How good are large language models at product risk assessment?

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

Foreign executives, digital transformation, and innovation performance: Evidence from Chinese-listed firms

This study investigates the effect of foreign executives on firms' innovation performance and the mediation role of digital transformation in Chinese-listed firms from 2011 to 2021. Our findings indicate that the presence of foreign executives in top management teams promotes firms' innovation performance by enhancing digital transformation. Further analyses show that foreign executives contribute significantly to improving firms' radical innovation performance rather than incremental innovation performance. We also examine the moderating effect of negative performance feedback and financing constraints between foreign executives and innovation performance, finding that foreign executives can promote innovation performance particularly in firms with negative performance feedback and weak financing constraints.

Heterogeneous peer effects of college roommates on academic performance

Understanding how student peers influence learning outcomes is crucial for effective education management in complex social systems. The complexities of peer selection and evolving peer relationships, however, pose challenges for identifying peer effects using static observational data. Here we use both null-model and regression approaches to examine peer effects using longitudinal data from 5,272 undergraduates, where roommate assignments are plausibly random upon enrollment and roommate relationships persist until graduation. Specifically, we construct a roommate null model by randomly shuffling students among dorm rooms and introduce an assimilation metric to quantify similarities in roommate academic performance. We find significantly larger assimilation in actual data than in the roommate null model, suggesting roommate peer effects, whereby roommates have more similar performance than expected by chance alone. Moreover, assimilation exhibits an overall increasing trend over time, suggesting that peer effects become stronger the longer roommates live together. Our regression analysis further reveals the moderating role of peer heterogeneity. In particular, when roommates perform similarly, the positive relationship between a student's future performance and their roommates' average prior performance is more pronounced, and their ordinal rank in the dorm room has an independent effect. Our findings contribute to understanding the role of college roommates in influencing student academic performance.

Integrating the ESM usage and work engagement for employee agility performance: based on regulatory focus theory

This present research aims to clarify the intricate conjunction of enterprise social media (ESM) utilization and employee agility with a main focus on uncovering the underlying mechanisms that work through the mediating influence of work engagement and the moderating influence of regulatory focus. Drawing upon regularity focus theory, 353 Chinese samples of ESM users in organizational contexts are analyzed using SPSS 23.0. The empirical findings substantiate a robust and significant positive linkage between ESM usage and worker agility. Further reinforcing the model, the mediating role of work engagement is established as it channels the impact of ESM usage on worker agility. Turning to the moderating effects, the study unveils the differential impact of prevention focus and promotion focus, wherein individuals with a lower prevention focus exhibit a more pronounced positive linkage between ESM usage and worker agility. Similarly, individuals with a higher promotion focus demonstrate a heightened positive association between ESM usage and worker agility. By comprehensively inspecting the intricate dynamics of ESM usage, work engagement, and regulatory focus, this study enhances our theoretical understanding of how these factors synergistically shape employee agility, ultimately furnishing organizations with invaluable insights to foster and cultivate an agile workforce.

Assessing the Impact of Recommendation Novelty on Older Consumers: Older Does Not Always Mean the Avoidance of Innovative Products

Personalized recommendations that use digital technologies to predict user interests and preferences and give guiding conclusions have become a widely used digital marketing tool on e-commerce platforms. Given that existing consumer behavior research has not reached a consensus on the relationship between age and the adoption of innovative products, whether recommendation novelty can stimulate older consumers' acceptance of innovative products remains uncertain. Grounded in the aging and social influence literature, this experimental study investigated the moderating role of individual cognitive age on the impact of recommendation novelty on consumer perceptions regarding stereotype threat and receptiveness to innovativeness. An experiment involving 239 online shoppers was conducted to investigate the experiences of cognitively younger and older adults while using low or high levels of recommendation novelty designed for this study. Results reveal the tension for older adults when using highly recommended novelty, as they perceive these to be more of a stereotype threat, but they also have a higher level of receptiveness to innovativeness. This finding is contrary to the common belief that "the older the consumer, the less receptive to innovativeness", providing novel insight into the information systems literature. Theoretically, this research shows how increasing the level of recommended novelty affects stereotype threat and receptiveness to innovativeness (of consumers of different cognitive ages). For practitioners, the results provide important guidelines on the kind of personalized recommendations that are appropriate for consumers with different cognitive ages.

Automated vehicles for older adults with cognitive impairment: a survey study

As the population is ageing, the number of older adults with cognitive impairment (CI) is increasing. Automated vehicles (AVs) can improve independence and enhance the mobility of these individuals. This study aimed to: (1) understand the perception of older adults (with and without CI) and stakeholders providing services and supports regarding care and transportation about AVs, and (2) suggest potential solutions to improve the perception of AVs for older adults with mild or moderate CI. A survey was conducted with 435 older adults with and without CI and 188 stakeholders (e.g. caregivers). The results were analysed using partial least square - structural equation modelling and multiple correspondence analysis. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided recommendations to improve older adults' perception of AVs including education and adaptive driving simulation-based training.Practitioner summary: This study investigated the perception of older adults and other stakeholders regarding AVs. The findings suggested relationships between older adults' level of cognitive impairment, mobility, knowledge of AVs, and perception of AVs. The results provided guidelines to improve older adults' perception of AVs.

From "online brains" to "online lives": understanding the individualized impacts of Internet use across psychological, cognitive and social dimensions

In response to the mass adoption and extensive usage of Internet-enabled devices across the world, a major review published in this journal in 2019 examined the impact of Internet on human cognition, discussing the concepts and ideas behind the "online brain". Since then, the online world has become further entwined with the fabric of society, and the extent to which we use such technologies has continued to grow. Furthermore, the research evidence on the ways in which Internet usage affects the human mind has advanced considerably. In this paper, we sought to draw upon the latest data from large-scale epidemiological studies and systematic reviews, along with randomized controlled trials and qualitative research recently emerging on this topic, in order to now provide a multi-dimensional overview of the impacts of Internet usage across psychological, cognitive and societal outcomes. Within this, we detail the empirical evidence on how effects differ according to various factors such as age, gender, and usage types. We also draw from new research examining more experiential aspects of individuals' online lives, to understand how the specifics of their interactions with the Internet, and the impact on their lifestyle, determine the benefits or drawbacks of online time. Additionally, we explore how the nascent but intriguing areas of culturomics, artificial intelligence, virtual reality, and augmented reality are changing our understanding of how the Internet can interact with brain and behavior. Overall, the importance of taking an individualized and multi-dimensional approach to how the Internet affects mental health, cognition and social functioning is clear. Furthermore, we emphasize the need for guidelines, policies and initiatives around Internet usage to make full use of the evidence available from neuroscientific, behavioral and societal levels of research presented herein.

