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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Does digital-industrial technology integration reduce corporate carbon emissions?

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

Automatic uncovering of patient primary concerns in portal messages using a fusion framework of pretrained language models

OBJECTIVES

The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care.

MATERIALS AND METHODS

We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural Network for precise identification of patient primary concerns via multi-class classification. We examined 3 traditional machine learning models, 9 BERT-based language models, 6 fusion models, and 2 ensemble models.

RESULTS

The outcomes of our experimentation underscore the superior performance achieved by BERT-based models in comparison to traditional machine learning models. Remarkably, our fusion model emerges as the top-performing solution, delivering a notably improved accuracy score of 77.67 ± 2.74% and an F1 score of 74.37 ± 3.70% in macro-average.

DISCUSSION

This study highlights the feasibility and effectiveness of multi-class classification for patient primary concern detection and the proposed fusion framework for enhancing primary concern detection.

CONCLUSIONS

The use of multi-class classification enhanced by a fusion of multiple pretrained LMs not only improves the accuracy and efficiency of patient primary concern identification in PPMs but also aids in managing the rising volume of PPMs in healthcare, ensuring critical patient communications are addressed promptly and accurately.

Digital economy's role in shaping carbon emissions in the construction field: Insights from Chinese cities

Achieving net-zero greenhouse gas emissions in the construction sector is essential to sustainable development policy. Previous studies have ignored the impact of the digital economy on carbon emissions in the construction industry. Using relevant city-level data from China from 2011 to 2021 and employing ArcGIS and Stata software, this study examines the current status of carbon emissions from the construction industry and investigates the impact of the digital economy on these emissions. The findings reveal that (1) from 2011 to 2021, carbon emissions of the construction industry have a pattern of decreasing-increasing-decreasing-increasing across the country. There is an increasing concentration of areas with high and relatively high carbon discharges in Heilongjiang, Jilin, Ningxia, Inner Mongolia, Shanxi, Guangxi, and Guizhou. (2) The standard deviation ellipse indicates the core area of carbon emissions in China's construction industry is moving northeast and becoming more decentralized. (3) Through a series of robustness tests, the digital economy has been proven to effectively reduce carbon emissions from the construction sector in municipal areas. (4) In severely cold regions, mild regions, and high-population-density cities, the digital economy reduces building sector's carbon output. However, it stimulates carbon emissions in the hot summer and cold winter regions. (5) Mechanism tests show that the digital economy reduces China's urban construction carbon emissions by fostering technological progress and green innovation. Urban resilience further strengthens the contribution of the digital economy to reducing carbon discharges in the urban construction sector of China. This article presents empirical evidence demonstrating how the digital economy empowers the construction industry to curtail emissions.

Authentic Leadership Behaviors and Thriving at Work: Empirical Evidence From The Information Technology Industry in Australia

Authentic leaders display an exceptional level of integrity and honesty, a high level of awareness and responsibility as well as a commitment to achieving their goals; as a result, they develop more trusting relationships with their employees, which could be translated into many positive outcomes, such as enhancing the ability to thrive at work. The present study aims to determine the role of authentic leadership´s (AL's) four dimensions (self-awareness, relational transparency, balanced processing, and internalized moral perspective) in fostering an environment that offers workers the opportunity to do well, including in terms of two related elements (vitality and learning). An online questionnaire was conducted to collect data from a sample of 402 participants from the information technology (IT) industry in Australia. The study used WarpPLS software to analyze the collected data by the structural equation model. According to the results, balanced processing of AL has a positive and significant effect on two aspects of thriving at work, namely vitality and learning, Moreover, the internalized moral perspective inherent in the aforementioned phenomenon affects learning. The current study is novel as it is among examples of pioneering research that employ the path model, and it uses multi-dimensional structures to examine authentic leadership and thriving at work in the workplace. The research also discusses theoretical contributions, managerial implications, and limitations along with future study directions.

Understanding Engagement With Forensic Smartphone Apps: The Service Design Engagement Model

Justice services have begun to integrate the use of mobile applications into treatment, support, and rehabilitative programs for forensic clients. One such application that been adopted to support forensic clients is "eRecovery": a smartphone application that provides clients recovering from a substance addiction with support for managing relapse. In this article, we report on evaluation findings from a trial of eRecovery in an Australian Community Justice Centre, and reflect on several issues relating to fostering and sustaining client engagement with similar applications within forensic and justice settings. We propose the Service Design Engagement Model to organize, visualize, and describe the stages and factors important to adoption, appropriation, and on-going routine use of the software by forensic clients. The model recognizes the role of contextual and environmental factors in supporting users through the early stages of engagement, and the importance of user agency in longer-term engagement with therapeutic apps.

Blessing or curse? The role of digital technology innovation in carbon emission efficiency

Digital technology advancement provides a significant impetus to achieve China's "dual-carbon" goals, yet it also gives rise to a series of challenges. Therefore, studying the relationship between digital technology innovation and carbon emission efficiency is of paramount importance. This study theoretically analyzes and empirically tests the influence of digital technology innovation (DTI) on total factor carbon emission efficiency (TFCE) using panel data from 268 Chinese cities between 2006 and 2021. The results indicate that: (1) DTI exhibits a "U-shaped" pattern on urban TFCE, with a decrease followed by an increase. (2) Conventional technological innovation (TI) also displays a "U-shaped" relationship with TFCE, with the turning point occurring earlier than that of DTI. DTI surpasses TI in bringing about later-stage improvements in carbon emission efficiency. (3) Mechanism tests reveal that digital technology innovation indirectly affects TFCE through energy effects, technological effects, structural effects, and regulatory effects. (4) The impact of DTI on urban TFCE varies significantly due to differences in geographical location and resource endowments. (5) The development of urban polycentricity advances the turning point at which DTI enhances TFCE while amplifying both the initial "pro-carbon" effect and the subsequent "carbon reduction" effect of DTI. (6) DTI has a spatial spillover effect on urban TFCE. This study provides empirical evidence and policy recommendations for policymakers to advance the digitalization, greening, and decarbonization transformation of cities.

