires creating "multidimensional value" through collaboration among doctors, patients, families, and communities. This framework emphasizes functional value (efficiency), social value (community ties), emotional value (well-being), and health value (better outcomes). However, most research narrowly focuses on doctor-patient collaboration, overlooking broader dynamics involving families and community healthcare providers. By explicitly exploring the goals and collaborative roles of doctor-patient-family value co-creation in community chronic disease management, we aim to develop well informed strategies to enhance interaction and resource integration, offering insights for China and scalable solutions for global health.

Artificial intelligence and employee outcomes: Investigating the role of job insecurity and technostress in the hospitality industry

Drawing on self-determination theory (SDT), this research examines how the utilization of artificial intelligence (AI) in hospitality organizations is influencing employee work and career outcomes (well-being and career success). We explore the underlying role of job insecurity in the associations of AI use with employee wellbeing and career success. We further explore the boundary condition effect of technostress in our proposed model. This study used a three-wave online survey approach to collect data from 277 workers of fast-food chain restaurants in the People's Republic of China. We used Smart PLS 4 to analyze our data. The results showed a positive relationship among AI use and employee well-being, but not with career success. Job insecurity mediates the relationship between AI use and employee outcomes. Additionally, technostress moderated the associations between AI use and employee well-being and career success. This study contributes to the theory and practice in the field of AI and hospitality industry and helps understand the nexus between increasing use of AI and employees' work and career outcomes.

Does Fintech lead to enhanced environmental sustainability? The mediating role of green innovation in China and India

Fintech and green innovations are increasingly recognized as potential solutions for enhanced environmental sustainability. In this paper, we investigate the impact of Fintech on environmental sustainability through the lens of green innovation in manufacturing. Using questionnaire data from 477 manufacturing firms in China and India between February and June 2024, the study employs Partial Least Squares-Structural Equation Modelling to analyze the dynamic relationships. We find that both Fintech and green innovation significantly contribute to improving the environmental sustainability of manufacturing firms. Results further show that Fintech positively supports manufacturing firms' green innovation developments. Moreover, green innovations partially mediate Fintech's effect on environmental sustainability. Our results also highlight regional differences: the impact of Fintech and green innovation on environmental sustainability is stronger in China than in India. Additionally, Fintech's role in supporting green innovations is more pronounced in Chinese firms than in India. The paper highlights the importance of investments in Fintech and green innovation by manufacturing firms, particularly in emerging markets, to address environmental issues for sustainability.

Nudging sustainable fashion choices: An experimental investigation on generation Z fashion consumers

Despite the growing cognizance of Generation Z (Gen Z) fashion consumers about the externalities of fast fashion, an attitude-behaviour gap persists in their willingness to pay for sustainable fashion. This study uses dual-processing theory to examine how nudging communications in online fashion retail influence Gen Z's sustainable fashion choices and willingness to pay. It also explores how Gen Z's fashion-related knowledge and involvement and ecological consciousness moderate the effects of nudging. The study used a vignette-based experiment with dummy webpages from a leading Indian online fashion store to test nudging effects on sustainable fashion brands. The subjects were 252 Gen Z fashion consumers from India. The findings revealed a significant association between nudging conditions with participants' fashion choices with verbal nudges having a stronger influence than visual nudges. Moderation tests indicated that verbal nudging is more effective for those with high environmental orientation and high fashion familiarity.

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

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

Assessing the performance of Portuguese public hospitals before and during COVID-19 outbreak, with optimistic and pessimistic benchmarking approaches

