Strategies to improve recruitment, retention, working conditions, and skills among the long-term care workforce: An umbrella review of existing evidence.

The United States should treat STEM talent development as a core pillar of national security, but opportunities for STEM workforce training and education have not developed in a coordinated manner.

Advancing CAR-T Cell Manufacturing in Latin America: Current Landscape, Future Directions, and Challenges.

The Nigerian construction industry remains plagued by longstanding systemic deficiencies such as payment delays, low procurement transparency, weak record management, and limited digital maturity. While blockchain technology offers solutions through decentralisation, transparency, and automated verification, its adoption in Nigeria remains minimal. This study explores the critical success factors (CSFs) influencing blockchain adoption and their interactions in shaping implementation readiness. A systematic literature review and quantitative survey involving 218 respondents from various sectors were conducted. The study evaluated twelve CSFs across technological, organisational, environmental, and regulatory dimensions, with descriptive results showing moderate-to-high perceived importance. Using the DEMATEL method, the study identified cyber security, digital infrastructure, interoperability, and technical compatibility as the primary drivers, while organisational and environmental factors were found to be dependent. Regulatory clarity and government support were the most influential factors, highlighting their importance for large-scale implementation. The study recommends investment in digital infrastructure, regulatory sandboxes, blockchain standards, workforce development, and phased pilot projects for public procurement.

ABSTRACT Despite the devastating impact of COVID-19 and repeated calls for political commitment to health security, our analysis of 43 manifestos from 16 countries and the European Parliamentary elections revealed that only four parties made specific policy pledges on pandemic prevention, preparedness and response, with six providing brief mentions. The vast majority (33 parties) did not mention pandemic prevention, preparedness and response. When referenced, the pandemic was often framed as a rare, one-off crisis or an economic shock rather than a catalyst for systemic health reform. Some parties used it for political critique or validation of past performance, while others framed preparedness in terms of national security or economic resilience rather than public health. In contrast, manifestos overwhelmingly prioritized healthcare system expansion, equity, and access, with a significant emphasis on universal health coverage, mental health, and workforce development. The findings underscore a stark misalignment between global health priorities and domestic political agenda. Political reluctance to emphasize pandemic prevention, preparedness and response appears to be influenced by pandemic fatigue, voter preferences for forward-looking narratives, and institutional incentives favouring short-term tangible outcomes. This persistent neglect of the pandemic in electoral discourse raises concerns about the global community’s ability to sustain momentum for pandemic resilience. We call for stronger engagement between the global health community and political actors to elevate pandemic prevention, preparedness and response as a strategic, cross-cutting priority for future policymaking.

This study aims to investigate how structural forces and social support influence the career pathways of tourism students majoring in hotel business program in Thailand, focusing on their transition from academic training to professional employment within the tourism industry. The research intends to clarify the individual and combined influence of key variables on students’ satisfaction during internships, perceived readiness for industry demands, and long term commitment to tourism-related careers, and further explores contextual socio-cultural and institutional relations that mediates students’ adaptation and integration into the workforce. A quantitative approach was used via structured surveys distributed to 300 tourism bachelor’s students in the hotel business program in Phuket who had completed their internships. Stru ctural Equation Modeling (SEM) was employed to analyze causal relationships. The results reveal that both social (parental support) and structural factors (person-organization fit, internship quality, and abusive supervision) significantly affect internship satisfaction and industry commitment. The findings point out the importance of regional industry practices and social expectations in creating tourism workforce development. The discussion emphasizes how disparities in industry standards, societal perceptions of tourism careers, and familial attitudes toward service work collectively influence students’ career decisions. The findings suggest that building a sustainable tourism workforce, policy interventions should not only address organizational practices which are internship regulations and supervisory training, but also engage families and communities in more favorable directions around careers in tourism. Moreover, academic institutions should strengthen partnerships with the industry to encourage meaningful internships that enhance both skill development and affective commitment.

