Search Results (301)

Introduction: The work-related quality of life affects employee satisfaction and organizational effectiveness, with a direct impact on the quality of healthcare. This study aims to investigate the work-related quality of life (WRQoL) among nurses in tertiary healthcare, as perceived by the nurses themselves, in relation to their demographic and professional characteristics. At the same time, it seeks to highlight the way in which the individual dimensions of WRQoL influence their sexual and mental health. Materials and Methods: A descriptive cross-sectional study was conducted in 2023 in a General Hospital in Greece. Data were collected using structured questionnaires assessing sociodemo-graphic and occupational characteristics, WRQoL, mental health (Depression, Anxiety and Stress Scale—DASS-21), and female sexual function (Female Sexual Function Index—FSFI-19). Pearson correlation analysis and multiple linear regression analysis were performed. The regression model was adjusted for age, marital status, number of children, and work experience. Results: The results demonstrated a significant negative association between depression and sexual function (β = −0.388, p = 0.029), while stress was positively associated with sexual function (β = 0.371, p = 0.038). The overall regression model was statistically significant (p = 0.001), explaining 18.6% of the variance in sexual function. Conclusions: The findings highlight the close interrelationship between work-related quality of life, mental health, and sexual function among nurses. Poorer psychological well-being was associated with reduced sexual function, emphasizing the impact of occupational and emotional burden on nurses’ overall health. These results underline the importance of supportive workplace environments and targeted interventions to promote mental and sexual well-being among healthcare professionals. Full article

In contemporary organizations, digital learning environments and AI-supported instructional modalities play an increasingly important role in workforce upskilling and operational efficiency. Despite growing investments in video-based learning and AI-generated instructional agents, empirical evidence on their effectiveness remains inconclusive. This study examines whether different digital learning modalities influence skill acquisition, task performance, retention, and user perceptions in a simulated work-related context. An experimental study was conducted with 65 participants assigned to one of three learning conditions: static instructional material, video-based instruction with human narration, and video-based instruction with an AI-generated avatar. Performance was assessed through a pretest–posttest design, a practical task simulating a typical data-processing activity, and a delayed retention test after seven days. Participants also evaluated the learning experience in terms of clarity, engagement, and overall effectiveness. The results revealed no statistically significant differences between instructional modalities in knowledge acquisition, task performance, or retention. Similarly, no statistically significant differences were observed in participants’ self-reported ratings. However, qualitative findings suggested that some participants perceived the AI-generated avatar as somewhat distracting, despite generally positive evaluations of the video-based formats. These findings did not provide evidence that more technologically advanced and resource-intensive learning formats led to superior performance outcomes in the present sample. The findings highlight the importance of instructional design quality over technological complexity and point to a potential mismatch between user preferences and actual performance. From a management perspective, the results raise relevant questions regarding the cost-effectiveness of AI-supported learning solutions and provide evidence-based insights for decision-making in organizational learning and digital transformation strategies. Full article

This study explores how Machiavellian leadership behaviors may become embedded in ethical mentorship relationships and how these dynamics influence trust formation, dependency, emotional ambivalence, and trust erosion within higher education institutions (HEIs). Drawing on destructive leadership and impression management perspectives, this study examines how ethical rhetoric and developmental language may function as mechanisms through which manipulation, reciprocity expectations, and dependency become normalized within organizational mentorship relationships. A qualitative research design was adopted, using semi-structured interviews with sixteen participants employed within multicultural HEIs in the United Arab Emirates. The data were analyzed using thematic analysis to identify recurring patterns related to mentorship experiences, ethical self-presentation, emotional tension, and evolving trust dynamics. The findings revealed five interrelated themes: “The Wolf in a Scholar’s Robe,” where mentors project ethical identities while pursuing self-interest; “Debts That Never End,” reflecting the use of gratitude and reciprocity to create ongoing obligation; “Trust Fractures,” characterized by the erosion of interpersonal and institutional trust following perceived manipulation; “Ambivalence of Gratitude,” capturing the emotional conflict between appreciation and resentment; and “Signals of Dual Image,” highlighting the contrast between public ethical performance and private exploitative behavior. Together, these findings demonstrate how ethical mentorship may simultaneously function as a source of professional support and a mechanism of subtle control. This study contributes to the literature by conceptualizing performative ethical mentorship as a potential mechanism through which manipulative leadership behaviors may become legitimized within academic institutions. It further extends current scholarship by integrating Machiavellian leadership, ethical mentorship, emotional ambivalence, and trust dynamics within an analysis of multicultural HEI environments in the UAE, highlighting how performative ethical leadership may gradually erode psychological safety, relational trust, and organizational confidence. Full article