Sipping a sustainable life: Exploring drivers and barriers in consumer attitudes toward non or low alcoholic spirits

Alcohol consumption continues to be prevalent and is on the rise in many countries, posing a grave risk for the health and wellbeing of millions and creating a strain on health services worldwide. A hopeful trend has emerged, however, as consumers' growing preference for healthier, sustainable lifestyles has led traditional alcoholic brands to innovate, launching reduced or non-alcoholic (NoLo) options. This aligns with the SDGs and is reflected in NoLo spirits representing four of Spain's top ten disruptive innovations of 2022. This paper uses a mixed methodology in a qualitative-quantitative sequential approach to gain insight into this phenomenon. The study involved 13 in-depth interviews with HoReCa (an acronym for Hotels, Restaurants, and Caterings) professionals and four focus groups among consumers. Second, behavioral reasoning theory (BRT) was used in a quantitative study aiming to explore motivations for and against consuming NoLo spirits. Data from a survey of 620 participants was conducted and analyzed using SEM-PLS to measure the antecedents of consumer's behavioral intention towards NoLo spirits and to gauge the potential for marketing opportunities. The research reveals that the purchase intention of NoLo spirits is strongly related to health consciousness, while enjoying the effects of alcohol for fun and entertainment, and the social pressure to drink hinders its consumption. In addition, it was found that "reasons for" are more substantial than "reasons against" the consumption of those beverages, differing significantly by age group. Results offer implications for theory and practice, including recommendations for practitioners and regulators willing to improve sustainability in the industry. Further, this paper helps augment the innovation adoption literature by using BRT in the paradoxical context of consumers' increasing alcohol abuse despite their professed attempts to adopt healthier lifestyles.

Protocol for a randomised controlled field experiment on the effect of different gamification designs of physical activity

Gamification is finding growing application in the field of physical activity, promising engaging and motivating experiences that foster behavioural change. However, existing empirical work has insufficiently scrutinised whether the reported positive outcomes emerge because of gamification and what type of gamification design leads to optimal results. This protocol for a parallel four-arm randomised controlled field experiment was purposely designed to investigate the effect of different gamification designs on motivation, perceived usefulness, and the intended behavioural change in physical activity (increase in step counts). Participants were randomly assigned to either: 1) a competitive gamified group; 2) a cooperative gamified group; 3) a hybrid (competitive-cooperative) gamified group; or 4) a control group. The design of the gamified interventions was guided by gamification design frameworks identified in literature. The data gathered includes: 1) a longitudinal panel dataset of step counts to investigate the causal effect of gamification on physical activity behaviour; and 2) self-reported data to examine the effect of gamification on the users' intrinsic motivation and perceived usefulness of the experience. This protocol outlines the procedure and processes followed during this experiment to facilitate replicability for future studies.

The desirability bias in personality-related syllogistic reasoning

INTRODUCTION

The belief-bias effect is a tendency to evaluate syllogistic statements based on believability rather than on formal logic validity. Following this rationale, the study examines desirability bias as the tendency to evaluate syllogistic conclusions based on their desirability when reasoning is conducted on personality-relevant categorical syllogisms.

METHODS

For this purpose, 60 syllogisms were constructed based on the items of the Big Five questionnaire. Syllogisms were subsequently categorized as desirable (e.g., "I empathize with others") and undesirable (e.g., "I am passive") based on their conclusion. In each task, the second premise and the conclusion were formulated in the first person to increase a respondent's identification with the content. A total of 300 university students (Mage = 20.08, SD = 2.02) participated in the study.

RESULTS

A 2 (syllogism validity: valid, invalid) × 2 (syllogism desirability: desirable, undesirable) repeated measures ANOVA was employed. The analysis showed a greater tendency to accept desirable conclusions on valid syllogisms (valid desirable rather than valid undesirable) and reject undesirable conclusions on invalid syllogisms (invalid undesirable rather than invalid desirable).

CONCLUSION

These findings have implications for socially desirable responding in cognitive tasks, which may be further developed as a source of self-relevant content as well as for further extension of belief bias in the form of desirability bias.

Mixed Methods Illustration of Teachers' Trauma-Informed Attitudes and Practice

Traumatic events during childhood are crucial to consider when addressing children's social and emotional development, as childhood trauma is associated with negative impacts, including academic achievement. Additionally, positive classroom environments and teachers' trauma-informed attitudes and behavior play a role in supporting recovery from children's trauma-related experiences. Aspire, Connect, Thrive (ACT) is a trauma-informed school-based intervention that examined students' Social Emotional Competence (SEC) and resilience for K-8th grade students in a disadvantaged, urban elementary school in Connecticut contending with the effects of students' exposure to trauma. The present study examines the experience of ACT teachers who received professional development and subsequently implemented learned content in the classroom (N = 17; 70.6% female, mean age = 44 years; 47.1% racial/ethnic minority; mean years teaching = 15.6) through qualitative evidence of trauma sensitivity (observed and self-reported) and clinician-ratings of teachers' positive classroom environment. Quantitative results indicate significant change over time in teachers' attitudes and trauma-informed classroom responses. Interview themes suggest (1) teachers learned from and implemented the intervention content in their classrooms dependent upon the support the teacher was given, (2) teachers' perspectives on the connections between the student-teacher relationship and trauma-informed attitudes or practices influenced teacher behavior, and (3) teachers' own emotions and experiences implementing trauma-informed practices were key to classroom management.

Electronic medication administration record (eMAR) in Swedish home healthcare-Implications for Nurses' and nurse Assistants' Work environment: A qualitative study

BACKGROUND

The electronic medication administration record (eMAR) is an eHealth system that has replaced the traditional paper-based medication administration used in many healthcare settings. Research has highlighted that eHealth technologies can change working methods and professional roles in both expected and unexpected ways. To date, there is sparse research that has explored how nurses and nurse assistants (NA) in home healthcare experience eMAR in relation to their work environment.

AIM

The aim was to explore how nurses and nurse assistants experienced their work environment, in terms of job-demand, control, and support in a Swedish home healthcare setting where an electronic medication administration record had been implemented to facilitate delegation of medical administration.

METHOD

We took a qualitative approach, where focus groups were used as data collection method. The focus groups included 16 nurses and nine NAs employed in a Swedish municipality where an eMAR had been implemented 6 months before the first focus groups were performed. The analysis adapted the job-demand-control-support model, by condensing the professionals' experiences into the three categories of demand, control, and support, in alignment with the model.

RESULTS

NAs experienced high levels of job demand and low levels of job control. The use of the eMAR limited NAs' ability to control their work, in terms of priorities, content, and timing. In contrast, the nurses described demands as high but manageable, and described having a high level of control. Both professions found the eMar supportive.

CONCLUSION

Nurses and NAs in home healthcare experienced changes in their work environment regarding demand, control, and support when an eMAR was implemented to facilitate delegation of medical administration. In general, nurses were satisfied with the eMAR. However, NAs felt that the eMAR did not cover all aspects of their daily work. Healthcare organisations should be aware of the changes that digitalisation processes entail in the work environment of nurses and NAs in home healthcare.

Superior medical resources or geographic proximity? The joint effects of regional medical resource disparity, geographic distance, and cultural differences on online medical consultation

Online medical consultation platforms enable patients to seek health advice from physicians across geographic regions. In this study, we analyze patterns of online consultation between patients and physicians. We examine the joint effects of regional medical resource disparity, geographic distance, and cultural differences between patients and physicians on patients' decisions about which physicians they consult online. Using a unique dataset of city-to-city tuples based on 813,684 online consultation records and combining it with region-level data from multiple external sources, we find that while regional medical resource disparity drives patients from medically disadvantaged regions to seek online consultations with physicians from medically advantaged regions, geographic distance and cultural differences tend to constrain these consultations. We also find that cultural differences can amplify the impact of regional medical resource disparity, whereas geographic distance may lessen this effect. Further, we discover that the constraining effect of geographic distance is partly due to the online-to-offline nature of online medical consultations. Moreover, additional analyses suggest that physicians' online reputation and information about physicians' participation on the platform can help alleviate the negative effects of geographic distance and cultural differences. These findings hold significant implications for the allocation of medical resources and the formulation of healthcare policies.

