How article category in Wikipedia determines the heterogeneity of its editors

Collaboration is essential to advancing knowledge and, ultimately, entire societies. With the development of Web 2.0, the possibilities have risen to unprecedented levels and allowed for the collaborative creation of the world's largest compendium of knowledge that ever existed - Wikipedia. Collaboration is not a safeguard of quality per se, however. Rather, the quality of Wikipedia articles rises with the number of editors per article as well as a greater diversity among them. Here, we address a not yet documented potential threat to those preconditions: self-selection of Wikipedia editors to articles. Specifically, we expected articles with a clear-cut link to a specific country (e.g., about its highest mountain, "national" article category) to attract a larger proportion of editors of that nationality when compared to articles without any specific link to that country (e.g., "gravity", "universal" article category), whereas articles with a link to several countries (e.g., "United Nations", "international" article category) should fall in between. Across several language versions, hundreds of different articles, and hundreds of thousands of editors, we find the expected effect within Wikipedia: The more exclusively an article topic is linked to a particular nation, the higher the proportion of editors from that country is among the contributors.

The willingness and influencing factors to choose institutional elder care among rural elderly: an empirical analysis based on the survey data of Shandong Province

BACKGROUND

The ageing of the population has become an escalating problem in China, which has led to an increasing demand for healthcare throughout society. The care services of elderly institutions, as a more mature way of aging, can alleviate various social problems brought about by ageing to a certain extent. The aim of this paper is to explore the degree of acceptance of institutional care by rural elderly people in Shandong Province and the factors that influence whether rural elderly people accept institutional care services.

METHODOLOGY

Based on the theory of planned behavior, an analytical framework was constructed for the willingness of rural elderly people to receive nursing services from elderly care institutions. Using survey data from 192 rural elderly people in Shandong Province, descriptive statistics, binary logistic regression, and horizontal comparative analysis methods were used to analyze the willingness of rural elderly people to provide for the elderly and its influencing factors.

RESULT

Only 17.71% of respondents expressed willingness to receive services from elderly care institutions. Among them, education level, trust in elderly care institutions, and support from adult children have a significant positive impact on whether rural elderly people receive nursing services from elderly care institutions; The number of children, the level of understanding of elderly care institutions, neighbors' choices of elderly care methods, and their ability to contribute to the family have a significant negative impact on whether rural elderly people receive nursing services from elderly care institutions. There are significant differences in the willingness and influencing factors of rural elderly people to provide for the elderly among different regions.

CONCLUSION

The non-acceptance of institutional care by rural older people is a general phenomenon rather than a sample characteristic, thus justifying the supplementary status of institutional care services. The pension intention of the rural elderly in Shandong Province is obviously affected by personal will factors, and the influencing factors are various. The traditional concept of old-age care in Shandong province has a strong path-dependent effect on the choice of the rural elderly. There is heterogeneity in the willingness and influencing factors of the rural elderly in different regions and countries. Based on this, this paper puts forward the following suggestions: strengthen the spiritual and cultural construction of residents; The government should pay attention to the correct guidance of public opinion; And increase pension subsidies. It is hoped that reduce the burden of national elderly care through these suggestions.

The acceptance and attitudes towards using assistive technology for people with stroke in Jordan: caregivers' perspectives

The aim of this study is to evaluate the acceptance and attitudes toward assistive technology (AT) for people with stroke from their caregivers' perspectives in Jordan. Also, this study further validates the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire. This is a cross-sectional study that includes a three-sections survey: the first section contains demographic data, the second section includes the Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire, and the third section consists of two optional open-ended questions. Among 123 caregivers of people with stroke over 18 years of age who participated in this study, 23% were male. The findings indicate a moderate to high acceptance of using AT for stroke survivors, confirm the validity and reliability of the UTAUT questionnaire, and clarify novel issues regarding AT based on the caregivers' perspectives.

Academics' continuance intention to use learning technologies during COVID-19 and beyond

The COVID-19 pandemic has revolutionized the teaching pedagogy in higher education as universities are forecasted to increase investments in learning technology infrastructure to transition away from traditional teaching methods. Therefore, it is crucial to investigate whether academics intend to continually integrate learning technologies as part of a permanent pedagogical change beyond the COVID-19 pandemic. Drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT), and Expectation Confirmation Model (ECM), this study examines the salient determinants influencing the continuance intention of academics to use learning technologies in their teaching pedagogy during and after COVID-19. Primary data collected from a private university was analyzed using the partial least squares structural equation modelling technique (PLS-SEM). The findings revealed two sequential mediating relationships which serve as the mechanism linking the relationship between facilitating conditions and their continuance intention to use learning technologies during and beyond the COVID-19 pandemic.

Sorting Insiders From Co-Workers: Remote Synchronous Computer-Mediated Triage for Investigating Insider Attacks

OBJECTIVE

Develop and investigate the potential of a remote, computer-mediated and synchronous text-based triage, which we refer to as InSort, for quickly highlighting persons of interest after an insider attack.

BACKGROUND

Insiders maliciously exploit legitimate access to impair the confidentiality and integrity of organizations. The globalisation of organisations and advancement of information technology means employees are often dispersed across national and international sites, working around the clock, often remotely. Hence, investigating insider attacks is challenging. However, the cognitive demands associated with masking insider activity offer opportunities. Drawing on cognitive approaches to deception and understanding of deception-conveying features in textual responses, we developed InSort, a remote computer-mediated triage.

METHOD

During a 6-hour immersive simulation, participants worked in teams, examining password protected, security sensitive databases and exchanging information during an organized crime investigation. Twenty-five percent were covertly incentivized to act as an 'insider' by providing information to a provocateur.

RESULTS

Responses to InSort questioning revealed insiders took longer to answer investigation relevant questions, provided impoverished responses, and their answers were less consistent with known evidence about their behaviours than co-workers.

CONCLUSION

Findings demonstrate InSort has potential to expedite information gathering and investigative processes following an insider attack.

APPLICATION

InSort is appropriate for application by non-specialist investigators and can be quickly altered as a function of both environment and event. InSort offers a clearly defined, well specified, approach for use across insider incidents, and highlights the potential of technology for supporting complex time critical investigations.

Empirical Evidence of Internal and External Factors Influencing Users' Motivation Toward Teleconsultation Use

Introduction: The use of teleconsultation systems has increased in recent years, which has improved patients' access to health care providers and enabled seamless interaction between them. The literature points out several factors that either facilitate or impede the use of teleconsultation. However, there is a lack of studies that provide empirical evidence of factors that influence consumers' motivation toward the use of teleconsultation systems. Aim and Objective: This study aimed to provide empirical evidence of the internal and external factors that influence consumers' motivation toward the use of teleconsultation systems. Methods: A cross-sectional survey was used to collect data from consumers who used a real-time teleconsultation system called the Sehha application in Saudi Arabia between March 13 and June 14, 2021. SPSS 27.0.1 was used for descriptive analysis. Results: Four hundred eighty-five participants completed the survey, 471 of whom were included in the analysis. The findings confirmed that internal and external factors exert an influence on consumers' motivation toward the use of teleconsultation systems. The findings indicated that the presence of factors such as saving time, saving cost, accessibility to health care, ease-of-use, reliable internet access, availability of devices, and appropriate places during the online connection would increase consumers' motivation toward teleconsultation systems use. Also, the findings indicated that users' familiarity with systems similar to teleconsultation systems, users' perception of teleconsultation convenience, the influence of others on users' decision to use teleconsultation, and user's skills and confidence in using teleconsultation easily, and their trust in the teleconsultation system would also increase their motivation to use it. Furthermore, the findings showed that demographic factors, including age, gender, level of education, and employment status, did not influence users' motivation toward the use of teleconsultation Conclusions: This study provided empirical evidence of a variety of internal and external factors that exert an influence on consumers' motivation toward the use of teleconsultation systems.

Exploring nationwide policy interventions to control COVID-19 from the perspective of the rapid learning health system approach

Introduction

The health systems needed to improve their learning capacities during the COVID-19 pandemic. Iran is one of the countries massively struck by the pandemic. This study aimed to explore whether and how the policy interventions made by Iran's policymakers at the national level to control COVID-19, could improve the rapid learning characteristics of the health system.

Methods

A guide to clarify rapid learning health system (RLHS) characteristics was developed. The guide was used by two independent authors to select the policy interventions that could improve RLHS characteristics, then, to analyze the content of the selected policy interventions. In each stage, results were compared and discussed by all three authors. Final results were presented based on different RLHS characteristics and the potential mechanisms of contribution.