Artificial intelligence (AI) is transforming how organizations develop human potential, offering scalable and data-driven support for coaching and capability building. This study proposes and validates a conceptual framework for integrating AI into organizational coaching processes to enhance competence development and strategic alignment. AI-supported coaching in this research is treated as an emerging organizational technology whose potential organizational value depends less on model capability and more on governance design, decision rights, and auditable evaluation outputs. Following a mixed-methods, multi-phase design, the research combined a Systematic Literature Review (SLR) with the construction of a layered design architecture in which OSCAR serves as the primary coaching-process scaffold, complemented by KSA for competency specification, Situational Leadership for adaptive guidance, and KPIs for monitoring and governance. The framework structures AI-supported coaching across 10 interrelated phases, from contextual anchoring to review and measurement, while preserving iterative re-entry to earlier phases whenever review evidence, contextual change, or insufficient progress makes adjustment necessary. Prototyping demonstrated feasibility and coherence across models, while the focus group provided qualitative expert feedback on the framework’s clarity, governance needs, and perceived usefulness for competence development. At this stage, however, the KPI structures generated by the framework and the descriptive comparison across AI tools should be interpreted as prototype-level outputs rather than as empirically validated performance measures or evidence of added value over baseline approaches. Because the evaluation relied on two fictional prototyping scenarios and a small expert-oriented focus group (n = 6), the findings should be interpreted as evidence of prototype demonstration and qualitative refinement rather than of real-world effectiveness or organizational impact. The study also does not include a control group or comparison with traditional human coaching, so the added value of the AI-supported framework over alternative coaching arrangements remains a question for future empirical testing. Findings suggest that AI can usefully support organizational coaching by personalizing dialogue, structuring reflection, and generating auditable development artefacts, provided ethical safeguards and human oversight remain integral. The research contributes a preliminarily validated, ethics-informed, and governance-aware framework for AI adoption in organizational coaching and offers practical insights for embedding AI-enabled development in learning organizations. Full article

As artificial intelligence reshapes professional workflows, understanding what drives effective AI use among employees has become a critical concern for organizations. Moving beyond traditional technology acceptance frameworks, this study develops an integrative multi-level model to examine the behavioral determinants of AI use performance (AUP) among journalists. Drawing on the Technology Acceptance Model (TAM) and the Expectation Confirmation Model (ECM) and incorporating individual and organizational factors, a survey was conducted among 543 journalists in China. Hypotheses are tested via a hybrid PLS-SEM and artificial neural network (ANN) approach to capture both linear and non-linear relationships. The findings reveal that expectation confirmation significantly enhances AUP by driving perceived usefulness and satisfaction. Digital literacy, personal trust in AI, and organizational support positively influence AUP, whereas communication barriers exert the strongest negative effect. Demographic variables (gender, age, education) show no significant impact. Notably, the ANN sensitivity analysis identifies communication barriers as the most influential predictor overall, a finding not apparent from linear analysis alone. This study advances theoretical understanding of employee behavioral responses in AI-integrated professional contexts and offers practical insights into how organizations can foster effective employee–AI collaboration through targeted communication strategies and supportive infrastructure. Full article

Artificial intelligence (AI) is transforming the modern workplace by offering unprecedented opportunities to enhance employee creativity and organizational innovation. In the context of digital transformation, organizations are striving to ensure sustainable performance; however, research remains limited on how perceived AI fairness and attitudes toward AI jointly influence creativity. Grounded in Social Exchange Theory and the Technology Acceptance Model, this study proposes a moderated mediation model to examine how perceived AI fairness shapes employees’ attitudes toward AI and, in turn, their creativity, with gender acting as a moderator of the relationship between fairness perceptions and attitudes toward AI. Data were collected from 214 highly skilled employees from diverse cultural backgrounds working in technologically advanced environments. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal a positive association between perceived AI fairness and creativity. Attitudes toward AI partially mediate this relationship; however, gender does not exert a significant moderating effect. The findings highlight the importance of AI fairness, reinforced by positive attitudes toward AI, in enhancing employee creativity. They also underscore the need for responsible and equitable AI practices and provide context-specific insights into the ethical challenges of AI in socio-technologically vulnerable environments. Finally, the findings point to a shift toward a more egalitarian and inclusive organizational landscape, in which gender differences become less salient in the context of digital transformation. Full article