Digital transformation and enterprise low-carbon innovation: A new perspective from innovation motivation

From the perspective of innovation motivation, low-carbon innovation is divided into substantive low-carbon innovation and strategic low-carbon innovation. On this basis, this study empirically investigates the impact and mechanism of digital transformation on enterprise low-carbon innovation using data from China's A-share listed enterprises from 2005 to 2019. The results show that digital transformation promotes the overall level of enterprise low-carbon innovation, substantial low-carbon innovation, and strategic low-carbon innovation, with a more significant impact on strategic low-carbon innovation. For enterprises with large-scale, belonging to high-monopoly industries and located in high-marketization regions, the promotion of digital transformation is more significant and facilitates strategic low-carbon innovation more than substantive low-carbon innovation. Based on the internal capability perspective, enhancing management capability, R&D capability, and environmental information disclosure capability are three important channels of digital transformation affecting low-carbon innovation.

Socio-ecological predictors of dengue in high incidence area of Delhi, India

Despite the amplified vector-control measures, sporadic-epidemic outbreaks of dengue incidence occurred in Delhi, intermittently. This study aimed to identify the major individual, household, and community level predictors of dengue cases in the hot-spots of Delhi. Primary survey data was collected from the selected sample of 347 households, at the South- West district of Delhi. This survey has interviewed the head of the household to collect the information of dengue incidences within last one year and household information related to socio-economic, demographic, environmental factors, such as housing pattern, density, water storage containers, drainage and garbage collection site and method, mosquito protection measures and awareness. Among 347 households, 54 households had reported dengue cases, and 69 individuals had reported dengue cases in last one year. Garbage and water collection site and methods, drainage and household type, household monthly income, indoor bamboo plants, construction site (within 500 m), presence of tertiary care hospital, were the significant predictors of dengue incidences in Delhi. In conclusion, strategic control measures and intense social interventions such as household and community awareness, promotion of healthy practices should be promoted to control the dengue incidences.

Impact of stakeholder pressure on digital process innovation: An empirical analysis

Digital technologies can bring about fundamental changes in corporate processes, which may result in a shift from process innovation to digital process innovation. However, owing to resource constraints and various stakeholders, digital process implementation is extremely challenging for firms. Based on stakeholder theory, this study explores whether and how stakeholder pressure for digitalization can facilitate corporate digital process innovation and unravels the mediating effect of routine reconfiguration and the moderating effect of strategic flexibility. The findings from a survey of 351 firms prove that stakeholder pressure for digitalization can facilitate corporate digital process innovation via routine reconfiguration. Moreover, this study finds that increased strategic flexibility can strengthen the positive mediating effect of routine reconfiguration. The findings contribute to the deep understanding of digital process innovation and offer a boundary condition for the effectiveness of stakeholder pressure.

Probing the Role of Digital Payment Solutions in Gambling Behavior: Preliminary Results From an Exploratory Focus Group Session With Problem Gamblers

BACKGROUND

Technology has significantly reshaped the landscape and accessibility of gambling, creating uncharted territory for researchers and policy makers involved in the responsible gambling (RG) agenda. Digital payment solutions (DPS) are the latest addition of technology-based services in gambling and are now prominently used for deposit and win withdrawal. The seamless collaboration between online gambling operators and DPS, however, has raised concerns regarding the potential role of DPS platforms in facilitating harmful behavior.

OBJECTIVE

Using a focus group session with problem gamblers, this study describes a preliminary investigation of the role of DPS in the online gambling context and its influence on players' gambling habits, financial behavior, choices of gambling environment, and the overall outcome of gambling subjective experiences.

METHODS

A total of 6 problem gamblers participated in a one-and-half-hour focus group session to discuss how DPSs are integrated into their everyday gambling habits, what motivates them to use DPS, and what shifts they observe in their gambling behavior. Thematic analysis was used to analyze the empirical evidence with a mix of inductive and deductive research approaches as a knowledge claim strategy.

RESULTS

Our initial findings revealed that the influence of DPSs in online gambling is multifaced where, on the one hand, their ability to integrate with players' existing habits seamlessly underscores the facilitating role they play in potentially maximizing harm. On the other hand, we find preliminary evidence that DPSs can have a direct influence on gambling outcomes in both subtle and pervasive ways-nudging, institutionalizing, constraining, or triggering players' gambling activities. This study also highlights the increasingly interdisciplinary nature of online gambling, and it proposes a preliminary conceptual framework to illustrate the sociotechnical interplay between DPS and gambling habits that ultimately capture the outcome of gambling's subjective experience.

CONCLUSIONS

Disguised as a passive payment enabler, the role of DPS has so far received scant attention; however, this exploratory qualitative study demonstrates that given the technological advantage and access to customer financial data, DPS can become a potent platform to enable and at times trigger harmful gambling. In addition, DPS's bird's-eye view of cross-operator gambling behavior can open up an opportunity for researchers and policy makers to explore harm reduction measures that can be implemented at the digital payment level for gambling customers. Finally, more interdisciplinary studies are needed to formulate the sociotechnical nature of online gambling and holistic harm minimization strategy.

Role of social media to improve job performance with mediating role of transactive memory capability and employee creativity

The increased usage of social media in organizational settings has raised questions about its effect on job performance. This study explains the interplay between social media usage, transactive memory capability, employee creativity, and job performance within the Chinese organizational context. The rationale for this study stems from the need to understand how social media usage can enhance job performance through cognitive and creative processes within teams. On the basis of earlier literature, the survey questionnaire was designed to collect data and the survey included validated scales to measure these constructs. The data is collected from 816 employees in China via online resources like social media and emails and then Structural Equation Modeling is used for empirical analysis through AMOS software. The findings show the positive impact of social media on job performance while transactive memory capability and employee creativity mediates this relationship. These findings contribute to a better understanding of how social media can be leveraged to improve job performance. Practical implications highlight the importance of fostering transactive memory capability through social media platforms, facilitating employee creativity, and ultimately, bolstering job performance. Additionally, this study underscores the need for organizations to strategically harness the potential of social media as a catalyst for innovation and knowledge sharing, thus optimizing workforce performance in the digital era.