Results

Five hundred policy interventions were developed during the first 7 months of the outbreak. Thirty-one policy interventions could potentially improve RLHS characteristics (6.2%). Two characteristics, such as the timely production of research evidence and the appropriate decision support were addressed by selected policy interventions. Policies, that could improve learning capacities, focused on decision-maker groups more than user groups or researcher groups.

Conclusions

Most of the developed policy interventions during the first months of the epidemic did not address the learning capacities of the health system. To improve health system functions, improving RLHS characteristics of the health system, especially in patient-centered and data linkage characteristics, is recommended.

Examining information systems use to facilitate the workplace accommodation process

BACKGROUND

The workplace accommodation process is often affected by ineffective and inefficient communications and information exchanges among disabled employees and other stakeholders. Information systems (IS) can play a key role in facilitating a more effective and efficient accommodation process since IS has been shown to facilitate business processes and effect positive organizational changes.

OBJECTIVE

Since there is little to no research that exists on IS use to facilitate the workplace accommodation process, this paper, as a critical first step, examines how IS have been used in the accommodation process.

METHODS

Thirty-six interviews were conducted with disabled employees from various organizations. Open, axial, and selective coding were part of the analysis. Fuzzy set qualitative comparative analysis was used to identify different levels of IS use based on participants' descriptions.

RESULTS

An IS used in the workplace accommodation process consists of electronic request form, accommodation checklist, special budget, specific role, ancillary service, formal policy and procedure. There are different levels of IS use in the current accommodation process. The high-level IS use often results in a better accommodation performance than the low-level IS use, including high efficiency, high effectiveness, and low emotional tolls. Nevertheless, the high-level IS use often uses a specific, inflexible template as well as disregards human elements in the accommodation process.

CONCLUSION

This work provides implications that future IS design should raise awareness of disability and accommodation, account for individual differences, involve multiple stakeholder inputs, as well as address the fundamental social issues in the accommodation process.

Association between digital engagement and urban-rural disparities in Chinese women's depressive symptoms: A national-level cross-sectional study

Objectives

This study aims to investigate the impact of digital engagement on urban-rural disparities in depressive symptoms among Chinese women.

Methods

Using a dataset from the China Family Panel Studies (CFPS) wave 2020, this study analyzes the impact of digital engagement on the urban-rural disparity in women's depressive symptoms using multiple linear regression and recentered influence function (RIF) models. Furthermore, the extent to which digital engagement affects the urban-rural disparity in women's depressive symptoms was calculated using the RIF decomposition method.

Results

Analysis showed that rural women had significantly higher levels of depressive symptoms compared to urban women; digital engagement significantly reduced women's depressive symptoms levels and mitigated the urban-rural disparity for women with moderate to high levels of depressive symptoms, and the mitigating effect was stronger for the highly depressed sample, but still widened the urban-rural disparity in women's depressive symptoms overall. In addition, the results of the RIF decomposition showed that digital engagement explained 28.28% of the urban-rural disparity in women's depressive symptoms.

Conclusion

There is a significant disparity in depressive symptoms levels between urban and rural women in China. Digital engagement reduces women's depressive symptoms, but it also widens the depressive symptoms disparity between urban and rural women overall. Digital engagement is potentially positive for reducing women's depressive symptoms.

Psychometric properties of the Chinese version of the Need for Privacy Scale

Introduction

The need for privacy is a high-order psychological need of human, which is closely related to human mental health problems in the digital age. The Need for Privacy Scale (NFP-S) is a reliable measure of need for privacy. This study tested its psychometric characteristics among Chinese populations.

Methods

Firstly, we modified and translated the NFP-S into Chinese version (NFP-SC). Subsequently, we invited 15 participants to complete pre testing of the NFP-SC and determined the final version. Next, we collected questionnaire data from 1130 participants for confirmatory factor analysis to confirm factor structure and validate convergent validity.

Results

The results showed that the bifactor Exploratory Structural Equation Modeling (bifactor-ESEM) could better reflect the potential structure of NFP-SC, which included one general factor of need for privacy and three specific factors which were the informational need for privacy, the psychological need for privacy, and the physical need for privacy. Based on the bifactor-ESEM model, the measurement invariance of NFP-SC was demonstrated across gender groups. The general factor and specific factor of NFP-SC showed good reliability with high McDonald's coefficient omega. Convergent validity was tested by verifying the relationship between NFP-SC and four covariates.

Conclusions

Our study results showed that NFP-SC exhibited satisfactory psychometric properties in the Chinese context, meaning that it could be applied for future studies on investigating need for privacy in Chinese populations. Future research could build panel data by gathering data from different periods, and supplement the test-retest reliability of NFP-S to improve its application effect.

The influence of digital literacy on mHealth app usability: The mediating role of patient expertise

Objective

Mobile health (mHealth) applications are emerging as important healthcare technologies that can provide cost savings, better access to care, contribute to improved clinical outcomes, and support public health. An increasing number of mobile health (mHealth) applications are becoming available to download and use on mobile devices. However, unlocking this potential requires ensuring widespread acceptance and adoption of these applications. In this context, the aim of the study is to determine the impact of individuals' digital literacy levels on mobile health application usability and the mediating role of patient expertise in this impact.

Methods

The population of our study consists of individuals who reside in Yozgat city center and are 18 years old and over. Within the scope of the study, 647 individuals who agreed to participate in the research were reached. A survey form consisting of four sections (Socio-demographic characteristics, Digital Literacy Scale, mHealth App Usability Questionnaire, and Patient Expertise Scale) was used as a data collection tool in the study. Descriptive statistical methods were used to analyze the data and partial least squares path analysis (PLS-SEM) was used to analyze the research model.

Results

Digital literacy affects both patient expertise (β = 0.790, t = 35.560, p = 0.000) and mHealth app usability (β = 0.831, t = 46.020, p = 0.000). Additionally, it has been determined that patient expertise has a mediating role in the effect of digital literacy on mHealth app usability (β = 0.536, t = 17.477, p = 0.000).

Conclusions

It appears that individuals' digital literacy is an important precursor to the usability of mHealth apps and increases their usage experience. In this sense, it is thought that the concept of digital literacy can be used to increase the usability of mHealth apps for individuals. Overall, the findings provide new evidence for the healthcare context by integrating user diversity, particularly individuals' digital literacy, mHealth apps, and prior experience with mHealth.

Strategy development to increase consumer intention of purchasing prescription drugs through e-pharmacy in Indonesia

BACKGROUND

The global COVID-19 pandemic has forced people to obtain health products and services from home. Similar to other e-commerce, medicines are bought online and delivered using a courier service.

OBJECTIVE

By being fully concerned to patient safety, this study aims to determine development strategies to increase intention in purchasing prescription drugs through e-pharmacy.

METHODS

Two stages of measurement are employed in this study, namely confirmatory factor analyis using PLS-SEM and pairwise comparison using AHP method. To discover consumer perception in using e-pharmacy, the basic model of Theory of Planned Behavior (TPB) is employed with several extensions.

RESULTS

The results of PLS-SEM express that Trust has a major role as an intervening variable to enhance the indirect effect of Subjective Norms and Perceived Values on Purchase Intention. In general, PLS-SEM structural model is declared "fit" (GFI = 0.93 ≥ 0.90; RMSEA = 0.045 ≤ 0.08; SRMR = 0.033 ≤ 0.05). Measurement model test proves that all selected indicators are valid to represent their related constructs (Loading Factor ≥ 0.50), and all selected constructs are reliable to build the whole path model (CR ≥ 0.7; AVE ≥ 05). Meanwhile, the results of AHP indicate that strengthening government policies and regulations is prioritized to increase consumer intention of purchasing prescription drugs through e-pharmacy, followed by protection of user confidential data in the second place. Those two eigenvectors are 0.236 and 0.185 respectively.

CONCLUSION

Future research is suggested to add perceived risk as latent variable in the study of consumer behavior for any high-risk products.

Use of Social Media in Orthopaedic Surgery Training and Practice: A Systematic Review

Background

Social media use has grown across healthcare delivery and practice, with dramatic changes occurring in response to the coronavirus (COVID-19) pandemic. The purpose of this study was to conduct a comprehensive systematic review to determine the current landscape of social media use by (1) orthopaedic surgery residencies/fellowship training programs and (2) individual orthopaedic surgeons and the change in use over time.

