Validation of the Arabic eHealth literacy questionnaire: a factor and Rasch analysis study

Introduction

Amidst the rapid digitalization of healthcare, there is a need for tools that accurately assess eHealth literacy across cultural contexts. This study focused on the validation of an Arabic version of the eHealth Literacy Questionnaire (eHLQ), a tool to facilitate patient engagement and health outcomes in digital healthcare.

Method

Using a convenience sampling method, the study recruited a diverse sample of 657 participants from Jordan (58.9% females and 41.1% males).

Results

Confirmatory Factor Analysis and Rasch analysis supported a six-factor model and demonstrated satisfactory item performance within established thresholds. The findings revealed good internal consistency with Cronbach's α ranging between ranging between 0.71 to 0.84. Differential Item Functioning analysis indicated no gender-specific variations.

Discussion

The validated Arabic eHLQ is a reliable tool that can help in supporting the development of tailored interventions to improve healthcare delivery in Arabic-speaking regions.

The refugees and health crisis: migration policy management and government response to Afghan migrants

BACKGROUND

The health crisis during the pandemic and its aftermath have caused multidimensional shifts within the economic and societal structure for refugees and other marginalized communities. Many countries have implemented programs to cater for the additional needs of underserved populations, but refugees and other migrants are usually not covered by these programs. In this context, this study attempts to explore the impact of the crisis on Afghan refugee's vulnerability and the relationship between health services, relief packages, and risk communication.

METHODS

The proposed model is tested with 427 Afghan refugees' families from five major cities of Pakistan. The partial least squares structural equation modelling (PLS-SEM) is used to test the vulnerability significance with the crisis and government response in facilities.

FINDINGS

The research findings show that post pandemic economic crisis, the access to health services, relief packages and risk communication is directly associated with Afghan refugees' vulnerability (β = 0.471, β = 0.501, β = 0.271 & β = 0.259). Notably the relationship between post pandemic economic crisis and Afghan refugees' vulnerability is mediated by limited access to health services and unavailability of relief packages. Unavailability of relief packages and lack of risk communication mediates the effect of refugees' crisis on vulnerability. Overall, the proposed model explains 63.3% of the variance in Afghan refugees' vulnerability with government services. It indicates that Afghan refugees are unable to access relief packages, and there is insufficient communication of risk factors. The lack of government facilities is due to the harder closed-door policy of the Pakistani government which has worsened the vulnerability of Afghan refugees after the sudden victory of the Taliban in Afghanistan.

CONCLUSIONS

In spite of hosting Afghan refugees for the last forty years, the government of Pakistan has no clear systemized policy towards Afghans till now. The paper offers practical policy implications as there is a need for migration policy management combining flexibility and friendliness cooperation to provide government services to refugees. Government preparedness has to include refugee populations in responses to emergencies and look into the current state of new Afghan refugees' flows, and take further extension in the continuation of migration management.

The Chinese version of Selection, Optimization, and Compensation Questionnaire: psychometric properties among adolescent students

Objective

This study established the reliability and validity of the Selection, Optimization, and Compensation Questionnaire in a sample of senior secondary school students in China.

Methods

The data for this study were sourced from 1,080 students from multiple senior secondary schools using the SOC Questionnaire and the Learning Engagement Scale. This study conducted Exploratory Factor Analysis and Confirmatory Factor Analysis. The factor structure analysis of the psychometric properties of SOC Questionnaire were examined on reliability, convergent validity, concurrent criterion validity, and incremental validity.

Results

The EFA results suggested that a three-factor solution was most appropriate for the SOC Questionnaire. The three-factor CFA model of this study calculated correlations different from what was published with an American sample of adolescents by the questionnaire developers. The reliability coefficients (Cronbach's α, McDonald's ω), composite reliability (rho_c), and reliability coefficient (rho_a), convergent and discriminant validity were good. Concurrent criterion validity, and incremental validity were demonstrated by the SOC Questionnaire and the LES.

Conclusion

The 17-item, 3-factor SOC Questionnaire demonstrated strong reliability and validity, thus offering a new multidimensional of the SOC Questionnaire to evaluate intentional self-regulation among adolescents in schools.

User avoidance behavior in pharmaceutical e-commerce intelligent customer service: a stressor-strain-outcome perspective

Introduction

This study explores the implementation of Intelligent Customer Service (ICS) in pharmaceutical e-commerce, aiming to enhance user acceptance and service efficiency while addressing the psychological factors influencing user behavior. It expands the boundaries of technology acceptance research by focusing on ICS use and avoidance in high-risk environments.

Method

A total of 418 valid questionnaires were collected from participants, ensuring data quality through rigorous screening. The study employed SPSS for data normality tests and SmartPLS for structural equation modeling to analyze the relationships between emotional stress, system overload, and user avoidance behavior.

Results

The findings indicate that system overload, information overload, and service overload significantly contribute to user emotional stress, which in turn drives avoidance behavior. The analysis revealed strong explanatory power (R 2 values ranging from 0.450 to 0.586) and confirmed the mediating role of emotional stress in the relationship between overload factors and user avoidance.

Discussion

This research highlights the critical role of emotional stress in user interactions with ICS, suggesting that pharmaceutical e-commerce companies must refine their ICS design to meet diverse user needs and reduce cognitive burdens. By leveraging big data and establishing robust feedback mechanisms, companies can enhance user experience and loyalty. The study also identifies limitations in demographic representation and suggests future research should incorporate qualitative methods for a deeper understanding of user behavior.

eHealth Literacy and Cyberchondria Severity Among Undergraduate Students: Mixed Methods Study

Background

With the development of the internet, health care websites have become increasingly important by enabling easy access to health information, thereby influencing the attitudes and behaviors of individuals toward health issues. However, few studies have addressed public access to health information and self-diagnosis.

Objective

This study investigated the background factors and status of cyberchondria severity among college students by conducting a nationwide sample survey using the Cyberchondria Severity Scale. Further, we explored the perspective of eHealth literacy of those with scores higher than 1 SD from the mean by analyzing their recent experiences using web-based health information.

Methods

A nationally representative sample of college students was surveyed, and 802 valid responses were obtained (male: 435/802, 54.2%; female: 367/802, 45.8%; mean age 20.3, SD 1.4 years). The Cyberchondria Severity Scale was used, which consisted of 4 dimensions (increased anxiety, obsessive-compulsive hypochondria, perceived controllability, and web-based physician-patient interaction). Additionally, we recruited 9 volunteers who scored more than 1 SD above the mean for in-depth interviews on their web-based health information-seeking behaviors.

Results

Significant differences were found across the 4 dimensions of cyberchondria severity (F3,2403=256.26; P<.001), with perceived controllability scoring the highest (mean 2.75, SD 0.87) and obsessive-compulsive hypochondria scoring the lowest (mean 2.19, SD 0.77). Positive correlations were observed between perceived controllability, web-based physician-patient interactions, increased anxiety, and obsessive-compulsive hypochondria (r=0.46-0.75, P<.001). Regression analysis indicated that health concern significantly predicted perceived controllability (β coefficient=0.12; P<.05) and web-based physician-patient interaction (β coefficient=0.16; P<.001). Interview data revealed that students often experienced heightened anxiety (8/9, 89%) and stress (7/9, 78%) after exposure to web-based health information, highlighting the need for improved health literacy and reliable information sources.

Conclusions

The study identified both benefits and risks in college students' use of web-based health information, emphasizing the importance of critical consciousness and eHealth literacy. Future research should examine how college students move from self-awareness to actionable change and the development of critical health literacy, which are essential for effective digital health engagement.

Unable to comply with regulations: How deterrent and social learning factors contribute to workplace safety violation

BACKGROUND

Workplace safety violation is a significant challenge for global enterprises. However, prior studies have generated inconsistent findings, which calls for a holistic framework to reveal the complex causality between antecedent conditions and workplace safety violations in high-risk industries.

