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Retirement is a preparation for transitioning from one role to another and transitioning to a new stage of life. The deepening aging of the population encourages the policymakers to start the Bridge Employment plan when the society faces the unprecedented challenges of decreasing labor supply, heavier burdens of retirement and slow economic growth. The purpose of this study, the decision model for Bridge Employment has been developed by systematically reviewing the research literature.

A bibliometric analysis was conducted to cover publications on Bridge Employment for Return to Work published from 1994 to 2023, including a total of 1,936 publications collected from the Web of Science and Scopus. The patterns and trends in terms of sources of publications, intellectual structure and major topics were analyzed.

After carefully examining the results of the selected studies, three categories of individual (micro level), organizational (medium level) and contextual (macro level) factors were identified as effective factors on bridge employment and model development. Each of the mentioned factors, along with the legal, financial, managerial, educational-administrative and consulting requirements, form the basis for the development of the model and decision framework for Paul’s employment.

This model can be a basis as a framework for bridge recruitment planning so that organizations can once again use their skills–knowledge–expertise in different jobs and even training younger people.

Postneonatal mortality (PNM), which differs from infant and perinatal mortality, has been observed in the past 25 years with respect to the health outcomes of children. While infant and perinatal mortality have been well-evaluated regarding racial differentials, there are no substantial data on PNM in this perspective. The purpose of this study was to assess whether or not social determinants of health adversely affect racial/ethnic PNM differentials in the USA.

A cross-sectional, nonexperimental epidemiologic study design was used to assess race as an exposure function of PNM using Cohort Linked Birth/Infant Death Data (2013). The outcome variable assessed PNM, while the main independent variables were race, social demographic variables (i.e. sex and age) and social determinants of health (i.e. marital status and maternal education). The chi-square statistic was used to assess the independence of variables by race, while the logistic regression model was used to assess the odds of PNM by race and other confounding variables.

During 2013, there were 4,451 children with PNM experience. The cumulative incidence of PNM was 23.6% (n = 2,795) among white infants, 24.3% (n = 1,298) among Black/African-Americans (AA) and 39.5% (n = 88) were American-Indian infants (AI), while 21.3% (n = 270) were multiracial, χ² (3) = 35.7, p < 0.001. Racial differentials in PNM were observed. Relative to White infants, PNM was two times as likely among AI, odds ratio (OR) 2.11 (95% confidence interval [CI] 1.61, 2.78). After controlling for the confounding variables, the burden of PNM persisted among AI, although slightly marginalized, adjusted odds ratio (aOR) 1.70, (99% CI 1.10, 2.65).

In a representative sample of US children, there were racial disparities in PNM infants who are AI compared to their white counterparts, illustrating excess mortality. These findings suggest the need to allocate social and health resources in transforming health equity in this direction.

Young graduates in Morocco are encountering an increasingly challenging labor market environment. Confronted with intense competition, job insecurity, and unclear career trajectories, many find themselves in low-skilled positions despite possessing relevant qualifications. This issue is particularly pronounced among vocational training graduates, who experience professional downgrading at a rate three times higher (33.6%) compared to their peers from general education (11.6%) (HCP, 2018). Our study aims to investigate professional downgrading among young vocational training graduates in Morocco, focusing on the factors contributing to this phenomenon and identifying potential solutions to address it.

Our study is based on the insertion and career path survey conducted by the Department of Professional Training with graduates of professional training programs in Morocco. For this edition, the survey was conducted in 2020, encompassing all 31,498 graduates of the 2016 professional training programs. The Heckman self-selection model is employed to analyze and explore various dimensions of downgrading. Factors such as gender, age, marital status, parental education, and the choice of vocational training field are scrutinized to understand their influence on downgrading.

The study reveals several key findings: Women exhibit a lower probability of professional downgrading compared to men. Young graduates are more vulnerable to downgrading, emphasizing the necessity for career guidance and mentorship programs to facilitate their entry into the job market. Marital status plays a role, with married individuals having a higher likelihood of downgrading. Parental education, particularly that of mothers, proves critical in preventing subjective downgrading of vocational training graduates, highlighting the need for adult literacy and education programs. The effectiveness of the National Agency for the Promotion of Employment and Competencies (ANAPEC) programs in preventing downgrading among vocational training graduates is questioned, suggesting the need for program revisions tailored to this population. The choice of vocational training field significantly impacts downgrading, with graduates of technical training programs experiencing advantages. This emphasizes the importance of diversifying training fields and aligning them with market demands.

This study provides valuable insights into the phenomenon of professional downgrading among young vocational training graduates in Morocco. The findings emphasize the need for targeted policy interventions. Recommendations include supporting young graduates, reassessing programs offered by the ANAPEC, and enhancing technical training to better align with the evolving demands of the labor market.

The present study examines the interplay between age, marital status, alpha female status and various adaptive performance dimensions among a cohort of 380 female professionals.

This study adopts a positivist approach to collect and analyse the data, utilizing appropriate statistical techniques to explore the relationships between the variables of interest.

The study elucidates the significant role of alpha female status in predicting adaptive performance. It finds that alpha females possess distinct competencies, particularly in learning and training, indicative of proactive behaviour and self-efficacy. While older participants tend to demonstrate higher performance levels, the study reveals no significant correlation between age and alpha female status, suggesting that leadership traits may develop independently of age. Furthermore, marital status exerts a modest influence on adaptive performance. The interplay of age and marital status significantly affects adaptive performance, potentially due to the Cumulative Advantage Paradigm, which is the accumulation of advantages or disadvantages throughout an individual's life course.

