Future Work Research Articles

Strategies for Career Readiness in the Age of General Artificial Intelligence

Abstract: As artificial intelligence and automation continue to rapidly transform work and skills requirements, preparing both current and future workers for careers in this evolving landscape is imperative. This practitioner-focused research brief explores strategies for developing career readiness in the age of advancing technologies like general AI. Through a review of relevant literature on forecasting AI's labor market impacts and in-demand future skills, key competencies are identified that complement human strengths versus automatable tasks. These include social-emotional abilities, creative and analytical problem-solving, and digital/technical fluency. The brief then outlines evidence-based approaches for cultivating these skills throughout education and careers, such as embedding complementary skills training, investing in lifelong learning pathways, leveraging mentoring, and fostering a growth mindset. Practical organizational examples demonstrate how leading companies are proactively implementing such strategies. The brief concludes that a focus on essential human capabilities empowered by technology portends continued meaningful work and career prosperity.

New Trends in Migration from Kyrgyzstan to the Russian Federation

In recent decades, population migration has become one of the main components of socio-economic development of Kyrgyzstan. In recent years, Kyrgyz citizens have been working in Russia and Kazakhstan. A comparative analysis of the number and structure of flows of Kyrgyz labour migrants is carried out on the basis of data from a sample national survey of household budgets, the National Statistical Committee of Kyrgyzstan, the Federal Migration Service of Russia, the Main Directorate for Migration Issues of the Ministry of Internal Affairs of Russia, and Rosstat. The key problems of the social and legal situation of Kyrgyz migrants in Russia were identified: lack of registration at the place of stay, restriction/ ban on entry, non-payment of wages, access to medical care, and receipt of pensions. Gradually, under the influence of external and internal factors, new trends of labour migration to the Middle East and the Persian Gulf, the Republic of Korea and Japan, Europe and America have emerged. Migration flows are becoming more and more organised, as they involve the country's public authorities, private employment agencies, international companies and other actors. The study shows that the key needs for Kyrgyz migrant workers in the near future are concentrated in the following regions (in addition to traditional destinations): first, Western European countries (Great Britain and Germany); second, East Asia (Republic of Korea and Japan); third, Eastern European countries (Poland, Hungary, Bulgaria); fourth, the Middle East (Turkey and the Gulf countries); fifth, Northern Europe (Sweden and Finland). The official discourse in Kyrgyzstan is increasingly gaining momentum on the need to transform migration policy from large-scale export of labour resources to employment of surplus labour resources within the country by creating new jobs and expanding production. New ideological approaches to the transition of Kyrgyzstan from the category of countries– exporters of labour resources to the category of countries actively developing their own production and labour market are practically formed.

The relationship between cognitive emotion regulation strategies and emotional manipulation among health colleges students: a cross-sectional correlational study.

Emotional intelligence is commonly associated with career success. Employees with higher emotional intelligence tend to reap greater benefits. However, emotional manipulation has been reported as a dark side of emotional intelligence, which refers to the self-perceived ability to control the emotions and actions of others for self-benefit. Healthcare professionals with high emotional intelligence often improve the overall patient experience. However, their ability to manipulate emotions can have a detrimental impact on the quality of treatment. This cross-sectional correlational study assessed cognitive emotion regulation strategies (CER) and emotional manipulation among students of health colleges. Two instruments were used to collect the data: 1) the emotional manipulation scale and 2) the cognitive emotion regulation questionnaire. A total of 362 students from health colleges responded to the questionnaire. The students had a moderate tendency to use emotional manipulation (25.09 ± 6.79 out of 50). The most frequently used CER strategies included adaptive strategies such as positive reappraisal with a mean score of 7.45 ± 2.15 out of 10 and maladaptive strategies such as rumination with a mean score of 7.33 ± 2.23 out of 10. The emotional manipulation score had a small but statistically significant negative correlation with two adaptive CER strategies: positive refocusing (r = -0.146, p = 0.005) and focus on planning (r = -0.144, p = 0.006). This study sheds light on the relationship between CER strategies and emotional manipulation, suggesting that poor use of adaptive strategies is associated with emotional manipulation. This finding highlights the importance of designing interventional programs that improve the ability of health colleges students to regulate their cognitive and emotional responses, thus improving their overall well-being and performance as future healthcare workers.