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

BACKGROUND

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

PURPOSE

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

METHOD

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

RESULTS

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

CONCLUSION

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

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

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

mRNA Vaccine Hesitancy: Spreading Misinformation Through Online Narratives

This research examined the themes that emerge from online discussions of the COVID-19 vaccines to assist health communicators and officials in combating misinformation in health-related discussions. Using framing theory and the diffusion of innovation framework, this study presents findings from a semantic network analysis of 3842 tweets collected during the first week of February 2022. The authors calculated betweenness and page rank centrality scores for Twitter users participating in the online dialogue and identified 36 semantic themes. Findings revealed that the most influential dialogue participants were retired health and medical professionals, data analysts, journalists, online advocates, and politicians. The frames identified in the study contained several misinformation narratives about the COVID-19 vaccines. The authors discuss the implications of these findings for health officials and communicators as well as the theoretical implications of the diffusion of misinformation and framing as a tool to reiterate untruths.

Catalysts of digital excellence: Unraveling the threads of connectivity, embedment, and visibility in enterprise social media for enhanced task and innovative performances

In an era characterized by rapid digital transformation, this research delves into the intricate dynamics of enterprise social media (ESM) ubiquitous connectivity, drawing on the influential framework of social cognitive theory (SCT), we unravel the complex relationships among compatibility, presenteeism, ESM-enabled embeddedness, and the visibility of digital interactions, shedding light on how these factors collectively shape task performance and innovative contributions in the contemporary hybrid work landscape. By incorporating SCT into our research model, we not only enhance the theoretical underpinning but also respond to the imperative of understanding how individual cognition and observational learning impact behaviors in digital work environments. Data is collected from 467 participants from China. Results indicated that ESM-enabled embeddedness mediates the connection between presenteeism and both digital-enabled task performance, digital-enabled innovative performance. Findings conformed that ESM-enabled embeddedness mediates the connection between compatibility and both digital-enabled task performance, digital-enabled innovative performance. ESM visibility strengthens the connection between ubiquitous connectivity (presenteeism, compatibility) and ESM-enabled embeddedness. In addition, results also indicated that ESM visibility moderates the mediation effect of ESM-enabled embeddedness between the dimensions of ESM ubiquitous connectivity (presenteeism) and both digital-enabled task performance, digital-enabled innovative performance. In contrast, ESM visibility did not moderates the mediation effect of ESM-enabled embeddedness between the dimensions of ESM ubiquitous connectivity (compatibility) and both digital-enabled task performance, digital-enabled innovative performance. This study not only contributes depth to ESM literature but also lays the groundwork for future research endeavors, encouraging exploration of diverse contexts and additional moderating factors to comprehensively grasp the intricate dynamics within modern digital workspaces.

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

RATIONALE

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Indicators of technostress, their association with burnout and the moderating role of support offers among nurses in German hospitals: a cross-sectional study

OBJECTIVES

To examine the level of indicators of technostress among nurses with and without a leadership position, the relationship between indicators of technostress and burnout and the moderating role of support offered by employers. The availability of support offers and further needs of nurses were also explored.

DESIGN

Cross-sectional online survey.

SETTING

Acute care hospitals in Germany.

PARTICIPANTS

303 nurses (73.3% female) who have worked at the hospital for at least 1 year and a minimum of 10 hours per week.

PRIMARY AND SECONDARY OUTCOME MEASURES

Indicators of technostress (complexity, overload, usefulness, lack of technical support and unreliability) served as predictors in multiple linear regression analyses to examine their association with the primary outcome burnout. Support of employers was included as a moderator variable. Validated subscales from the Digital Stressors Scale and Copenhagen Burnout Inventory as well as open-ended questions were applied.

RESULTS

There were no differences in the level of indicators of technostress found between nurses with and without a leadership position. Techno-overload (β=0.259, p=0.004) and techno-complexity (β=0.161, p=0.043) were significantly associated with burnout. Support by the employer moderated the relationship between lack of technical support and burnout significantly (R² change=0.026, F(1,292)=7.41, p=0.007). Support offers such as training, IT service and contact persons on the ward helped nurses to be more confident in the use of information and communication technologies. However, they expressed further needs with regard to these and new offers.

CONCLUSIONS

There was an association between two indicators of technostress and burnout. Therefore, particular attention should be paid to supporting nurses in terms of techno-overload and techno-complexity. Furthermore, there is still a need for customised support and further offers from employers in the use of digital technologies.

Functional diversity in human song

Functional diversity-i.e., the diversity of morphophysiological characteristics of species in a biological community-revolutionized ecology in recent decades, shifting the focus of the field from species to ecosystems. While its ecological applications are known, its adaptability to other disciplines, specifically music, is explored here. We retrieved fourteen characteristics of 12,944 songs by the top 100 artists of the 2010s decade on four streaming platforms. Then, we calculated the three main components of functional diversity-richness, evenness, and divergence-to each artist using probabilistic hypervolumes. Furthermore, we investigated to what extent functional diversity and the traits of an artist, its albums and songs has an effect on their popularity across streaming platforms such as Spotify. High functional richness, where an artist's songs differ greatly sonically, correlated with increased listens of up to 244,300,000. This would lead to estimated profit earnings exceeding $1,000,000 per richness gain. Danceable, highly-energetic, melodic, pop, and, notably, melancholic songs, albums, and artists are more listened to than their counterparts in streaming services. We captured how patterns in human song might reflects the social state of human societies in recent years and demonstrate the potential of applying functional diversity concepts and tools across scientific and economic domains, extending its relevance beyond ecology. By demonstrating applications of state-of-the-art functional diversity metrics using music as a case study, we intent to communicate the often-complex concepts of functional diversity using the familiar realm of music, which is an intrinsic trait of human cultures across the globe.

Evaluating the drivers of B2B performance: An empirical analysis based on Alibaba

The rapid development of B2B has brought about fierce competition among suppliers, and how to gain customer attention and improve performance has become a common concern in academia and industry. This study examined the drivers and mechanisms of B2B performance from an enterprise capability perspective. We collected transaction and enterprise data from 325 suppliers on Alibaba 1688 platform and constructed a structural equation model (SEM). Results showed that supplier service capability, logistics capability, and production capacity all positively impacted B2B performance through the mediating role of customer attention. In addition, we found that service and logistics capabilities are more critical for attracting customer attention for Original Equipment Manufacturer (OEM) suppliers than for non-OEM suppliers. The findings contribute to understanding B2B commerce and provide constructive directions for B2B suppliers to improve their performance.