The therapeutic alliance, long regarded as a cornerstone of effective behavioral health treatment, remains difficult to measure and operationalize across diverse levels of care. This study examines how provider attachment style and related interpersonal characteristics—assessed through the Care Predictor Index (CPI), a 234-item psychometric instrument—predict patient retention outcomes across five behavioral health organizations. Drawing upon attachment theory, alliance research, and data from over six months of clinical practice, the study evaluates how therapist CPI scores correlate with treatment completion and discharges against medical advice (AMA) within detoxification, residential, partial hospitalization, intensive outpatient, and outpatient settings. The CPI integrates elements from the Adult Attachment Questionnaire (AAQ), the Counselor Activity Self-Efficacy Scales (CASES), and the Analog to Multi-Broadband Inventories (AMBI) to generate multidimensional provider profiles that capture attachment, confidence, and personality traits empirically linked to alliance formation. Findings demonstrate that therapists with CPI scores above 70 achieved higher treatment completion and lower AMA rates, underscoring the predictive validity of attachment-informed provider assessment. Beyond identifying measurable therapist level predictors, this analysis situates relational competence as a central determinant of program retention and proposes the CPI as a scalable mechanism for workforce development, quality improvement, and outcome optimization across the continuum of behavioral health care.

Background: As awareness of the possibilities for trans people to attain parenthood grows, trans, non-binary and other people with diverse genders are increasingly accessing perinatal care as part of their family-building journeys. International literature confirms that midwives can feel clinically challenged by, and poorly prepared for, working with pregnant trans people, but also that they are motivated to provide high quality care and desire professional support to do so. This two-phase study included interviews with trans people who were or had been pregnant, and/or whose partners were or had been pregnant, which informed the development of a nationwide perinatal care workforce survey. Aim: Phase Two aimed to identify current practice relating to inclusion, and the knowledge, beliefs and education needs of the perinatal care workforce in relation to working with pregnant trans people. Method: An online nationwide survey of perinatal care providers was undertaken in 2022. Data were collected through single- and multi-response questions, Likert scales and open-ended text boxes. Analyses included descriptive statistics and content analysis of open-text responses. Results: Of 476 respondents, this paper reports only the midwives’ responses (67%; n = 317). Fewer than 25% of midwives recalled receiving any specific education about providing culturally safe care for trans people, but most (78%) identified interest in accessing education if it were made available. Midwives are knowledgeable regarding some clinical aspects of gender affirming care, e.g., the effects of hormone therapy on fertility, but we identified some knowledge gaps. Most articulated positive attitudes towards caring for pregnant trans, takatāpui and intersex people but a minority raised concerns about what they perceived as the ‘erasure of women’ within wider efforts to be inclusive. Many noted workforce pressure as a barrier to progressing change. Conclusion: Some midwives are already implementing inclusive practices, primarily led by Lead Maternity Carers (LMCs) who champion affirming and inclusive community-based care. Ensuring that trans people and whānau can anticipate consistently affirming care when they engage in services beyond their LMC, particularly during hospital-based care, needs prioritisation as a workforce development strategy. To date, midwives have not been well prepared to provide inclusive care to this community, but they are willing to engage in education to support affirming and inclusive practice.

This study investigates the role of generative Artificial Intelligence (AI) in enhancing Apprenticeship Systems (ASs) by transforming Tacit Knowledge (TK) into Explicit Knowledge (EK), thereby improving Knowledge Transfer (KT) efficiency. A controlled experiment was conducted with 50 novice live-stream hosts, divided into the Experimental Group (EG) and the Control Group (CG). The EG used to train tools augmented with AI, while the CG used traditional methods. The experimental design included competency tests in seven areas, including on-camera presence, communication skills, and learning ability, and the use of statistical methods to compare the performance results of the two groups. The results established a significant improvement within the EG. The resultant indicators for expressiveness in shots (85 vs. 70), verbal expression (88 vs. 72), and learning capacity (86 vs. 71) exhibited statistically significant differences (p-values < 0.01). These outcomes suggest that the utilization of AI tools effectively enhances the development of various competencies, accelerates learning, enhances adaptability, and provides instant corrective feedback. The study's implication includes the utilization of AI in apprenticeship models, which have the potential for higher scalability, preservation of crucial TK, and workforce development, especially in industries that require Experiential Learning (EL).