OBJECTIVE

By embracing deterrence theory and social learning theory, this study aimed to examine how punishment (i.e., perceived punishment certainty and perceived punishment severity), shame (i.e., perceived shame certainty and perceived shame severity) and coworker safety violations (CSV) combine into configurational causes of employee safety violations (ESV).

METHODS

A two-wave sampling approach was used to obtain 370 usable samples from various high-risk industries in China. The confirmatory factor analysis was performed to test construct validity, and an emerging fuzzy set qualitative comparative analysis (fsQCA) was conducted to explore the complex causality between ESV and its multiple antecedents.

RESULTS

The fsQCA results indicate that no single antecedent condition is necessary for predicting high ESV, but three distinct configurations of multiple antecedents equivalently lead to high ESV. Among all configurations, a lack of perceived punishment severity, a lack of perceived shame certainty and severity, and high CSV play important roles in explaining ESV.

CONCLUSIONS

This study represents a pioneering endeavor utilizing fsQCA to explore how different combinations of punishment, shame and social learning antecedents contribute to high ESV, which goes beyond previous research focusing on antecedents independently and offers new insights into interconnected antecedents of ESV and their complex causality.

The relationship between environmentally induced emotion and memory for a naturalistic virtual experience

Emotional stimuli (e.g. words, images) are often remembered better than neutral stimuli. However, little is known about how memory is affected by an environmentally induced emotional state (without any overtly emotional occurrences) - the focus of this study. Participants were randomly assigned to discovery (n = 305) and replication (n = 306) subsamples and viewed a desktop virtual environment before rating their emotions and completing objective (i.e. item, temporal-order, duration) and subjective (e.g. vividness, sensory detail, coherence) memory measures. In both samples, a Partial Least Squares Correlation analysis showed that an emotional state characterised by high negative emotion (i.e. threat, fear, anxiety) and arousal was reliably associated with better memory in both objective (i.e. item) and subjective (i.e. vividness and sensory detail) domains. No reliable associations were observed for any temporal memory measures (objective or subjective). Thus, an environmentally induced state of negative emotion corresponds with enhanced memory for indices of episodic memory pertaining to "what" happened, but not necessarily "when" it happened.

Demographic Characteristics and Relational Coordination in ICU Teams: Implications for Building Diverse and Effective Healthcare Collaboration

OBJECTIVE

To determine if professional roles and demographic characteristics predict relational coordination (RC) among healthcare professionals in the ICU.

BACKGROUND

Race, age, and sex diversity are increasing in the medical and nursing workforce, raising questions regarding how well healthcare professionals are collaborating. RC is a validated model for coordinating interdependent work among healthcare professionals.

METHODS

The research team conducted a secondary analysis from a 2-group parallel randomized controlled trial. Study variables were examined using multiple regression.

RESULTS

One hundred two participants completed the survey. Professional role, race, age, and experience were not associated with RC. Sex and education were significantly associated with RC. Males and participants with bachelor's degrees reported higher RC within roles.

CONCLUSION

Diverse and inclusive work environments are critical to patient and staff outcomes. Nurse leaders can use RC to foster teamwork and coordinate patient care among healthcare professionals, despite demographic characteristics and professional roles.

Is digital-green synergy the future of carbon emission performance?

Amid the new industrial revolution, digital technology and green finance play pivotal roles in shifting towards a low-carbon economy. This paper establishes a coherent research framework by integrating digital technology, green financing, and carbon emission performance. Utilizing a multifaceted dataset that combines provincial panel data with corporate listings databases, this study evaluates the development of green finance using a hybrid weighing methodology that merges the analytical hierarchy process (AHP) with the spatial-temporal entropy weight method. This work empirically analyzes the effects and mechanisms through which these factors influence carbon emission performance, employing instrumental variables and models with two-way fixed effects. The results show that: (1) Green finance (green) and digital technology both have a significant and direct impact on enhancing carbon emission performance (cep). (2) The synergistic effect is particularly pronounced in the central and western regions, as well as in areas characterized by lenient environmental regulations and weaker commercial credit systems. (3) This synergy is primarily achieved through promoting industrial upgrades, alleviating financial mismatches, and reducing information asymmetry. The study also shows that synergy shapes threshold features in the positive effect of synergy on cep when combined with regulatory actions and economic growth. (4) While the digitalization of businesses may initially increase carbon emissions, the combined impact of digital technology and green effectively mitigates these increases and leads to a substantial reduction in emissions. These findings suggest designing policy initiatives that are both unique and flexible, and increasing the extent and complexity of the integration between digital technology and green. The outcomes of this study offer significant guidance for policy development and industry practices.

Synergistic governance efficiency of industrial pollution and CO2 emissions under the digital economy

Using panel data for 284 Chinese cities, this study explores the nonlinear relationship between the digital economy and the synergistic governance efficiency of industrial pollution and CO2 emissions (SGEIPCE). The study also investigates the transmission mechanism of two-way knowledge flows within this relationship using the double fixed effect model and two-stage least square method. The results show that the digital economy has a significant U-shaped relationship on the SGEIPCE: the impact first decreases and then increases. When the level of digital economy exceeds infection point, the SGEIPCE increases. The marginal effect identified through the heterogeneity analysis indicates that Chinese cities with high innovative talent agglomeration and low industrial Internet level are the first to cross the inflection point of the U-shaped relationship, and the promoting effect of the digital economy on the SGEIPCE is greater in these two types of cites. Further, when the digital economy crosses the inflection point, it indirectly improves the SGEIPCE by increasing the level of knowledge absorption and knowledge overflow. Knowledge overflow is the most critical transmission mechanism by which China's digital economy affects SGEIPCE. These results provide empirical support and a decision-making basis for promoting the mutually beneficial cooperation between digital economy and industrial synergistic governance.

Citizen preferences for online hate speech regulation

The shift of public discourse to online platforms has intensified the debate over content moderation by platforms and the regulation of online speech. Designing rules that are met with wide acceptance requires learning about public preferences. We present a visual vignette study using a sample ( n = 2,622 ) of German and US citizens that were exposed to 20,976 synthetic social media vignettes mimicking actual cases of hateful speech. We find people's evaluations to be primarily shaped by message type and severity, and less by contextual factors. While focused measures like deleting hateful content are popular, more extreme sanctions like job loss find little support even in cases of extreme hate. Further evidence suggests in-group favoritism among political partisans. Experimental evidence shows that exposure to hateful speech reduces tolerance of unpopular opinions.

Racial-Ethnic Disparities in Hearing Aid Use: Price Responsiveness Among Older Adults with Hearing Loss

OBJECTIVE

To explore the role of racial-ethnic background, income, residential context, and historic variation in hearing aid (HA) price HA usage among a nationally representative cohort of older adults with hearing loss.

METHODS

Multilevel logistic regression models evaluated data from the 2012 through 2017 Medical Expenditure Panel Survey (MEPS) to 1) compare historic HA use between subgroups, 2) test for differential responsiveness to price changes between racial and ethnic groups, and 3) assess the relative role of demographic characteristics and HA use.

RESULTS

Between 2012 and 2017, the price of economy HAs decreased by 5% while HA use among Non-Hispanic (NH) Whites and Hispanics with hearing loss increased by 30% and 20% respectively, but usage among NH-Blacks increased by less than 10%. After controlling for relevant covariates, NH-Blacks were two times less likely than NH-Whites to use a HA. Household income and price were only significant for NH-Whites who showed that a 1% increase in income was associated with a 10% increase in the likelihood of HA use. Calculation of subgroup participation showed that, when the price of HAs dropped by 1%, the likelihood of HA use by NH-Whites increased by 14.2%, Hispanics increased by 13.2%, and Others increased by 14.8%, but only 2.8% among NH-Blacks.

CONCLUSION

Results suggest that cost is not the primary barrier to HA utilization among minoritized individuals from racial and ethnic groups. Additional analyses are needed to evaluate the role of social, cultural, and environmental influences on HA utilization.