Analysis of the impact of pre-professional education on the health of medical students

The solution to the problem of the observed deterioration in the health of students in medical universities is currently very acute, since it is directly related to the productivity of future medical workers and determines the stability of the country's health care system.The aim of the study is to assess the health status of students of the N.V. Sklifosovsky Institute of Clinical Medicine of Sechenov University using the example of graduates of the Resource Center "Medical Sechenov Pre-University" of the Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation in comparison with graduates of other educational institutions. Methods: the authors conducted an analysis of the literature on the problem of morbidity among students and a one-time selective comparative study of the morbidity level of students of the N.V. Sklifosovsky Institute of Clinical Medicine of Sechenov University. To identify reliable differences between the studied characteristics, Student's t-test was used.Results. The study showed an increase in the overall morbidity of students by the sixth year, while it was less pronounced (by 10%) among Pre-University graduates. The study showed a change in the structure of morbidity by the sixth year of study: in the first year, the leading positions are occupied by diseases of the eye and its adnexa, diseases of the musculoskeletal system and connective tissue, mental disorders and behavioral disorders, while in the sixth year, diseases of the eye and its adnexa remained the leading ones in the structure of diseases, and the second and third places were occupied by diseases of the respiratory system and the genitourinary system. The revealed results, in the form of a decrease in the overall morbidity among the Pre-University graduates by the 6th year of study are presumably the outcome of previously conducted work in the process of their training at the stage of pre-professional education which was cinducted to form a health culture based on the principles of promoting a healthy lifestyle and giving up bad habits which increase the risks of health disorders.

Education of Future Language Workers: Supporting Students’ Startups as a Teaching Strategy

The article discusses the role of student start-ups in general and their introduction into the academic curriculum as graduation projects in particular. The paper provides an overview and short history of the student start-up as a concept and the term, underlining, on the one hand, a contemporary demand for student entrepreneurship encouragement, their social capital built-up and University-industry collaboration but problematic ambiguity of their realization, on the other. The authors claim the innovations as it goes is most challenging for both teachers and students of non-business academic programs and requires a certain shift in teaching strategies as well as the curriculum. The paper dwells on the existing background of student start-ups in non-business fields and underlines that in such circumstances teaching and extracurricular activities become a major tool to promote the entrepreneurial intentions among the students. The authors claim the academic training can benefit from a suchlike approach and the transdisciplinary projects may serve as a practice-oriented cumulative ground for student start-ups. The paper illustrates how these projects can be implemented. The authors have stepped up their efforts towards introducing a student start-up to show how a certain student project can later launch them into business resulting in creating a new venture.

Wet bulb globe temperature from climate model outputs: a method for projecting hourly site-specific values and trends.

Increasing temperature will impact future outdoor worker safety but quantifying this impact to develop local adaptations is challenging. Wet bulb globe temperature (WBGT) is the preferred thermal index for regulating outdoor activities in occupational health, athletic, and military settings, but global circulation models (GCMs) have coarse spatiotemporal resolution and do not always provide outputs required to project the full diurnal range of WBGT. This article presents a novel method to project WBGT at local spatial and hourly temporal resolutions without many assumptions inherent in previous research. We calculate sub-daily future WBGT from GCM output and then estimate hourly WBGT based on a site-specific, historical diurnal cycles. We test this method against observations at U.S. Army installations and find results match closely. We then project hourly WBGT at these locations from January 1, 2025, to December 31, 2100, to quantify trends and estimate future periods exceeding outdoor activity modification thresholds. We find regional patterns affecting WBGT, suggesting accurately projecting WBGT demands a localized approach. Results show increased frequency of hours at high WBGT and, using U.S. military heat thresholds, we estimate impacts to future outdoor labor. By mid-century, some locations are projected to average 20 or more days each summer when outdoor labor will be significantly impacted. The method's fine spatiotemporal resolution enables detailed analysis of WBGT projections, making it useful applied at specific locations of interest.