Methods

We searched 3 electronic databases (PubMed, MEDLINE, and Embase) from their inception to April 2022 for all studies that analyzed the use of social media in orthopaedic surgery. Two reviewers independently determined study eligibility, rated study quality, and extracted data. Methodology was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Results

Twenty-eight studies were included, of which 11 analyzed social media use by orthopaedic surgery residency and fellowship training programs and 17 examined its use by individual orthopaedic surgeons. Among residency and fellowship programs, Instagram was identified as the most common platform used, with 42% to 88% of programs reporting program-specific Instagram accounts, followed by Twitter/X (20%-52%) and Facebook (10%-38%). Social media was most commonly used by programs for recruitment and information dissemination to prospective residency applicants (82% and 73% of included studies, respectively). After the start of the COVID-19 pandemic, there was a 620% and 177% increase in the number of training programs with Instagram and Twitter/X accounts, respectively. Individual use of social media ranged from 1.7% to 76% (Twitter/X), 10% to 73% (Facebook), 0% to 61% (Instagram), 22% to 61% (LinkedIn), and 6.5% to 56% (YouTube).

Conclusions

Instagram, Twitter/X, and Facebook are the premier platforms that patients, residency applicants, and institutions frequent. With the continued growth of social media use anticipated, it will be critical for institutions and individuals to create and abide by guidelines outlining respectful and professional integration of social media into practice.

Level of Evidence

Level IV.

Affordance trajectories and the usefulness of online records access among older adults in Sweden

Objective

The current understanding of the breadth of individual differences in how eHealth technologies are perceived as useful for different purposes is incomprehensive. The aim/purpose of the study is to improve the understanding of diverse perceptions of the usefulness of technologies by exploring older adults' use of their patient-accessible electronic health records (PAEHRs).

Methods

The study applies and extends Affordance Theory based on an empirical analysis of data from the NORDeHEALTH 2022 Patient Survey on attitudes toward PAEHR in Norway, Sweden, Finland, and Estonia. Responses from 3964 participants in Sweden, aged 65 + years were analysed. Data included demographics and agreement ratings to reasons for using PAEHR. To analyse variation in the reasons for using PAEHR, group comparisons were conducted based on gender (male/female), age group (65-74, 75-84 and 85+) and earlier encouragement to use PAEHR.

Results

Overall, the findings suggest that PAEHRs have multiple parallel affordance trajectories and affordance potencies that actualise differently depending on needs. The top reasons, pointing to both orientational and goal-oriented affordances for using PAEHR, were improving understanding of health issues, getting an overview of medical history/treatment and ensuring understanding of what the doctor said. Men reported more often sharing information with relatives or friends as a reason to access PAEHR. Women were more inclined, albeit similarly to men less frequently, to read their PAEHR for detecting errors. Age had little influence on reasons for using PAEHR.

Conclusions

The study applies and extends Affordance Theory in the context of older adults' PAEHR use based on findings from the largest national investigation of reasons for older users to access PAEHR in Sweden demonstrating the applicability of the theory in improving the understanding of the diversity of individual perceptions on eHealth technologies.

Do hospital data breaches affect health information technology investment?

Objectives

Data breaches are a financial and operational threat to hospitals. In this study, we examine the association between a data breach and information technology capital and labor investment.

Methods

In this retrospective cohort study, we used American Hospital Association data from 2017 to 2019 and an unbalanced panel of hospitals with 6751 unique hospital-year observations. The breached group had 482 hospital-years, and the control group had 6269 hospital-years. We estimated the association between data breaches, information technology capital, and labor investment using the average treatment effect with propensity-score matching.

Results

From 2017 to 2019, hospitals experienced more hacking and information technology incidents but fewer thefts and losses. We found that hospital data breaches were associated with a 66% increase in employed information technology staff and a 57% increase in outsourced information technology staff. Breaches were not associated with information technology operating expenses and information technology capital expenses.

Conclusion

Higher information technology labor investment due to the remediation of data breaches is an added cost to the healthcare system. Hospitals and policymakers should consider initiatives to improve cybersecurity and protect patient data.

Healthcare providers' use of dashboards with patient reported outcomes reinforces patients to fill out patient reported outcome measures

Background

Patient reported outcomes are used to assess the impact of medical interventions on perceived health in both clinical trials and daily care. Further, patient-reported outcome measures (PROMs) optimize the consultation. However, patient completion of PROMs before their consultation, and healthcare provider's (HCP) use of PROMs in their consultation are suboptimal. In this cross-sectional study, we examined whether viewing a PROM dashboard before or during consultation consecutively resulted in higher patient completion of PROMs.

Methods

As part of regular care, patients were asked to fill out PROMs prior their consultation. HCPs' dashboard views were logged. A chi-square test was performed on dashboard viewed (yes/no) with consecutively filling out PROMs (yes/no). The odds ratio (OR) of consecutively filling out PROMs after a dashboard view was calculated.

Results

38.016 consecutive appointments were linked to a previous appointment in which a dashboard could be viewed. In 2740 cases, a dashboard was viewed by the HCP, against 35.276 cases in which a dashboard was not viewed. Follow-up adherence in completing PROMs was 49%. The chi-square test showed statistical significance of p < .001. The OR of filling out a consecutive PROM when a dashboard was viewed was 3.16 (p < .001, 95% CI [2.9-3.5]).

Discussion

Patients are more likely to complete PROMs for their follow-up appointment when an HCP has viewed PROMs during or before consultation. HCPs should be aware of their responsibility in addressing PROMs, because using PROMs in consultation does not only have a positive effect on communication, but also on patient completion of PROMs.

Identification of required capabilities of digital health ecosystems when preventing and managing non-communicable diseases

Objective

Non-communicable diseases cause annual mortality for 41 million people worldwide. These diseases include coronary heart disease, cancer, stroke, diabetes, and musculoskeletal as well as mental disorders. Innovation ecosystems in healthcare are multifactor networks in which different stakeholders interact together to create socio-economic (patient and cost) value via research, co-creation, and traditional market activities. Although there is much evidence about the impact of digital health interventions and the capabilities needed to support individual actors and specific diseases in non-communicable disease prevention and management, the current understanding of the concept of innovation ecosystems associated with theories is not well understood. There is also a lack of research about innovation ecosystems in the healthcare context. Or understanding of the holistic perspective of the capabilities needed in innovation ecosystems to support future digital health. The objective of this study was to answer this research gap by identifying what capabilities are needed in future digital health ecosystems related to people with non-communicable diseases or at risk of non-communicable diseases. By doing this, the study will help different organisations and policies address this very challenging situation.

Methods

To answer this objective, a qualitative interview-based study including 34 semi-structured interviews was conducted in Finland. Complex adaptive systems theory was used as a theoretical lens to analyse empirical data.

Results and conclusion

Several new capabilities were identified for digital health innovation ecosystems to make organisation managers and policymakers aware of how to deal with future health system demands. From the organisational perspective, capabilities are needed to use non-medical and heterogeneous data to support better treatments and clinical decision-making and provide better and safer data access. From the management perspective, hospitals need capabilities to allow critical experts to participate in innovation work, and overall, all ecosystem actors need capabilities to orchestrate research and innovation actions in the area of digital health.

What engagement strategies are useful in facilitating the implementation of electronic health records in health care settings? A rapid review of qualitative evidence synthesis using the normalization process theory

Objective

The study aimed to identify and describe the engagement strategies used in implementing electronic health records in health care settings and to ascertain why they were successful or not, using normalization process theory.

Methods

In this rapid review, we searched PubMed and CINAHL for qualitative and mixed methods primary studies published from 2010 to 2023 (June). We identified 41 studies that explored the implementation of EHRs, involving clinicians as participants. For quality appraisal, we employed the standards for reporting qualitative research (SRQR) tool. For analysis, a qualitative comparative analysis, using the normalization process theory was conducted. This was followed by a narrative synthesis to compile and analyze key findings.

Results

About 56% (n = 23) of the studies were conducted in hospitals, while the remaining were done in mental health, maternity, and ambulatory care settings. Participants included a range of clinicians such as nurses, physicians, doctors, dentists, pediatricians and other specialists. Evidence shows that prior to implementation, effective communication of the vision of EHRs and early user involvement in decision-making are useful engagement strategies in preparing users for implementation. Tailored training and on-demand technical support for users sustain system usage during the roll out. Lastly, ongoing engagement with users is essential for continuous user support and system improvements.

Conclusion

User engagement improves the chances of successful implementation, particularly if engagement strategies are effective for the specific stages of implementation. The success of these strategies is more evident when they ensure normalization process theory tenets, which include user coherence, cognitive participation, collective action and reflective monitoring.