Exploring the effect of supply chain integration and supply chain transparency on SME environmental performance under conditions of environmental unpredictability

This research aims to study the impact of supply chain integration in bolstering SME supply chain transparency and environmental performance. Drawing on stakeholder theory, the study focuses customer and supplier integration as well as internal integration in the operations of the supply network. Manufacturing SMEs provided survey data suggesting that integration of both customers and suppliers improves SME supply chain transparency, while internal integration plays no role in this regard. Findings reveal that environmental unpredictability strengthens links between supply chain integration and transparency. Furthermore, strong results in terms of environmental issues depend significantly on supply chain transparency. Overall, this work provides much needed investigation into how the integration of the supply chain shapes SME supply chain transparency and environmental performance by offering insights for further research.

Young adults' adoption and use of mental health apps: efficient, effective, but no replacement for in-person care

Objective: Millions of people use mobile phone or computer-based applications-apps-to maintain their mental health and connect with treatment providers through text- and video-based chat functions. The present study sought to understand young adults' motivations for adopting this technology using the unified theory of acceptance and use of technology (UTAUT), how they use mental health apps, and the gratifications they receive from using mental health apps. Participants: One hundred-eighteen mental health app users responded to an online survey. Methods: A survey was conducted with students at a Midwestern university. The survey included questions regarding current mental health services, mental health apps used, UTAUT and gratifications survey items. Results: A regression analysis suggested users' performance expectancies, effort expectancies, and facilitating conditions predicted the adoption of mental health apps. Young adults most often use mental health apps for stress relief. While they preferred in-person treatment, users described mental health apps as efficient and helpful. Conclusion: Overall, the results reinforce the sense of optimism for the future of mental health apps, suggesting the potential for apps to supplement-but not necessarily replace-in-person care.

Biomedical data analytics for better patient outcomes

Medical professionals today have access to immense amounts of data, which enables them to make decisions that enhance patient care and treatment efficacy. This innovative strategy can improve global health care by bridging the divide between clinical practice and medical research. This paper reviews biomedical developments aimed at improving patient outcomes by addressing three main questions regarding techniques, data sources and challenges. The review includes peer-reviewed articles from 2018 to 2023, found via systematic searches in PubMed, Scopus and Google Scholar. The results show diverse disease-specific applications. Challenges such as data quality and ethics are discussed, underscoring data analytics' potential for patient-focused health care. The review concludes that successful implementation requires addressing gaps, collaboration and innovation in biomedical science and data analytics.

Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective

Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients' rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce resistance to AI monitoring.

Factors Influencing Telemedicine Adoption Among Health Care Professionals: Qualitative Interview Study

BACKGROUND

Telemedicine is transforming health care by enabling remote diagnosis, consultation, and treatment. Despite rapid adoption during the COVID-19 pandemic, telemedicine uptake among health care professionals (HCPs) remains inconsistent due to perceived risks and lack of tailored policies. Existing studies focus on patient perspectives or general adoption factors, neglecting the complex interplay of contextual variables and trust constructs influencing HCPs' telemedicine adoption. This gap highlights the need for a framework integrating risks, benefits, and trust in telemedicine adoption, while addressing health care's unique dynamics.

OBJECTIVE

This study aimed to adapt and extend the extended valence framework (EVF) to telemedicine, deconstructing factors driving adoption from an HCP perspective. Specifically, it investigated the nuanced roles of perceived risks, benefits, and trust referents (eg, technology, treatment, technology provider, and patient) in shaping behavioral intentions, while integrating contextual factors.

METHODS

We used a qualitative research design involving semistructured interviews with 14 HCPs experienced in offering video consultations. The interview data were analyzed with deductive and inductive coding based on the EVF. Two coders conducted the coding process independently, achieving an intercoder reliability of 86.14%. The qualitative content analysis aimed to uncover the nuanced perspectives of HCPs, identifying key risk and benefit dimensions and trust referents relevant to telemedicine adoption.

RESULTS

The study reveals the complex considerations HCPs have when adopting telemedicine. Perceived risks were multidimensional, including performance risks such as treatment limitations (mentioned by 7/14, 50% of the participants) and reliance on technical proficiency of patients (5/14, 36%), privacy risks related to data security (10/14, 71%), and time and financial risks associated with training (7/14, 50%) and equipment costs (4/14, 29%). Perceived benefits encompassed convenience through reduced travel time (5/14, 36%), improved care quality due to higher accessibility (8/14, 57%), and operational efficiency (7/14, 50%). Trust referents played a pivotal role; trust in technology was linked to functionality (6/14, 43%) and reliability (5/14, 36%), while trust in treatment depended on effective collaboration (9/14, 64%). Transparency emerged as a critical antecedent of trust across different referents, comprising disclosure, clarity, and accuracy. In addition, the study highlighted the importance of context-specific variables such as symptom characteristics (10/14, 71%) and prior professional experience with telemedicine (11/14, 79%).

CONCLUSIONS

This study expands the EVF for telemedicine, providing a framework integrating multidimensional risks, benefits, trust, and contextual factors. It advances theory by decomposing trust referents and transparency into actionable subdimensions and emphasizing context-specific variables. Practically, the findings guide stakeholders: policy makers should prioritize transparent regulations and data security, health care organizations should provide training and support for HCPs, and technology developers must design telemedicine solutions aligning with trust and usability needs. This understanding equips health care to address barriers, optimize adoption, and leverage telemedicine's potential for sustainable clinical integration.

Cross-Cultural Sense-Making of Global Health Crises: A Text Mining Study of Public Opinions on Social Media Related to the COVID-19 Pandemic in Developed and Developing Economies

BACKGROUND

The COVID-19 pandemic reshaped social dynamics, fostering reliance on social media for information, connection, and collective sense-making. Understanding how citizens navigate a global health crisis in varying cultural and economic contexts is crucial for effective crisis communication.

OBJECTIVE

This study examines the evolution of citizen collective sense-making during the COVID-19 pandemic by analyzing social media discourse across Italy, the United Kingdom, and Egypt, representing diverse economic and cultural contexts.

METHODS

A total of 755,215 social media posts from X (formerly Twitter) were collected across 3 time periods: the virus' emergence (February 15 to March 31, 2020), strict lockdown (April 1 to May 30, 2020), and the vaccine rollout (December 1, 2020 to January 15, 2021). In total, 284,512 posts from Italy, 261,978 posts from the United Kingdom, and 209,725 posts from Egypt were analyzed using the latent Dirichlet allocation algorithm to identify key thematic topics and track shifts in discourse across time and regions.

RESULTS

The analysis revealed significant regional and temporal differences in collective sense-making during the pandemic. In Italy and the United Kingdom, public discourse prominently addressed pragmatic health care measures and government interventions, reflecting higher institutional trust. By contrast, discussions in Egypt were more focused on religious and political themes, highlighting skepticism toward governmental capacity and reliance on alternative frameworks for understanding the crisis. Over time, all 3 countries displayed a shift in discourse toward vaccine-related topics during the later phase of the pandemic, highlighting its global significance. Misinformation emerged as a recurrent theme across regions, demonstrating the need for proactive measures to ensure accurate information dissemination. These findings emphasize the role of cultural, economic, and institutional factors in shaping public responses during health crises.

CONCLUSIONS

Crisis communication is influenced by cultural, economic, and institutional contexts, as evidenced by regional variations in citizen engagement. Transparent and culturally adaptive communication strategies are essential to combat misinformation and build public trust. This study highlights the importance of tailoring crisis responses to local contexts to improve compliance and collective resilience.

Leveraging Sentiment-Topic Analysis for Understanding the Psychological Role of Hype in Emerging Technologies-A Case Study of Electric Vehicles

This study presents a novel approach to examining the psychological impact of emerging technologies through the development of a Hype Cycle Model (HCM), utilizing sentiment analysis and topic modeling. Focusing on electric vehicles, we investigate how public sentiment-captured via social media comments-reflects the psychological effects of technology adoption and hype. Our model integrates both qualitative and quantitative analyses, utilizing sentiment scoring and topic modeling to explore thematic psychological trends. An analysis of approximately 43,000 social media comments on electric vehicles demonstrated that the integration of expert knowledge with public sentiment provides a comprehensive understanding of technology hype dynamics. The results revealed that sentiment analysis enables real-time tracking of emotional responses to emerging technologies, while Correlated Topic Modeling (CTM) offers contextual insights into the positioning of technologies within the HCM. These findings demonstrate that understanding public sentiment towards emerging technologies can provide valuable insights for both organizations and policymakers in technology forecasting and adoption planning. Our approach transforms the traditional black box implementation by Gartner Inc. into a transparent framework that illuminates the psychological underpinnings of technology hype, revealing how collective excitement, expectations, and emotional responses shape the trajectory of emerging technology adoption.