Self-perceptions of aging, physical activity, and depressive symptoms in older community residents with varied neighborhood walkability in Taiwan

BACKGROUND

Prior research has identified the mediating effect of physical activity in the relationship between self-perceptions of aging and physical health. However, this impact on mental health is unknown, and the influence of environmental contexts proposed by ecological models in this regard remains largely unexplored. Therefore, this study aimed to investigate the role of physical activity in the relationship between self-perceptions of aging and depressive symptoms in older adults, and compare the impact across four levels of neighborhood walkability.

METHODS

A sample of 1,055 community-dwelling older adults aged 65 or above was obtained through random-digit-dialing computer-assisted telephone interviewing. The individual's neighborhood walkability was calculated using Walk Score®, and categorized into four levels: car-dependent, somewhat walkable, very walkable, and walker's paradise. Partial least squares structural equation modelling was employed.

RESULTS

We found that more positive self-perceptions of aging were associated with fewer depressive symptoms and a mediation effect of physical activity in this relationship. Among the four levels of neighborhood walkability, the mediation effect of physical activity was only statistically significant in the lowest level (car-dependent). The findings supported our hypotheses regarding the mediating effect of self-perceptions of aging on depressive symptoms via physical activity. Neighborhood walkability might potentially influence the mediating role of physical activity.

CONCLUSIONS

This study emphasizes key areas on intervention programs and policy formulation to promote mental health in older adults.

Gender effects in crowdfunded business loan campaigns

Crowdfunding is a growing source of finance for entrepreneurs. In this paper, we investigate the existence of a gender effect in the time needed to obtain a business loan through crowdfunding. Using data from three Dutch crowdfunding platforms, survival analysis of the time to completion for 934 business loan campaigns shows that female entrepreneurs have a 20% shorter campaign completion time compared to male entrepreneurs, whereas couples do not differ from males. This effect persists across the different platforms. Subsequent analysis shows that female entrepreneurs do not have the disadvantage they face in traditional lending channels when requesting funds through crowdfunding, and that herding behavior by investors benefits female entrepreneurs most.

Breaking down barriers: rationalisations and motivation to stop among Chinese male smokers under cigarette dependence

BACKGROUND

Smoking rationalisation beliefs are a huge barrier to quitting smoking. What types of rationalisations should be emphasised in smoking cessation interventions? Although past literature has confirmed the negative relationship between those beliefs and motivation to stop smoking, little is known regarding the importance and performance of those beliefs on motivation with varying cigarette dependence. The study aimed to ascertain rationalisations that are highly important for motivation yet perform poorly in different cigarette dependence groups.

METHODS

The cross-sectional study was conducted from November 19 to December 9, 2023 in Guiyang City, China. Adult male current smokers were enrolled. Partial least squares structural equation modelling was used to test the hypothesis. The multi-group analysis was used to determine the moderating effect of cigarette dependence, and the importance-performance map analysis was utilised to assess the importance and performance of rationalisations.

RESULTS

A total of 616 adult male current smokers were analysed, and they were divided into the low cigarette dependence group (n = 297) and the high cigarette dependence group (n = 319). Except for risk generalisation beliefs, smoking functional beliefs (H1: -β = 0.131, P < 0.01), social acceptability beliefs (H3: β = -0.258, P < 0.001), safe smoking beliefs (H4: β = -0.078, P < 0.05), self-exempting beliefs (H5: β = -0.244, P < 0.001), and quitting is harmful beliefs (H6: β = -0.148, P < 0.01) all had a significant positive influence on motivation. Cigarette dependence moderated the correlation between rationalisations and motivation. In the high-dependence group, the social acceptability beliefs and smoking functional beliefs were located in the "Concentrate Here" area. In the low-dependence group, the social acceptability beliefs were also situated in there.

CONCLUSIONS

Social acceptability beliefs and smoking functional beliefs showed great potential and value for improvement among high-dependence smokers, while only social acceptability beliefs had great potential and value for improvement among low-dependence smokers. Addressing these beliefs will be helpful for smoking cessation. The multi-group analysis and the importance-performance map analysis technique have practical implications and can be expanded to other domains of health education and intervention practice.

Dynamic risk prediction of survival in liver cirrhosis: A comparison of landmarking approaches

Electronic health records (EHR) data provides the researcher and physician with the opportunity to improve risk prediction by employing newer, more sophisticated modeling techniques. Rather than treating the impact of predictor variables on health trajectories as static, we explore the use of time-dependent variables in dynamically modeling time-to-event data through the use of landmarking (LM) data sets. We compare several different dynamic models presented in the literature that utilize LM data sets as the basis of their approach. These techniques include using pseudo-means, pseudo-survival probabilities, and the traditional Cox model. The models are primarily compared with their static counterparts using appropriate measures of model discrimination and calibration based on what summary measure is employed for the response variable.

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

PURPOSE

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

DESIGN AND METHODS

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

RESULTS

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

CONCLUSIONS

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

How epidemic information and policy information impact anti-infection behaviors: a cross-cultural study under social influence framing

Three preregistered experiments examined to what extent information about an epidemic situation provided by experts and information about anti-infection policies promoted by governments/media influenced anti-infection behaviors. The above effects were examined among populations from different countries (in Experiments 2 and 3) and across self-construals (in Experiment 3). In three experiments, participants (N =706) were presented with a scenario where experts provided (or did not provide) information about an epidemic situation and governments/media promoted (or did not promote) information about anti-infection policies. After that, participants indicated their willingness to adopt anti-infection behaviors. Results across three experiments showed that both types of information independently increased participants' anti-infection behaviors. In Experiments 2 and 3, we further found that the epidemic information had a larger impact on inducing anti-infection behaviors than the policy information, which was robust and consistent across countries and self-construals. Findings were discussed under the framework of social influence and in terms of practical implications for pandemic situations like the COVID-19.

