Retention Initiatives Research Articles

Factors influencing career choices and post-fellowship perspectives in adult hematology/oncology physicians: A nationwide cross-sectional study.

9015 Background: We aimed to investigate the timing and influence of factors behind career choices in hematology and medical oncology, assess levels of job satisfaction, and identify factors contributing to professional retention and the prevention of attrition. Methods: An anonymous survey with 13 questions was distributed to practicing hematologists and oncologists who were members of the American Society of Clinical Oncology and/or American Society of Hematology. The respondents encompassed diverse areas of primary focus within the field, varied practice settings, and all geographical regions. Results: Out of 423 respondents, 66% were male and 32% female. The majority identified as White (69%), followed by Asian (19%), Middle Eastern (4%), Hispanic (3%), and Black (1%). Most were practicing either Medical Oncology (43%) or combined Hematology/Oncology (36%), with 46% working in an academic/university setting and 57% located in an urban region. In terms of timing, about a third had decided on their career choice in medical school, with the majority of the remaining having decided by residency. While most of those surveyed were practicing in the area they had hoped to, about one-sixth (17.5%) appeared to be working in an area they hadn't planned on. Most said they would choose their current profession again (67% definitely yes, 24% likely yes). Science and academic interest (81%) ranked the highest when combining the top two responses for factors influencing choice, followed by mentor influence (47%), with work/life balance (19%) and financial considerations (6%) being less frequently cited. Satisfaction levels were generally high across key dimensions (Table), with intellectual fulfillment receiving the highest satisfaction (63.1% very satisfied, 26% satisfied). Importantly, better work/life balance (37% respondents), fewer non-medical tasks (35%), and a higher salary (20%) were key considerations to deter professional attrition. Conclusions: This study offers valuable insights into the career perspectives of Hematologists and Medical Oncologists, providing a foundation for developing strategies for career development and retention initiatives within the specialty. Efforts should be undertaken to enhance participation from different minorities within Hematology/Oncology and physicians practicing Classical Hematology to identify specific support and retention needs for these areas. [Table: see text]

Customer Churn Prevention For E-commerce Platforms using Machine Learning-based Business Intelligence

Aims & Background: Businesses in the E-commerce sector, especially those in the business- to-consumer segment, are engaged in fierce competition for survival, trying to gain access to their rivals' client bases while keeping current customers from defecting. The cost of acquiring new customers is rising as more competitors join the market with significant upfront expenditures and cutting-edge penetration strategies, making client retention essential for these organizations. Objective: The main objective of this research is to detect probable churning customers and prevent churn with temporary retention measures. It's also essential to understand why the customer decided to go away to apply customized win-back strategies. Methodology: Predictive analysis uses the hybrid classification approach to address the regression and classification issues. The process for forecasting E-commerce customer attrition based on support vector machines is presented in this paper, along with a hybrid recommendation strategy for targeted retention initiatives. You may prevent future customer churn by suggesting reasonable offers or services. Results: The empirical findings demonstrate a considerable increase in the coverage ratio, hit ratio, lift degree, precision rate, and other metrics using the integrated forecasting model. Conclusion: To effectively identify separate groups of lost customers and create a customer churn retention strategy, categorize the various lost customer types using the RFM principle.

Initiatives supporting student retention in early childhood teacher education qualifications

This paper describes a case study using quantitative and qualitative approaches to investigate student engagement and retention within an online early childhood teacher education program at a regional Australian university. Two key interventions, the identification and support of disengaged students and the Embedded Tutors Program are described and examined. Initial findings on these retention initiatives, developed to support Early Childhood Education undergraduates studying in the online environment, are presented. Additionally, discussion of the findings through the theory of practice architectures highlights the practices and institutional arrangements that create the conditions to support student retention. This study is significant in planning for Early Childhood Education workforce quality and supply. It may offer guidance to institutions for their retention practices with early childhood teacher undergraduates studying in the online environment.

“The COVID-19 pandemic and operational challenges, impacts, and lessons learned: a multi-methods study of U.S. prison systems”

BackgroundThe purpose of this study was to examine how the COVID-19 pandemic changed U.S. prison operations and influenced the daily work of prison staff.MethodsIn collaboration with the National Institute of Corrections, we administered a survey to 31 state correctional agencies in April 2021 and conducted five focus groups with 62 correctional staff.ResultsUsing a framework of bounded rationality, we find that daily operations were strained, particularly in the areas of staffing, implementing public health policy efforts, and sustaining correctional programming. While prison systems and staff were under-prepared to respond to the pandemic, they attempted to address complex problems with the limited resources they had.ConclusionsResults underscore a need in corrections for prioritizing further developments and reviews of collaborative policies and practices for managing crisis situations. Seeking avenues for leveraging technological innovations to improve operations and facilitate enhanced communication are especially warranted. Finally, meaningful reductions in the prison population, changes in physical infrastructure, and expansions of hiring and retention initiatives are critical for positioning prisons to manage future emergencies.