Framework for types of metainferences in mixed methods research

BACKGROUND

The generation of metainferences is a core and significant feature of mixed methods research. In recent years, there has been some discussion in the literature about criteria for appraising the quality of metainferences, the processes for generating them, and the critical role that assessing the "fit" of quantitative and qualitative data and results plays in this generative process. However, little is known about the types of insights that emerge from generating metainferences. To address this gap, this paper conceptualize and present the types and forms of metainferences that can be generated in MMR studies for guiding future research projects.

METHODS

A critical review of literature sources was conducted, including peer-reviewed articles, book chapters, and research reports. We performed a non-systematic literature search in the Scopus, Web of Science, Ovid, and Google Scholar databases using general phrases such as "inferences in research", "metainferences in mixed methods", "inferences in mixed methods research", and "inference types". Additional searches included key methodological journals, such as the Journal of Mixed Methods Research, International Journal of Multiple Research Approaches, Methodological Innovations, and the Sage Research Methods database, to locate books, chapters, and peer-reviewed articles that discussed inferences and metainferences.

RESULTS

We propose two broad types of metainferences and five sub-types. The broad metainferences are global and specific, and the subtypes include relational, predictive, causal, comparative, and elaborative metainferences. Furthermore, we provide examples of each type of metainference from published mixed methods empirical studies.

CONCLUSIONS

This paper contributes to the field of mixed methods research by expanding the knowledge about metainferences and offering a practical framework of types of metainferences for mixed methods researchers and educators. The proposed framework offers an approach to identifying and recognizing types of metainferences in mixed methods research and serves as an opportunity for future discussion on the nature, insights, and characteristic features of metainferences within this methodology. By proposing a foundation for metainferences, our framework advances this critical area of mixed methods research.

Time efficiency as a mediator between institutional support and higher education student engagement during e-learning

This study examined the relationship between institutional support and student engagement in e-learning, with time efficiency as a potential mediator among Saudi university students. This study employed a cross-sectional, questionnaire-based research design. A sample of 752 Saudi university students from different provinces in the Kingdom of Saudi Arabia completed an online questionnaire. The results of the measurement model showed good reliability and validity for all constructs. The results of the structural model and hypothesis testing showed that this study partially supported the hypotheses. Notably, there was a significant positive relationship between student support during e-learning and student engagement. In addition, student support was found to be a predictor of student's time efficiency (short-term planning, long-term planning, time attitude). Furthermore, the results revealed that long-term planning and time attitude, both components of time efficiency, act as mediators between support provided to students by a higher education (HE) institution during e-learning and their level of engagement. The findings shed light on the underlying mechanisms that explain students' e-learning engagement.

Investigating the impact of user perception and gamification elements on repurchase decisions in game live broadcasting

As a branch of online live broadcasting, the development of game live broadcasting is also getting faster and faster. Based on the theory of affordance-psychological outcome-behavioral (A-P-B), this paper introduces three gamification elements of user activity visibility, user level visibility and purchase effect visibility, and three user-perceived experience values of perceived hedonic value, perceived cognitive value and perceived social value to establish the model. After collecting data through questionnaires, an empirical analysis based on partial least squares structural equation modelling (PLS-SEM) was carried out using SPSS and SmartPLS data analysis methods to explore the influencing factors of viewers' re-purchase behaviors in game live broadcasting from the perspective of the visibility of gamification elements. The results of this study show that in game live broadcasting, there is a certain influence between the visibility of gamification elements and the perceived value of users, and that the visibility of user activity, the visibility of purchasing effects, and the visibility of user level all have a significant positive effect on the perceived value of the user experience. This study enriches the literature on the business aspects of game live broadcasting and consumer behavior and has a certain significance in guiding live broadcasting business scenarios to improve the re-purchasing behavior of live broadcast viewers.

When I Receive Too Much Social Support: The Effect of Social Support Overload on Users' Life Burnout and Discontinuance in Fitness Apps

BACKGROUND/OBJECTIVES

As fitness apps increasingly incorporate social interaction features, users may find themselves overwhelmed by an excess of received support, struggling to effectively manage it. Highlighting a novel recipient-centric perspective, we aim to investigate the impact of social support overload on users' life burnout and discontinuance within fitness apps.

METHODS

Utilizing Social Support Theory and Basic Psychological Needs Theory, we develop a model to examine how emotional, network, and informational support overload affect life burnout and discontinuance through the frustration of basic psychological needs: autonomy, competence, and relatedness. A total of 443 fitness app users were included in our study, and we employed Structural Equation Modeling (SEM) to empirically test this model.

RESULTS

The results highlight the significant mediating role of the frustration of basic psychological needs between social support overload and life burnout/discontinuance. Network and informational support overload positively correlate with frustration of all needs, whereas emotional support overload shows a complex relationship. All need frustrations are linked to life burnout, but only autonomy and relatedness frustrations significantly lead to discontinuance. Additionally, gender and app use proficiency are significant control variables impacting discontinuance.

CONCLUSIONS

This study adopts a novel recipient-centric perspective to explore social support overload, examining its effects on life burnout and discontinuance and offering practical implications for both users and app managers.

Public attitude and media governance of biometric information dissemination in the era of digital intelligence

Absrtact: In the era of digital intelligence, biometrics plays a critical role in mediating sensitive information dissemination, human-computer interaction, and governance in both virtual and real-world settings, including the evolving metaverse. Based on an empirical analysis of 1,862 participants, the current study investigated factors influencing public perception, acceptance, and risk awareness of biometric technologies. The findings highlight the critical roles of perceived trust (PT) and technical prudence (TP) in driving behavioral intentions (BI), with their positive effects outweighing the significant deterrent impact of perceived risks (PR). While PT and perceived availability (PA) significantly enhance the adoption of biometric technologies, TP exhibited an unexpected positive influence, suggesting that cautious users may still embrace biometrics if perceived as secure and trustworthy. These results emphasize the urgency of refining legal and regulatory frameworks, improving risk mitigation strategies, and enhancing user confidence to foster the responsible adoption and utilization of biometric technologies. This study offers valuable insights into the interplay of factors such as perceived trust, risks, and technological prudence in shaping behavioral intentions, contributing to a deeper understanding of biometrics in a rapidly digitizing society.

A Comprehensive Survey of Deep Learning Approaches in Image Processing

The integration of deep learning (DL) into image processing has driven transformative advancements, enabling capabilities far beyond the reach of traditional methodologies. This survey offers an in-depth exploration of the DL approaches that have redefined image processing, tracing their evolution from early innovations to the latest state-of-the-art developments. It also analyzes the progression of architectural designs and learning paradigms that have significantly enhanced the ability to process and interpret complex visual data. Key advancements, such as techniques improving model efficiency, generalization, and robustness, are examined, showcasing DL's ability to address increasingly sophisticated image-processing tasks across diverse domains. Metrics used for rigorous model evaluation are also discussed, underscoring the importance of performance assessment in varied application contexts. The impact of DL in image processing is highlighted through its ability to tackle complex challenges and generate actionable insights. Finally, this survey identifies potential future directions, including the integration of emerging technologies like quantum computing and neuromorphic architectures for enhanced efficiency and federated learning for privacy-preserving training. Additionally, it highlights the potential of combining DL with emerging technologies such as edge computing and explainable artificial intelligence (AI) to address scalability and interpretability challenges. These advancements are positioned to further extend the capabilities and applications of DL, driving innovation in image processing.