Review of the Factors Affecting Acceptance of AI-Infused Systems

OBJECTIVE

The study aimed to provide a comprehensive overview of the factors impacting technology adoption, to predict the acceptance of artificial intelligence (AI)-based technologies.

BACKGROUND

Although the acceptance of AI devices is usually defined by behavioural factors in theories of user acceptance, the effects of technical and human factors are often overlooked. However, research shows that user behaviour can vary depending on a system's technical characteristics and differences in users.

METHOD

A systematic review was conducted. A total of 85 peer-reviewed journal articles that met the inclusion criteria and provided information on the factors influencing the adoption of AI devices were selected for the analysis.

RESULTS

Research on the adoption of AI devices shows that users' attitudes, trust and perceptions about the technology can be improved by increasing transparency, compatibility, and reliability, and simplifying tasks. Moreover, technological factors are also important for reducing issues related to human factors (e.g. distrust, scepticism, inexperience) and supporting users with lower intention to use and lower trust in AI-infused systems.

CONCLUSION

As prior research has confirmed the interrelationship among factors with and without behaviour theories, this review suggests extending the technology acceptance model that integrates the factors studied in this review to define the acceptance of AI devices across different application areas. However, further research is needed to collect more data and validate the study's findings.

APPLICATION

A comprehensive overview of factors influencing the acceptance of AI devices could help researchers and practitioners evaluate user behaviour when adopting new technologies.

The Store-and-Forward Telemedicine Service User-satisfaction Questionnaire: Development and validation of a questionnaire to monitor and assess health care providers' experiences

INTRODUCTION

With wider adoption of store-and-forward telemedicine accelerating, particularly post-coronavirus disease 2019, it is essential to understand health care providers' (HCPs) satisfaction with digital solutions offered by telemedicine organizations to (continuously) guarantee service quality. We developed the Store-and-Forward Telemedicine Service User-satisfaction Questionnaire to monitor and assess HCPs' experiences with contracted telemedicine organizations.

METHODS

Questionnaire construction (phase 1) consisted of exploratory literature search on validated telemedicine satisfaction questionnaires, a telemedicine domain and human factors expert focus group, stakeholder focus group (customer service employee and telemedicine account managers), and two pre-testing rounds among 18 HCPs. The pilot questionnaire (phase 2) was sent to 2179 HCPs for validity and reliability assessment.

RESULTS

Phase 1: Two validated questionnaires (73 items overall) were used as input for Store-and-Forward Telemedicine Service User-satisfaction Questionnaire. Revisions resulted in 61 items. Phase 2: the pilot 61-item Store-and-Forward Telemedicine Service User-satisfaction Questionnaire instrument was completed by 181 of 2179 invited HCPs. Forty-one mandatory items of the pilot Store-and-Forward Telemedicine Service User-satisfaction Questionnaire rated on a 5-point Likert scale were included in psychometric analyses and resulted in six reliable scales: training, communication, organization policy and strategy, interaction platform, usage platform, and working conditions.

DISCUSSION

The Store-and-Forward Telemedicine Service User-satisfaction Questionnaire is a reliable and valid questionnaire for measuring HCPs' satisfaction with store-and-forward telemedicine services as part of a continuous quality improvement cycle. Reimbursement questions were excluded due to low response. As adoption of telemedicine may be impeded by financial compensation issues, this requires consideration in future telemedicine questionnaires. Store-and-Forward Telemedicine Service User-satisfaction Questionnaire including video consultation items is needed to monitor also synchronous services as these expanded in the coronavirus disease 2019 pandemic.

First test of the theory of reasoned goal pursuit: predicting physical activity

OBJECTIVE

This study applied the theory of reasoned goal pursuit (TRGP) in predicting physical activity among Australian undergraduate students, providing the first empirical test of the model.Methods: The research comprised an elicitation study (N = 25; MAge= 25.76, SDAge= 11.33, 20 female, 5 male) to identify readily accessible procurement and approval goal beliefs and behavioural, normative, and control beliefs; and, a two-wave prospective online survey study (N = 109; MAge = 21.88, SDAge = 7.04, 63 female, 46 male) to test the tenets of the TRGP in relation to meeting World Health Organization physical activity guidelines during the COVID-19 pandemic among first year university students.Results: A linear PLS-SEM model displayed good fit-to-data, predicting 38%, 74%, and 48% of the variance in motivation, intention, and physical activity, respectively. The model supported the majority of hypothesised pattern of effects among theory constructs; in particular, the proposition that beliefs corresponding to procurement and approval goals would be more consequential to people's motivation and, thus, their intentions and behaviour, than other behavioural and normative beliefs, respectively.Conclusions: Results lend support for the TRGP and sets the agenda for future research to systematically test the proposed direct, indirect, and moderation effects for different health behaviours, populations, and contexts.

Supplemental data for this article is available online at https://doi.org/10.1080/08870446.2022.2026946 .

Visual and steering behaviours during lane departures: a longitudinal study of interactions between lane departure warning system, driving task and driving experience

Lane Departure Warning Systems (LDWS) generate a warning in case of imminent lane departure. LDWS have proven to be effective and associated human-machine cooperation modelled. In this study, LDWS acceptance and its impact on visual and steering behaviour have been investigated over 6 weeks for novice and experienced drivers. Unprovoked lane departures were analysed along three driving tasks gradually more demanding. These observations were compared to a baseline condition without automation. The number of lane departures and their duration were dramatically reduced by LDWS, and a narrower visual spread of search during lane departure events was recorded. The findings confirmed LDWS effectiveness and suggested that these benefits are supported by visuo-attentional guidance. No specific influence of driving experience on LDWS was found, suggesting that similar cognitive processes are engaged with or without driving experience. Drivers' acceptance of LDWS lowered after automation use, but LDWS effectiveness remained stable during prolonged use.Practitioner summary: Lane Departure Warning Systems (LDWS) have been designed to prevent lane departure crashes. Here, LDWS assessment over a 6-week period showed a major drop in the number of lane departure events increasing over time. LDWS effectiveness is supported by the guidance of drivers' visual attention during lane departure events.

Convolutional neural network-based program to predict lymph node metastasis of non-small cell lung cancer using 18F-FDG PET

PURPOSE

To develop a convolutional neural network (CNN)-based program to analyze maximum intensity projection (MIP) images of 2-deoxy-2-[F-18]fluoro-D-glucose (FDG) positron emission tomography (PET) scans, aimed at predicting lymph node metastasis of non-small cell lung cancer (NSCLC), and to evaluate its effectiveness in providing diagnostic assistance to radiologists.

METHODS

We obtained PET images of NSCLC from public datasets, including those of 435 patients with available N-stage information, which were divided into a training set (n = 304) and a test set (n = 131). We generated 36 maximum intensity projection (MIP) images for each patient. A residual network (ResNet-50)-based CNN was trained using the MIP images of the training set to predict lymph node metastasis. Lymph node metastasis in the test set was predicted by the trained CNN as well as by seven radiologists twice: first without and second with CNN assistance. Diagnostic performance metrics, including accuracy and prediction error (the difference between the truth and the predictions), were calculated, and reading times were recorded.

RESULTS

In the test set, 67 (51%) patients exhibited lymph node metastases and the CNN yielded 0.748 predictive accuracy. With the assistance of the CNN, the prediction error was significantly reduced for six of the seven radiologists although the accuracy did not change significantly. The prediction time was significantly reduced for five of the seven radiologists with the median reduction ratio 38.0%.

CONCLUSION

The CNN-based program could potentially assist radiologists in predicting lymph node metastasis by increasing diagnostic confidence and reducing reading time without affecting diagnostic accuracy, at least in the limited situations using MIP images.

Global Breakdowns and Transformations in the World of Sports After Covid-19

The world has spent the first phase of the crisis caused by the Covid-19 pandemic, which is powerful and invisible, threatening the lives of every person without discrimination, with the struggle in the field of health. The second stage, which we are still in, is the period in which the economic crisis that occurred as a result of the measures taken is tried to be overcome. The third stage is a new order that Covid-19 has begun to shape. The-sports world has been affected by the crisis caused by the Covid-19 pandemic in the first two stages. It is clear, then, that it will be heavily affected by the third stage. The strategies it will have globally after the Covid-19 pandemic will determine the new role of sports in the global order. In this section, considering these three stages, the breaks, challenges and transformations that may take place in the world of sports after the Covid-19 pandemic are discussed and evaluated.