The COVID-19 pandemic had a profound impact on the tertiary sector, particularly in healthcare, which faced unprecedented demand despite the existence of limited resources, such as hospital beds, staffing resources, and funding. The magnitude and global scale of this crisis provide a compelling incentive to thoroughly analyse its effects. This study aims to identify best practices within the Portuguese national healthcare service, with the goal of improving preparedness for future crises and informing policy decisions. Using a Benefit-of-the-Doubt (BoD) approach, this research constructs composite indicators to assess the pandemic's impact on the Portuguese public hospitals. The study analyzes monthly data from 2017 to May 2022, highlighting critical trends and performance fluctuations during this period. The findings reveal that each COVID-19 wave led to a decline in hospital performance, with the first wave being the most severe due to a lack of preparedness. Furthermore, the pandemic worsened the disparities among examined hospitals. Pre-pandemic top performers in each group improved their performance and were more consistently recognized as benchmarks, with their average benchmark frequency increasing from 66.5% to 83.5%. These top entities demonstrated greater resilience and adaptability, further distancing themselves from underperforming hospitals, which saw declines in both performance scores and benchmark frequency, widening the performance gap. The superior performance of top entities can be attributed to pre-existing strategic tools and contextual factors that enabled them to withstand the pandemic's challenges more effectively. HIGHLIGHTS: • The pandemic aggravated the differences between the hospitals examined. • The top-performing entities further distanced themselves from the remaining entities after the pandemic • Entities considered benchmarks before the pandemic remained the same, and became even more consistent during the pandemic. • The top-performing entities achieved higher scores than their pre-pandemic performance levels. • Benchmarking models for composite indicators with diverse decision-making preferences, and treatment of imperfect knowledge of data.

Resistance, tensions and consent to digital working in healthcare

Earlier research has extended knowledge about how the nature of healthcare work is changing, and the implications this has for professionals seeking to deliver effective, robust and state-of-the-art services. However, since the onset of the Covid-19 pandemic there has been a rapid mobilization of digital services across the sector that has raised new challenges. In this Special Issue (SI), we therefore aim to offer novel insights on how new patterns of work are playing out in this new era of digital healthcare. As digitalization has become widespread, even ubiquitous, it is now necessary to identify the theoretical, practical and empirical issues that affect the organization of health work now and how it might affect it in the future. Our overarching research question in this SI, which we address through the nine selected articles we present in this Editorial, is: How is digital work in healthcare being organized post-Covid 19, and how does this impact interprofessional collaborations, clinical work practices, professional identities and relations of power?

Understanding patient perception of digital value co-creation in electronic health record through clustering approach

Patients are central to healthcare services, and comprehending their perceptions is crucial for fostering effective value co-creation. This study aimed to investigate the user characteristics and perceptions of value co-creation within the context of Mobile Electronic Health Records (EHR). Using a questionnaire collected from 422 patients, the study employed the K-modes clustering algorithm in R-Studio to group users based on shared characteristics and perceptions of value co-creation. The analysis revealed three distinct user clusters, which are high familiarity-positive perception, low familiarity-positive perception and high familiarity-neutral to negative perception. These clusters characterized by unique attributes such as socio-economic, history of medical visit, intention to use, technological familiarity, and different perception of value co-creation in Mobile EHR systems. Descriptive statistics were used to further interpret the clusters, revealing differences in user characteristics and perception across cluster. The findings emphasize the importance of alignment between user expectations and system interactions. Effective alignment fosters value co-creation through resource access, sharing, integration, and recombination, while misalignment may result in value destruction. This study highlights the need to design and implement Mobile EHR systems that align with the diverse characteristics and of their users to enhance engagement and promote value co-creation.

One-shot intervention reduces online engagement with distorted content

Depression is one of the leading causes of disability worldwide. Individuals with depression often experience unrealistic and overly negative thoughts, i.e. cognitive distortions, that cause maladaptive behaviors and feelings. Now that a majority of the US population uses social media platforms, concerns have been raised that they may serve as a vector for the spread of distorted ideas and thinking amid a global mental health epidemic. Here, we study how individuals ( n = 838 ) interact with distorted content on social media platforms using a simulated environment similar to Twitter (now X). We find that individuals with higher depression symptoms tend to prefer distorted content more than those with fewer symptoms. However, a simple one-shot intervention can teach individuals to recognize and drastically reduce interactions with distorted content across the entire depression scale. This suggests that distorted thinking on social media may disproportionally affect individuals with depression, but simple awareness training can mitigate this effect. Our findings have important implicasstions for understanding the role of social media in propagating distorted thinking and potential paths to reduce the societal cost of mental health disorders.