Explainable analysis of infrared and visible light image fusion based on deep learning

Explainability is a very active area of research in machine learning and image processing. This paper aims to investigate the explainability of visible light and infrared image fusion technology in order to enhance the credibility of model understanding and application. Firstly, a multimodal image fusion model was proposed based on the advantages of convolutional neural networks (CNN) for local context extraction and Transformer global attention mechanism. Secondly, to enhance the explainability of the model, the Delta Debugging Fuse Image (DDFImage) algorithm was employed for generating local explanatory information. Finally, we gain deeper insights into the internal workings of the model through feature importance analysis of the generated explanatory fusion images. Comparative analysis with other explainability algorithms demonstrates the superior performance of our algorithm. This comprehensive approach not only improves the explainability of the model but also provides more reference for practical application of the model.

Interdisciplinary systems may restore the healthcare professional-patient relationship in electronic health systems

OBJECTIVE

To develop a framework that models the impact of electronic health record (EHR) systems on healthcare professionals' well-being and their relationships with patients, using interdisciplinary insights to guide machine learning in identifying value patterns important to healthcare professionals in EHR systems.

MATERIALS AND METHODS

A theoretical framework of EHR systems' implementation was developed using interdisciplinary literature from healthcare, information systems, and management science focusing on the systems approach, clinical decision-making, and interface terminologies.

OBSERVATIONS

Healthcare professionals balance personal norms of narrative and data-driven communication in knowledge creation for EHRs by integrating detailed patient stories with structured data. This integration forms 2 learning loops that create tension in the healthcare professional-patient relationship, shaping how healthcare professionals apply their values in care delivery. The manifestation of this value tension in EHRs directly affects the well-being of healthcare professionals.

DISCUSSION

Understanding the value tension learning loop between structured data and narrative forms lays the groundwork for future studies of how healthcare professionals use EHRs to deliver care, emphasizing their well-being and patient relationships through a sociotechnical lens.

CONCLUSION

EHR systems can improve the healthcare professional-patient relationship and healthcare professional well-being by integrating norms and values into pattern recognition of narrative and data communication forms.

Influence of Social Media in Multidisciplinary Cleft Care in Indonesia

Social media has played a pivotal role in relaying healthcare-related information, especially in efforts to improve cleft management. Cleft management involves a multidisciplinary team throughout the years of comprehensive intervention, from birth to adulthood.

To investigate the behaviors of parents and patients with clefts regarding social media use in improving cleft-related outcomes, knowledge, and awareness.

This questionnaire-based descriptive study was conducted online and involved both closed- and short-ended questions.

Parents and patients with cleft lip and palate provided consent to participate in the study.

Patient demographics, history, and timing of cleft treatment, barriers to care, and social media use were explored.

Fifty-six participants were enrolled in this study. The mean ages of the mothers and fathers of children with cleft were 34 (range, 24-57) and 36 (range, 26-59) years, respectively, and more than one-half were university graduates. WhatsApp, Instagram, and YouTube were used by 100%, 89%, and 89% of parents, respectively, 82% of whom were part of a cleft community group. Seventy-two percent underwent labioplasty, and 75% underwent palatoplasty at the ideal time. Parents exhibited low perceived barriers to care, with 33% and 37% reporting limitations on knowledge and accommodation, respectively.

Social media is the key to bridging the gap between the large number of cases and facility limitations and specialized human resources. Cleft centers should integrate combined platforms (WhatsApp, YouTube, and Instagram) for marketing and education purposes. Social media and community groups facilitate sharing, engagement, and empowerment of patients and caregivers to improve cleft-related outcomes.

A service ecosystems perspective to explore social prescribing value co-creation for vulnerable young people in NEET situation

BACKGROUND

Social prescribing inherently embodies a co-productive nature, particularly within the 'holistic' model facilitated by the pivotal role of Link Workers. Most attention is focused on collecting evidence about the micro-level relationship between Link Workers and their clients. However, little is known about how this co-productive relationship influences or is influenced by value co-creation at different levels, given the involvement of multiple actors in delivering the intervention. To advance research on the operational processes underlying social prescribing, we propose a conceptual framework utilizing the Service Ecosystems perspective to investigate the application of social prescribing with young people in NEET situations in Italy.

METHODS

A single case study was conducted as part of the European C.O.P.E. (Capabilities, Opportunities, Places, and Engagement) initiative, examining the implementation of social prescribing targeting young NEETs (Not in Education, Employment, or Training) in Italy. Semi-structured interviews were conducted with 27 participants, including six members of the C.O.P.E. coordination team, six Link Workers, and 15 young people aged 15-34 years.

RESULTS

Findings are presented showing the ecosystem dynamics at each intervention phase: the referral process, co-production of an individualized action plan, and connection with and activation of community assets.

DISCUSSION

This research illustrates how social prescribing is not a linear path but rather a complex intervention with multiple interacting elements across ecosystem layers. The dyadic relationship between Link Workers and clients operates within broader care services, fostering continuity of care. The service ecosystem perspective offers a valuable framework for examining the dynamic interactions between actors and understanding how their resource integration processes and institutional arrangements foster the emergence of opportunities to support an invisible and hard-to-reach target group, such as young people in NEET situations.

Unearthing the determinants of digital innovation adoption in the agricultural sector: The role of food security awareness and agricultural experience

Extant research has widely acknowledged the role of digital innovation as a facilitator of digital transformation, presenting solutions for various challenges in various industries. However, prior research demonstrates inadequate discussions on the determinants of digital innovation adoption for digital transformation in developing countries, particularly in the agricultural sector. To address this gap, this study investigates the effect of food security awareness, innovation characteristics, and the moderating role of agricultural experience on behavioral intention to adopt digital innovation in the agricultural sector. A dyadic model based on diffusion innovation theory and the technology acceptance model is proposed to investigate the phenomenon. This study employed a cross-sectional quantitative approach to investigate the phenomenon based on survey data collected from 207 study participants in Ghana's agricultural sector and the partial least square structural equation modeling technique. The study's findings revealed that personal innovativeness significantly affects food security awareness (β = 0.574; p < 0.000), relative advantage (β = 0.699; p < 0.000), compatibility (β = 0.687; p < 0.000), and complexity (β = 0.312; p < 0.000). In addition, food security awareness (β = 0.336; p < 0.000), compatibility (β = 0.257; p < 0.000), and agricultural experience (β = 0.238; p < 0.003) significantly affect behavioral intention to adopt digital innovation. Furthermore, the study revealed that agricultural experience (β = -0.145; p < 0.036) moderates the relationship between compatibility and behavioral intention. Together, these variables explain 78.9 % of the variance in behavioral intention to adopt digital innovation in the agricultural sector in Ghana. The study contributes to the literature on digital innovation adoption in the agricultural sector in developing countries and proffers actionable insights for practitioners.

Social network sites (SNS) an archetype of techno-social stress: A systematic review

Background

Social Networking Sites (SNS) are widely used platforms known for both their hedonic and social connectivity benefits. Although there is considerable interest in understanding how personal technostress affects individual well-being, a significant gap remains in the systematic exploration of this topic within the literature.

Methods

This review systematically examined 41 empirical studies from Scopus and PubMed published between 2014 and 2023, following PRISMA guidelines, and assessed for methodological quality using the Mixed Method Appraisal Tool. Only English-language articles were considered to avoid translation complexities. Studies were categorized and coded using the Stressor-Strain-Outcome (SSO) model to examine demographic variations in stressor impacts and coping mechanisms.

Results

The findings reveal a complex interplay of technological, behavioral-technological, and social stressors. Technological complexities often exacerbate social stressors like FoMO (Fear of Missing Out) and social overload, resulting in psychological (e.g., anxiety, depression), behavioral (e.g., reduced engagement), and physical strains (e.g., sleep disruptions). Demographic factors significantly influence stress responses, with younger users and women particularly affected. Key intervention strategies identified include digital detox practices, mindfulness techniques, and user-centered SNS design modifications.