In high-demand financial environments, employees’ capacity to regulate and sustain personal energy may constitute a critical yet underdeveloped organizational resource. Drawing on the Job Demands–Resources (JD-R) model and Conservation of Resources (COR) theory, this study conceptualizes energy management as a multidimensional personal resource that may support adaptive functioning and innovation under demanding work conditions. Despite increasing conceptual attention to energy-related constructs, systematic scale validation and cross-level performance evidence remain limited. This research adopts a two-study design to develop and validate a multidimensional Energy Management Scale within financial institutions. Study 1 (N = 299 employees from 11 financial institutions) examines the factorial structure, reliability, and nomological validity of the scale. Confirmatory factor analysis is used to examine the proposed four-dimensional configuration of physical, emotional, mental, and spiritual energy. The scale demonstrates acceptable internal consistency reliability and evidence of structural validity, including convergent and discriminant validity. Structural modeling results reveal that overall energy management is positively related to innovative behavior and organizational citizenship behavior. However, perceived workload was significantly associated only with physical energy, suggesting that demand-related mechanisms of energy may not operate uniformly across energy components. Additionally, exploratory institution-level aggregation analyses showed preliminary, counterintuitive negative associations between mean organizational energy levels and return on equity (ROE) in some years. Given the limited number of institutional clusters, these cross-level findings are preliminary and intended to provide initial external criterion evidence rather than confirmatory causal inference. Study 2 (N = 148 employees from two institutions) further examines alternative scale versions and external validity through stress coping capacity, job satisfaction, and life satisfaction. Results were discussed to examine the robustness and predictive validity of the scale across samples. Collectively, this study advances energy management research by providing a psychometrically supported measurement instrument and preliminary multilevel evidence of its organizational relevance. The findings position energy management as a measurable human-capital resource with implications for sustainable workforce innovation and performance in financial institutions. Full article

Digitalization and artificial intelligence (AI) are seen as promising pathways for small and medium-sized enterprises (SMEs) to enhance performance while preserving environmental and social resources. This paper identifies organizational determinants of AI maturity that can enable SMEs to use AI in a more sustainable, responsible, and capacity-enhancing manner. AI adoption becomes relevant to sustainability not only because a company adopts advanced technology but because this technology is embedded in leadership practices, employee competencies, interdisciplinary collaboration, and organizational learning. From this perspective, perceived benefits and management commitment are not outcomes of sustainability but mechanisms that help explain how SMEs transition from technological awareness to building organizational capacity. Such capacity building can be a necessary prerequisite for subsequent sustainability-oriented outcomes, such as efficient resource utilization, employee upskilling, responsible AI management, and long-term resilience. We conducted a cross-sectional survey among 402 managers from Polish SMEs (62 micro, 193 small, 147 medium) across manufacturing, services and trade industries. Respondents (mean age ≈ 42.5 years) assessed perceived benefits of AI, engagement of top leadership, AI maturity and competitive pressure. Partial least-squares structural equation modeling revealed that perceived benefits strongly predicted leadership engagement (β = 0.647), explaining 62.8% of its variance. Perceived benefits (β = 0.384) and leadership engagement (β = 0.362) in turn were the key drivers of AI maturity, with the model accounting for 65.5% of variance in AI maturity. Competitive pressure positively but weakly moderated the relationship between perceived benefits and leadership engagement (β = 0.011), while its moderating effect on the relationship between perceived benefits and AI maturity was not significant (β = −0.008). These findings suggest that articulating clear benefits of AI and securing active leadership engagement are more decisive for advancing AI maturity than external competitive pressure. The contribution of the study is to integrate the perceived benefits of AI, top management commitment and AI maturity into a model, empirically validated and interpreted from a socio-technical perspective of sustainable digital transformation in SMEs, while quantifying the moderating role of competitive pressure in the under-researched context of Central and Eastern Europe. For practitioners, investing in awareness of AI’s benefits and developing committed leadership may yield more sustainable digital transformation than reacting solely to external pressures. Full article

Background/Objectives: Assessing population healthcare needs is essential for effective primary health care (PHC) planning; however, existing approaches often rely on biomedical or service-centered frameworks (i.e., approaches focusing on utilization patterns, clinical indicators, and provider performance metrics) that may not adequately capture the multidimensional and context-dependent nature of health needs. This study aimed to develop and validate the Primary Care Needs Assessment (PCNA) questionnaire, a participatory, multidimensional, and context-sensitive instrument for assessing perceived unmet healthcare needs and contextual determinants of health in community-based PHC settings. Methods: A sequential mixed-methods design was employed. In the qualitative phase, focus groups with PHC professionals and semi-structured interviews with community members informed item generation. The resulting questionnaire was administered to a sample of 817 participants recruited from community and primary care settings. Exploratory factor analysis (EFA) was conducted on a subsample (n = 520), followed by confirmatory factor analysis (CFA) on an independent subsample (n = 297). Internal consistency was assessed using Cronbach’s alpha. Results: EFA identified a 10-factor structure explaining 55.05% of the variance. CFA supported a refined 9-factor model with good fit indices (χ²/df = 1.675, RMSEA = 0.048, CFI = 0.92, TLI = 0.90, SRMR = 0.06). The instrument demonstrated satisfactory internal consistency (α = 0.76). Findings also highlighted unmet needs related to mental health, access to specialized services, and structural barriers (e.g., geographic distance, financial cost, limited service availability, and organizational constraints in accessing care), underscoring the multidimensional nature of health needs. Conclusions: The PCNA is a valid and reliable instrument that captures the complex interplay of individual, social, and contextual factors shaping health needs in PHC. By integrating community perspectives with psychometric validation, it provides a practical tool for supporting evidence-informed planning and more responsive, person-centered PHC systems (i.e., systems that adapt service provision to community-identified priorities and evolving population needs). Full article