Doctoral Contribution to Nursing Science in Sub-Saharan Africa: A Document Review

Nursing science is at serious risk of extinction. The lack of funding for research, absence of healthcare policies underpinned by nursing science, and general lack of understanding of nursing metaparadigms all contribute to the stunted growth in nursing science. Doctoral research is a platform for the development and refinement of nursing science. The purpose of this qualitative retrospective document review was to describe the doctoral contribution to nursing in sub-Saharan Africa (SSA). Electronic dissertations for doctoral degrees in nursing within a 5-year period from universities in SSA were included. The extracted data comprising the purpose of the studies, the models used in the studies, and the studies' contributions to nursing science were analyzed against a knowledge contribution framework. In total, 166 documents were included, mostly from South African universities, with a predominant focus on developing models, frameworks, and strategies within nursing practice. Only 17% of the studies applied grand nursing theories or models, with the rest of the studies applying theories from other disciplines. The contribution to nursing science from the doctoral studies was poor. The low uptake of nursing models in doctoral research in SSA may significantly contribute to the lack of refinement of nursing science within SSA. Structured approaches focused on integrating the nursing metaparadigms, theories, and models and fundamental underpins for doctoral education in Africa are essential to influencing the refinement of nursing science.

Work interruptions of office workers: The influence of the complexity of primary work tasks on the perception of interruptions

BACKGROUND

Research demonstrates that work interruptions are considered one of the most common work stressors. Understanding the mechanisms of work interruptions is therefore vital to reducing worker stress and maintaining performance.

OBJECTIVE

The aim of this research is to investigate the influence of the frequency of work interruptions on subjective workload in the context of office work. Specifically, the mediating influence of interruption perception as well as the moderating influence of the complexity of the primary task are examined.

METHOD

The work interruptions of 492 office workers in Germany were collected by means of a one-day diary study. A mediation model and a conditional indirect effect model were calculated to examine the influence of interruption frequency on subjective workload, mediated by the individual perception of these interruptions as well as moderated by the complexity of the primary work tasks.

RESULTS

The analyses indicated a significant mediation and moderation. This implies that, on the one hand, the perception of work interruptions significantly mediates the relationship between the frequency of work interruptions and subjective workload. On the other hand, more complex primary work tasks seem to strengthen the positive relationship between interruption frequency and perceived interruption overload.

CONCLUSION

The study underlines that work interruptions need to be considered in a much more differentiated way than is currently the case. Both in research and in terms of intervention measures in the work context, the various influencing factors need to be identified for an assessment of the effects on the working person to be possible.

Factors influencing telemedicine adoption among physicians in the Malaysian healthcare system: A revisit

Background

The Malaysian healthcare system is under strain due to an aging population, the rising prevalence of chronic diseases, and heavy workloads among physicians. As costs and requirements continue to rise, telemedicine is critical for bridging gaps in supply and demand. However, there are limited studies on telemedicine adoption among Malaysian physicians. Furthermore, the existing literature on telemedicine adoption does not contain a comprehensive framework that integrates the multidimensional social influence, and technological, clinical, and individual factors.

Objective

This research investigates the adoption of telemedicine among Malaysian physicians. It draws from the Technology Acceptance Model (TAM) and Kelman's Social Influence Theory.

Methods

A survey was conducted among 230 participants in hospitals located in Kuala Lumpur and Selangor. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Results

The study identified crucial factors influencing telemedicine adoption, including informational influences, rewards, perceived ease of use, and usefulness. Meanwhile, the Importance-performance Map Analysis (IPMA) identified perceived ease of use as the most important factor for physicians, but the highest performance was patient's records.

Conclusions

The proposed integrated model enhances the understanding of telemedicine adoption and highlights the differential effects of individual, technological, clinical, and multidimensional social influence factors from the physicians' perspective. The findings can guide future studies and influence implementation strategies for telemedicine promotion in the Malaysian healthcare context. Hospitals should prioritize user-friendly technology and information provision, while telemedicine providers should enhance the accessibility of patient records to facilitate telemedicine adoption. Policymakers should consider supporting training programs that will boost physicians' confidence in effectively utilizing telemedicine.

Is information evaluated subjectively? Social media has changed the way users search for medical information

Objective

In recent years, social media platforms, such as TikTok and RedBook, have emerged as important channels through which users access and share medical information. Additionally, an increasing number of healthcare professionals have created social media accounts through which to disseminate medical knowledge. This paper explores why users obtain their medical information from social media and how the signals transmitted by social platforms affect use behaviours.

Methods

We combined the elaboration likelihood model and signal theories to construct a comprehensive model for this study. We used simple random sampling to investigate users' behaviours related to social media usage. A total of 351 valid questionnaires were completed by people in Mainland China. The participants were enthusiastic about social media platforms and had searched for health-related information on social media in the past three months. We analysed the data using partial least squares structural equation modelling to investigate the influence of two pathways and two signals (objective and subjective judgement pathways and positive and negative signals) on social media use behaviours.

Results

When seeking medical information on social media, users tend to rely on subjective judgment rather than objective judgment, although both are influential. Furthermore, in the current era, in which marketing methods involving big data algorithms and artificial intelligence prevail, negative signals, such as information overload, have a more pronounced impact than positive signals.

Conclusions

This study demonstrates that the subjective judgment path has a greater impact on users than the objective judgment path. Platforms are encouraged to focus more on users' emotional needs. The paper also discusses the negative impact of information overload on users, sounding an alarm for enterprises to control their use of homogeneous information resulting from the excessive use of big data algorithms.

Distal and proximal factors of wearable users' quantified-self dependence: A cognitive-behavioral model

Objective

While using self-tracking devices for physical health has become ubiquitous, the potential for quantified-self (QS) dependence as a detrimental outcome for mental health is under-explored. This study examined the mechanism of wearable users' QS dependence by investigating both the distal and proximal factors based on a cognitive-behavioral model.

Methods

A total of 535 wearable users aged 18-35 years were surveyed in this study. The surveys included control variable questions related to age, gender, monthly income, BMI, and wearable use experience. Key variable measures included distal factor (habitual use of wearables), proximal factors (perceived external regulation, recognition, and perceived irreplaceability), and perceived QS dependence. Structural equation modeling (SEM) was used to test research hypotheses.

Results

The results revealed that habitual use of wearables as a distal factor alone was negatively associated with perceived QS dependence. However, it positively influenced perceived external regulation, recognition, and perceived irreplaceability, which in turn significantly contributed to perceived QS dependence, suggesting the suppression effect of the proximal factors.

Conclusions

The relationships between habitual use of wearables and QS dependence are complex. Although habitual use may seem apparently harmless, it can indirectly foster maladaptive cognitions, thereby promoting dependence. These findings underscore the potential threats of maladaptive cognitions that may arise from leveraging technology to promote physical health, thus offering guidance to technology designers for interventions.

From use, value and user-centered design to context: A mixed methods analysis of a hospital electronic medical record enhancement

Objective

This study sought to determine the use and perceived value of a user-centered electronic medical record (EMR) enhancement for stroke care and understand if its value was in alignment with its intended design. The EMR enhancement was introduced into Queensland public hospitals in Australia and included a summary page for enhanced interprofessional collaboration and data collection forms for efficient data extraction.

Methods

A mixed methods design was adopted and data collected from four hospital sites. We conducted 15 semistructured interviews with multidisciplinary end-users across participating sites and analyzed this data using inductive thematic techniques. Usage log data was extracted from the EMR to determine its use.

Results

Relative use of the summary page showed moderate use, varying from 66 ± 22.5 uses for each stroke patient admission per month (Site 1) to 26.7 ± 9.1 (Site 2). Interviews identified key themes of "visibility" and providing a "quick snapshot" of patient data as the main positive attributes. Technology "functionality" was perceived negatively. Use of the data collection forms was minimal, with inconsistency across sites: (Site 3, 0% to Site 2, 47%). Negative themes of "inefficiency," poor "functionality" and the "trust" required in data entry practices were found.

Conclusions

Despite its user-centered design, clinicians did not always use the enhancement in line with its intended design, or grasp its intended value. Our findings highlight the challenges of user-centered design to accurately reflect clinical workflows within different contexts. A greater understanding is required of how to optimize user-centered EMR design for specific hospital contexts.