Conclusion

This review emphasizes the need for targeted approaches to mitigate SNS-induced technostress to foster balanced, health-oriented digital engagement. Future research should focus on developing comprehensive frameworks to address technostress impacts on diverse user groups better and support sustainable digital well-being practices.

Sparking employee's creativity in digital work: A new look on the role of perceived usefulness

Telecommuting platform is an important medium for collaboration in the digital era and empowering employees to work from anywhere. However, existing research has paid less attention to how employees' perception of telecommuting platform affects their behavior during working from home, especially the impact on their digital creativity. Drawing on self-determination theory, a dual path moderated mediation model was proposed to investigate the effect of perceived usefulness on employees' digital creativity. Based on survey data from 881 employees, we found that perceived usefulness has a significant positive impact on employees' digital creativity; work autonomy and telecommuting efficacy play a mediating role in the relationship between perceived usefulness and employees' digital creativity; psychological individualism positively moderates the relationship between perceived usefulness and employees' digital creativity through work autonomy. However, psychological individualism does not show a significant moderating effect on the relationship between perceived usefulness and employees' digital creativity through telecommuting efficacy.

An empirical study on logistic service quality, customer satisfaction, and cross-border repurchase intention

Domestic e-retailers acknowledge logistics service quality (LSQ) as a critical success factor in business excellence. However, exponential growth in cross-border e-commerce (CBEC) requires a re-evaluation of the relationship between LSQ and consumers repurchase intention. By integrating the technology acceptance model, this study investigates the impact of LSQ on repurchase intention based on the LSQ (experience)-satisfaction-repurchase intention consequence chain. Data were collected from 466 Chinese consumers who had engaged in online shopping with international vendors. Partial least squares structural equation modeling was employed to examine the effectiveness of the research model. The results reveal that delivery service quality, return logistics services, and cross-border online shopping experiences significantly influence customer satisfaction. Nevertheless, the relationships between delivery information service, delivery stability, price fairness, and customer satisfaction are not supported. Price fairness, cross-border online shopping experience, and customer satisfaction positively affect cross-border repurchase intentions. Additionally, customer satisfaction mediates the relationships between LSQ, price fairness, cross-border online shopping experience, and repurchase intention. The novelty of this study lies in its focus on the cross-border dimension, introducing additional factors, such as price fairness and cross-border online shopping experiences, including other variables that affect LSQ and customer satisfaction, in contrast to domestic e-commerce. This study contributes to the literature by providing new insights into the complex dynamics of LSQ in CBEC and highlighting the nuanced role of customer satisfaction as a mediator in different market contexts. It offers empirical findings and valuable insights into the multiple dimensions of LSQ and customer satisfaction, thus contributing to the body of knowledge.

The Impact of Linguistic Signals on Cognitive Change in Support Seekers in Online Mental Health Communities: Text Analysis and Empirical Study

BACKGROUND

In online mental health communities, the interactions among members can significantly reduce their psychological distress and enhance their mental well-being. The overall quality of support from others varies due to differences in people's capacities to help others. This results in some support seekers' needs being met, while others remain unresolved.

OBJECTIVE

This study aimed to examine which characteristics of the comments posted to provide support can make support seekers feel better (ie, result in cognitive change).

METHODS

We used signaling theory to model the factors affecting cognitive change and used consulting strategies from the offline, face-to-face psychological counseling process to construct 6 characteristics: intimacy, emotional polarity, the use of first-person words, the use of future-tense words, specificity, and language style. Through text mining and natural language processing (NLP) technology, we identified linguistic features in online text and conducted an empirical analysis using 12,868 online mental health support reply data items from Zhihu to verify the effectiveness of those features.

RESULTS

The findings showed that support comments are more likely to alter support seekers' cognitive processes if those comments have lower intimacy (βintimacy=-1.706, P<.001), higher positive emotional polarity (βemotional_polarity=.890, P<.001), lower specificity (βspecificity=-.018, P<.001), more first-person words (βfirst-person=.120, P<.001), more future- and present-tense words (βfuture-words=.301, P<.001), and fewer function words (βlinguistic_style=-.838, P<.001). The result is consistent with psychotherapists' psychotherapeutic strategy in offline counseling scenarios.

CONCLUSIONS

Our research contributes to both theory and practice by proposing a model to reveal the factors that make support seekers feel better. The findings have significance for support providers. Additionally, our study offers pointers for managing and designing online communities for mental health.

Value Cocreation and Codestruction in Digital Health Services: Protocol for a Systematic Review

BACKGROUND

To successfully design, develop, implement, and deliver digital health services that provide value, they should be cocreated with patients. However, occasionally, the value may also be codestructed. In the field of health care, the concepts of value cocreation and codestruction still need to be better established within emerging digital health services. Studying these concepts is essential for developing effective and sustainable patient-centered care.

OBJECTIVE

The aim of the study is (1) to understand the antecedents, decisions, and outcomes of value cocreation and codestruction in digital health services, (2) to define the dynamics between value cocreation and codestruction, and (3) to map future research areas of value cocreation and codestruction within digital health services.

METHODS

The systematic review will be conducted in accordance with the Joanna Briggs Institute methodology for mixed method systematic reviews and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. The review considers scientific qualitative, quantitative, or mixed method studies published in English, Finnish, or Swedish that concern either value cocreation or codestruction in digital health services. Studies focusing on physical robotics and online health communities, as well as non-peer-reviewed and nonscientific papers, will be excluded. The searches were conducted using Scopus and MEDLINE during this protocol creation. Critical appraisal will be done using suitable checklists for qualitative, quantitative, and mixed method studies. The review will adhere to a convergent integrated approach as outlined in the Joanna Briggs Institute methodology for mixed methods systematic reviews.

RESULTS

The searches resulted in a total of 837 records. The antecedents, decisions, and outcomes of value cocreation and codestruction in the context of digital health services will be described in a finalized systematic review. In the outcomes, our main interest is the effect on patient outcomes and experiences and professional experiences.

CONCLUSIONS

Since our study involves diverse scientific fields, there is a risk that our search does not capture all relevant papers. To mitigate this risk, we used 2 large databases for the searches. In addition, the value cocreation or codestruction terms may not have been used in all studies focusing on the collaborative roles of patients and providers, especially in the medical field, and that may be difficult to capture. The review reveals the current understanding of value cocreation and codestruction in digital health services and shapes the research agenda for these phenomena. Value cocreation can be used to both design and efficiently use digital health services trying to maximize the value for patients.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/63015.

Equalization of basic public services enabled by digitization: A study of mechanism and heterogeneity

Digitalization has penetrated into every aspect of life. However, research on the mechanisms through which digitalization affects the equalization of basic public services, as well as the heterogeneity of its impact on different fields of these services, is still insufficient. Based on the panel data of 30 provincial-level administrative regions in China from 2013 to 2023, this paper studies the mechanism and heterogeneity of the impact of digital development on the equalization of basic public services. The research finds that the improvement of the digital development level can significantly promote the equalization process of basic public services, and this finding remains robust after a series of endogeneity and robustness tests. The discussions on regional heterogeneity and spatial complexity show that digitalization makes a greater contribution to the equalization of basic public services in the central and western regions and the northeast than in the east. However, achieving equalization of basic public services across regions through digitalization is challenging. The development of digitalization and the equalization of basic public services are limited by territorial cohesion in geographical space. Underdeveloped regions have poor access to digitalization for achieving equalization of basic public services. This leads to a 'digital divide' between developed and underdeveloped regions. It also results in a 'low-lying area' phenomenon in basic public services. Additionally, the promoting effect of digitalization on the equalization of different areas of basic public services varies significantly. The effect is strongest for basic living services. It is moderate for environmental protection services and education services. The effect on medical services is not significant.

Community health system capacities and capabilities within an evolving community health policy framework: mixed methods study of stakeholders in central Uganda

OBJECTIVES

Empowering communities through identifying and unlocking community capacities and capabilities is vital for improving community health systems. This study assessed the community health system's status quo and readiness for implementing a government-led, partner-supported community health worker project.

DESIGN

A mixed methods cross-sectional study.