National Statistical Offices (NSOs) are increasingly adopting new analytical practices to address growing demands for timely, granular and policy-relevant statistics. Among these, Non-Specialist Data Science (NSDS) has emerged as a strategic approach to expanding analytical capacity by enabling professionals without formal data-science training to conduct advanced analysis within secure institutional environments. This paper presents a comparative study of governance models for NSDS in three NSOs: the UK Office for National Statistics (ONS), France's National Institute of Statistics and Economic Studies (INSEE) in partnership with the Centre d’Accès Sécurisé aux Données (CASD), and Statistics New Zealand (Stats NZ). Drawing on documentary analysis and semi-structured interviews, the study explores how these organisations embed NSDS within the Generic Statistical Business Process Model (GSBPM) and complementary governance mechanisms such as the Five Safes. The findings highlight the importance of secure analytical environments, tiered access regimes, methodological oversight and structured capacity building in supporting expanded analytical participation without undermining statistical quality, confidentiality or institutional credibility. The paper argues that NSDS should be understood primarily as a governance transformation rather than merely a technical innovation, with implications for workforce development, organisational design and international standard-setting in official statistics.

Purpose This study explores the current state and challenges of metaverse research in emerging economies, evaluates its future potential across key sectors and introduces the Metaverse Platform for Apprenticeship, Collaboration and Training (MPACT) as a conceptual framework for tacit knowledge diffusion and workforce development in digitally immersive environments. Design/methodology/approach A bibliometric approach was employed to analyze metaverse research in emerging economies between 2005 and 2026, drawing on 4,337 peer-reviewed publications indexed in Scopus and Web of Science. Using visualization and mapping techniques, the study examined research outputs, collaboration networks and influential contributions, enabling the identification of key trends, existing challenges and future research directions. Findings The findings reveal that emerging economies such as China, India and the UAE are leading digital innovation in sectors like education, healthcare and cultural heritage through metaverse technologies. However, persistent digital infrastructure and institutional gaps in regions including Africa, Central Asia and Latin America continue to constrain equitable access and adoption. The MPACT platform holds considerable promise for tacit knowledge diffusion by utilizing immersive learning environments that enable realistic simulations, expert observation and guided mentorship, thereby facilitating cross-border skill development and collaboration between emerging and developed economies. Research limitations/implications While the study offers valuable insights into the metaverse's role in emerging economies, its scope is bounded by the reliance on bibliometric methods, which are effective for mapping patterns and thematic linkages but are not designed to address causal relationships, empirical validation or technical implementation. The proposed MPACT framework for tacit knowledge diffusion makes a conceptual contribution, though it remains at a theoretical stage without mathematical modeling or empirical application, thus offering a foundation for future research. Practical implications Metaverse adoption in emerging economies calls for context-sensitive strategies that emphasize infrastructure development, digital literacy and workforce training in immersive technologies and content creation. The MPACT framework supports this by enabling experiential learning through virtual apprenticeships, with public-private partnerships driving scalable, inclusive pilot programs aligned with regional needs and human capital priorities. Originality/value This analysis provides key insights for business leaders, policymakers, IT developers and stakeholders in emerging economies to stay updated on metaverse trends and invest in workforce skills. By promoting frameworks like MPACT, it supports inclusive, ethical approaches that drive sustainable growth, digital transformation, experiential virtual apprenticeships and scalable pilot programs through public–private partnerships aligned with regional needs.