Functional analysis of cyclic diguanylate-modulating proteins in Vibrio fischeri.

As bacterial symbionts transition from a motile free-living state to a sessile biofilm state, they must coordinate behavior changes suitable to each lifestyle. Cyclic diguanylate (c-di-GMP) is an intracellular signaling molecule that can regulate this transition, and it is synthesized by diguanylate cyclase (DGC) enzymes and degraded by phosphodiesterase (PDE) enzymes. Generally, c-di-GMP inhibits motility and promotes biofilm formation. While c-di-GMP and the enzymes that contribute to its metabolism have been well-studied in pathogens, considerably less focus has been placed on c-di-GMP regulation in beneficial symbionts. Vibrio fischeri is the sole beneficial symbiont of the Hawaiian bobtail squid (Euprymna scolopes) light organ, and the bacterium requires both motility and biofilm formation to efficiently colonize. C-di-GMP regulates swimming motility and cellulose exopolysaccharide production in V. fischeri. The genome encodes 50 DGCs and PDEs, and while a few of these proteins have been characterized, the majority have not undergone comprehensive characterization. In this study, we use protein overexpression to systematically characterize the functional potential of all 50 V. fischeri proteins. All 28 predicted DGCs and 14 predicted PDEs displayed at least one phenotype consistent with their predicted function, and a majority of each displayed multiple phenotypes. Finally, active site mutant analysis of proteins with the potential for both DGC and PDE activities revealed potential activities for these proteins. This work presents a systems-level functional analysis of a family of signaling proteins in a tractable animal symbiont and will inform future efforts to characterize the roles of individual proteins during lifestyle transitions.

Intention to use personal health record system and its predictors among chronic patients enrolled at public hospitals in Bahir Dar city, northwest Ethiopia: using modified UTAUT2 model.

Chronic diseases are the leading causes of death in the world. In sub-Saharan Africa, it leads to more mortality than almost every other region in the world. Currently, digital health technology like personal health records plays a crucial role in managing patients with chronic diseases. In low-resource countries like Ethiopia, it is uncertain how many chronic patients intend to use PHRs and the accompanying circumstances. Hence, the aim of this study was to assess chronic patients' intention to use PHRs and its predictors enrolled in public health hospitals in Bahir Dar city, northwest Ethiopia. An institutional-based cross-sectional study was conducted among 924 respondents from April 5 to May 9, 2023, in Bahir-Dar city public hospitals. A stratified sampling technique followed by a systematic sampling technique was applied to select the study participants. An interviewer-administrated questionnaire was conducted using Kobo Collect. A UTAUT2 model was applied to develop theoretical frameworks. SPSS version 25 software was used to estimate the descriptive statistics, and the structural equation model analysis was used to evaluate model constructs using AMOS version 21 software. In this study, a total of 908 study subjects participated. The proportion of chronic patients' intention to use PHR was 46.7% [95.0% CI (43.4-50.1)]. According to the findings, performance expectancy (β = 0.259, p-value <0.001), effort expectancy (β = 0.214, p-value <0.001), social influence (β = 0.174, p-value <0.001), and facilitating condition (β = 0.114, p-value <0.01) had a significant effect on the intention to use PHRs. Generally, the overall intention to use PHR was low. Our finding illustrates that the effects of performance expectancy, effort expectancy, social influence, and facilitating conditions had a positive effect on patients' intentions to use PHRs. The effect of effort expectancy on the intention to use a PHR was positively moderated by age. Since the findings of this study would help policymakers and programmers to future academics interested in this area and insight to future research workers. Therefore, implementers should focus on improving patient capacity, motivating users, and raising awareness regarding PHR.