This study contributes to the existing literature by providing a nuanced understanding of how demographic factors converge to influence adaptive performance in professional settings. It highlights the importance of recognising and nurturing alpha females in organizations and considering the interactions between age and marital status when designing career development programmes and support systems.

Turnover intention is a critical predictor of an employee’s turnover behaviour. A high level of turnover rate significantly affects the productivity and morale of an enterprise. Previous research has indicated that job satisfaction plays a critical role in influencing an employee's turnover intention, but the underlying factors related to job satisfaction remain under-explored, which impedes the development of effective strategies for reducing turnover intention. In addition, little research examined job satisfaction and turnover intention in the context of the COVID-19 pandemic, specifically in the Chinese construction industry. This study aims to investigate the impact of job satisfaction on turnover intention among professionals in the construction industry.

A questionnaire survey was employed to collect viewpoints from 449 professionals in the Chinese construction industry, followed by descriptive analysis, correlation analysis and structural equation modelling analysis to derive results.

The findings indicate that professionals in the industry generally have a slightly high level of job satisfaction while a slightly low level of turnover intention in the special period of the pandemic outbreak. Leadership and management, training and career development and interpersonal relationships are critical underlying factors leading to their turnover intention. Although demographic factors have no moderating effect between job satisfaction and turnover intention, among them, age, marital status and years of working experience have strongly positive relationships with job satisfaction while significantly negative relationships with turnover intention.

The findings provide valuable insights to fully understand the critical factors leading to turnover intention from the perspective of job satisfaction, which is helpful in developing effective measures to address the turnover problems for enterprises in the Chinese construction industry and those industries with similar characteristics in other regions.

This paper analyzes the differential experiences of women in the Canadian labour market who hold lower-skilled jobs and have school-age children during two waves of Covid compared with more typical conditions pre-pandemic. The article seeks to test the hypothesis that workers at the intersection of womanhood, motherhood and precarious employment would endure even more disadvantageous labour market outcomes during the Covid pandemic than they did prior to it.

We employ a Gender-Based Plus (GBA+) and intersectionality lens to examine the differential effect of Covid on the effect of the trifecta of being a woman in a lower-skilled job and facing a motherhood penalty from school-age children. We use a Difference-in-Difference framework with Canadian Labour Force Survey (LFS) data to examine the differential effect of two waves of Covid on three labour market outcomes: employment, hours worked and hourly wages.

We find that being a woman in a lower-skilled job with school-age children is associated with lower employment, hours worked and wages in normal times compared to males in those same situations. Such women also face the most severe adjustment consequence from the Covid shock, with that adjustment concentrated on the margin of employment and restricted to the First Wave and not the subsequent Omicron Wave.

The paper studies a specific intersectional group, assesses pre-pandemic, peak-pandemic and late-pandemic differences in labour market outcomes and runs separate estimations for different job skill levels. We also study a more comprehensive list of labour market outcomes than most studies of a similar nature.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

Current academic research on teacher learning is increasing in number and deepening in quality, but at the same time, the heterogeneity is growing significantly. Similar work is challenging to cross-check regarding conclusions due to the different research foci. This paper aims to provide a reliable theoretical framework and offers solid insights based on the existing research.

Based on the Onion model, 67 core literature in English and Chinese were coded through qualitative meta-analysis methods to explore environmental, behavioral, competence, belief, identity, mission and other factors that may impact teacher learning.

It was found that the quantitative structure of the current relevant studies was in an inverted triangular shape with three levels of steps, respectively, which can be summarized as structural environment, core behaviors and dominant mission. The heterogeneity between the findings mainly originated from two situations, oppositional and complementary and some structural adjustments were made to the Onion model according to the coding results to better represent the interaction of influences between the levels. It also analyzes current research trends and the centrality of learned behaviors based on the coding results.

The design of teacher learning activities should combine theoretical, practical and inquiry learning to ensure that teachers are kept fresh and motivated by sustained and varied stimuli.

To the best of the authors’ knowledge, this study is the first to analyze teacher learning influences through qualitative meta-analysis and create node saturation to analyze the results, resulting in highly credible and valuable research findings.

The present study examines the fluctuations in Socioeconomic and demographic (SED) factors and the prevalence of Non-Communicable Diseases (NCDs) across clusters of states in India. Further, it attempts to analyze the extent to which the SED determinants can serve as predictive indicators for the prevalence of NCDs.

The study uses three rounds of unit-level National Sample Survey self-reported morbidity data for the analysis. A machine learning model was constructed to predict the prevalence of NCDs based on SED characteristics. In addition, probit regression was adopted to identify the relevant SED variables across the cluster of states that significantly impact disease prevalence.

Overall, the study finds that the disease prevalence can be reasonably predicted with a given set of SED characteristics. Also, it highlights age as the most important factor across a cluster of states in understanding the distribution of disease prevalence, followed by income, education, and marital status. Understanding these variations is essential for policymakers and public health officials to develop targeted strategies that address each state’s unique challenges and opportunities.

The study complements the existing literature on the interplay of SEDs with the prevalence of NCDs across diverse state-level dynamics. Its predictive analysis of NCD distribution through SED factors adds valuable depth to our understanding, making a notable contribution to the field.