To describe the characteristics of effective workforce and staffing culture among doctors and nurses at two tertiary hospitals in Jamaica, and to explore perceptions of senior managers relating to the health workforce for the delivery of quality care. A mixed-methods study was done among 216 nurses and 112 doctors, and 17 senior managers. Data on patient safety culture and the effective workforce component were collected for quantitative component. In-depth interviews were done for the qualitative component. Quantitative data were analyzed using descriptive and inferential statistics, and qualitative data were thematically analyzed and compared with selected elements of the quantitative data. Staffing culture for patient safety among doctors and nurses was poor (35% positive score). More nurses (73.6%) than doctors (34.8%) reported working 40-59h per week. A higher proportion of nurses (85%) than doctors (67.9%) practiced responsibly with consideration of fatigue and human factors (p = 0.001), with a significant difference by institution (Institution A - 75.0%, Institution B - 81.6%; p = 0.009). Fewer than 70% of respondents reported receiving annual performance appraisals. Qualitative findings revealed issues with staff capacity development, performance management, and persistent staffing challenges, which contributed to gaps in staffing culture for patient safety. Staffing culture for patient safety was suboptimal among doctors and nurses. Key challenges identified by senior managers include inadequate staffing, limited capacity development, and weak performance appraisal systems. Strategic investment in workforce development, effective performance management, and evidence-based staffing policies is critical to strengthen clinical governance and achieve quality health care delivery.

Purpose This study aims to develop and validate a multidimensional scale to measure environmental, social and governance (ESG) awareness among frontline production employees, addressing a critical gap in understanding how ESG principles are perceived and enacted at the employee level. Design/methodology/approach A theory-driven approach was used to design a 12-item scale grounded in social cognitive theory, moral action model and ethical climate theory. Data were collected via anonymous questionnaires from 486 production workers in China’s Baijiu manufacturing sector. The scale was tested using exploratory factor analysis and confirmatory factor analysis to establish its factorial structure, reliability and validity. Findings Results confirmed a robust three-factor structure corresponding to ESG awareness. The model demonstrated excellent fit indices (e.g. comparative fit index = 0.998, root mean square error of approximation = 0.012) and strong internal consistency. The scale captures cognitive, emotional and normative dimensions of ESG engagement. Practical implications The scale provides organizations with a tool to assess and enhance employee-level ESG alignment, supporting ESG reporting, workforce development and sustainable operations. Originality/value This research contributes a novel, psychometrically validated instrument that integrates ESG theory with employee behavioral measurement, offering new insights for embedding sustainability from the ground up.

The African region has experienced significant growth in health workforce development due to concerted efforts and investments. This progress has improved access to healthcare services and addressed critical shortages of health workers. However, the region still struggles to meet the Sustainable Development Goal (SDG) indicator threshold of 44.5 medical doctors, nurses, and midwives per 10,000 population. An estimated deficit of 6.1 million health workers is anticipated by 2030 unless urgent actions are taken. This shortage is exacerbated by increased health worker migration, driven by the demand in high-income nations and the dual challenges of an ageing workforce and population. Addressing the factors driving healthcare worker migration is crucial to strengthen local healthcare systems and ensure quality medical services. Weak mechanisms for tracking health worker migration, due to limitations in health planning and workforce information systems, impede understanding of this situation. Countries in the African region can undertake initiatives such as pursuing mutually beneficial bilateral or multilateral agreements to manage international migration of health workers. Additionally, harnessing the potential benefits of migrant health workers in improving health systems and protecting their labour rights is essential. African countries should conduct thorough health labour market analyses to plan the production, funding, employment, and retention of sufficient health workers. Exploring contextual factors and policies that influence health workers' choices and potential incentives to encourage the return of migrant health workers is also vital. Dialogues among internal stakeholders and between countries can lead to mutually beneficial mechanisms for skills exchange and proportionate investment.