Domain-Specific Greed

Greed, the insatiable and excessive desire and striving for more even at the expense of others, may be directed toward various goods. In this article, we propose that greed may be conceptualized as a domain-specific construct. Based on a literature review and an expert survey, we identified 10 domains of greed which we operationalized with the DOmain-SPEcific Greed (DOSPEG) questionnaire. In Study 1 (N = 725), we found support for the proposed structure and convergent validity with related constructs. Bifactor-(S-1) models revealed that generic greed is differentially related to the greed domains, indicating that generic greed primarily captures a striving for money and material things. In the second study (N = 591), we found that greed domains had incremental validity beyond generic greed with regard to corresponding criteria assessed via self- and other-reports. We conclude that greed can be conceptualized as a domain-specific construct and propose an onion model reflecting this structure.

A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis

Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient's complete health history to make informed decisions about future events. However, previous work has mostly relied on so-called black-box models, which are unintelligible to humans, making it difficult for clinicians to apply such models. Our work introduces PatWay-Net, an ML framework designed for interpretable predictions of admission to the intensive care unit (ICU) for patients with symptoms of sepsis. We propose a novel type of recurrent neural network and combine it with multi-layer perceptrons to process the patient pathways and produce predictive yet interpretable results. We demonstrate its utility through a comprehensive dashboard that visualizes patient health trajectories, predictive outcomes, and associated risks. Our evaluation includes both predictive performance - where PatWay-Net outperforms standard models such as decision trees, random forests, and gradient-boosted decision trees - and clinical utility, validated through structured interviews with clinicians. By providing improved predictive accuracy along with interpretable and actionable insights, PatWay-Net serves as a valuable tool for healthcare decision support in the critical case of patients with symptoms of sepsis.

Physiotherapy services during the COVID-19 pandemic: A mediated model of physiotherapists' self-efficacy, tele-physiotherapy role stressors, and motivation to provide tele-physiotherapy

BACKGROUND

Occupational self-efficacy is a stable predictor for professionals' motivation to engage with new methods and tasks. Yet, the delivery of tele-physiotherapy (Tele-PT) by physiotherapists (PTs) during the coronavirus disease of 2019 (COVID-19) outbreak without advance training may have had the potential to increase work stress and damage their motivation, regardless of their occupational self-efficacy.

OBJECTIVES

The present study examined whether the relations between PTs' overall occupational self-efficacy and motivation to provide Tele-PT was mediated by role stress (i.e. role conflict and ambiguity).

DESIGN AND METHOD

Between February 4 and April 23, 2021, 150 Israeli PTs completed an online survey that measured their overall occupational self-efficacy, their role stress induced by the provision of Tele-PT, their motivation to provide Tele-PT, and their demographic characteristics.

RESULTS

PTs' overall occupational self-efficacy was positively associated with PTs' motivation to provide Tele-PT (r= 0.328, p < .01) and fully mediated by role conflict (0.1757, 95% CI = [0.0231, 0.3797]) and by role ambiguity (0.1845, 95% CI = [0.0196, 0.4184]) (components of role stress) caused by the provision of Tele-PT.

CONCLUSIONS

It is important to investigate the predictors and mediators of the motivation to provide Tele-PT because in the post-COVID-19 era health organizations are likely to adopt many tele-medicine services, and they need to find ways to mitigate perceived challenges.

Data on mathematics teacher educators' proficiency and willingness to use technology: A structural equation modelling analysis

The role of Mathematics Teacher Educators (MTEs) in preparing future teachers to effectively integrate technology into their mathematics instruction is of paramount importance yet remains an underexplored domain. Technology has the potential to enhance the development of 21st-century skills, such as problem-solving and critical thinking, which are essential for students in the era of the fourth industrial revolution. However, the rapid evolution of technology and the emergence of new trends like data analytics, the Internet of Things, machine learning, cloud computing, and artificial intelligence present new challenges in the realm of mathematics teaching and learning. Consequently, MTEs need to equip prospective teachers with the knowledge and skills to harness technology in innovative ways within their future mathematics classrooms. This paper presents and describes data from a survey of 104 MTEs in Zambia. The study focuses on MTEs' proficiency, perceived usefulness, perceived ease of use, and willingness to incorporate technology in their classrooms. This data-driven article aims to unveil patterns and trends within the dataset, with the objective of offering insights rather than drawing definitive conclusions. The article also highlights the data collection process and outlines the procedure for assessing the measurement model of the hypothesised relationships among variables through structural equation modelling analysis. The data described in this article not only sheds light on the current landscape but also serves as a valuable resource for mathematics teacher training institutions and other stakeholders seeking to understand the requisites for MTEs to foster technological skills among prospective teachers of mathematics.

Economic policy uncertainty and enterprise export resilience in China: Does the digital economy matter?

In the new era of international trade, escalating uncertainty and the swift development of the digital economy stand out as two pivotal transformations. These phenomena individually exert significant influences on enterprises' exports; however, their combined effects on export resilience remain underexplored. Hence, drawing on existing theories, this paper analyzes the weakening effect of economic policy uncertainty on export resilience and explores the influence of regional digital economic development on this attenuation effect. Furthermore, empirical tests are conducted using micro-level data from China. The study findings reveal: (1) Economic policy uncertainty weakens firms' export resilience by increasing transaction costs; (2) Digital economic development mitigates this weakening effect by reducing transaction costs, with a more pronounced effect observed among highly efficient firms. The findings suggest that amid escalating uncertainty, vigorously promoting digital economic development holds profound policy significance for the high-quality development of international trade.

Ethnocentrism and place identity in the consumption of local products

Research on the consumption of local products is essential to promote sustainability, boost local economies, and preserve cultural identity. Although a positive relationship has been demonstrated between attitude towards local products and consumption determinants, the role of the former as a mediator has not been sufficiently explored. This study examines how the attitude towards local products mediates between consumer ethnocentrism and consumption intention, as well as between place identity and consumption intention. A total of 1325 wine and cheese consumers in the Canary Islands were surveyed using a moderated mediation model, applying PLS-SEM. The results indicate that attitude towards local products mediates the aforementioned relationships but does not moderate them according to the type of local product. Consequently, marketing strategies should focus on the emotional and cultural connection that consumers establish with local products, highlighting their value in terms of identity and belonging.

Top of tide: Nexus between organization agility, digital capability and top management support in SME digital transformation

In the swiftly evolving business landscape, digital transformation (DT) has emerged as a crucial strategy for firms to gain a competitive edge. Despite the abundance of literature on DT in firms, there remains a dearth of empirical research that defines and analyzes crucial antecedents of small and medium-sized enterprises' (SMEs) DT from an internal perspective. To fill this research gap, this study examines the correlation between organizational agility and digital capability in cultivating SMEs' DT while also evaluating top management support as a moderating variable through the lens of internal factors of SMEs. The results indicate that both organizational agility and digital capability have a positive impact on SMEs' DT, with organizational agility significantly influencing digital capability. Furthermore, the findings highlight that digital capability serves as a mediator between organizational agility and SMEs' DT. In addition, top management support plays a moderating role in these relationships to a certain extent. Additionally, we explicate the concept of digital capabilities from the perspective of dynamic capability. Our study contributes to an enhanced understanding of the effect of organizational agility and digital capability on SMEs' DT, as well as the role of top management support. We provide recommendations for managers to enhance organizational agility and suggest that SMEs should improve their digital thinking to better perceive digital technology changes, enhance digital operation capabilities, and better integrate digital resources.