The role of social media ads for election outcomes: Evidence from the 2021 German election

Social media ads have become a key communication channel in politics. However, the relationship between political ads from social media and election outcomes is not fully understood. Here, we aim to estimate the association between online political advertising and election outcomes during the 2021 German federal election. For this, we analyze a large-scale dataset of 21,641 political ads from Facebook and Instagram that received ≈126 million impressions. Using regression analysis, we show that political advertising on social media has a positive relationship with a candidate's election outcome and may even sway elections. All else equal, ≈200,000 additional impressions are predicted to increase a candidate's votes by 2.1%. We further use a causal sensitivity analysis to evaluate how unobserved confounding may affect our estimates. We find that the estimated impact of ads cannot be reasonably explained away, highlighting the significance of social media for election outcomes.

Technophobia Mediates the Associations Between Age, Education Level, and Readiness to Adopt New (Health) Technology Among Aging Adults

Current research on technophobia and readiness to adopt new technology in the aging population is often limited to the context of specific technologies and treats technophobia as a unidimensional construct. In this study, we investigate the role of demographic variables and various aspects of technophobia in determining Slovenian aging adults' readiness to adopt new technology. Partial least squares structural equation modeling revealed that age and educational level generally significantly predicted technophobia and indirectly contributed to readiness to adopt new technology via the human versus machine ambiguity dimension of technophobia. Moreover, age and human versus machine ambiguity were significant direct negative predictors of readiness to adopt new technology. Findings obtained specifically in the health sub-domain were similar. Our results have important implications for addressing the low adoption of new technology among aging adults as they provide guidance on whom should be targeted with interventions and which aspects need to be addressed.

Factors influencing sustainable E-participation in public service delivery: A case of rail infrastructure project

This research aims to analysis factors influencing sustainable e-participation in development projects. The case of a semi-high-speed rail infrastructure project in a south Indian state is examined in this paper. The analysis considers e-participation-related social media content and news items from 2017 to 2022. Results reveal development themes and campaign strategies influence long-term e-participation. The findings demonstrate that government social media initiatives significantly influence knowledge generation in development projects and thus better-informed e-participation. The growing information-seeking culture among e-participants, on the other hand, compels for knowledge resources and the readiness of the initiators to divulge suitable decisions to meet citizens' requirements. Current research is limited by its concentration on a rail project. The moderators are expected to construct campaign event plans and involve rail initiatives to enable sustainable e-participation. Unlike previous studies that focused on the delays due to e-participation, the current research portrays the improvement of public service delivery.

How is patient trust transferred from online medical platforms to offline?

Introduction

The function of the internet medical platform has expanded from online consultation to offline diagnosis and treatment appointment, forming a complete service process combining online and offline, improving the patient's medical experience and promoting the transfer of online trust to offline. However, the existing studies pay insufficient attention to the dynamic and multi-stage characteristics of online medical trust, especially the lack of in-depth discussion on the trust transfer of patients from online to offline.

Methods

This study builds a patient trust transfer model based on relevant theories, and analyzes the influence mechanism of online reputation feedback on patients' online and offline trust combined with text mining technologies such as sentiment analysis. The research adopts the multi-dimensional analysis method, comprehensively considers the online and offline scenarios, and reveals the key drivers of trust transfer through large-scale data analysis.

Results

The study found that doctors' online reputation feedback and interaction quality were important factors affecting patients' trust transfer. Positive online interaction and high-quality reputation feedback significantly enhanced patient trust and promoted the transfer of online trust to offline. The trust transfer process is dynamic and multi-stage, and the influencing factors of different stages are different. The study also revealed the significant difference in trust mechanism between online medicine and traditional medicine.

Discussion

This study revealed the formation and transfer mechanism of trust in online health care by building a trust transfer model, filling the gap in related research. The results provide practical guidance for the online medical platform to optimize the service process and enhance the trust of patients. In the future, we can further explore the trust transfer mechanism under different cultural backgrounds to promote the globalization of Internet medicine.