Artificial intelligence (AI) is a transformative technology used in various industrial sectors including healthcare. In pharmacy practice, AI has the potential to significantly improve medication management and patient care. This review explores various AI applications in the field of pharmacy practice. This review evaluates the integration of AI tools such as IBM Watson, Medisafe, ScriptPro, and BenevolentAI into various pharmaceutical functions, including drug discovery, medication management, clinical decision support, pharmacovigilance, and inventory systems. AI applications in pharmacy contribute to optimizing operations by automating prescription verification, predicting medication adherence, minimizing dispensing errors, and enabling real-time inventory control. The integration of AI in pharmacy has the potential to improve patient safety, reduce medication errors, and enhance the overall quality of care. However, challenges such as data standardization, regulatory frameworks, and workforce development must be addressed to ensure the successful adoption of AI in pharmacy practice. This review provides insights into the current state of AI in pharmacy and its future directions.

This study examines how the In-Country Value (ICV) strategy affects Omanisation and human capital development in Oman’s oil and gas sector. Based on the resource-based view, the research uses a descriptive approach and surveys 65 purposively selected employees from four major companies. Partial least squares structural equation modelling (PLS-SEM) shows that ICV initiatives significantly improve in-job training and Omanisation outcomes, accounting for over 70% of the variance in workforce qualification. The findings add to the literature on local content policies by demonstrating how ICV can build dynamic capabilities and competitive advantage in emerging economies. Practical implications for policymakers and industry leaders are discussed. The study finds a positive link between the acceptance of training and development initiatives, such as In-Job Training, the Omanisation Plan, and the ICV strategy, thereby supporting the overall enhancement of Omanisation and the training and development of the Omani workforce. These results confirm the effectiveness of implementing ICV strategies in promoting workforce development and aligning with the country's value strategy objectives. The research offers valuable insights for policymakers, industry practitioners, and researchers interested in ICV and human resources development within the context of Oman.

Background/Objectives: Clinical instruction and mentorship are essential components of nursing education and early professional development. In Greece, while nursing curricula align with EU directives mandating both theoretical and clinical training, significant gaps persist in the quality, coordination, and legislative support of mentorship. This work aims to (i) synthesise evidence on clinical instruction and mentorship in Greece and draw on selected European examples to provide contextual insight, and (ii) integrate national stakeholder perspectives to generate actionable recommendations for a Greek clinical mentorship framework. Methods: A narrative literature review was conducted, identifying 19 eligible articles examining mentorship, clinical instruction and preceptorship in European and Greek contexts. In addition, a national stakeholder focus group with 25 participants, including representatives from academia, healthcare institutions, regulatory bodies, and nursing associations, was held in Athens in 2024. Data from both sources were thematically analysed and integrated to identify gaps, best practices, and context-specific recommendations. Results: Findings revealed inconsistent collaboration between universities and clinical institutions, limited training and recognition for clinical instructors, and the absence of a unified national framework. Stakeholders highlighted structural barriers to clinical mentoring such as understaffing and lack of policy support and expressed strong interest in a mentorship reform. Comparative analysis with European models demonstrated feasible pathways for Greece, including structured training, certification, and non-financial incentives. During the national stakeholder focus group, a dual-pathway mentorship system tailored for nursing students and newly hired nurses was most recommended to ensure both continuity and quality in professional development of nurses. Conclusions: Despite alignment with EU directives, Greece lacks an integrated national mentorship framework that ensures consistent clinical learning and supports workforce development. Two priority policy actions emerge from this work: (1) establishing a legally supported national certification and training system for clinical mentorship, and (2) educational structures in the clinical setting to improve educational quality, workforce retention and patient care outcomes.