The Impact of Performance Expectancy, Workload, Risk, and Satisfaction on Trust in ChatGPT: Cross-Sectional Survey Analysis

BACKGROUND

ChatGPT (OpenAI) is a powerful tool for a wide range of tasks, from entertainment and creativity to health care queries. There are potential risks and benefits associated with this technology. In the discourse concerning the deployment of ChatGPT and similar large language models, it is sensible to recommend their use primarily for tasks a human user can execute accurately. As we transition into the subsequent phase of ChatGPT deployment, establishing realistic performance expectations and understanding users' perceptions of risk associated with its use are crucial in determining the successful integration of this artificial intelligence (AI) technology.

OBJECTIVE

The aim of the study is to explore how perceived workload, satisfaction, performance expectancy, and risk-benefit perception influence users' trust in ChatGPT.

METHODS

A semistructured, web-based survey was conducted with 607 adults in the United States who actively use ChatGPT. The survey questions were adapted from constructs used in various models and theories such as the technology acceptance model, the theory of planned behavior, the unified theory of acceptance and use of technology, and research on trust and security in digital environments. To test our hypotheses and structural model, we used the partial least squares structural equation modeling method, a widely used approach for multivariate analysis.

RESULTS

A total of 607 people responded to our survey. A significant portion of the participants held at least a high school diploma (n=204, 33.6%), and the majority had a bachelor's degree (n=262, 43.1%). The primary motivations for participants to use ChatGPT were for acquiring information (n=219, 36.1%), amusement (n=203, 33.4%), and addressing problems (n=135, 22.2%). Some participants used it for health-related inquiries (n=44, 7.2%), while a few others (n=6, 1%) used it for miscellaneous activities such as brainstorming, grammar verification, and blog content creation. Our model explained 64.6% of the variance in trust. Our analysis indicated a significant relationship between (1) workload and satisfaction, (2) trust and satisfaction, (3) performance expectations and trust, and (4) risk-benefit perception and trust.

CONCLUSIONS

The findings underscore the importance of ensuring user-friendly design and functionality in AI-based applications to reduce workload and enhance user satisfaction, thereby increasing user trust. Future research should further explore the relationship between risk-benefit perception and trust in the context of AI chatbots.

Human-annotated rationales and explainable text classification: a survey

Asking annotators to explain "why" they labeled an instance yields annotator rationales: natural language explanations that provide reasons for classifications. In this work, we survey the collection and use of annotator rationales. Human-annotated rationales can improve data quality and form a valuable resource for improving machine learning models. Moreover, human-annotated rationales can inspire the construction and evaluation of model-annotated rationales, which can play an important role in explainable artificial intelligence.

Navigating board dynamics: Configuration analysis of corporate governance's factors and their impact on bank performance

This research utilizes the fsQCA technique to investigate how a combination of corporate governance conditions or factors collectively influences the performance of banks. Examining key elements such as board size, busy directors, independent directors, CEO duality, and women on the board, the research employs data collected from the annual reports of 30 banks spanning from 2010 to 2020. The necessary condition analysis (NCA) underscores that no individual condition or factor is indispensable for the ultimate outcome. Nevertheless, the sufficiency analysis reveals distinct solutions, each representing a unique set of conditions or factors sufficient to generate the outcome. The study concludes that the relationship between corporate governance characteristics and bank performance is complex and multifaceted, with neither ROA nor ROE reliant on a singular input condition or factor. The theoretical contributions of the findings align with or partially support various theories and propositions within the realm of corporate governance. Notably, the application of fsQCA contributes to enhance the methodological understanding of corporate governance studies in existing literature.

Navigating the decision-making landscape of AI in risk finance: Techno-accountability unveiled

The integration of artificial intelligence (AI) systems has ushered in a profound transformation. This conversion is marked by revolutionary extrapolative capabilities, a shift toward data-centric decision-making processes, and the enhancement of tools for managing risks. However, the adoption of these AI innovations has sparked controversy due to their unpredictable and opaque disposition. This study employs the transactional stress model to empirically investigate how six technological stressors (techno-stressors) impact both techno-eustress (positive stress) and techno-distress (negative stress) experienced by finance professionals and experts. To collect data for this research, an e-survey was distributed to a diverse group of 251 participants from various sources. The findings, particularly the identification and development of techno-accountability as a significant factor, contribute to the risk analysis domain by improving the failure mode and effect analysis framework to better fit the rapidly evolving landscape of AI-driven innovations.

Green innovation and enterprise digital transformation: Escape from the "dilemma" of development and governance choices

The digital economy is now the expected norm for economic development, warranting strategic importance for enterprise digital transformation. Nonetheless, enterprises have a lengthy journey to embark upon for digital transformation. On the one hand, resource-based demands pose a significant challenge due to the development characteristics of the initiative; on the other hand, excessive emphasis on economic gains may result in severe environmental issues. Therefore, this paper examines whether green innovation, which combines environmental and economic benefits, can effectively address the above dilemma. The study includes all A-share listed companies from 2010 to 2020 as the research sample, and empirically investigates the impact of green innovation on enterprise digital transformation and its mechanism based on resource-based view. The study concluded that (i) green innovation has a significant positive impact on corporate digital transformation performance, exhibiting asymmetric effects. The robustness tests confirmed the validity of the findings. (ii) Enterprises that actively engage in green innovation can effectively reduce their financial constraints, enhance their operational capacity, and enable the efficient allocation of resources, thereby promoting digital transformation within the enterprise. (iii) There is a regional imbalance in the conversion of green innovation performance into economic performance. The aforementioned results offer fresh insights for investigating the connection between green innovation and digital transformation. Additionally, these findings hold significant implications for the discourse on the synergistic advancement of the environment and economy.

Unlocking future learning: Exploring higher education students' intention to adopt meta-education

Despite the potential of meta-education to transform higher education, there remains a scarcity of research investigating students' adoption intentions. This study aimed to identify factors influencing students' intentions to adopt meta-education using an extended Decomposed Theory of Planned Behavior model (DTPB). Data was collected via an online survey of 596 higher education students from Jordan who were purposefully selected. Structural equation modeling using partial least squares analysis revealed attitude, social influence, and perceived behavioral control as key antecedents of adoption intention. Furthermore, newly added variables including perceived enjoyment, herd behavior, student autonomy, and student innovativeness showed efficiency in explaining variance in attitude, social influence, and perceived behavioral control. Overall, the extended model provided meaningful insights on factors driving students' willingness to adopt meta-education. The study contributes to theory by extending the decomposed TPB model in the context of emerging educational technologies. It also provides practical implications for policymakers and educators aiming to encourage meta-education adoption.