What drives the vaccination intention against COVID-19? Application of EPPM, TAM, and theories of risk assessment

Vaccines are widely used to fight against COVID-19. However, COVID-19 vaccine hesitancy appears as some individuals are concerned with COVID-19 vaccines. This study investigates the vaccination intention against COVID-19 in China with the Extended Parallel Process Model (EPPM), Technology Acceptance Model (TAM), and theories of risk information assessment. Results showed that the formation mechanism of vaccination intention could be considered a psychological process, as subjective knowledge was a primary influence on correspondents' weighting of both the potentially positive (usefulness) and negative effects (threat) of vaccination. This unequal consideration then resulted in different levels of fear arousal between subjects. Driven by usefulness/threat perception and fear, people conducted different decision strategies, so-called analytical assessment, and experiential assessment to make vaccination decision. In addition to the direct effects of experiential assessment on vaccination intention, two decision strategies and fear arousal also affected people's vaccination intention through the mediation role of vaccination attitude. For policymakers and stakeholders, this study provides a knowledge base for confidence-building, and emotional guidance concerning against COVID-19 vaccination.

I Do Not Want to Miss a Thing! Consequences of Employees' Workplace Fear of Missing Out for ICT Use, Well-Being, and Recovery Experiences

As more and more employees have access to work-related information and communication technologies (ICTs) anywhere and anytime, new challenges arise in terms of well-being and recovery experiences. Feelings of workplace fear of missing Out (wFoMO) and workplace telepressure may be personal demands that add to the literature of the job demands-resources (JD-R) theory. In this study, we proposed a model in which wFoMO and workplace telepressure were associated with employee well-being variables via the use of ICTs during leisure time. Therefore, we analyzed the data of N = 130 employees who answered two questionnaires in the interval of one work week. The results revealed negative indirect effects between wFoMO/workplace telepressure and psychological detachment/perceived stress via ICT use. The results were more ambivalent regarding the dependent variables burnout, relaxation, and control. This strengthens the literature that categorized ICT use as a job demand. However, we also found positive indirect effects on perceived informational benefits, which supports the idea of ICTs being both a job demand and a job resource in light of the JD-R theory. This study contributes to past research on work-related ICT use during leisure time and demonstrates the relevance of personal demands such as wFoMO for employees' well-being.

Omnichannel integration strategy based on BOPS

Technological innovation and the upgrading of consumer preferences have greatly accelerated the rapid development of the "new retail" omnichannel model. Meeting the personalized and seamless interactive experience expected by consumers requires integrating the advantages of both offline and online channels and expanding the integrated and intelligent omnichannel layout. This has emerged as a complex problem that the industry urgently needs to address. In order to tackle this issue, we conducted a study on a Buy-Online-and-Pick-up-in-Store (BOPS) pricing game between offline stores and e-commerce departments, considering factors such as match probability and network cost of return. Furthermore, we proposed the Buy-Online-and-Pick-up-in-Store-and-Return-Online (BORO) strategy and conducted an analysis on the variation in market share and revenue levels for both offline stores and e-commerce departments under this strategy. The results demonstrate that: (i) the omnichannel strategy of BOPS can increase the revenues of both offline stores and e-commerce departments only when the distance costs are moderate; (ii) the BORO strategy provides greater benefits to offline stores compared to e-commerce departments; and (iii) the effectiveness of the BORO strategy is influenced by factors such as match probability, distance cost, and product return. This research not only provides a theoretical foundation but also practical insights for the strategic channel management of omnichannel brand merchants.

Effects of Internal and External Factors on Hospital Data Breaches: Quantitative Study

BACKGROUND

Health care data breaches are the most rapidly increasing type of cybercrime; however, the predictors of health care data breaches are uncertain.

OBJECTIVE

This quantitative study aims to develop a predictive model to explain the number of hospital data breaches at the county level.

METHODS

This study evaluated data consolidated at the county level from 1032 short-term acute care hospitals. We considered the association between data breach occurrence (a dichotomous variable), predictors based on county demographics, and socioeconomics, average hospital workload, facility type, and average performance on several hospital financial metrics using 3 model types: logistic regression, perceptron, and support vector machine.

RESULTS

The model coefficient performance metrics indicated convergent validity across the 3 model types for all variables except bad debt and the factor level accounting for counties with >20% and up to 40% Hispanic populations, both of which had mixed coefficient directionality. The support vector machine model performed the classification task best based on all metrics (accuracy, precision, recall, F1-score). All the 3 models performed the classification task well with directional congruence of weights. From the logistic regression model, the top 5 odds ratios (indicating a higher risk of breach) included inpatient workload, medical center status, pediatric trauma center status, accounts receivable, and the number of outpatient visits, in high to low order. The bottom 5 odds ratios (indicating the lowest odds of experiencing a data breach) occurred for counties with Black populations of >20% and <40%, >80% and <100%, and >40% but <60%, as well as counties with ≤20% Asian or between 80% and 100% Hispanic individuals. Our results are in line with those of other studies that determined that patient workload, facility type, and financial outcomes were associated with the likelihood of health care data breach occurrence.

CONCLUSIONS

The results of this study provide a predictive model for health care data breaches that may guide health care managers to reduce the risk of data breaches by raising awareness of the risk factors.

Optimal strategy of in-game items with conspicuous consumption: whether to provide the grinding version?

In the virtual world, whether or not to spend money on in-game items distinguishes paying players from non-paying players. Due to the existence of conspicuous psychology, paying players will greatly increase their conspicuous utility after purchasing an item in addition to the utility of the item itself. In this case, whether providing different versions of items can bring greater revenue to the game company is a question worth investigating. In this study, two analytical models considering conspicuous intensity are developed to compare the optimal pricing strategy of the game company providing the single-version item or dual-version items. The single-version item can only be purchased, while a relatively low-quality version that can be obtained by grinding is provided in the dual-version strategy. Grinding means using time in games to get items instead of spending in games. The results suggest that it is more profitable for companies to offer dual-version items when conspicuous intensity is strong. Game companies can also adjust the time needed to acquire the grinding version item and the quality gap between the two versions to achieve greater revenue. The research contributes to providing a theoretical basis and decision support for game companies to decide whether to provide different versions of in-game items.

Can digital transformation reduce corporate stock price crashes?

PURPOSE

The purpose of this paper is to study the impact of enterprises' digital transformation on the risk of stock price crashes, but also to study the mediating role of enterprises' financialization and accounting conservatism in the enterprises' digital transformation on stock price crash risk.

DESIGN/METHODOLOGY/APPROACH

Based on the data of 2,599 listed companies in China from 2010 to 2019, this paper constructs indicators of enterprise digital transformation through word frequency analysis method, and uses fixed-effects model and mediated-effects model to explore the impact and mechanism of enterprise digital transformation on the stock price crash risk.

FINDINGS

This study shows that firms' digital transformation reduces the risk of stock price crashes and that financialization of firms and accounting conservatism play a significant mediating effect between enterprises' digital transformation and the risk of stock price crashes.

ORIGINALITY/VALUE

This study enriches the study of stock price crash risk by including digital transformation in the field of stock price crash research, and it examines the mediating roles of financialization of enterprises and accounting conservatism, which provides a new explanatory mechanism to the study of the correlation between digital transformation of enterprises and the risk of stock price crash.

Online identity work dynamics of Instagram micro-influencers: an extreme case approach

Background

Advanced media technologies have become an integral part of people's daily lives, providing them with new tools and environments for the formation and enactment of their identities. To date, the literature acknowledges that media technologies, such as social networking sites, are used to form and enact online identities, and that these platforms can simultaneously pose challenges to individuals' identity work. However, we know little about the precise online identity work strategies that individuals employ in response to the challenges they face over time.

Objective

This paper examines the online identity work dynamics of Instagram micro-influencers, for whom social network sites enable and guide them in forming and enacting their online identities on a daily basis. The study was guided by the following research question: what are the challenges that Instagram micro-influencers perceive online and what are the online identity work strategies that they employ in response to these challenges over time?

Methods

This study employs an extreme case approach to rigorously explore the lives of seven micro-influencers on Instagram. We combine in-depth data from narrative interviews, longitudinal data from online autobiographical narratives revealed through the participants' Instagram timelines, and follow-up interviews.

Results

Our analysis revealed three main themes that highlight the challenges that Instagram micro-influencers face online: (1) amplified social expectations, (2) feelings of inauthenticity, and, as a result thereof, (3) psychological distress. We found that these challenges were viewed as catalysts for their online identity work processes. We identified three key online identity work strategies that the Instagram micro-influencers employed in response over time: (1) experimenting with their online identities, followed by either (2) segmenting between their online and offline identities, or (3) adding identities through online multiplicity.

Conclusion

Our research provides new insights into how individuals may respond to the challenge of managing their online identities over time by engaging in different online identity work strategies. This study highlights the importance of designing online media technologies that enable individuals to cope with online challenges. We emphasize the need to design online spaces for (1) the expression of authentic identities, (2) community building, and (3) online multiplicity.