Who is in the driving seat? Assessing innovation performance feedback and digital transformation of manufacturing enterprises

The use of digital technologies has enabled enterprises to enhance their innovation capabilities and reconstruct their competitive advantage throughout the wave of digital transformation. Previous research has examined the driving forces behind digital transformation through the lens of institutional theory, resource-based views, dynamic capacities, and upper echelons theory. However, these studies have ignored the fact that the decision makers with bounded rationality formulate digital transformation strategies based on "heuristic decisions". In order to address the above research gap, this study examines the impact of innovation expectation gap on digital transformation of enterprises based on the behavioral theory of the firm. In this paper, Chinese A-share manufacturing enterprises listed from 2010 to 2021 are used as the research sample. The results show that as the innovation expectation gap widens, enterprises will be more motivated to implement digital transformation to improve their innovation performance. Accordingly, the innovation expectation gap has a positive impact on the digital transformation of enterprises. After CEO power and CEO traits are embedded in the research framework, it is found that CEO power can strengthen the positive impact of innovation expectation gap on enterprise digital transformation. In addition, if the CEO has both functional diversity and digital literacy, CEO power's strengthening effect on the relationship between innovation expectation gap and enterprise digital transformation can also be enhanced. The study provides new insights for the study of enterprises digital transformation decision-making from the perspective of innovation expectation gap, which helps to expand the research topics of the behavioral theory of the firm.

The development of media truth discernment and fake news detection is related to the development of reasoning during adolescence

The spread of online fake news is emerging as a major threat to human society and democracy. Previous studies have investigated media truth discernment among adults but not among adolescents. Adolescents might face a greater risk of believing fake news, particularly fake news that is shared via social media, because of their vulnerabilities in terms of reasoning. In the present study, we investigated (1) the development of media truth discernment and the illusory truth effect from adolescence to adulthood and (2) whether the development of media truth discernment and the illusory truth effect are related to the development of reasoning ability. To accomplish this task, we recruited 432 adolescents aged 11 to 14 years as well as 132 adults. Participants were asked to rate the perceived accuracy of both real and fake news headlines. Participants were exposed to half of the news items before entering the rating phase. Finally, participants completed the Cognitive Reflection Test (CRT). Media truth discernment (i.e., the difference between participants' ratings of fake and real news) developed linearly with increasing age, and participants rated familiarized headlines as more accurate than novel headlines at all ages (i.e., the illusory truth effect). Finally, media truth development (but not the illusory truth effect) was related to the development of reasoning abilities with increasing age. Our findings highlight the urgent need to improve logical thinking among adolescents to help them detect fake news online.

How does negative new media coverage impact audit fees, cost cover, or risk premium? Based on the data from WeChat official account by Crawler Technology

This study empirically investigates the relationship between negative new media coverage and audit fees by collecting a sample of nonfinancial listed companies on the main board of the Shanghai Stock Exchange (SSE) from 2017 to 2019, along with data on negative new media coverage of official WeChat public accounts founded by the most influential national financial newspaper obtained using a crawler. This study revealed that: 1. Audit fees are significantly and positively related to negative news media coverage; 2. The increase in audit fees is due to the fact that if a listed company undergoes negative new media coverage, the accounting firm that audits the company will consequently increase risk premium and thus audit fees. We found no evidence that accounting firms spend more time and effort on audit work after a listed company experiences negative new media coverage; 3. Analyst-tracking has a moderating effect on negative new media coverage and audit fees, leading to an increase in audit fees; 4. Negative media reporting on non-state-owned enterprises is more likely to cause accounting firms to increase their audit fees than their state-owned peers, whereas "non-Big Four" accounting firms are more likely to increase their audit fees for companies with negative new media reports. This study, based on the differing impacts of negative new media coverage, intended to unravel the intricate relationship between different types of negative new media coverage and audit fees, help understand the mechanism whereby negative reporting impacts audit fees, and provides a benchmark for the development of a feasible audit fee system.