SETTING

Two districts and one city in central Uganda.

PARTICIPANTS

21 key informants (KIIs) with district leaders, 4 focus group discussions (FGDs) with community health workers (CHWs) termed as village health teams in the Ugandan setting and a survey of 487 CHWs and 419 pregnant women who had childbirth 12 months before.

STUDY MEASURES

KIIs and FGDs explored community health system resources using the WHO health systems building blocks and the UNICEF health system strengthening maturation model. However, the surveys explored the work-related attributes and services delivered by the CHWs and to the community, respectively.

ANALYSIS

A framework analysis was used for qualitative data in NVivo 14. While descriptive and stratified analyses were conducted for quantitative data in Stata I/C 15.0: proportions for the varied geographical entities were compared using the t-test with p values <0.05 considered significant, one-way ANOVA was used to compare means.

RESULTS

Overall, all sites had relatively strong governance of community health only challenged by multiple implementing partners that were weakly coordinated. There was an exclusive paper-based information management system that linked to the national DHIS-2 software. Community reporting rates varied between 20% and 80%. Community health financing was weak, similarly to commodities availability. The mean age of the community health workforce was high at 50.9 (SD 11.9); the majority reported adequate skills in service delivery except for community first aid, Kangaroo mother care and noncommunicable diseases. Households' most received CHW services included home visits, treatment for sick under-five children and child immunisation.

CONCLUSIONS

The existing CHW system has governance and reporting strengths but could be enhanced through revitalization, enhanced coordination of stakeholders, providing appropriate training, work tools, supervision and engaging the community for accountability of results.

The Impact of Cloaking Digital Footprints on User Privacy and Personalization

Our online lives generate a wealth of behavioral records-digital footprints-which are stored and leveraged by technology platforms. These data can be used to create value for users by personalizing services. At the same time, however, it also poses a threat to people's privacy by offering a highly intimate window into their private traits (e.g., their personality, political ideology, sexual orientation). We explore the concept of cloaking: allowing users to hide parts of their digital footprints from predictive algorithms, to prevent unwanted inferences. This article addresses two open questions: (i) can cloaking be effective in the longer term, as users continue to generate new digital footprints? And (ii) what is the potential impact of cloaking on the accuracy of desirable inferences? We introduce a novel strategy focused on cloaking "metafeatures" and compare its efficacy against just cloaking the raw footprints. The main findings are (i) while cloaking effectiveness does indeed diminish over time, using metafeatures slows the degradation; (ii) there is a tradeoff between privacy and personalization: cloaking undesired inferences also can inhibit desirable inferences. Furthermore, the metafeature strategy-which yields more stable cloaking-also incurs a larger reduction in desirable inferences.

Adoption of AI writing tools among academic researchers: A Theory of Reasoned Action approach

This research explores the determinants affecting academic researchers' acceptance of AI writing tools using the Theory of Reasoned Action (TRA). The impact of attitudes, subjective norms, and perceived barriers on researchers' intentions to adopt these technologies is examined through a cross-sectional survey of 150 researchers. Structural Equation Modeling (SEM) is employed to evaluate the measurement and structural models. Findings confirm the positive influence of favorable attitudes and subjective norms on intentions to use AI writing tools. Interestingly, perceived barriers did not significantly impact attitudes or intentions, suggesting that in the academic context, potential benefits may outweigh perceived obstacles to AI writing tool adoption. Contrarily, perceived barriers do not significantly affect attitudes and intentions directly. The TRA model demonstrates considerable explanatory and predictive capabilities, indicating its effectiveness in understanding AI writing tool adoption among researchers. The study's diverse sample across various disciplines and career stages provides insights that may be generalizable to similar academic contexts, though further research with larger samples is needed to confirm broader applicability. Results offer practical guidance for tool developers, academic institutions, and publishers aiming to foster responsible and efficient AI writing tool use in academia. Findings suggest strategies such as demonstrating clear productivity gains, establishing AI Writing Tool programs, and developing comprehensive training initiatives could promote responsible adoption. Strategies focusing on cultivating positive attitudes, leveraging social influence, and addressing perceived barriers could be particularly effective in promoting adoption. This pioneering study investigates researchers' acceptance of AI writing tools using a technology acceptance model, contributing to the understanding of technology adoption in professional contexts and highlighting the importance of field-specific factors in examining adoption intentions and behaviors.

Impacts of Hospital Data Breach on Healthcare Quality

OBJECTIVE

To examine the effects of data breach incidents on healthcare quality and to explore potential mechanisms.

DATA SOURCE

Hospital-level data breach reports from the U.S. Department of Health and Human Services and patient-level hospitalization records from Florida State Inpatient Database during 2013-2017.

STUDY DESIGN

We employ a propensity score matching difference-in-difference model to estimate changes in a patient's emergency department (ED) door-to-hospital admission hours, days to undergo principal procedure after admission, length of stay days, and in-hospital mortality rates following data breaches. We compare the health information technology (HIT) functionalities of breached and non-breached hospitals during both pre and post periods.

DATA COLLECTION/EXTRACTION METHODS

Our primary analysis covers 1,295,537 records of inpatients admitted through the EDs of 12 hospitals.

PRINCIPAL FINDINGS

Data breaches are associated with long-term improvements in healthcare quality, particularly in the timeliness of patient care and acute myocardial infarction (AMI) mortality. Over time, patients experience a reduction of 0.56 h in ED door-to-hospital admission time (95% confidence interval [CI]: -1.04 to -0.06 h) and a decrease of 0.18 days in time to undergo the principal procedure after hospital admission (95% CI: -0.23 to -0.13 days). Additionally, AMI patients experience a one percentage point reduction in in-hospital mortality (95% CI: -2 to -0.06 percentage points), while mortality rates for other patient groups remain unchanged. Hospitals affected by data breaches show long-term advancements in their HIT functionalities.

CONCLUSIONS

Hospital data breach incidents are associated with improved healthcare quality. This improvement may be attributed to hospitals' enhanced functionality of HIT.

A caution against customized AI in healthcare

This article critiques the shift towards personalized AI in healthcare and other high-stakes domains, cautioning that without careful deliberation, customized AI systems can compromise the diversity and reach of human knowledge by restricting exposure to critical information that may conflict with users' preferences and biases. Customized AI should be applied with caution and intention where access to a wide and diverse range of perspectives is essential for impartial, informed decision making.

How digital leadership adds affective commitment of new generation employees: an affective events perspective

How do leaders' responses to the digital era affect new generation employees' affective commitment? As digital leaders have led to new ways of distributing digital resources and building virtual relationships, employees are facing a shift in the way of interaction, which influences their affective response to organizations. This study aims to understand how digital leaders interact with new generation employees to influence changes in employees' affective commitment to organizations. We have developed a chain mediating model and tested it on data collected from 408 new generation employees working in China. Ultimately, we found that digital leadership is associated with more positive changes in new generation employees' affective commitment. Furthermore, both employee empowerment and employee voice behavior mediate the relationship between digital leadership and affective commitment, forming a chain mediation mechanism in this relationship. We conclude with a discussion of theoretical implications and practical applications.

Examining Intersectionality and Barriers to the Uptake of Video Consultations Among Older Adults From Disadvantaged Backgrounds With Limited English Proficiency: Qualitative Narrative Interview Study

BACKGROUND

The rapid shift to video consultation services during the COVID-19 pandemic has raised concerns about exacerbating existing health inequities, particularly for disadvantaged populations. Intersectionality theory provides a valuable framework for understanding how multiple dimensions of disadvantage interact to shape health experiences and outcomes.

OBJECTIVE

This study aims to explore how multiple dimensions of disadvantage-specifically older age, limited English proficiency, and low socioeconomic status-intersect to shape experiences with digital health services, focusing on video consultations.