Background: Role stress is common among frontline nurses and is associated with demanding work conditions and organizational contexts. High-performance work systems (HPWSs) represent bundled human resource management practices that may be relevant to nurse role stress. This study examined the association between perceived HPWSs and role stress and further evaluated the possible roles of psychological capital and professional identity in this relationship. Methods: A multicenter cross-sectional survey was conducted from May to October 2024 in 10 tertiary public hospitals across four Chinese cities. Frontline registered nurses were recruited using cluster sampling and completed an anonymous questionnaire assessing perceived HPWSs, role stress, psychological capital, and professional identity. Descriptive statistics, univariate analyses, and Pearson correlation analyses were performed. Indirect associations were tested using PROCESS with 5000 bootstrap resamples. Sensitivity analyses were conducted with additional covariate adjustment and after excluding the role clarity items from the HPWS measure. Results: A total of 2824 valid questionnaires were included. The mean role stress score was 2.88 ± 0.69. Perceived HPWS was negatively associated with role stress (B = −0.143, p < 0.001) and positively associated with psychological capital (B = 0.217, p < 0.001) and professional identity (B = 0.044, p = 0.028). Psychological capital was positively associated with professional identity (B = 0.191, p < 0.001). Bootstrap analyses showed significant indirect associations through psychological capital (effect = −0.075, 95% CI [−0.094, −0.056]), professional identity (effect = −0.008, 95% CI [−0.015, −0.001]), and their serial linkage (effect = −0.007, 95% CI [−0.011, −0.005]). The overall pattern remained broadly similar in the sensitivity analyses. Conclusions: Perceived HPWS was associated with lower nurse role stress, with significant indirect association patterns involving psychological capital and professional identity. These findings highlight the potential relevance of both individual psychological resources and organizational human resource practices in understanding nurse role stress. Full article

This study investigates the influence of artificial intelligence-driven sustainable human resource management (AI-SHRM) on employee job engagement and resilience, with a particular focus on the mediating role of relational contracts. Anchored in the social exchange paradigm, the study examines how the fulfillment of relational contracts fosters positive work outcomes, thereby enhancing overall organizational performance. Additionally, this research explores the role of perceived artificial intelligence decision-making (PAIDM) in amplifying these outcomes by promoting fairness and transparency within HR practices. Utilizing data from a three-wave field survey of 481 respondents in China, the findings reveal that AI-SHRM significantly enhances relational contracts, leading to increased job engagement and resilience. Moreover, PAIDM serves as a significant moderating factor, intensifying the positive effects by strengthening perceptions of equitable treatment. This research advances both theoretical and practical perspectives on AISHRM, relational contracts, and the role of AI-driven decisions in contemporary workplace dynamics, offering critical insights for future organizational studies. Full article

The rapid expansion of Generative Artificial Intelligence (GAI) is transforming higher education systems, particularly public institutions seeking to advance toward smart governance models and digital transformation. In this context, digital teaching competence emerges as a strategic factor for the effective, ethical, and pedagogically sound adoption of these technologies. This study assesses the level of digital competence among public higher education faculty in Paraguay and examines its predictive capacity regarding the adoption of GAI tools using machine learning models. A nationwide quantitative study was conducted with a sample of 800 faculty members from public universities across Paraguay. Data were collected through a structured questionnaire based on international digital competence frameworks, incorporating additional variables such as attitudes toward GAI, technological experience, institutional infrastructure, and perceived organizational support. Data analysis involved the application of machine learning techniques, including Logistic Regression, Random Forest, and Gradient Boosting, to identify the variables with the strongest predictive power regarding faculty readiness and willingness to integrate GAI into teaching practices. Model performance was evaluated using metrics such as accuracy, F1-scores, and the AUC-ROC. The findings identify key predictors of technological readiness and structural gaps within Paraguay’s public higher education system. This research provides empirical evidence from Latin America on the factors influencing GAI adoption in public sector educational contexts and contributes to the design of educational policies aimed at fostering smart universities and digitally sustainable academic ecosystems. Full article