Encourage or inhibit: A study on the impact of corporate digital transformation on management's tone manipulation of information disclosure

Digitalization is anticipated to substantially improve information transparency and enhance the capital market's information environment. However, during the initial phase of digital transformation, companies face challenges in achieving high-quality information disclosure. This is because digital technology implementation and organizational adjustment are still at early stages. Concurrently, investors face difficulties in assessing the accuracy of disclosed information. This challenge provides management with the opportunity to overstate the benefits of digital transformation. This study investigates the impact of corporate digital transformation on management's tone manipulation behavior, using a sample of Chinese A-share listed companies from 2012 to 2021. Findings indicate that corporate digital transformation significantly fosters management's tone manipulation during its exploration phase. Media slant positively moderates this relationship. Further analysis supports the paper's hypothesis: companies with weaker financial flexibility and lower risk information disclosure levels show a stronger positive correlation between digital transformation and tone manipulation. Concurrently, mechanism analysis reveals that management overconfidence partially mediates the relationship. This suggests that digital transformation increases managerial overconfidence, thereby promoting tone manipulation. The conclusion offers new insights into enhancing management discussion and analysis information disclosure quality from a corporate strategic transformation perspective. It serves as a valuable reference for accurately identifying misleading management signals.

The Impact of Social Determinants of Health, Health Resources, and Environmental Factors on Infant Mortality Rates in Three Gulf Cooperation Council (GCC) Countries

Worldwide, there has been a notable decline in the infant mortality rate (IMR) in the last 20 years. Regionally, the Gulf Cooperation Council (GCC) countries echo the global trends to a certain extent. This study aims to explore the impact of social determinants of health (SDOH), health resources (HRS), and environmental (ENV) factors on the IMR in Bahrain, Qatar, and Kuwait. It is a retrospective time-series study using yearly data from 1990 to 2022. Partial Least Square Structural Equation Model (PLS-SEM) was utilized to construct an exploratory model of the IMR for each country. The results showed that SDOH, HRS, and ENV factors influenced IMRs in three GCC countries. In all three countries' models, only HRS exerted a direct effect on the IMR (Bahrain: -0.966, 95% CI -0.987 to -0.949; Kuwait: -0.939, 95% CI -0.979 to -0.909; and Qatar: -0.941, 95% CI -0.976 to -0.910). On the other hand, ENV factors and SDOH only influenced the IMR indirectly and negatively. Their beta coefficients ranged from -0.745 to -0.805 for ENV factors and -0.815 to -0.876 for SDOH. This study emphasizes the importance of adopting multi-faceted public health strategies that focus on improving socioeconomic conditions, expanding healthcare resources, and reducing environmental degradation. By adopting these multi-dimensional approaches, Bahrain, Qatar, and Kuwait can continue to progress in reducing IMRs and improving overall public health outcomes.

From defensive reasoning to innovation: how digital tools foster positive emotions in organizations

Researchers of organizational learning and innovation have frequently claimed that defensive reasoning is an inducer of negative emotions present in most organizations, inhibiting continuing innovation and development and individuals' effective learning. Although a significant amount of research has been conducted on the factors that reduce defensive reasoning in an organization, the breakthrough process and its outcomes have not yet been studied. This study uses narrative network analysis on longitudinal data from a Chinese tourist resort to explore how organizational factors-such as institutional environments, social media platforms, and virtual-reality role transformations-help employees overcome defensive reasoning and foster innovation. It demonstrates how digital management tools and corporate social platforms transform negative emotions into positive, creativity-enhancing actions. By analyzing individual defenses from both general and job position perspectives, the study introduces a comprehensive theoretical framework that highlights the role of emotional guidance and digital tools in reducing defensiveness, promoting collaboration, and improving organizational effectiveness and innovation.

Explore factors influencing residents' green lifestyle: evidence from the Chinese General Social Survey data

Introduction

This paper explores the multifaceted dynamics and various determinants impacting residents' green lifestyles in China, focusing on drop-off recycling, low-carbon purchasing, and civic advocating.

Methods

Using data from the 2021 Chinese General Social Survey and the Chinese Statistical Yearbook, we provide an integrated paradigm to position green lifestyles in a hierarchical framework, explore the individual-level mediating mechanisms nested within macro influences, and elucidate the relative strengths of determinants.