Safety-Seeking Behaviors and Anxiety Maintenance in People With Aphasia: A Viewpoint

PURPOSE

People with aphasia (PWA) often experience higher levels of anxiety and social isolation than people without aphasia. Although the presence of anxiety is appreciated in PWA, literature examining the etiology and persistent nature of anxiety in PWA is underdeveloped. Safety-seeking behaviors, or maladaptive acts used by individuals to decrease anxiety from a feared outcome, have been reported as key facilitators of long-term anxiety toward feared situations across a variety of clinical populations. The purpose of this viewpoint is to explore the concept of safety-seeking behaviors and discuss their potential relevance to the maintenance of anxiety in PWA. We further discuss the distinction between maladaptive (i.e., safety seeking) and adaptive (i.e., coping) behaviors and how this knowledge may improve the quality of clinical services for PWA.

CONCLUSIONS

The present review advocates for further exploration of the safety-seeking behaviors that are used by PWA. Until critical attention is given to this subject, clinicians may remain ill-equipped to identify and depict whether a self-management strategy is facilitative or inhibitive to PWA's communicative participation goals. Critically, a behavior that may be "maladaptive" for one individual may be "adaptive" for another. Future research should seek to identify common behavioral and cognitive strategies that PWA implement to reduce acute perceptions of anxiety. This knowledge may help facilitate holistic aphasia rehabilitation by allowing clinicians to foster conversations around behaviors that inhibit or promote successful communicative participation.

Factors Affecting Breast Screening Behavior of First-Degree Relatives of Breast Cancer Patients in China: A Cross-sectional Study

BACKGROUND

Breast cancer is the most common cancer in women, and first-degree relatives (FDRs) of breast cancer patients have a significantly higher risk of developing breast cancer. However, the factors affecting breast cancer screening behavior of FDRs in China remain unclear.

OBJECTIVE

The aim of this study was to determine the social cognitive theory factors influencing screening behaviors of FDRs.

METHODS

A cross-sectional survey was conducted, and 430 FDRs were recruited. Data were collected using demographic information and self-reported questionnaire based on the social cognitive theory. The structural equation modeling method was used to analyze the influence of social cognitive factors on breast cancer screening behavior.

RESULTS

The model showed a good fit (goodness of fit = 0.462). Goal setting and self-regulation (β = 0.631, P < .001) and positive outcome expectation (β = 0.098, P = .042) were positively related to breast cancer screening behavior. Negative outcome expectation was negatively related to breast cancer screening behavior (β = -0.102, P = .024). In addition, positive outcome expectation, negative outcome expectation, and goal setting and self-regulation are mediators of self-efficacy (β = 0.475, P < .001) to breast cancer screening behavior.

CONCLUSION

Goal setting and self-regulation are important influences on breast cancer screening behavior. The social cognitive theory is both applicable to and effective in explaining and predicting breast cancer screening behavior.

IMPLICATIONS FOR PRACTICE

Health professionals can develop appropriate intervention strategies based on the social cognitive theory among FDRs. It is necessary to focus on the people who influence women, such as spouses, mothers, or daughters.

A narrative review of the development and performance characteristics of electronic delirium-screening tools

BACKGROUND

Electronic delirium-screening tools are an emergent area of research.

OBJECTIVE

The objective of this study was to summarise the development and performance characteristics of electronic screening tools in delirium.

METHODS

Searches were conducted in Pubmed, Embase, and CINAHL Complete databases to identify electronic delirium-screening tools.

RESULTS

Five electronic delirium-screening tools were identified and reviewed. Two were designed for and tested within a medical setting, and three were applied to intensive care. Adaptive design features, such as skip function to reduce test burden, were variably integrated into instrument design. All tools were shown to have acceptable psychometric properties, but validation studies were largely incomplete.

CONCLUSIONS

Electronic delirium-screening tools are an exciting area of development and may offer hope for improved uptake of delirium screening.

The Role of Decision Authority and Stated Social Intent as Predictors of Trust in Autonomous Robots

Prior research has demonstrated that trust in robots and performance of robots are two important factors that influence human-autonomy teaming. However, other factors may influence users' perceptions and use of autonomous systems, such as perceived intent of robots and decision authority of the robots. The current study experimentally examined participants' trust in an autonomous security robot (ASR), perceived trustworthiness of the ASR, and desire to use an ASR that varied in levels of decision authority and benevolence. Participants (N = 340) were recruited from Amazon Mechanical Turk. Results revealed the participants had increased trust in the ASR when the robot was described as having benevolent intent compared to self-protective intent. There were several interactions between decision authority and intent when predicting the trust process, showing that intent may matter the most when the robot has discretion on executing that intent. Participants stated a desire to use the ASR in a military context compared to a public context. Implications for this research demonstrate that as robots become more prevalent in jobs paired with humans, factors such as transparency provided for the robot's intent and its decision authority will influence users' trust and trustworthiness.

Are there patients with an intracapsular fracture of the hip who may benefit from an uncemented hemiarthroplasty?

Aims

Cemented hemiarthroplasty is an effective form of treatment for most patients with an intracapsular fracture of the hip. However, it remains unclear whether there are subgroups of patients who may benefit from the alternative operation of a modern uncemented hemiarthroplasty - the aim of this study was to investigate this issue. Knowledge about the heterogeneity of treatment effects is important for surgeons in order to target operations towards specific subgroups who would benefit the most.

Methods

We used causal forest analysis to compare subgroup- and individual-level treatment effects between cemented and modern uncemented hemiarthroplasty in patients aged > 60 years with an intracapsular fracture of the hip, using data from the World Hip Trauma Evaluation 5 (WHiTE 5) multicentre randomized clinical trial. EuroQol five-dimension index scores were used to measure health-related quality of life at one, four, and 12 months postoperatively.

Results

Our analysis revealed a complex landscape of responses to the use of a cemented hemiarthroplasty in the 12 months after surgery. There was heterogeneity of effects with regard to baseline characteristics, including age, pre-injury health status, and lifestyle factors such as alcohol consumption. This heterogeneity was greater at the one-month mark than at subsequent follow-up timepoints, with particular regard to subgroups based on age. However, for all subgroups, the effect estimates for quality of life lay within the confidence intervals derived from the analysis of all patients.

Conclusion

The use of a cemented hemiarthroplasty is expected to increase health-related quality of life compared with modern uncemented hemiarthroplasty for all subgroups of patients aged > 60 years with a displaced intracapsular fracture of the hip.