Профессионально-образовательная мобильность современной молодежи: современное понимание и ключевые тенденции

The article examines issues that cover the subject field of the essence of professional and educational mobility of modern youth, its types, as well as the factors that support and stimulate it. Particular attention in the research process is paid to the career scenarios that underpin professional and educational mobility. The features of employment and professional education in the traditional and new economy are outlined. In addition, the emphasis is placed on the synergetic paradigm, within which a modern understanding of the category of professional and educational mobility is developing. Practical aspects of the mobility of the younger generation in Russia are considered using the results of a sociological survey conducted by the Institute of Sociology of the Russian Academy of Sciences. Conclusion dwells upon the fact that professional and educational mobility of young people contributes to increasing the competitiveness of future workers in the labor market, which is associated with career scenarios, requirements, favorable social and organizational factors that contribute to the fastest integration into a new community.

Future of Work: The Impact of Intelligent Technologies for Leaders and Knowledge Workers

The future of work (FOW) is being influenced by emerging technologies such as machine learning, artificial intelligence (AI), and predictive analytics. With 89% of businesses adopting digital strategies, experts predict that AI will enhance productivity and proficiency over the next decade. However, concerns about the impact of AI on employment and the workforce remain. The pace of AI development contradicts stakeholder expectations, leading to uncertainty about AI automation, competitiveness in local markets, online disruptions, job and skill redesign, and high pressure on the workforce. AI has shown benefits in automating processes and improving productivity, quality, and reliability. Descriptive analytics tools like Office 365 Delve (O3D) can help reinforce working relationships, improve work-life balance, and support communication. However, there is a gap between organizations and employees when it comes to adopting new technology tools. A case study was conducted at Achievers Point University (APU) to examine the use of O3D, its impacts, and user perceptions. The results showed that non-users do not trust the implementation of O3D, but users who use it effectively view output accuracy as well as input. In terms of well-being and trust, 62% of respondents trust O3D as a tool for improving work performance in time management and capturing work activity data. The findings from this case study can inform C-suite executives, decision-makers, and business leaders about developing strategies to mitigate risks during technology implementations

A Novel Job Similarity Index for Career Transition in the Mining Industry

In this study, with the primary goal of capturing ongoing digital transformation and automation impacts on the mining industry and its workforce, we conduct several interviews with mining industry experts in the USA and analyze our survey reports qualitatively and quantitatively through exploratory analysis. After the interpretation of the insights of industry experts, we proceed to generate a personalized and customized data analysis through a novel metric based on skills, knowledge, competencies, and occupational requirements, which quantifies the job similarities for occupations in the mining industry based on the publicly available database of the United States Department of Labor. We utilize text analytics to tokenize and classify the interviews to capture a better understanding of major response categories. The temporal analysis shows that the critical competency needs in the data science and autonomy category increases from 28% in current demands to 43%. In defining our metric, we also calculate Kullback–Leibler (KL) divergence for each job profile that enables determining whether and to what extent that job is transitionary in our test set based on the mean, standard deviation, and kurtosis of each job of interest. Our analysis reveals that the in-group job transitions are significantly easier than the between-group transitions, proving our initial assumptions and common sense. The generated heat maps provide the opportunity to present the gap between the current job and desired job profiles that provide feasible career change options, among others, offering individualized career paths for job seekers and promoting potential job transitions. Through the collection of industry-specific individual employee data, the AI system is envisaged to continue to learn as end users engage with the system, thus creating a central data hub specifically for the future workforce in the mining industry. Although the study has limitations on generalizability for qualitative assessments, it presents itself as a valuable application of how qualitative and quantitative approaches could be of value for future worker training in the mining sector.

The future of work of academics in the age of Artificial Intelligence: State-of-the-art and a research roadmap

The Future of Work (FoW) has garnered significant attention among scholars and practitioners, with the advent of Artificial Intelligence (AI) playing an important role in shaping this discourse. Despite the common perception that intelligent machines pose a threat to workers in routine roles, AI technologies are increasingly being utilized for advanced tasks carried out by knowledge workers. Drawing on state-of-the-art research and real-life examples we develop an integrated framework to explore the future of academic work. Our focus is on academics, an essential yet under-researched group of knowledge workers, and we discuss their work in relation to AI across space, time, and task dimensions. Our analysis reveals that the usage of AI technologies can have implications for the research, teaching, and service activities of academics and thereby also for the creation, acquisition, dissemination, and application of knowledge. Based on our framework we develop scenarios and propose a future research roadmap.