Technical and Vocational Education and Training (TVET) plays a vital role in workforce development and sustainable economic growth globally. This review examines challenges affecting TVET quality and employability, including skill gaps, curriculum and teaching limitations, institutional barriers, and prevalent perception issues. It highlights the increasing integration of digital innovations such as augmented reality and digital pedagogy, alongside Industry 4.0 competencies, to address these challenges. The review synthesizes strategies for enhancing TVET quality through curriculum reform, industry collaboration, digital pedagogy enhancement, and enrollment interventions. Furthermore, it emphasizes TVET's contribution to sustainable development goals through the embedding of green skills and its positive impact on employment outcomes. The findings underscore the need for coherent policy frameworks aligning TVET with evolving labor markets and sustainability priorities to foster inclusive growth and workforce readiness.

Artificial intelligence (AI) is driving discovery, innovation, and economic growth across most sectors and has the opportunity to transform society by addressing important grand challenges, such as predicting and managing natural disasters or disease outbreaks, and developing cures for diseases. While AI provides opportunities for major positive impact, it also has the potential to lead to negative social, environmental, and economic consequences if it is not pursued responsibly. To ensure the responsible progress of AI, specific consideration must be given to ensure the development, access, and impacts of AI are broad and inclusive. Such a democratization of AI is only possible through partnerships that bring together workforce development, research, and cyberinfrastructure resources, along with appropriate policies and regulations to ensure safe and ethical use. These partnerships must be supported by diverse teams of researchers with different perspectives and approaches, and through engagement with the broader public. In this paper, we explore the importance of democratizing AI research and innovation and the role of democratizing access to advanced cyberinfrastructure, including high-performance computing, in achieving this goal. Specifically, we introduce the University of Utah’s Responsible AI Initiative (One-U RAI) as a concrete example and discuss a recent effort aimed at achieving these goals through public-private partnerships across government, academia, and industry. The One-U RAI provides the framework for responsible, transdisciplinary AI development for societal impact in the areas of environment, health, and education, and is built upon a foundation of research expertise, advanced cyberinfrastructure, and community engagement to catalyze excellence in responsible AI.

Background: Rural youth make up 70 % of India’s population, yet they remain excluded from many modern jobs because of long standing deficits in quality education, vocational training and digital infrastructure. As artificial intelligence (AI) accelerates automation and digitization, it simultaneously threatens low skilled employment and creates opportunities for adaptive learning platforms and remote mentorship. A persistent rural urban divide in digital literacy and internet access complicates the uptake of such technologies. Review: The literature indicates a split between digital and sector specific upskilling initiatives. Digital platforms such as the India Digital Hub use AI powered recommendation engines to personalize learning and better align training with labor market needs. Sectoral programs, including agropreneurship and vocational education, incorporate AI tools for precision agriculture but struggle with outdated curricula and social biases that favour white collar work. Studies emphasize that without systemic interventions, AI benefits may remain unevenly distributed and leave rural youth vulnerable to cyclical unemployment. Methodology: This review followed PRISMA guidelines and searched five databases (IEEE Xplore, Scopus, ACM Digital Library, Web of Science and Google Scholar) using clustered keywords around AI technologies, skill development, rural youth and the Indian context. The initial search produced 823 records; after removing duplicates and irrelevant entries, 433 remained. Title and abstract screening excluded 326 studies, leaving 73 for full text review. Ultimately, 15 studies met the inclusion criteria. Results: AI driven platforms show promise in bridging geographical barriers and tailoring learning to local labour markets. However, their success depends on reliable connectivity, vernacular content and community-based mentorship. Sector specific initiatives demonstrate the potential of AI in precision agriculture but are hampered by access to capital and entrenched perceptions about vocational careers. Across studies, there is consensus that scalable models must connect localized training with evolving labour market demands. Conclusion: AI can transform rural workforce development but may also deepen inequalities if implemented without attention to digital literacy, infrastructure and sociocultural context. Vernacular AI tools and hybrid learning models offer inclusive potential, yet effective deployment requires ethical frameworks, participatory design and flexible policies that accommodate regional diversity. Future research should prioritise longitudinal studies and subnational analyses to inform targeted interventions.