Sociomaterial perspective as applied in interprofessional education and collaborative practice: a scoping review

Learning and working together towards better health outcomes today have become more complex requiring an investigation on how interprofessional education (IPE) and interprofessional collaboration (IPC) practices could be sustained and further developed. Through a sociomaterial perspective, we can better understand IPE and IPC practices by foregrounding the material aspect of learning and working together and examining its relationship with humans and their interactions. This article aimed to examine existing literature that discusses the application of sociomaterial perspectives in IPE and IPC. A scoping review was conducted following Arksey and O'Malley's framework to explore the extent within the current body of knowledge that discuss how sociomaterial perspective is applied in IPE and IPC practices. A systematic database search was performed in September 2021 to retrieve literature published from 2007 onwards, with forty-three papers meeting the inclusion criteria. These papers included research articles, book chapters, conference papers and commentaries, with the majority originating from Europe. The thematic analysis revealed the following themes: (1) power as a sociomaterial entity shaping IPE and IPC; (2) inclusion of non-health professionals in reimagining IPE and IPC practices, and (3) the critical understanding of sociomateriality. The findings suggest that a sociomaterial perspective can allow for the reimagination of the contemporary and future practices of interprofessionalism.

Community notes increase trust in fact-checking on social media

Community-based fact-checking is a promising approach to fact-check social media content at scale. However, an understanding of whether users trust community fact-checks is missing. Here, we presented n = 1,810 Americans with 36 misleading and nonmisleading social media posts and assessed their trust in different types of fact-checking interventions. Participants were randomly assigned to treatments where misleading content was either accompanied by simple (i.e. context-free) misinformation flags in different formats (expert flags or community flags), or by textual "community notes" explaining why the fact-checked post was misleading. Across both sides of the political spectrum, community notes were perceived as significantly more trustworthy than simple misinformation flags. Our results further suggest that the higher trustworthiness primarily stemmed from the context provided in community notes (i.e. fact-checking explanations) rather than generally higher trust towards community fact-checkers. Community notes also improved the identification of misleading posts. In sum, our work implies that context matters in fact-checking and that community notes might be an effective approach to mitigate trust issues with simple misinformation flags.

The influence of service performance in China's sci-tech commissioner system: Using social network analysis and interpretable machine learning

The Sci-Tech Commissioner System (SCS) is a result of exploratory efforts by the Chinese government to use science and technology to strengthen the agricultural sector. Social network analysis (SNA) and machine learning (ML) techniques make it feasible to assess the service performance in China's SCS by using indicators such as group types and structure features. In this study, SNA and a clustering algorithm were employed to categorize service group types of sci-tech commissioners. By comparing the accuracy of different classification algorithms in predicting the clustering results, LightGBM algorithm was finally select to determine the clustering features of sci-tech commissioners and establish an interpretable ML model. Then, the SHAP was used to algorithm to analyze influences affecting service performance. Results show that the service forms of sci-tech commissioners are group-oriented, and that group types include small groups of young commissioners with close cooperation, larger groups of young and middle-aged commissioners, small groups of middle-aged and old commissioners with close cooperation, and isolated points of highly-influential commissioners. Furthermore, while group size is not the determinant of a commissioner's average performance, group structure and coordination ability were found to be more critical. Moreover, while differences in distinct types of service performance are caused by various factors, but good group structures and extensive social contacts are essential for high service performance.

Countering technostress in virtual work environments: The role of work-based learning and digital leadership in enhancing employee well-being

Virtual work has been highlighted as an important business trend nowadays. Technostress caused by information and communication technology threatens employee well-being in a virtual context. We integrate insights from the Job Demands-Resources theory to explore the impact of technostress on employee well-being and examine work-based learning and digital leadership capability as buffers of this negative impact via the attenuating effect of work exhaustion. We collected multi-wave survey data from 300 virtual employees to test the theoretical model. Results revealed a significant negative impact of technostress on employee well-being. However, work-based learning and digital leadership capability buffered employees' well-being from this negative effect by reducing their work exhaustion. Our findings extend our understanding of work design and shed light on how to cope with virtual work demands.

Factors influencing college students' online rumor refuting behavior during major public health crises: the moderating effect of group norms

This study integrates SOR (Stimuli-Organism-Response) theoretical framework and rational behavior theory within a theoretical framework, incorporating group norms as a moderating factor to investigate the psychological mechanisms influencing Chinese college students' online rumor-refutation behavior amidst public health crises. Using the structural equation modeling research method, data was collected via questionnaires from 1,254 participants in the context of the COVID-19 pandemic. The findings indicate that both online and offline information seeking are positively correlated with college students' attitudes and subjective norms. Moreover, the attitudes and subjective norms of college students are positively correlated with the online rumor refuting behavior. Furthermore, group norms serve to strengthen the connection between college students' attitudes and their engagement in online refuting rumors. These results illuminate the psychological underpinnings driving college students' online rumor-refuting actions, offering practical and policy implications for effectively managing rumor behaviors.

Extending the theory of planned behavior model to explain people's behavioral intentions to follow China's AI generated content law

AI Generated Content Law was extensively promoted in 2023; hence, it is crucial to uncover factors influencing people's behavioral intentions to comply with the AI Generated Content Law. This study extends the theory of planned behavior to explore the factors influencing people to follow AI Generated Content Law in China. In addition to the factors in TPB model, such as one's attitudinal factors, normative factors, and perceived behavioral control, we add another factor-moral obligation to extend the theory of planned behavior model. We used convenient sampling and there were 712 effective samples. Using the statistical software Amos17.0, the result shows that attitude, subjective norms, perceived behavioral control and moral obligation all have positive effects on intentions to follow AI Generated Content Law.