Research on the impact of digital transformation on innovative high-quality development in the context of environmental regulation in agricultural enterprises

Digital transformation is an important strategic choice for agricultural enterprises to adapt to economic development in the new era. The innovation quality of patents with core technology and high commercial value is significantly higher than that of low-quality patents such as weak patents developed through technological imitation. This study investigates the impact of digital transformation on innovative high-quality development in the context of environmental regulation in agricultural enterprises for the timeframe from 2012 to 2020. The purpose of this study is to examine whether the goal of improving innovation quality can be achieved through digital transformation in agricultural companies. The results show that digital transformation can effectively promote the improvement of innovation quality in companies, and environmental regulation has a significant positive moderating effect on the relationship between them. "Violating agricultural operation" is a specific appellation for the diversified management of listed agricultural companies, and it is one of the management modes of agricultural enterprises. For listed agricultural companies, the greater the degree of enterprise diversification, the greater the degree of "violating agricultural operation". The influence mechanism test shows that "violating agricultural operation" plays a part in mediating effect in the process of digital transformation promoting innovation quality improvement.

SNS citizenship behavior based on D&M information system success model and social capital theory: Mediating role of subjective well-being

Social media has become integral to contemporary society, with online behaviors impacting individual experiences and the wider community. In Bangladesh, a developing country, SNS have played a pivotal role in the nation's digitalization efforts. This study explores the relationship between social capital theory, D&M Information System Model, subjective well-being, and SNS Citizenship Behavior (SCB) among active social media users in Bangladesh. Data was collected from 418 participants through an online survey, and hypotheses were tested using structural equation modeling. The findings indicate that the items of the D&M model positively influenced the aspects of social capital theory, excluding service quality. In contrast, social interaction ties and shared values were positively associated with SCB, although social trust did not exhibit a significant relationship. Additionally, subjective well-being mediated the connection between social capital and SCB. This research offers valuable insights into the factors influencing online prosocial behavior and provides practical implications for cultivating a positive communication culture in the digital era. The model proposed in this study holds significant implications for Bangladesh's policymakers and social networking site authorities, guiding their efforts in implementing technology-based initiatives.

The study of female college students' consumer psychology mechanism toward male celebrity endorsed products: Tempted or coerced?

The trend of male celebrities endorsing female products is increasing. However, research is lacking on whether this influence is due to the positive emotions generated by the male celebrity's attractiveness or the peer pressure due to mass purchases by the celebrity's fans, and how these effects differ across products with different attributes. This study aims to fill the gap in the existing literature by investigating the influence of male endorsers on female consumers purchase intention, and to deepen the understanding of the mechanisms by which attractiveness and conformity jointly influence purchase decisions. This study used a mixed-design text experiment to investigate the impact of male endorsers' attractiveness and conformity on female college students' positive product attitude and purchase intention for gender-neutral product, female skincare product, and female intimate product, based on the Theory of Planned Behaviour (TPB). The data collected from 456 female college students were analyzed using bootstrap analysis. The study found that both male endorsers' attractiveness and conformity can enhance female college students' positive product attitude and promote their purchase intention for gender-neutral product. However, for female skincare product, male endorsers' attractiveness affects their positive product attitude and purchase intention. Nevertheless, when conformity was present, attractiveness no longer had an effect. Furthermore, for individuals with high levels of loneliness, attractiveness had a detrimental effect on their positive product attitude. On the other hand, conformity had a positive effect by promoting positive product attitude and increasing purchase intention. For female's intimate product, attractiveness did not affect positive product attitude and purchase intention, but the positive effect of conformity remained significant, and both relationships were not moderated by loneliness. It enhances our comprehension of the intricate dynamics underlying the influence of male celebrity endorsements on consumer purchasing decisions, and also offers theoretical justification for the selection of male endorsers for diverse female product.

Unveiling the shadows: Beyond the hype of AI in education

Despite the wave of enthusiasm for the role of Artificial Intelligence (AI) in reshaping education, critical voices urge a more tempered approach. This study investigates the less-discussed 'shadows' of AI implementation in educational settings, focusing on potential negatives that may accompany its integration. Through a multi-phased exploration consisting of content analysis and survey research, the study develops and validates a theoretical model that pinpoints several areas of concern. The initial phase, a systematic literature review, yielded 56 relevant studies from which the model was crafted. The subsequent survey with 260 participants from a Saudi Arabian university aimed to validate the model. Findings confirm concerns about human connection, data privacy and security, algorithmic bias, transparency, critical thinking, access equity, ethical issues, teacher development, reliability, and the consequences of AI-generated content. They also highlight correlations between various AI-associated concerns, suggesting intertwined consequences rather than isolated issues. For instance, enhancements in AI transparency could simultaneously support teacher professional development and foster better student outcomes. Furthermore, the study acknowledges the transformative potential of AI but cautions against its unexamined adoption in education. It advocates for comprehensive strategies to maintain human connections, ensure data privacy and security, mitigate biases, enhance system transparency, foster creativity, reduce access disparities, emphasize ethics, prepare teachers, ensure system reliability, and regulate AI-generated content. Such strategies underscore the need for holistic policymaking to leverage AI's benefits while safeguarding against its disadvantages.

Competition of multiplatform firms: Implications for the Internet of Things

The Internet of Things (IoT) technology trend is transforming business and society. This creates a need to understand strategic behavior in the consumer IoT, where firms tend to offer multiple platform devices, and new generations of devices are introduced frequently. We propose a novel analytical model that formalizes the concept of a multiplatform firm that offers a system of platforms, such as a smartphone, and a new platform device, such as a smartwatch, and orchestrates a multiplatform ecosystem. The analysis shows how a platform design decision, like offering a new standalone device, affects consumer choices and market outcomes. We identify two classes of new devices that matter, and show when a new platform device may disrupt the smartphone market. Moreover, we characterize conditions under which it is profitable for a vendor to make its new platform device look and feel more like its smartphone. Overall, we provide insights into how multiplatform firms differ from platform firms. We identify future research opportunities on the economics of consumer IoT and multiplatform ecosystems.

Introduction to Large Language Models (LLMs) for dementia care and research

Introduction

Dementia is a progressive neurodegenerative disorder that affects cognitive abilities including memory, reasoning, and communication skills, leading to gradual decline in daily activities and social engagement. In light of the recent advent of Large Language Models (LLMs) such as ChatGPT, this paper aims to thoroughly analyse their potential applications and usefulness in dementia care and research.

Method

To this end, we offer an introduction into LLMs, outlining the key features, capabilities, limitations, potential risks, and practical considerations for deployment as easy-to-use software (e.g., smartphone apps). We then explore various domains related to dementia, identifying opportunities for LLMs to enhance understanding, diagnostics, and treatment, with a broader emphasis on improving patient care. For each domain, the specific contributions of LLMs are examined, such as their ability to engage users in meaningful conversations, deliver personalized support, and offer cognitive enrichment. Potential benefits encompass improved social interaction, enhanced cognitive functioning, increased emotional well-being, and reduced caregiver burden. The deployment of LLMs in caregiving frameworks also raises a number of concerns and considerations. These include privacy and safety concerns, the need for empirical validation, user-centered design, adaptation to the user's unique needs, and the integration of multimodal inputs to create more immersive and personalized experiences. Additionally, ethical guidelines and privacy protocols must be established to ensure responsible and ethical deployment of LLMs.