Health care in future community: innovatively discover and respond to the needs of today's seniors

Introduction

In the context of the digital economy, the emergence and application of emerging technologies have accelerated the integration of traditional social structures with new technologies, leading to the inception of the "Future Community" as an innovative urban unit. With an aging population's rapid and sustained rise, integrating health care for older adults with modern information technology is gradually moving towards holistic governance. This approach utilizes the Future Community as a medium and aims for quality enhancement and increased efficiency, which instrumentally addresses the diversified health care needs of China's aging era.

Methods

In this study, we employed a questionnaire survey method that covered 11 communities in Tianjin City to understand better the current status and characteristics of their health care services.

Results

The survey results show that the means of community health care for older adults are gradually being upgraded, and the demands are shifting. Then, we arrive at three conclusions: firstly, technological innovation and smart approaches have the potential to positively influence the quality of health care in these communities. Secondly, allocating health care resources within communities can have a salutary effect on the psychological well-being of seniors. Thirdly, actively involving seniors in community life and governance can elevate their self-worth.

Discussion

At last, in conjunction with current challenges, we think that deepening multi-party collaboration, educating specialized talents, and bridging the "digital gap" would be effective ways to establish a future community for seniors.

Can welfare states buffer technostress? Income and technostress in the context of various OECD countries

Many workers are experiencing the downsides of being exposed to an overload of information and communication technology (ICT), highlighting the need for resources to cope with the resulting technostress. This article offers a novel cross-level perspective on technostress by examining how the context of the welfare state influences the relationship between income and technostress. Showing that individuals with higher income experience less technostress, this study argues that the welfare state represents an additional coping resource, in particular in the form of unemployment benefits. Since unemployment benefits insure income earners in the case of job loss, the negative effect of income on technostress should increase with higher levels of unemployment generosity. In line with these expectations, empirical results based on original survey data collected in collaboration with the OECD show that the impact of income on technostress varies across welfare state contexts. Implications for public health and policymakers are being discussed.

Investigating the Impact of Automation on the Health Care Workforce Through Autonomous Telemedicine in the Cataract Pathway: Protocol for a Multicenter Study

BACKGROUND

While digital health innovations are increasingly being adopted by health care organizations, implementation is often carried out without considering the impacts on frontline staff who will be using the technology and who will be affected by its introduction. The enthusiasm surrounding the use of artificial intelligence (AI)-enabled digital solutions in health care is tempered by uncertainty around how it will change the working lives and practices of health care professionals. Digital enablement can be viewed as facilitating enhanced effectiveness and efficiency by improving services and automating cognitive labor, yet the implementation of such AI technology comes with challenges related to changes in work practices brought by automation. This research explores staff experiences before and after care pathway automation with an autonomous clinical conversational assistant, Dora (Ufonia Ltd), that is able to automate routine clinical conversations.

OBJECTIVE

The primary objective is to examine the impact of AI-enabled automation on clinicians, allied health professionals, and administrators who provide or facilitate health care to patients in high-volume, low-complexity care pathways. In the process of transforming care pathways through automation of routine tasks, staff will increasingly "work at the top of their license." The impact of this fundamental change on the professional identity, well-being, and work practices of the individual is poorly understood at present.

METHODS

We will adopt a multiple case study approach, combining qualitative and quantitative data collection methods, over 2 distinct phases, namely phase A (preimplementation) and phase B (postimplementation).

RESULTS

The analysis is expected to reveal the interrelationship between Dora and those affected by its introduction. This will reveal how tasks and responsibilities have changed or shifted, current tensions and contradictions, ways of working, and challenges, benefits, and opportunities as perceived by those on the frontlines of the health care system. The findings will enable a better understanding of the resistance or susceptibility of different stakeholders within the health care workforce and encourage managerial awareness of differing needs, demands, and uncertainties.

CONCLUSIONS

The implementation of AI in the health care sector, as well as the body of research on this topic, remain in their infancy. The project's key contribution will be to understand the impact of AI-enabled automation on the health care workforce and their work practices.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/49374.

[Application of scientific knowledge: knowledge translation in an institute of science and technology in public health]

Knowledge translation (KT) aims at the practical use of scientific research results and at the monitoring of the benefits caused to the population's health. In health, the government and especially society expect that investments in research will produce results that go beyond the production and publication of knowledge, provoking outcomes such as public policies, systems, products, and technologies to benefit the health of the population. However, closing the gaps between research and application requires overcoming a number of challenges. This study aimed to propose strategies to foster the process of transforming the scientific knowledge generated in research into actions and products that contribute to improving the population's health based on the identification of barriers and facilitating factors of a health science and technology institute. The reports of interviews conducted with 16 researchers showed 10 categories of barriers, especially: "limited funding to the science and technology institute" and "insufficient technical support for knowledge translation". "Infrastructure and institutional support" was the facilitating factor category participants mentioned the most. Finally, we developed the artifact "strategies and approaches for overcoming barriers to implement research results". Among the strategies, we suggest the inclusion of a knowledge translation discipline in stricto sensu graduate programs and the creation of an instance in the organizational structure of the science and technology institute to technically and managerially support the application of research results.

Helping patient educators meet health literacy needs: End-user testing and iterative development of an innovative health literacy editing tool

Objective

The Sydney Health Literacy Lab (SHeLL) Editor is an online text-editing tool that provides real-time assessment and feedback on written health information (assesses grade reading score, complex language, passive voice). This study aimed to explore how the design could be further enhanced to help health information providers interpret and act on automated feedback.

Methods

The prototype was iteratively refined across four rounds of user-testing with health services staff (N = 20). Participants took part in online interviews and a brief follow-up survey using validated usability scales (System Usability Scale, Technology Acceptance Model). After each round, Yardley's (2021) optimisation criteria guided which changes would be implemented.

Results

Participants rated the Editor as having adequate usability (M = 82.8 out of 100, SD = 13.5). Most modifications sought to reduce information overload (e.g. simplifying instructions for new users) or make feedback motivating and actionable (e.g. using frequent incremental feedback to highlight changes to the text altered assessment scores).

Conclusion

terative user-testing was critical to balancing academic values and the practical needs of the Editor's target users. The final version emphasises actionable real-time feedback and not just assessment.

Innovation

The Editor is a new tool that will help health information providers apply health literacy principles to written text.

Chatbots for future docs: exploring medical students' attitudes and knowledge towards artificial intelligence and medical chatbots

Artificial intelligence (AI) in medicine and digital assistance systems such as chatbots will play an increasingly important role in future doctor - patient communication. To benefit from the potential of this technical innovation and ensure optimal patient care, future physicians should be equipped with the appropriate skills. Accordingly, a suitable place for the management and adaptation of digital assistance systems must be found in the medical education curriculum. To determine the existing levels of knowledge of medical students about AI chatbots in particular in the healthcare setting, this study surveyed medical students of the University of Luebeck and the University Hospital of Tuebingen. Using standardized quantitative questionnaires and qualitative analysis of group discussions, the attitudes of medical students toward AI and chatbots in medicine were investigated. From this, relevant requirements for the future integration of AI into the medical curriculum could be identified. The aim was to establish a basic understanding of the opportunities, limitations, and risks, as well as potential areas of application of the technology. The participants (N = 12) were able to develop an understanding of how AI and chatbots will affect their future daily work. Although basic attitudes toward the use of AI were positive, the students also expressed concerns. There were high levels of agreement regarding the use of AI in administrative settings (83.3%) and research with health-related data (91.7%). However, participants expressed concerns that data protection may be insufficiently guaranteed (33.3%) and that they might be increasingly monitored at work in the future (58.3%). The evaluations indicated that future physicians want to engage more intensively with AI in medicine. In view of future developments, AI and data competencies should be taught in a structured way during the medical curriculum and integrated into curricular teaching.

Communicating about online health information with patients: Exploring determinants among telemental health providers

Objective

To investigate determinants of telemental health (TMH) providers' openness to discuss and confidence to use online mental health information with patients, focusing on providers' eHealth literacy and perceived usefulness of online MH information.

Methods

TMH providers (N = 472) completed a web-based survey with questions about discussing and using online health information with patients, perceived usefulness of the Internet as a source of patient information, and eHealth literacy.

Results

Providers were open to discussing online health information with patients if they were not treating substance abuse disorders (b = -0.83), felt the Internet was a useful resource (b = 0.18), and felt confident in their skills to evaluate the online information (b = 0.21). Providers were confident using online health information if they worked in a small clinic (b = 0.37), felt the Internet was a useful resource (b = 0.31), knew where to access relevant online health information (b = 0.13), and had skills to help their patients find (b = 0.17) and evaluate (b = 0.54) online information.