METHODS

Following familiarization visits and interviews with service providers, 17 older people with multiple markers of disadvantage (older age, low socioeconomic status, and limited English proficiency) were recruited in the Redbridge borough of London. Data collection included narrative interviews and ethnographic observations during home visits. Field notes captured participants' living conditions, family dynamics, and technological arrangements. Guided by intersectionality theory and digital capital concepts, interviews explored participants' experiences accessing health care remotely. Intersectional narrative analysis was used to identify key themes and examine how different forms of disadvantage interact. We developed theoretically informed narrative portraits and user personas to synthesize findings.

RESULTS

Analysis revealed that the digitalization of health care can exacerbate existing inequities, erode trust, compound oppression, and reduce patient agency for multiply disadvantaged patient populations. Examining intersectionality illuminated how age, language proficiency, and socioeconomic status interact to create unique barriers and experiences. Key themes included the following: weakened presence in digital interactions, erosion of therapeutic relationships, shift from relational to distributed continuity, increased complexity leading to disorientation, engagement shaped by previous experiences of discrimination, and reduced patient agency.

CONCLUSIONS

This study provides critical insights into how the digitalization of health care can deepen disparities for older patients with low income and limited English proficiency. By applying intersectionality theory to digital health disparities, our findings underscore the need for multifaceted approaches to digital health equity that address the complex interplay of disadvantage. Recommendations include co-designing inclusive digital services, strengthening relational continuity, and developing targeted support to preserve agency and trust for marginalized groups in an increasingly digital health care landscape.

Determinants for Drunk Driving Recidivism-An Application of the Integrated Prototype Willingness Model

The paper applies the prototype willingness model (PWM) and incorporates components of the theory of planned behavior (TPB), along with deterrence factors, to understand the behavioral intentions, willingness, and recidivism behaviors of individuals penalized for drunk driving. It explores psychological and social factors influencing repeat offenses, focusing on attitudes, subjective norms, prototypes, and deterrence. The PWM outlines two pathways-reasoned (based on intentions) and social reactive (based on willingness). The model helps predict risky behaviors like drunk driving. Thirteen hypotheses are proposed in this study to examine how various factors, such as attitudes, subjective norms, and deterrence, influence willingness, intentions, and behavior. Surveys were conducted among individuals attending road safety classes after being penalized for drunk driving. A total of 1156 individuals participated in the survey, with 855 valid responses collected. The results indicate that behavioral willingness had a stronger impact on recidivism than intention. On the other hand, subjective norms did not significantly affect the intent to reoffend, but attitudes, deterrence, and PBC did. The findings suggest that focusing on behavioral willingness, deterrence, and educational interventions could help reduce repeat drunk driving offenses. The paper offers insights for policymakers to improve prevention strategies, by focusing on the psychological motivators of repeat offenders.

The Sri Lankan enigma: demystifying public healthcare information systems acceptance

The deployment of Health Information Systems (HIS) in Sri Lanka has been low in adoption compared to developed countries. There has been a dearth of studies to identify the factors that improve the adoption of HIS in developing countries. Thus, this study investigates the factors influencing the acceptance of HIS among public healthcare staff. A survey was administered among 170 medical professionals, including nurses and doctors. Partial Least Squares Structural Equation Modelling (PLS-SEM) was applied to the dataset with 5000 bootstrap subsamples. The research model was developed based on the prior literature and by extending the Technology Acceptance Model (TAM) to the context of public healthcare. A positive relationship was observed between the actual use of HIS and constructs such as perceived usefulness, perceived ease of use, attitude, behavioural intention, prior use of HIS by supervisors, computer anxiety and facilitating conditions. These findings confirm the applicability of the proposed extended TAM in the public healthcare system of a developing country. Furthermore, HIS practitioners and policymakers in the healthcare sector would find these results valuable.

Exploring Employee Perspectives on Workplace Technology: Usage, Roles, and Implications for Satisfaction and Performance

In a dynamic context, where market requirements and needs change often, it is important for companies to adapt to new demands as quickly as possible to continue to be successful. To be able to face numerous challenges, however, organizations need to focus on the needs of their employees, with their satisfaction being an intermediate objective in achieving performance. Since technology is a pillar of each business field, the aim of this study is to explore employees' perspectives on the use of technology at work, analyzing its main roles within the company, the benefits it provides from the employees' viewpoint and its implications for satisfaction and performance. To achieve this objective, the authors used existing results in the literature that indicated several methods for the analysis of this subject, and continued with qualitative focus group research that involved six employees working both in hybrid and remote setups, within companies providing services in the engineering area. Thus, in this qualitative study, the needs and preferences of engineering employees are analyzed towards the efficiency of work activities, the improvement of team collaboration, as well as the role of digital technologies in facilitating communication and collecting feedback. Also, the research results address the support of personal and professional development and emphasize the importance of balance between personal and professional life through workplace flexibility-an aspect relatively unexplored in the specialized literature. Apart from the theoretical contributions that the study offers for the development of the literature, the results of this research offer a practical perspective for companies in the field of engineering, suggesting future research directions and recommendations for optimizing performance and increasing the level of employee satisfaction through the implementation of appropriate and personalized digital solutions.

Tales of hope and hesitation: Smoking cessation experts' views on the opportunities and risks of digital behaviour change interventions

Objective

Smoking remains a global health challenge, with 1.14 billion active smokers worldwide. Many of these smokers seek cessation support. The rise of mHealth offers novel intervention methods, providing monitoring and tailored feedback. This study aimed to map the opportunities and challenges of integrating digital behaviour change interventions (mHealth) into smoking cessation practices by understanding professionals' perceptions of these tools.

Methods

A qualitative study was conducted involving semi-structured interviews with 11 experienced smoking cessation professionals in Flanders, Belgium. Data collection occurred between January and April 2023. Inductive thematic analysis was performed to identify key patterns and themes in the experts' views regarding mHealth interventions.

Results

The analysis revealed four primary themes: (1) The Inexorable March of Technology - experts acknowledged the inevitability of technology in smoking cessation but varied in enthusiasm; (2) The Shimmering Mirage of Possibility - technology was viewed as supplementary, offering efficiency and support but limited in depth; (3) The Footnotes to Enthusiasm - experts expressed concerns over privacy, inclusivity, and the potential for technology to displace human care; and (4) The Human Anchor - the irreplaceable role of human connection and therapeutic alliance, which digital tools might not be able to replicate.

Conclusion

Experts believe mHealth interventions can augment smoking cessation support but should not replace human-driven care. A blended approach, integrating digital tools with traditional therapeutic relationships, offers the most promise. Addressing concerns about privacy, inclusivity, and most importantly the limits of digital therapeutic alliances is essential for successful mHealth implementation in smoking cessation.

Supporting the care to breast cancer patients with unique needs: Evidence from online community members' responses

BACKGROUND

Breast cancer is the most common cancer diagnosed in women globally. Online cancer communities (OCCs) provide platforms for breast cancer patients to connect, share experiences, and support each other. These communities facilitate discussions on a range of health- and non-health-related topics. However, posts discussing unique topics may receive varying levels of attention and support. This study aims to devise a method for identifying and supporting such posts, enhancing community response and support strategies.

METHODS

We propose a Uniqueness Score Extraction Framework to compute health- and non-health-related uniqueness scores for online community posts. The framework utilizes deep learning-based natural language processing models to identify the topics discussed in OCCs and calculates the health- and non-health-related uniqueness scores of a post based on the uniqueness of the topics identified by the BERTopic model. We further employ econometric models to assess how the uniqueness scores of posts affect community members' responses to those posts.

RESULTS

Our study reveals that posts with a higher concentration of unique health-related topics in OCCs elicit quicker, more frequent, but shorter responses. Conversely, posts containing more unique non-health-related topics in the entire post prompt faster and longer responses, unless these topics become overly dominant, in which case the number of replies decreases, and response times are prolonged.

CONCLUSION

Our research develops a framework to identify posts with high uniqueness scores in OCCs, and sheds light on community member responses to these discussions. The findings indicate that while members are supportive, particularly regarding health-related topics, the post-content's nature and focus greatly affect their engagement. These discoveries could enhance our understanding of community dynamics in OCCs, offering valuable implications for researchers, OCC facilitators, and medical professionals in supporting patients within online platforms.