Results and discussion

Firstly, the random coefficient regression models show that environmental knowledge and environmental protection intention significantly positively affect green lifestyles. Adopting traditional media could enhance civic advocating, and using new media may bolster low-carbon purchasing tendencies. A higher per capita GDP, increased public expenditure on environmental protection, and a reduced proportion of secondary industry are significant factors that promote drop-off recycling and low-carbon purchasing. Secondly, the multilevel mediational effects identify that people's environmental protection intention is a salient mediating variable within the control of regional macro factors. Additionally, the sheaf coefficient clustering models underscore the prominence of ecological awareness and macro-level factors in shaping drop-off recycling and civic advocating.

Exploring a decade of deep learning in dentistry: A comprehensive mapping review

OBJECTIVES

Artificial Intelligence (AI), particularly deep learning, has significantly impacted healthcare, including dentistry, by improving diagnostics, treatment planning, and prognosis prediction. This systematic mapping review explores the current applications of deep learning in dentistry, offering a comprehensive overview of trends, models, and their clinical significance.

MATERIALS AND METHODS

Following a structured methodology, relevant studies published from January 2012 to September 2023 were identified through database searches in PubMed, Scopus, and Embase. Key data, including clinical purpose, deep learning tasks, model architectures, and data modalities, were extracted for qualitative synthesis.

RESULTS

From 21,242 screened studies, 1,007 were included. Of these, 63.5% targeted diagnostic tasks, primarily with convolutional neural networks (CNNs). Classification (43.7%) and segmentation (22.9%) were the main methods, and imaging data-such as cone-beam computed tomography and orthopantomograms-were used in 84.4% of cases. Most studies (95.2%) applied fully supervised learning, emphasizing the need for annotated data. Pathology (21.5%), radiology (17.5%), and orthodontics (10.2%) were prominent fields, with 24.9% of studies relating to more than one specialty.

CONCLUSION

This review explores the advancements in deep learning in dentistry, particulary for diagnostics, and identifies areas for further improvement. While CNNs have been used successfully, it is essential to explore emerging model architectures, learning approaches, and ways to obtain diverse and reliable data. Furthermore, fostering trust among all stakeholders by advancing explainable AI and addressing ethical considerations is crucial for transitioning AI from research to clinical practice.

CLINICAL RELEVANCE

This review offers a comprehensive overview of a decade of deep learning in dentistry, showcasing its significant growth in recent years. By mapping its key applications and identifying research trends, it provides a valuable guide for future studies and highlights emerging opportunities for advancing AI-driven dental care.

Impact of Scene Features of E-Commerce Live Streaming on Consumers' Flow and Purchase Intentions of Sporting Goods

Purpose-The purpose of this study is to examine the mechanism of scene features (i.e., visual appeal, presence, and scene-product matching) of e-commerce live streaming and how it impacts consumers' flow and purchase intentions of sporting goods. Design/methodology/approach-To test the hypotheses in the conceptualized model that was developed based on the Stimulus-Organism-Response (S-O-R) model, sports consumers (N = 340) who watched e-commerce live streaming responded to an online survey administration. Structural equation modeling (SEM) was applied to examine the research model and test the hypotheses. Findings-The results reveal that scene features positively affect consumer flow experience, in which scene-product matching is the main contributing factor. Moreover, the flow experience plays a critical mediating role in influencing purchase intentions; meanwhile, the moderation role of sport identification was not found to be statistically significant. Originality/value-This study fills the void to explore how scene features of e-commerce live streaming influence consumer behavior associated with sporting goods merchandise through immersed flow experience. Confirming the applicability of the S-O-R model in the sports e-commerce live streaming setting, the findings of this study identify dimensions of scene features of e-commerce live streaming and highlight the significance of developing scene-product congruence features when designing, operating, and promoting live streaming programs while enhancing immersive involvement.