Enhancing post-training evaluation of annual performance agreement training: A fusion of fsQCA and artificial neural network approach

This study aims to enhance the post-training evaluation of the annual performance agreement (APA) training organized by the Bangladesh Public Administration Training Centre (BPATC), the apex training institute for civil servants. Utilizing fuzzy-set qualitative comparative analysis (fsQCA) and artificial neural network (ANN) techniques within Kirkpatrick's four-stage model framework, data were collected from a self-administered questionnaire survey of 71 in-service civil servants who participated in the APA training program. This study employs an asymmetric, non-linear model analyzed through a configurational approach and ANN to explore interrelationships among the four Kirkpatrick levels namely, reaction, learning, behavior, and results. Findings indicate that trainees were satisfied across all levels, identifying a non-linear relationship among these levels in post-training evaluation process. The research highlights that "learning skills" are most significant in the APA post-training evaluation, followed by behavior, results, and reaction. Theoretically, this research advances Kirkpatrick's model and adds to the literature on public service post-training evaluation. Practically, it recommends prioritizing strategies that address cognitive barriers to enhance training effectiveness. This study's innovative approach lies in its concurrent use of fsQCA and ANN methods to analyze the success or failure of APA-related trainees, offering alternative pathways to desired outcomes and contrasting traditional quantitative methods that provide a single solution. The findings have practical implications for public service training institutions and bureaucratic policymakers involved in capacity development, guiding the creation of more effective in-service training courses for public officials. The methodology and analysis can be applied in other contexts, allowing bureaucratic policymakers to replicate these findings in their learning institutes to identify unique configurations that lead to successful or unsuccessful training outcomes, adopt effective strategies, and avoid detrimental ones.

The Effect of Digital Platform Strategies on Firm Value in the Banking Industry

After digital platforms have become successful in the information technology (IT) industry, incumbents from traditional industries increasingly implement digital platform strategies. However, there is mixed evidence on whether these incumbents benefit from digital platform strategies. To provide systematic insights, we focus on the banking industry. With the emergence of open banking, banks have begun implementing digital platforms to unlock the innovative power of third-party developers. We conducted an event study based on the announcement of digital platform strategies in a global sample of 165 banks. We show that, on average, investors react positively to the announcements. Contrary to our expectations, this effect is more substantial for banks from emerging markets than those from developed markets. Prior artificial intelligence (AI) orientation only partly contributes to investors' favorable perception of a digital platform strategy. These results point to the complex interplay of AI orientation and digital platform strategies, yielding questions for future research.

API integration and organisational agility outcomes in digital music platforms: A qualitative case study

Organisations deploy digital platforms to maximise value and transform their businesses. The success of most platforms is attributed to Application Programming Interfaces (APIs), the protocols enabling different software to communicate with each other. However, previous research on APIs has predominantly focused on the technical dimensions, such as design, and unintentionally neglected other social areas, such as organisational outcomes. This study seeks to advance organisational API research by adopting an agility perspective to explore the agility outcomes after API integration. Through rich qualitative data from a music digital firm, the findings revealed four primary agility outcomes: customer agility in the form of swift customer feedback, operational agility in the form of improved business process and delay reduction, partner agility in the form of embracing flexibility in processes and structures and expanding their ecosystem and decision agility in the form of fast decision making. A model showing the interplay and interdependencies of the agility outcomes was developed and provided depth and clarity to the findings. This study extends the literature by establishing how API integration influences organisational agility under conditions such as possessing capabilities and managing tensions during the integration process.

The social representation of digital transformation: The IT professionals' perspective

In this study, we aimed to identify how Information Technology professionals make sense of digital transformation, in order to compare this perception with the scientific literature on the topic. To conduct the research, we adopted the Social Representation Theory. Thus, via an online tool, we applied the words evocation technique as well as an ancillary questionnaire comprising open and closed questions. The expressions collected were then semantically treated and categorized, being then analyzed vis-à-vis their frequency of evocation, relevance, connectedness, and cooccurrence. Then, we performed similarity and content analyses for the open answers received. In doing so, we detected dissonance between scientific production on the concept of digital transformation and the perception of Information Technology professionals on this construct, concluding that such professionals have a technocentric view of digital transformation, based mainly on its technological aspects, which can prevent digital transformation initiatives from fully achieving the desired objectives.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Risk management of sports service supply chain using fuzzy comprehensive evaluation and intelligent neural network

The sports service supply chain faces various potential risks, such as market fluctuations, logistics issues, and partner uncertainties. To address these risks effectively, this study employs a combination of fuzzy comprehensive evaluation (FCE) methods and intelligent neural networks to create an innovative risk management framework. By considering diverse uncertainties and leveraging the analytical power of intelligent neural networks, this study aims to optimize the operation of the sports service supply chain and explore the risk factors within the public service supply chain of stadiums. This framework provides policy references to promote the healthy and sustainable development of the sports service industry. The main empirical findings, based on a representative survey of experts in China, are as follows: (1) When determining the weights of risk indicators for managing the public service supply chain of stadiums using the FCE method, the customer risk indicator is of paramount importance, with a weight of 0.286, accounting for 95.2 % of the total significance; and (2) In evaluating various risk indicators of the public service supply chain of stadiums through the neural network method, the customer risk indicator scores the highest, achieving a score of 76.02. Notably, the customer complaint risk indicator scores slightly higher at 79.33. Based on these findings, the study recommends focusing on enhancing customer experience within risk management strategies. Additionally, it suggests strengthening the supervision of platforms and third-party activities to ensure the stability and efficient operation of the stadium service supply chain. This study aims to provide theoretical support and reference indicators for evaluating the public service capabilities of stadiums.

Electronic word-of-mouth (eWOM) on social networking sites (SNS): Roles of information credibility in shaping online purchase intention

Electronic word of mouth (eWOM) on social networking sites (SNS) has become crucial in shaping online consumers' purchase intentions, reflecting the growing reliance on rich nature of user-generated content and recommendations shared on these platforms. This study aims to investigate the intricate relationships among different factors of eWOM information, including information credibility, information usefulness, information adoption, attitude towards information, and their impacts on online purchase intention. This study draws upon the Information Adoption Model (IAM) and the Information Acceptance Model (IACM) foundation theory which reveal the steps individuals take in adopting new information, and focuses on how perceptions and attitudes towards information shape acceptance. The study used a quantitative approach, utilizing a structured questionnaire to collect data from 337 Vietnamese individuals actively engaged in eWOM activities on various SNS platforms. Statistical analysis was conducted using partial least squares structural equation modeling (PLS-SEM). The findings show that information credibility significantly influences both information usefulness and adoption. Interestingly, while information usefulness shapes user attitudes, it does not directly impact online purchase intention. Similarly, a positive attitude toward eWOM does not necessarily lead to information adoption. This suggests that consumers may hold favorable views of eWOM content without actively adopting it. Information adoption emerges as a critical determinant of online purchase intention, emphasizing the importance of promoting user engagement and trust in eWOM information. These findings contribute to a deeper understanding of online consumer behavior and provide valuable guidance for stakeholders seeking to leverage eWOM effectively in digital marketing.