Results

We report the results on a questionnaire filled in by people with dementia (PwD) and their supporters wherein we surveyed the usefulness of different application scenarios of LLMs as well as the features that LLM-powered apps should have. Both PwD and supporters were largely positive regarding the prospect of LLMs in care, although concerns were raised regarding bias, data privacy and transparency.

Discussion

Overall, this review corroborates the promising utilization of LLMs to positively impact dementia care by boosting cognitive abilities, enriching social interaction, and supporting caregivers. The findings underscore the importance of further research and development in this field to fully harness the benefits of LLMs and maximize their potential for improving the lives of individuals living with dementia.

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

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

Empowering pro-environmental behavior in tourists through digital media: the influence of eco-guilt and empathy with nature

In the digital economy era, leveraging digital media to foster tourists' pro-environmental behavioral intention (TPEBI) has become crucial in the field of sustainable tourism. While existing studies have mainly focused on the driving mechanism of TPEBI within physical tourism contexts, the correlation between digital media information sharing and TPEBI remains unclear. Our study employs the cognitive-affective-conative framework to construct a theoretical model, considering eco-guilt and empathy with nature as mediating variables. It aims to explore the influencing mechanism of destination environmental information sharing through digital media on TPEBI from a presence perspective. Thereby, two scenario experiments were designed: Study 1 examined the impact of different formats of destination environmental threat information presentation on digital media on the sense of presence, while Study 2 explored the influencing mechanism of presence on TPEBI based on the conclusions of Study 1. Results indicate that (1) vivid and visible presentation formats of destination environmental threat information on digital media enhance individuals' sense of presence; (2) sense of presence positively influences TPEBI; and (3) eco-guilt and empathy with nature mediate between presence and TPEBI. These findings not only contribute to theoretical and empirical research on digital media information sharing in sustainable tourism but also offer guidance for governments and tourism destinations to effectively stimulate TPEBI through digital media, achieve the sustainable development of destinations.

The digital transformation in pharmacy: embracing online platforms and the cosmeceutical paradigm shift

In the face of rapid technological advancement, the pharmacy sector is undergoing a significant digital transformation. This review explores the transformative impact of digitalization in the global pharmacy sector. We illustrated how advancements in technologies like artificial intelligence, blockchain, and online platforms are reshaping pharmacy services and education. The paper provides a comprehensive overview of the growth of online pharmacy platforms and the pivotal role of telepharmacy and telehealth during the COVID-19 pandemic. Additionally, it discusses the burgeoning cosmeceutical market within online pharmacies, the regulatory challenges faced globally, and the private sector's influence on healthcare technology. Conclusively, the paper highlights future trends and technological innovations, underscoring the dynamic evolution of the pharmacy landscape in response to digital transformation.

Required data elements for interprofessional rounds through the lens of multiple professions

The lack of a proper system for ongoing open interprofessional communication among care providers increases miscommunications and medical errors. Seamless access to patient information is important for care providers to prevent miscommunication and improve patient safety. A shared understanding of the information needs of different care providers in an interprofessional team is lacking. Our purpose is to identify care providers' information needs from the perspective of different professions for communication, shared understanding about the patient, and decision-making. We conducted semi-structured interviews with 10 subject matter experts representing eight professions, including dentistry, dietetics, medicine, nursing, occupational therapy, pharmacy, physical therapy, and social work in a 465-bed academic hospital at a large urban Midwestern city. We used an in-house rounding tool presenting physicians' information needs and a hypothetical patient scenario to collect participants' feedback. Interview notes were coded using direct content analysis. We identified 22 additional essential data elements for an interprofessional rounding tool. We categorized those into six domains: discharge-related, social determinants of health, hospital safety, nutrition, interprofessional situation awareness, and patient history. A well-designed validated rounding tool that includes an interprofessional team of care providers' information needs could improve communication, care planning, and decision-making among them.

SALUS-A Study on Self-Tonometry for Glaucoma Patients: Design and Implementation of the Electronic Case File

BACKGROUND

 In times of omnipresent digitization and big data, telemedicine and electronic case files (ECFs) are gaining ground for networking between players in the health care sector. In the context of the SALUS study, this approach is applied in practice in the form of electronic platforms to display and process disease-relevant data of glaucoma patients.

OBJECTIVES

 The SALUS ECF is designed and implemented to support data acquisition and presentation, monitoring, and outcome control for patients suffering from glaucoma in a clinical setting. Its main aim is to provide a means for out- and inpatient exchange of information between various stakeholders with an intuitive user interface in ophthalmologic care. Instrument data, anamnestic data, and diagnostic assessments need to be accessible and historic data stored for patient monitoring. Quality control of the data is ensured by a reading center.

METHODS

 Based on an intensive requirement analysis, we implemented the ECF as a web-based application in React with a Datomic back-end exposing REST and GraphQL APIs for data access and import. A flexible role management was developed, which addresses the various tasks of multiple stakeholders in the SALUS study. Data security is ensured by a comprehensive encryption concept. We evaluated the usability and efficiency of the ECF by measuring the durations medical doctors need to enter and work with the data.

RESULTS

 The evaluation showed that the ECF is time-saving in comparison to paper-based assessments and offers supportive monitoring and outcome control for numerical and imaging-related data. By allowing patients and physicians to access the digital ECF, data connectivity as well as patient autonomy were enhanced.

CONCLUSION

 ECFs have a great potential to efficiently support all patients and stakeholders involved in the care of glaucoma patients. They benefit from the efficient management and view of the data tailored to their specific role.

Users' unverified information-sharing behavior on social media: The role of reasoned and social reactive pathways

Unverified or false information spread by irresponsible users can amplify the dissemination of fake news or misinformation. This phenomenon may not only undermine the credibility of social media platforms but also pose severe consequences for individuals and society. This study applies and extends the prototypical willingness model with the aim of comprehending the reasons, and decision-making process driving users' unverified information-sharing behavior a reasoned and intended pathway or an impulsive and unconscious one. Data from a sample of 646 users were analyzed using Structural Equation Modeling to assess the determinative effect of both the reasoned pathway (attitude toward unverified information-sharing, subjective norm, and perceived behavioral control) and the social-reaction pathway (prototype favorability and similarity). Findings highlight the substantial role of the social-reaction pathway in forecasting users' unverified information-sharing behavior, with prototype similarity and attitude being the dominant predictors. Meanwhile, components of the reasoned pathway, specifically perceived behavior control, and attitude, also exhibited significant contributions toward predicting the behavior. In summary, while a deliberate, reasoned process has some influence, the sharing of unverified information on social media by users is primarily an intuitive, spontaneous response to specific online circumstances. This study therefore offers valuable insights that could aid relevant stakeholders in effectively regulating the spread of misinformation. Against this backdrop, highlighting potential risks associated with sharing unverified information and the negative portrayal of users propagating misinformation may contribute to the development of a more critical perspective toward online information sharing by users themselves.

Meaning, trust, and belonging: Exploring the factors that foster elite forced migrant athletes' growth

BACKGROUND AND PURPOSE

Researchers have highlighted elite refugee athletes' acculturation and sport-related challenges upon transitioning into host country sports systems. Using a strength-based approach, we aimed to broaden this view through exploring the internal and external factors that have fostered refugee athletes' abilities to find meaning and growth following their transitions into a national sports system.

