Mobile Technology and Public Health Organizational System

Information technology has a transformation power and it enables to conquer complexity (Glaser, 2013). According to Trochim et al.(2006) Public health system is very complex. Recently with a wide spread of mobile technology globally, public and private health systems have also seen its rapid growth and integration targeting to reduce the existing complexity, costs, human errors and as a result to simplify the processes, increase health professionals mobility and improve patient outcomes. The aim of this paper is to review the socio-economic impact, benefits and challenges of mobile technology integration into the public health system for all the stakeholders and to identify whether it simplifies their existing problems or “complexifies” them

Teacher's conceptions and practices related to gifted education in Kazakhstan

Conceptions of giftedness are culturally grounded and differences on the ways that cultural groups define and describe giftedness are evident (Cahallan, 2009; Sternberg, 2007; see Phillipson & McCann, 2007). Cultural conceptions of giftedness largely determine the procedures for the identification and education of gifted students on that cultural group. The conceptions and beliefs that teachers hold about giftedness have a significant impact on the education of gifted students. Then, a closer examination of how teachers understand giftedness and how their beliefs, attitudes and expectations shape their classroom practices related to talent development is needed in Kazakhstan

Strengthening the ICUs' human resource-related responses to Covid-19: A rapid review of the experience during the first year of public health emergency

By drawing on macro-categories of key human resource (HR) management interventions recommended by the Organization for Economic Co-operation and Development (OECD) during the Covid-19 pandemic, this study aimed to explore whether and how Intensive Care Units (ICU) have strengthened their HRs during the first year of Covid-19 emergency. A rapid review was conducted to provide a quick synthesis of the literature in English identified in the Web of Science Core Collection (WoS), PubMed, and Scopus databases. A total of 68 articles qualified for the final analysis. The findings illustrated that health organisations were often guided by staffing ratios to estimate capacity to care, aimed to modify the scope of practice of providers, redeployed both internal and external staff to ICUs, created and adapted the Covid-19-specific staffing models, and implemented technological innovations to provide services to the unprecedented number of patients while protecting the physical and mental health of their staff. The insights of this research should be helpful for health leaders, HR Managers, and policymakers who have faced unprecedented challenges and tough decisions during this emergency. The findings could also inform beyond-Covid-19 ICU policies and guide future research

Are teachers biased when nominating students for gifted services? Evidence from Kazakhstan

The purpose of this experimental, vignette study was to analyze whether certain demographic characteristics of students (i.e. gender, ethnicity, and socioeconomic status) influence secondary education teachers in referring students for gifted services in Kazakhstan. A sample of 132 teachers were randomly assigned to one of eight profiles describing a typical gifted student with particular demographics and requested to indicate how strongly they believed the student should or should not be recommended for gifted services. Results evidenced that gender, ethnicity, and SES did not influence the Kazakhstani teachers’ referrals. The implications of teacher nominations in students’ identification for gifted programs and the discussion on the role of gifted education as perceived by school teachers in Kazakhstan and elsewhere are provided

Artificial intelligence in health‐care: implications for the job design of healthcare professionals

The adoption of Artificial Intelligence (AI) in the healthcare sector is growing, and AI-based technologies are envisioned to affect not only patient care but also how healthcare professionals work. Nevertheless, the actual impact of various AI applications on healthcare professionals’ jobs has not been studied yet. Bringing together a framework to analyse AI applications in health-care and the job design model, we analysed 80 publications from the grey-literature platform ‘SingularityHub’. Our findings demonstrate that AI applications in 1) diagnosis and treatment, 2) patient engagement and empowerment and 3) administrative activities have an impact on the various components of healthcare professionals’ job design, including job autonomy and control; skill variety and use; job feedback; social and relational aspects; and job demands. Implications for future research and practice are discussed

Teacher's conceptions and practices related to gifted education in Kazakhstan

Conceptions of giftedness are culturally grounded and differences on the ways that cultural groups define and describe giftedness are evident (Cahallan, 2009; Sternberg, 2007; see Phillipson & McCann, 2007). Cultural conceptions of giftedness largely determine the procedures for the identification and education of gifted students on that cultural group. The conceptions and beliefs that teachers hold about giftedness have a significant impact on the education of gifted students. Then, a closer examination of how teachers understand giftedness and how their beliefs, attitudes and expectations shape their classroom practices related to talent development is needed in Kazakhstan

3T Framework for AI Adoption in Human Resource Management: A Strategic Assessment Tool of Talent, Trust, and Technology

Artificial intelligence (AI) is steadily entering and transforming the management, work, and organizational ecosystems. We observe AI-based applications assisting employees in daily tasks, project management, decision-making, and collaboration. AI applications are increasingly assisting also Human Re-source Management (HRM) in undertaking time-critical tasks and managerial and administrative decision-making. However, more in-depth and comprehensive studies are needed to understand the specific factors affecting the full adoption of AI technology from a multi-level viewpoint and address the potential limitations of AI appropriation or its adverse outcomes in HRM.The purpose of this study is to investigate the conditions in which human talent may take advantage of the unique opportunities offered by AI. However, whereas previous studies were conducted on the individual perception of AI and technology readiness or adoption, an integrated approach aiming to combine talent management-related dimensions and managerial-related dimensions is still not avail-able. For this research gap, we build a strategic management assessment frame-work of the driving factors of Talent, Trust, and Technology (3T) in AI adoption in HRM. We investigate the impact of these trends on the human-related and technology ecosystems and provide an integrated analysis of individual micro (talent management) organizational macro (trust and technology) adoption of AI technology.The paper advances the current definition and understanding of individual human facilitators and impediments behind the ability to speed up the adoption of AI-based technology. The practical contribution can facilitate the human-centered and trustworthy design and adoption of AI