Evaluation of Printing Parameters on 3D Extrusion Printing of Pluronic Hydrogels and Machine Learning Guided Parameter Recommendation.

Bioprinting is an emerging technology for the construction of complex three-dimensional (3D) constructs used in various biomedical applications. One of the challenges in this field is the delicate manipulation of material properties and various disparate printing parameters to create structures with high fidelity. Understanding the effects of certain parameters and identifying optimal parameters for creating highly accurate structures are therefore a worthwhile subject to investigate. The objective of this study is to investigate high-impact print parameters on the printing printability and develop a preliminary machine learning model to optimize printing parameters. The results of this study will lead to an exploration of machine learning applications in bioprinting and to an improved understanding between 3D printing parameters and structural printability. Reported results include the effects of rheological property, nozzle gauge, nozzle temperature, path height, and ink composition on the printability of Pluronic F127. The developed Support Vector Machine model generated a process map to assist the selection of optimal printing parameters to yield high quality prints with high probability (>75%). Future work with more generalized machine learning models in bioprinting is also discussed in this article. The finding of this study provides a simple tool to improve printability of extrusion-based bioprinting with minimum experimentations.

Software for Bioprinting.

The bioprinting of heterogeneous organs is a crucial issue. To reach the complexity of such organs, there is a need for highly specialized software that will meet all requirements such as accuracy, complexity, and others. The primary objective of this review is to consider various software tools that are used in bioprinting and to reveal their capabilities. The sub-objective was to consider different approaches for the model creation using these software tools. Related articles on this topic were analyzed. Software tools are classified based on control tools, general computer-aided design (CAD) tools, tools to convert medical data to CAD formats, and a few highly specialized research-project tools. Different geometry representations are considered, and their advantages and disadvantages are considered applicable to heterogeneous volume modeling and bioprinting. The primary factor for the analysis is suitability of the software for heterogeneous volume modeling and bioprinting or multimaterial three-dimensional printing due to the commonality of these technologies. A shortage of specialized suitable software tools is revealed. There is a need to develop a new application area such as computer science for bioprinting which can contribute significantly in future research work.

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

Leveraging Tendon Vibration to Enhance Pseudo-Haptic Perceptions in VR.

Pseudo-haptic techniques are used to modify haptic perception by appropriately changing visual feedback to body movements. Based on the knowledge that tendon vibration can affect our somatosensory perception, this article proposes a method for leveraging tendon vibration to enhance pseudo-haptics during free arm motion. Three experiments were performed to examine the impact of tendon vibration on the range and resolution of pseudo-haptics. The first experiment investigated the effect of tendon vibration on the detection threshold of the discrepancy between visual and physical motion. The results indicated that vibrations applied to the inner tendons of the wrist and elbow increased the threshold, suggesting that tendon vibration can augment the applicable visual motion gain by approximately 13% without users detecting the visual/physical discrepancy. Furthermore, the results demonstrate that tendon vibration acts as noise on haptic motion cues. The second experiment assessed the impact of tendon vibration on the resolution of pseudo-haptics by determining the just noticeable difference in pseudo-weight perception. The results suggested that the tendon vibration does not largely compromise the resolution of pseudo-haptics. The third experiment evaluated the equivalence between the weight perception triggered by tendon vibration and that by visual motion gain, that is, the point of subjective equality. The results revealed that vibration amplifies the weight perception and its effect was equivalent to that obtained using a gain of 0.64 without vibration, implying that the tendon vibration also functions as an additional haptic cue. Our results provide design guidelines and future work for enhancing pseudo-haptics with tendon vibration.

Mental Health of Medical Students After Combating the COVID-19 Epidemic: A Cross-sectional Study in Vietnam.