METHODOLOGY

Data collection began with an arts-based drawing activity which was then discussed in a conversational interview. Fourteen (n = 11 male, 3 female) national and international refugee athletes participated. The interviews were analyzed using a reflexive thematic analysis, a form of qualitative analysis used to derive commonalities that connect athletes' experiences. The data is represented through polyphonic vignettes (narrative featuring multiple perspectives) to safeguard athletes' anonymity whilst showcasing varying perspectives.

RESULTS

Athletes were at various phases of growth at the time of the interviews. The primary internal factor that facilitated growth was responsibility to find and pursue meaning. External factors of trust and belonging, actualized through supporting elite athletes' personal differences, were external factors that fostered their abilities to find meaning.

CONCLUSION

Elite refugee athletes' growth occurred at the nexus of individual responsibility, trusting relationships, and inclusive sport environments. The findings inform individual and environmental growth-based interventions for current and future elite athletes who face varying adversities within their sports contexts.

Interruption Value Type and Source Matter in Different Phases of an Interruption Process: Emotional/Cognitive Impact and Neural Evidence

OBJECTIVE

To examine the effect of interruption value type (utilitarian, hedonic) and source (external, internal) in different phases of an interruption process.

BACKGROUND

Prior studies on interruption mostly focused on the cognitive outcomes of utilitarian interruptions. Hedonic interruptions are common in life; however, they are not sufficiently explored through research. Hedonic value is closely associated with emotional experiences, and, in turn, influences behaviors. Moreover, the way the effect of values is moderated by interruptions initiated by intrinsic motives is worth exploring.

METHOD

A 2 × 2 mixed design experiment was conducted with 48 participants who were asked to respond to instant messages during the writing task. The interruption value was induced by work or non-work tasks. The interruption source was manipulated by providing an alert. Functional near-infrared spectroscopy, behavioral data, and subjective measurements were collected and analyzed.

RESULTS

Hedonic interruptions increased emotional valence, while utilitarian interruptions decreased it. These effects were strengthened by internal interruptions. The effect of interruption value type on work exhaustion was also moderated by the source. Interruption value type and source influenced the attention allocation before an interruption occurred. Hedonic interruptions led to longer resumption lags, whereas utilitarian interruptions required longer interruption durations. Internal interruptions led to improved performance in the resumed task.

CONCLUSION

Interruption source modulate the effect of interruption value type, especially on emotional experience and attention allocation before an interruption occurs.

APPLICATION

Self-initiated hedonic interruptions have emotional benefits, while alerts for utilitarian interruptions will improve attention on the main task before interruptions.

Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy

Circulating hybrid cells (CHCs) are a newly discovered, tumor-derived cell population found in the peripheral blood of cancer patients and are thought to contribute to tumor metastasis. However, identifying CHCs by immunofluorescence (IF) imaging of patient peripheral blood mononuclear cells (PBMCs) is a time-consuming and subjective process that currently relies on manual annotation by laboratory technicians. Additionally, while IF is relatively easy to apply to tissue sections, its application to PBMC smears presents challenges due to the presence of biological and technical artifacts. To address these challenges, we present a robust image analysis pipeline to automate the detection and analysis of CHCs in IF images. The pipeline incorporates quality control to optimize specimen preparation protocols and remove unwanted artifacts, leverages a β-variational autoencoder (VAE) to learn meaningful latent representations of single-cell images, and employs a support vector machine (SVM) classifier to achieve human-level CHC detection. We created a rigorously labeled IF CHC data set including nine patients and two disease sites with the assistance of 10 annotators to evaluate the pipeline. We examined annotator variation and bias in CHC detection and provided guidelines to optimize the accuracy of CHC annotation. We found that all annotators agreed on CHC identification for only 65% of the cells in the data set and had a tendency to underestimate CHC counts for regions of interest (ROIs) containing relatively large amounts of cells (>50,000) when using the conventional enumeration method. On the other hand, our proposed approach is unbiased to ROI size. The SVM classifier trained on the β-VAE embeddings achieved an F1 score of 0.80, matching the average performance of human annotators. Our pipeline enables researchers to explore the role of CHCs in cancer progression and assess their potential as a clinical biomarker for metastasis. Further, we demonstrate that the pipeline can identify discrete cellular phenotypes among PBMCs, highlighting its utility beyond CHCs.

Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations

Healthcare organizations have realized that Artificial intelligence (AI) can provide a competitive edge through personalized patient experiences, improved patient outcomes, early diagnosis, augmented clinician capabilities, enhanced operational efficiencies, or improved medical service accessibility. However, deploying AI-driven tools in the healthcare ecosystem could be challenging. This paper categorizes AI applications in healthcare and comprehensively examines the challenges associated with deploying AI in medical practices at scale. As AI continues to make strides in healthcare, its integration presents various challenges, including production timelines, trust generation, privacy concerns, algorithmic biases, and data scarcity. The paper highlights that flawed business models and wrong workflows in healthcare practices cannot be rectified merely by deploying AI-driven tools. Healthcare organizations should re-evaluate root problems such as misaligned financial incentives (e.g., fee-for-service models), dysfunctional medical workflows (e.g., high rates of patient readmissions), poor care coordination between different providers, fragmented electronic health records systems, and inadequate patient education and engagement models in tandem with AI adoption. This study also explores the need for a cultural shift in viewing AI not as a threat but as an enabler that can enhance healthcare delivery and create new employment opportunities while emphasizing the importance of addressing underlying operational issues. The necessity of investments beyond finance is discussed, emphasizing the importance of human capital, continuous learning, and a supportive environment for AI integration. The paper also highlights the crucial role of clear regulations in building trust, ensuring safety, and guiding the ethical use of AI, calling for coherent frameworks addressing transparency, model accuracy, data quality control, liability, and ethics. Furthermore, this paper underscores the importance of advancing AI literacy within academia to prepare future healthcare professionals for an AI-driven landscape. Through careful navigation and proactive measures addressing these challenges, the healthcare community can harness AI's transformative power responsibly and effectively, revolutionizing healthcare delivery and patient care. The paper concludes with a vision and strategic suggestions for the future of healthcare with AI, emphasizing thoughtful, responsible, and innovative engagement as the pathway to realizing its full potential to unlock immense benefits for healthcare organizations, physicians, nurses, and patients while proactively mitigating risks.

Evolving Adult ADHD Care: Preparatory Evaluation of a Prototype Digital Service Model Innovation for ADHD Care

BACKGROUND

Given the prevalence of ADHD and the gaps in ADHD care in Australia, this study investigates the critical barriers and driving forces for innovation. It does so by conducting a preparatory evaluation of an ADHD prototype digital service innovation designed to help streamline ADHD care and empower individual self-management.

METHODS

Semi-structured interviews with ADHD care consumers/participants and practitioners explored their experiences and provided feedback on a mobile self-monitoring app and related service innovations. Interview transcripts were double coded to explore thematic barriers and the enablers for better ADHD care.

RESULTS

Fifteen interviews (9 consumers, 6 practitioners) revealed barriers to better ADHD care for consumers (ignorance and prejudice, trust, impatience) and for practitioners (complexity, sustainability). Enablers for consumers included validation/empowerment, privacy, and security frameworks, tailoring, and access. Practitioners highlighted the value of transparency, privacy and security frameworks, streamlined content, connected care between services, and the tailoring of broader metrics.