Match made in Heaven (or Hell?): Understanding the High Incidence of Tinder Rapes in Spain

A recent report revealed that 21.7% of women in Spain who went on a Tinder date were raped. These findings suggest that the incidence of sexual violence on Tinder dates in Spain may be higher than in other social contexts. This study explores the experiences of Tinder users in Spain to understand the factors contributing to this phenomenon and to propose measures for enhancing user safety. We conducted four focus groups separated by sociodemographic characteristics that replicated the typical victims' and perpetrators' profile (age and gender). Male participants initially expressed disbelief and attributed the phenomenon to Tinder's environment, pathological behavior, pornography, and women's actions. In contrast, female participants accepted the statistic as reflective of real-world issues, dismissing pathological explanations and highlighting systemic victim-blaming, fear-induced paralysis, and the impact of pornography as key factors. The findings underscore a significant disparity in perceptions between genders, with males often minimizing or misattributing the problem, while females recognizing deeper systemic issues. These insights suggest a need for targeted interventions and policies that address both the behavioral and perceptual factors contributing to sexual violence on dating platforms.

Unveiling the nexus of teacher commitment and job satisfaction: insights from Ecuador's educational landscape

Understanding the factors that determine teachers' organizational commitment and job satisfaction is fundamental in the education sector, since these two constructs are directly related to teacher effectiveness and the quality of education. Despite their importance, there is little research on these constructs in Latin America in general, and specifically in the Ecuadorian educational system. The objective of this work is thus to identify the extrinsic and intrinsic factors that influence the organizational commitment and job satisfaction of teachers in Ecuador, and to establish whether there is any relationship between organizational commitment and job satisfaction. To that end, an exploratory theoretical model based on the aforementioned variables is developed and tested on a sample of 6,316 Ecuadorian teachers, using structural equation modeling (SEM) techniques with partial least squares (PLS). The results reveal a significant relationship between both extrinsic and intrinsic factors and job satisfaction, as well as between these factors and organizational commitment. Furthermore, both extrinsic and intrinsic factors indirectly influence job satisfaction through organizational commitment. These findings underscore the importance of considering both external and internal aspects of work in efforts to promote job satisfaction and organizational commitment.

Acceptance of a mental health app (JoyPopTM) for postsecondary students: a prospective evaluation using the UTAUT2

Introduction

Mental health (MH) smartphone applications (MH apps) can support the increasing MH needs of postsecondary students and mitigate barriers to accessing support. Evaluating MH app acceptance using technology acceptance models is recommended to improve student engagement with MH apps. The JoyPopTM app was designed to improve youth resilience and emotion regulation. The JoyPopTM app is associated with improved student MH, but its acceptance has yet to be evaluated quantitatively. The present study used the Unified Theory of Acceptance and Use of Technology (UTAUT2) to evaluate and examine constructs and moderators influencing the acceptance (i.e., behavioural intention) and use of the JoyPopTM app.

Method

Participants were 183 postsecondary students attending a Canadian University who used the app for one week and completed measures before and after using the app. Relationships posited by the UTAUT2 were tested using partial least squares structural equation modelling (PLS-SEM).

Results

Most participants accepted the JoyPopTM app. The UTAUT2 model explained substantial variance in behavioural intention and app use. Performance expectancy, hedonic motivation, and facilitating conditions predicted behavioural intention, and behavioural intention and facilitating conditions predicted app use. Age moderated the association between facilitating conditions and behavioural intention. Experience moderated the relationship between performance expectancy, hedonic motivation, and social influence on behavioural intention.

Discussion

Results provide insight into factors influencing the acceptance of the JoyPopTM app and its ability to engage students. Results also provide valuable insights for evaluating and optimally designing MH apps.

How healthcare providers' IT identity is formed and how it affects the use of telemonitoring: a qualitative interview study in COPD care

BACKGROUND

Telemonitoring is a promising approach to facilitate patients' self-management and improve health outcomes, especially among people with chronic health conditions. Yet, many healthcare organisations struggle to implement telemonitoring successfully. IT identity, an individual's self-identification with an information technology (IT) tool, has been suggested to strongly predict and shape the use of technology. IT identity is related to three emotional responses: emotional energy, dependence and relatedness.