Conclusion

TMH providers are likely to use online health information resources if they know where and how to find them and perceive the Internet as a useful resource.

Innovation

To effectively discuss online health information with patients, providers require skills to evaluate the information with patients.

Theory of trust and acceptance of artificial intelligence technology (TrAAIT): An instrument to assess clinician trust and acceptance of artificial intelligence

BACKGROUND

Artificial intelligence and machine learning (AI/ML) technologies like generative and ambient AI solutions are proliferating in real-world healthcare settings. Clinician trust affects adoption and impact of these systems. Organizations need a validated method to assess factors underlying trust and acceptance of AI for clinical workflows in order to improve adoption and the impact of AI.

OBJECTIVE

Our study set out to develop and assess a novel clinician-centered model to measure and explain trust and adoption of AI technology. We hypothesized that clinicians' system-specific Trust in AI is the primary predictor of both Acceptance (i.e., willingness to adopt), and post-adoption Trusting Stance (i.e., general stance towards any AI system). We validated the new model at an urban comprehensive cancer center. We produced an easily implemented survey tool for measuring clinician trust and adoption of AI.

METHODS

This survey-based, cross-sectional, psychometric study included a model development phase and validation phase. Measurement was done with five-point ascending unidirectional Likert scales. The development sample included N = 93 clinicians (physicians, advanced practice providers, nurses) that used an AI-based communication application. The validation sample included N = 73 clinicians that used a commercially available AI-powered speech-to-text application for note-writing in an electronic health record (EHR). Analytical procedures included exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and partial least squares structural equation modeling (PLS-SEM). The Johnson-Neyman (JN) methodology was used to determine moderator effects.

RESULTS

In the fully moderated causal model, clinician trust explained a large amount of variance in their acceptance of a specific AI application (56%) and their post-adoption general trusting stance towards AI in general (36%). Moderators included organizational assurances, length of time using the application, and clinician age. The final validated instrument has 20 items and takes 5 min to complete on average.

CONCLUSIONS

We found that clinician acceptance of AI is determined by their degree of trust formed via information credibility, perceived application value, and reliability. The novel model, TrAAIT, explains factors underlying AI trustworthiness and acceptance for clinicians. With its easy-to-use instrument and Summative Score Dashboard, TrAAIT can help organizations implementing AI to identify and intercept barriers to clinician adoption in real-world settings.

Emotional experiences of service robots' anthropomorphic appearance: a multimodal measurement method

Anthropomorphic appearance is a key factor to affect users' attitudes and emotions. This research aimed to measure emotional experience caused by robots' anthropomorphic appearance with three levels - high, moderate, and low - using multimodal measurement. Fifty participants' physiological and eye-tracker data were recorded synchronously while they observed robot images that were displayed in random order. Afterward, the participants reported subjective emotional experiences and attitudes towards those robots. The results showed that the images of the moderately anthropomorphic service robots induced higher pleasure and arousal ratings, and yielded significantly larger pupil diameter and faster saccade velocity, than did the low or high robots. Moreover, participants' facial electromyography, skin conductance, and heart-rate responses were higher when observing moderately anthropomorphic service robots. An implication of the research is that service robots' appearance should be designed to be moderately anthropomorphic; too many human-like features or machine-like features may disturb users' positive emotions and attitudes.Practitioner Summary: This research aimed to measure emotional experience caused by three types of anthropomorphic service robots using a multimodal measurement experiment. The results showed that moderately anthropomorphic service robots evoked more positive emotion than high and low anthropomorphic robots. Too many human-like features or machine-like features may disturb users' positive emotions.

Run! This road has no ending! A systematic review of PLS-SEM application in strategic management research among developing nations

Partial least squares structural equation modelling (PLS-SEM) is emerging as a prominent methodological tool in strategic management research. Although it offers various advancements to stay relevant with growing research needs, the pace of PLS-SEM adoption may differ in different parts of the world. In this paper, we conducted a systematic review using the PRISMA framework and extracted from the top-ranking strategic management journals 120 articles published between 2011 and 2022 that presented a microscopic view on developing nations. Our findings reveal that despite the astounding methodological solutions offered by PLS-SEM, the studies from developing nations are still trailing behind developed nations in terms of fully exploiting the advancements of PLS-SEM to provide substantial insights to strategic management literature. This review identifies discrepancies in the current application of the method, discusses the most recent advancements and provides the best practices, standard guidelines and recommendations for the best use of PLS-SEM in strategic management research.

Examining human factors and ergonomics aspects in a manufacturing organisation's metrics system: measuring up to stakeholder needs

This research examines the status of human factors and ergonomics (HF/E) metrics in the case context of product realisation in an electronics manufacturing company. Interactions with 100+ stakeholders over a five year period were thematically analysed for metrics-related views and content. A disconnect between engineering metrics and HF/E metrics was evident. Engineers and HF/E specialists expressed different understandings of the gap between the disciplines and how to generate HF/E metrics that would fit the organisation. Other emerging themes provided insight for metrics development including improving indicator relatability, considerations for communication of information, and barriers to implementation of metrics. The results led to seven recommendations to help guide practitioners in developing and refining HF/E metrics as part of an organisation's metrics system. This macroergonomic case study provides key points for consideration when developing HF/E focussed metrics to support organisations being more proactive with HF/E in work system design. Practitioner summary: Metrics' presence, stakeholder views on metrics, and metrics-related content in a case organisation were thematically analysed with a macroergonomics focus. Human factors and ergonomics metrics (HF/E) were disconnected from engineering metrics thus limiting the design team's ability to handle human factors in design. Factors influencing HF/E metrics creation and integration were identified, resulting in seven recommendations for developing HF/E metrics.

Are ride-hailing services safer than taxis? A multivariate spatial approach with accommodation of exposure uncertainty

Despite many research efforts on ride-hailing services and taxis, limited studies have compared the safety performance of the two modes. A major challenge is the need for reliable mode-specific exposure data to model their safety outcomes. Moreover, crash frequencies of the two modes by injury severities tend to be spatially and inherently correlated. To fully address these issues, this study proposes a novel multivariate conditional autoregressive model considering measurement errors in mode-specific exposures (MVCARME). More specially, a classical measurement error structure accommodates the uncertainty of estimated mode-specific exposures, and a multivariate spatial specification is adopted to capture potential spatial and inherent correlations. The model estimation is accelerated by an integrated nest Laplace approximation method. The census tracts in the city of Chicago are set as the spatial analysis unit. The mode-specific exposures (vehicle-mile-traveled) in each census tract are estimated by trip assignments using ride-hailing and taxi trip data in 2019. The modeling results indicate that both ride-hailing crashes and taxi crashes are positively associated with transportation factors (e.g., vehicle-mile-traveled, mode-specific vehicle-mile-traveled, and traffic signal numbers), land use factors (i.e., number of educational and alcohol-related sites), and demographic factors (e.g., median household income, transit ratio, and walk ratio). By comparison, the proposed model outperforms the others (i.e., negative binomial models and multivariate conditional autoregressive model) by yielding the lowest deviance information criterion (DIC), Watanabe-Akaike information criterion (WAIC), mean absolute error (MAE), and root-mean-square error (RMSE). According to the results of t-tests, ride-hailing services are found to be prone to a higher risk of minor injury crashes compared with taxis, despite no significant difference between the risks of severe injury crashes. Methodologically, this study adds a robust safety evaluation approach for comparing crash risks of different modes to the literature. At the same time, practically, it provides researchers, practitioners, and policy-makers insights into the safety management of various mobility alternatives.

Order Online or Call it in? Conceptualization and Measurement of Preferences for Computer versus Human Interaction

Technology is increasingly integrated into everyday life and consequently, traditional social exchanges between human agents have evolved to include human-computer interaction, providing scientists new directions for understanding and predicting consumer behavior. Despite progress, there are conceptual and empirical limitations in current measures applied to consumer/user preferences. This paper documents the development and validation of the 10-item preference for computer versus human interaction (PCHI) scale across three distinct samples and incorporating items that (a) include direct comparisons between computers and humans, (b) are independent of specific contexts or technologies, and (c) capture major theoretical domains of social, consumer, and human factors psychology. Results support the hypothesized three-factor structure (efficiency, ease of use, and trust) and demonstrate the utility of this measure to predict everyday consumer decisions beyond extant measures. Additionally, the PCHI offers marketing, user experience, and other practitioners a brief instrument for developing interventions, training protocols, and modeling attitudes.