CONCLUSIONS

A consumer-centred approach to digital health service innovation, featuring streamlined, private, and secure solutions with enhanced mobile tools proves instrumental in bridging gaps in ADHD care in Australia. These innovations should help to address the gaps in ADHD care in Australia. These innovations should encompass integrated care, targeted treatment outcome data, and additional lifestyle support, whilst recognising the tensions between customised functionalities and streamlined displays.

The multi-dimensional impact of different sources of information on influenza vaccination of college students in China

Objective: To explore whether/how the willingness of Chinese college students to receive the influenza vaccines in the sample is affected by different information channels. Participants: Two hundred and four volunteers were recruited to participate in an anonymous online survey. All participants were college students, mainly undergraduates (81.86%), with a higher proportion of women (56.86%). Methods: Participants answered anonymous questionnaires through the website, including demographic data (age, gender, education, etc.), media exposure channels and frequency, views and attitudes toward influenza vaccines, etc. An ordered logistic regression analysis was conducted to explore the effects of different information sources on influenza vaccination among college students. Results: Exposure to traditional media, digital media, and interpersonal communication promotes college students' understanding of influenza vaccines. Exposure to digital media alleviates college students' hesitation to vaccinate, while interpersonal interaction and digital media exposure promote college students' willingness to vaccinate. Conclusions: Digital media is increasingly important in the lives of Chinese college students to promote healthy behaviors such as influenza vaccinations.

Digital technology integration in business model innovation for carbon neutrality: An evolutionary process model for SMEs

This study delves into the strategies employed by small and medium-sized enterprises (SMEs) to embed digital technology into their business models, aiming to reach carbon neutrality. We offer a comprehensive analysis of five high technology SMEs, unveiling an evolutionary process model that highlights their journey toward integrating technology. The integration process is delineated into three progressive stages. Initially, digital technology is seen as an 'enabler' that promotes the birth of an innovative business model, essentially transforming the mechanisms of value creation, delivery, and capture. As SMEs evolve to an intermediate stage, digital technology becomes a 'disruptor', reshaping and reinventing the business model in terms of how value is created, delivered, and captured. Entering the maturity stage, digital technology is elevated to the role of 'expertise', leading to a sophisticated business model that refines and optimizes these aspects of value. The influence of these business model innovations on carbon neutrality is complex and varies distinctly with each stage, reflecting the dynamic interplay between digital technology and business model evolution.

Assessing Patients Perception: Analyzing the Quality, Reliability, Comprehensibility, and the Mentioned Medical Concepts of Traumatic Brain Injury Videos on YouTube

OBJECTIVE

The aim of this study is to analyze the quality, reliability, comprehensibility, and the mentioned medical concepts of traumatic brain injury (TBI) related videos on YouTube.

METHODS

"Traumatic brain injury (TBI)" and Google Trends related queries were used, and 328 videos were included. Categorization, quality assessment via a 5-point Global Quality Scale, reliability evaluation using a modified DISCERN scale, comprehensibility assessment using Flesch-Kincaid Reading Ease and Flesch-Kincaid Grade Level, and consensus-based classification for usefulness were performed. Target audience categorization was content-based. Text mining techniques were used to identify biomedical terms in video transcripts.

RESULTS

Most of the videos were intended for nonhealthcare professionals and deemed useful. The videos had intermediate quality and a moderate level of reliability. The comprehensibility of the videos exceeded the recommended levels. Videos predominantly covered TBI symptoms, the severity of the condition, its impact on individuals, and possibly strategies related to diagnosis and treatment.

CONCLUSIONS

Results suggest the requirement for higher quality and reliability in YouTube content about TBI. Emphasis should be placed on clear and accurate language to promote comprehensibility. Continued research, guidelines, education, and platform oversight can enhance the spread of reliable health information on social media, benefiting creators, and consumers in this field.

Body size shapes song in honeyeaters

Birdsongs are among the most distinctive animal signals. Their evolution is thought to be shaped simultaneously by habitat structure and by the constraints of morphology. Habitat structure affects song transmission and detectability, thus influencing song (the acoustic adaptation hypothesis), while body size and beak size and shape necessarily constrain song characteristics (the morphological constraint hypothesis). Yet, support for the acoustic adaptation and morphological constraint hypotheses remains equivocal, and their simultaneous examination is infrequent. Using a phenotypically diverse Australasian bird clade, the honeyeaters (Aves: Meliphagidae), we compile a dataset consisting of song, environmental, and morphological variables for 163 species and jointly examine predictions of these two hypotheses. Overall, we find that body size constrains song frequency and pace in honeyeaters. Although habitat type and environmental temperature influence aspects of song, that influence is indirect, likely via effects of environmental variation on body size, with some evidence that elevation constrains the evolution of song peak frequency. Our results demonstrate that morphology has an overwhelming influence on birdsong, in support of the morphological constraint hypothesis, with the environment playing a secondary role generally via body size rather than habitat structure. These results suggest that changing body size (a consequence of both global effects such as climate change and local effects such as habitat transformation) will substantially influence the nature of birdsong.

A face of one's own: The role of an online personae in a digital age and the right to control one's own online personae in the presence of digital hacking

In the post-Covid world, our online personae have become increasingly essential mechanisms for presenting ourselves to the world. Simultaneously, new techniques for hacking online personae have become more widely available, easier to use, and more convincing. This combination, of greater reliance on online personae and easier malicious hacking, has created serious societal problems. Techniques for training users to detect false content have proved ineffective. Unfortunately, legal remedies for dealing with hacked personae have also been inadequate. Consequently, the only remaining alternative is to limit the posting of false content. In this discussion paper, we provide an overview of online personae hacking. As potential remedies, we propose to redesign search engine and social media algorithms allowing platforms to detect and restrict harmful false content and a new fundamental right for the EU Charter that would provide legal justification for platforms to protect online reputations. For those platforms that might choose not to protect online reputations, this new right would require that they do so.

Digital transformation as the driving force for sustainable business performance: A moderated mediation model of market-driven business model innovation and digital leadership capabilities

Global organizations are still facing challenges in achieving sustainable performance despite the surge in digital technologies. It is imperative that firms invest in digital capabilities to secure sustainable market performance in the face of a barrage of novel inventions. Today, ensuring a resilient future demands business to focus on digital ambidexterity capabilities (i.e., exploitation and exploration), digitalized strategy adoption, and digital transformation. This study investigates the intricate dynamics between digital capabilities and digitalization strategies and their impact on sustainable business performance. The research employed a questionnaire-driven methodology to gather data from managerial personnel within industries. Results show that digital exploitation and exploration capabilities significantly enhance sustainable business performance. The research also establishes the beneficial effect of adopting a digitalization strategy on business performance and innovation. Market-driven business model innovation emerges as a critical factor, not only driving sustainable performance but also serving as a mediating link between various digital strategies and business success. Moreover, the study highlights the importance of digital leadership capabilities, further strengthening the relationship between innovative business models and sustainable performance. The findings underscore the synergistic effect of digital competencies and strategic digitalization in promoting sustainable and innovative practices in today's digital-driven business landscape.