This study was conducted to investigate the prevalence of mental health (MH) symptoms and associated factors among medical students who were engaged in combating the coronavirus disease 2019 (COVID-19) epidemic in 4 provinces/cities of Vietnam. A cross-sectional study with 580 participants was conducted at a medical university in Northern Vietnam. MH was assessed using the 21-item Depression, Anxiety, and Stress Scale, which was previously standardized in Vietnam. Data were collected through a structured self-administered questionnaire. Multivariate logistic regression was employed to examine the association between MH symptoms and relevant factors. Out of a total of 2703 medical students, 21.5% responded to the questionnaire. Among the 580 respondents, the prevalence rates of depression, anxiety, and stress were 43.3%, 44.0%, and 24.7%, respectively. Factors significantly associated with self-reported depression included being female and having a COVID-19 infection. Similarly, being female and having a COVID-19 infection were significantly associated with self-reported anxiety. Factors associated with self-reported stress included being female, having a personal or family history of MH symptoms, working more than 8 hr/day, and having a COVID-19 infection. COVID-19 has adversely impacted the MH of medical students. Our findings are valuable in their potential to motivate universities, MH professionals, and authorities to offer mental healthcare services to this group. Furthermore, there is a pressing need for training courses designed to equip future healthcare workers with the skills to manage crises effectively.

Integrating Artificial Intelligence into Biomedical Science Curricula: Advancing Healthcare Education.

The integration of artificial intelligence (AI) into healthcare practice has improved patient management and care. Many clinical laboratory specialties have already integrated AI in diagnostic specialties such as radiology and pathology, where it can assist in image analysis, diagnosis, and clinical reporting. As AI technologies continue to advance, it is crucial for biomedical science students to receive comprehensive education and training in AI concepts and applications and to understand the ethical consequences for such development. This review focus on the importance of integrating AI into biomedical science curricula and proposes strategies to enhance curricula for different specialties to prepare future healthcare workers. Improving the curriculum can be achieved by introducing specific subjects related to AI such as informatics, data sciences, and digital health. However, there are many challenges to enhancing the curriculum with AI. In this narrative review, we discuss these challenges and suggest mitigation strategies.

Color Transfer for Images: A Survey

High-quality image generation is an important topic in digital visualization. As a sub-topic of the research, color transfer is to produce a high-quality image with ideal color scheme learned from the reference one. In this article, we investigate the mainstream methods of color transfer to provide a survey that introduces the related theories and frameworks. Such methods can be divided into three categories: statistical color transfer, semantic-based color transfer, and color transfer for special target. For these mainstream technical routes, we discuss the related research background, technical details, and representative methods. We also exhibit some new trends of the topic according to recent progress. Based on the comparisons, we discuss the unsolved issues of color transfer and potential solutions in future work.

What supports the emotional well-being of peer workers in an NHS mental health service?

Purpose This study aims to explore the experiences of peers working in a range of roles within a single NHS mental health service. This study also aims to provide evidence of the impact of existing support, organisational structure and culture around peer working and provide recommendations for a Good Practice Guide for Peer Working. Peer roles require lived experience of mental health conditions and/or services. While the impact on them of using their own lived experience is not fully understood, anecdotal evidence suggests that peer workers may experience a greater emotional impact than other mental health workers. Burnout and retention are particular concerns. Design/methodology/approach This was a two-stage study using focus groups and reflexive thematic analysis in Stage 1. The key themes formed the basis of the Stage 2 workshop, which provided recommendations for a Good Practice Guide. The study team consisted of peer researchers with lived experience, supported by a Lived Experience Advisory Panel. Findings There is a perceived lack of support and an increased peer burden for peer workers. Recommendations included relevant ongoing training and development; support and supervision; and organisational cultural change. Originality/value Working within a peer-led co-production framework, this study contributes to the development of the evidence base for peer emotional labour. Based on the findings, a Good Practice Guide for Peer Working is being developed to promote good practice for the development of future peer worker roles.