Challenge or Hindrance? The Dual Impact of Algorithmic Control on Gig Workers' Prosocial Service Behaviors

Algorithmic technological progress presents both opportunities and challenges for organizational management. The success of online labor platforms hinges on algorithmic control, making it imperative to explore how this control affects gig workers' prosocial service behaviors. Drawing from affective event theory, our study delves into the factors influencing gig workers' prosocial service behaviors in the online labor platform setting. We utilize the challenge-hindrance appraisal framework to highlight the pivotal role of algorithmic control. To rigorously test our hypotheses, we gathered empirical data from an online questionnaire survey of 660 gig workers. Our results indicate that challenge appraisals and hindrance appraisals in regard to platform algorithm control have a nuanced dual impact on gig workers' prosocial service behaviors. This relationship is clarified by the mediating function of work engagement. A challenge appraisal of platform algorithmic control can positively influence gig workers' prosocial service behaviors. However, hindrance appraisal of platform algorithmic control can negatively influence gig workers' prosocial service behaviors. Interestingly, workplace interpersonal capitalization boosts the effect of challenge appraisal on employees' prosocial service behaviors. However, it does not mitigate the adverse effects of hindrance appraisal on such behaviors. This study has multiple theoretical implications, and it also provides valuable practical insights into organizational management.

Feeling Supported as a Remote Worker: The Role of Support from Leaders and Colleagues and Job Satisfaction in Promoting Employees' Work-Life Balance

Due to the increasing use of remote work, understanding the dynamics of employee support and its implications for job satisfaction and work-life balance is crucial. Utilizing the Conservation of Resources (COR) theory as a theoretical framework, this research investigated how feeling supported by leaders and colleagues at work fosters work-life balance and job satisfaction among remote employees. The study involved 635 remote workers (females = 61%, mean age, 46.7, SD = 11) from various service-based industries and public administration in Italy. Results from the structural equation model showed a total mediating effect of job satisfaction in the link between colleague support and work-life balance (χ2(22) = 68.923, p = 0.00, CFI = 0.973, TLI = 0.955, RMSEA = 0.059 (90% CI = 0.044-0.075, p = 0.158), SRMR = 0.030), emphasizing the role of interpersonal relationships within the workplace in enhancing remote workers' job satisfaction and, consequently, their work-life balance. Contrary to expectations, the study found no significant direct or indirect link between leader support and work-life balance. This research highlights the significance of fostering strong social connections and ensuring employee satisfaction to promote well-being and work-life balance in remote work arrangements.

The impact of perceived vaginal and urinary symptoms and treatment burden in predicting sexual functioning among perimenopausal and postmenopausal women

OBJECTIVE

This study aimed to explore the relationship between urogenital symptom frequency and severity, perception of vaginal treatment burden, and female sexual desire, arousal, and satisfaction.

METHODS

A cross-sectional study was conducted with a sample of 326 patients from three tertiary care hospitals in the United Arab Emirates. The frequency and severity of urogenital symptoms, emotional and physical functioning, and treatment burden were assessed using the validated genitourinary syndrome of menopause symptoms and vaginal treatments acceptability questionnaire (GSM-SVATQ). To examine the mediating roles of emotional and physical functioning, as well as the perceived treatment burden on sexual functioning, a partial least squares-structural equation model was developed using the SmartPLS 4 Software.

RESULTS

The measurement model was successfully established. All constructs had a reliability of > 0.70 and discriminant validity of < 0.90. Emotional, physical and sexual functioning showed an adjusted R2 values of 0.377, 0.282 and 0.169, respectively.The multistep multiple mediator model revealed a full mediation effect of both emotional and physical functioning between symptom, treatment burden and sexual functioning. The model showed high predictive performance with all manifest variables showing lower mean absolute errors compared to the naiive benchmark model.

CONCLUSION

This study enhances our understanding of the relationships between urogenital symptoms, perceived treatment burden, emotional functioning, and sexual well-being. The findings emphasize the importance of addressing emotional well-being in managing urogenital symptoms and in addressing emotional factors associated with the use of vaginal treatments.

Organizing visions for data-centric management: how Norwegian policy documents construe the use of data in health organizations

PURPOSE

Norway, like other welfare states, seeks to leverage data to transform its pressured public healthcare system. While managers will be central to doing so, we lack knowledge about how specifically they would do so and what constraints and expectations they operate under. Public sources, like the Norwegian policy documents investigated here, provide important backdrops against which such managerial work emerges. This article therefore aims to analyze how key Norwegian policy documents construe data use in health management.

DESIGN/METHODOLOGY/APPROACH

We analyzed five notable policy documents using a "practice-oriented" framework, considering these as arenas for "organizing visions" (OVs) about managerial use of data in healthcare organizations. This framework considers documents as not just texts that comment on a topic but as discursive tools that formulate, negotiate and shape issues of national importance, such as expectations about data use in health management.

FINDINGS

The OVs we identify anticipate a bold future for health management, where data use is supported through interconnected information systems that provide relevant information on demand. These OVs are similar to discourse on "evidence-based management," but differ in important ways. Managers are consistently framed as key stakeholders that can benefit from using secondary data, but this requires better data integration across the health system. Despite forward-looking OVs, we find considerable ambiguity regarding the practical, social and epistemic dimensions of data use in health management. Our analysis calls for a reframing, by moving away from the hype of "data-driven" health management toward an empirically-oriented, "data-centric" approach that recognizes the situated and relational nature of managerial work on secondary data.

ORIGINALITY/VALUE

By exploring OVs in the Norwegian health policy landscape, this study adds to our growing understanding of expectations towards healthcare managers' use of data. Given Norway's highly digitized health system, our analysis has relevance for health services in other countries.