OBJECTIVE

To explore how healthcare professionals' IT identity is shaped, and how it affects their attitude towards and intended use of telemonitoring.

DESIGN

Qualitative, semistructured interview study.

SETTING

Primary care and hospitals (general and academic) in the Netherlands.

PARTICIPANTS

Sixteen nurses, pulmonologists, general practitioners and researchers working in chronic obstructive pulmonary disease (COPD) care.

RESULTS

Participants expressed varying emotional responses regarding the use of telemonitoring. We associated participants' responses with the three dimensions of IT identity. Regarding emotional energy, some expressed pride in innovating, while others lacked faith in using telemonitoring. Regarding dependence, different perceived intentions and needs for using telemonitoring were identified: to coach patients, prevent deterioration of health, achieve logistical advantages for patients and preserve the accessibility of healthcare. Regarding relatedness, some participants expressed a strong external but weak internal motivation to use telemonitoring.Based on emotional responses, we identified five manifestations of IT identity that illustrate how different healthcare professionals use telemonitoring in COPD care: the Scientist, Innovator, Protector, Empowerer and Conversationalist. These manifestations differ in their readiness to innovate and in their beliefs what it means to be a good healthcare provider: to protect or to coach.

CONCLUSION

Healthcare professionals' emotional energy, dependence and relatedness regarding telemonitoring in COPD care shaped their IT identity and how they used telemonitoring. Implementation strategies tailored towards the five manifestations of IT identity could help the sustainable implementation of telemonitoring in clinical practice.

Harmonizing patient-centric requirements for secure digital health services in heterogeneous settings

Implementing electronic health services with a patient-centric focus while adapting to the know-how of local contexts is a challenge. This paper addresses this challenge by establishing a template of modular requirements for designing a viable Electronic Health Record (EHR) system that enables transmission and sharing of patient data across primary, secondary, and specialized care, ensuring versatility in diverse healthcare environments and across varying socio-economic landscapes. The research is anchored in design science and employs an action research strategy, using northern Brazil as empirical case. The approach builds on generic requirements from standards established by the European Union, Fast Healthcare Interoperability Resources (FHIR), and the Swedish ePrescription journal system. These requirements are refined and adapted to the Brazilian context through a participatory method, considering development disparities across municipalities and aligning with national policy. A key feature is the integration of knowledge graphs, which, when combined with fieldwork iterations involving healthcare professionals and patient association representatives, facilitated the extraction of patient-centric requirements. Strategies from Brazilian healthcare policies targeting chronic kidney disease, selected as a significant challenge for specialized healthcare in emergent areas, were incorporated to generalize the design of EHR modules aimed at prevention and monitoring of population at risk. Results support that harmonization towards legacy system is strongly advised and discourage the introduction of systems designed from scratch.

Platform Governance, Institutional Distance, and Seller Trust in Cross-Border E-Commerce

Trust from sellers is essential for the success of cross-border e-commerce (CBEC) platforms, and effective platform governance plays a crucial role in shaping and maintaining this trust. However, institutional distance can lead to deviations in sellers' understanding and implementation of platform governance mechanisms, posing a threat to the establishment of trust relationships. Research on the impact of platform governance mechanisms on trust from the seller's perspective is still relatively limited. Therefore, we aim to investigate the mechanisms through which formal governance mechanisms (normative, supervisory, and reward-punishment mechanisms) and relational governance mechanisms (community building) influence seller trust, and we examine the moderating effect of institutional distance. Through empirical analysis of 391 valid questionnaires, our results show that normative mechanisms and community building enhance seller trust by reducing their perceived risks, while the supervisory mechanism and reward-punishment mechanism directly affect seller-perceived risks and platform trust. Institutional distance negatively moderates the governance effectiveness of these mechanisms. Our findings offer significant theoretical contributions by advancing the understanding of seller behavior, extending platform governance and trust theory in CBEC research field, and enriching institutional distance frameworks, while providing practical insights for platforms to optimize governance mechanisms to foster seller trust.