Background/Aim: Cardiovascular disease (CVD) represents a relevant global public health challenge with dyslipidemia as a major modifiable cardiovascular risk factor (CVRF). Recent advances have introduced injectable lipid-lowering therapies (LLT). Their clinical effectiveness in real-world practice seems to depend not only on pharmacological efficacy but also on patients’ acceptance, adherence, and persistence, influenced directly by perceived barriers and facilitators. The main objective of this scoping review is to map the barriers and facilitators related to the use of novel injectable LLTs among adult patients with dyslipidemia or CVD. Methods: This review was conducted in accordance with JBI methodology and reported according to Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for scoping reviews (PRISMA-ScR); pre-registration on Open Science Framework (OSF) was performed. A search was conducted in MEDLINE from PubMed, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL) from EBSCOhost, and Google Scholar up to June 2025. Eligible studies included qualitative, quantitative, mixed-methods, and review papers involving adult patients with dyslipidemia who reported experiences, perceptions or challenges related to the use of injectable LLT in any healthcare or community setting worldwide. Two reviewers independently screened studies, selected and extracted data. Results: Out of 665 records identified, 7 studies met the inclusion criteria. Patients’ adherence to injectable LLTs is shaped by psychological fears, prior negative experiences, and perceived efficacy. Satisfaction increases when patients feel supported and informed. Convenience, self-administration, and motivational meaning facilitate persistence. Organizational support and economic accessibility further influence uptake, highlighting that adherence depends on both patient experience and structural factors. Conclusions: Patient acceptance and persistence with injectable LLT depends on a complex interplay of emotional, clinical, organizational and economic factors, beyond pharmacological efficacy alone. Fear of injections, previous statin-related experiences, administrative complexity, and high costs remain major barriers, while shared decision-making, trust in healthcare providers, perceived efficacy, regimen convenience, and supportive structures act as strong facilitators. Addressing these challenges requires multidimensional and multidisciplinary strategies for policy makers and clinical managers. Full article

Despite strong evidence that gender-diverse leadership improves organizational innovation and performance, women remain underrepresented in leadership pipelines worldwide, particularly in Asia. While prior research largely examines the outcomes of gender diversity at the firm level, far less is known about the psychological and social factors that shape women’s leadership aspirations in the first place. Addressing this gap, this study applies Social Cognitive Career Theory (SCCT) to explain how contextual support and developmental experiences influence women’s leadership aspirations in a collectivist business environment. Using survey data from 400 adult women in Indonesia and structural equation modelling, the study examines how parental involvement shapes personal mastery, how personal mastery strengthens leadership self-efficacy, and how self-efficacy, role models, and perceived leadership traits jointly predict leadership aspiration. The findings show that parental involvement indirectly contributes to leadership aspiration through personal mastery and self-efficacy, while role models and leadership traits also play significant roles. Among all predictors, self-efficacy emerges as the strongest driver of women’s leadership aspiration. This study makes three contributions. First, it extends SCCT beyond traditional STEM career research into the domain of leadership aspiration. Second, it provides rare empirical evidence from a collectivist Asian context, highlighting the role of family and social environment in shaping women’s leadership pathways. Third, it shifts the focus of gender diversity research from representation outcomes to the formation of the female leadership pipeline, offering actionable insight for educators, families, and organizations seeking to foster future women leaders. Full article

Corporate social responsibility (CSR) is increasingly adopted as a strategic tool to enhance firms’ sustainability and financial performance (CFP). However, despite extensive research, evidence on the underlying factors influencing CSR and CFP remains scarce. This study addresses this gap by exploring the role of employee engagement as one possible mechanism through which CSR initiatives may translate into CFP. Adopting a systematic literature review on papers published in 2019–2024 and a comparative case study methodology, the paper analyzes two Italian firms characterized by different configurations of CSR practices, including varying degrees of formalization and integration into organizational culture. The study leverages semi-structured interviews with management, employee surveys capturing perceptions of CSR and engagement, and firm-level financial indicators. The findings suggest that CSR contributes to CFP through some dimensions of higher engagement and only when CSR is perceived by employees as authentic and embedded in everyday organizational practices. The paper contributes to the literature on the factors influencing the relationship between firms’ CSR activities and CFP and the role played by employee engagement. Moreover, it offers implications for managers to design CSR strategies that create both sustainable and financial value. Full article