Enhancing Educational Leadership and Management on Transnational Campuses in 2023 and Beyond

This article considers how transnational campuses can enhance educational leadership and management in 2023 and beyond by drawing on case study examples from one provider in eastern China. It considers the importance of recruitment and retention initiatives, and the roles that employment motivation, job satisfaction, and employee well-being play. Through utilizing a qualitative interview-based approach to data collection, the findings from this case study suggest that transnational campus leaders and managers should consider paying attention to several factors to meet potential employees’ expectations concerning what good leadership and management consist of in order to enhance recruitment and retention initiatives. The findings also indicate that staff perceive leadership and management facets as overlapping and complementary in many areas and believe that leadership is not solely reliant on position. Indeed, the belief is that good examples of leadership can be found throughout an organization and that these examples can be learned from. Finally, the results highlight the importance of role models, experience, people skills, and guided learning in shaping the next generation of leaders and how they approach their potential leadership tasks.

Toxic leadership behaviour of nurse managers and turnover intentions: the mediating role of job satisfaction

IntroductionGlobally, hospitals are confronted with major challenges of turnover of nurses. Knowledge of the factors that account for the turnover of nurses will aid in creating strategies that will enhance nurse managers’ leadership behaviour and job satisfaction to reduce turnover. The study, therefore, investigated the mediating role of job satisfaction on toxic leadership and turnover intentions of nurses.MethodsA multi-centre cross-sectional study was undertaken to assess 943 nurses using the Toxic-leadership Behaviour of Nurse Managers scale, Minnesota Satisfaction Questionnaire and Turnover Intention scale. Descriptive statistics was used to assess the prevalence of toxic leadership, job satisfaction and turnover and Pearson’s correlation examined the relationships between the variables. Hayes’ PROCESS macro approach of mediation was used to determine the effect of toxic leadership behaviour on the turnover intention on the possible influence of job satisfaction.ResultsThe response rate for the study was 76.0%. Mean scores for turnover intentions and toxic leadership behaviour were 3.71 and 2.42 respectively. Nurses who work with toxic managers showed a higher propensity to leave their jobs. Job satisfaction acted as a mediator between the toxic leadership practices of managers and turnover intentions. The total effect of toxic leadership behaviour on turnover intention comprised its direct effect (β = 0.238, SE = 0.017, 95% CI [0.205, 0.271]) and its indirect effect (β = -0.020, SE = 0.017).ConclusionsJob satisfaction acted as a mediating factor for toxic leadership behaviour and nurses’ turnover intentions. As part of nurse retention initiatives, avoiding toxic leadership behaviours will be the ultimate agenda. Nurse administrators should recognize the value of excellent leadership and develop a structured training programme through the use of evidence-based professional development plans for nurse managers.

“Each day I find ways to fight for my students”: Black Science Teachers as Advocates and Abolitionists

ABSTRACT In this article, we highlight the experiences of two Black early-career science teachers who transitioned from their STEM professions into the classroom. This study explored factors that influenced their decisions to choose education and how being introduced to abolitionist teaching during the preparation process informed their roles as educators. Abolitionist teaching served as the theoretical lens to examine their pursuit of teaching as a career and the classroom practices that they employed. Data sources included two semi-structured interviews with each participant and artifacts from the teacher preparation program and their science classrooms. We lifted up the voices and experiences of teachers through narrative inquiry and, two major themes emerged from their stories. Findings revealed that the participants were inspired to serve as role models and positioned themselves as extended family members for Black and Brown children to realize their potential. Findings also highlighted the significance of centering abolitionist teaching in the science teacher preparation program to equip and position these teachers to resist marring practices within their schools. We argue that educational reform efforts must acknowledge the value that Black teachers bring to science classrooms and create retention initiatives that protect and support them.

Centering the Marginalized: Creating a Coalition to Enhance Retention Initiatives in the Workplace

Purpose: This practitioner reflection provides a narrative of how I intervened to make Utah State University (USU) a more socially-just workplace for graduate students, by creating a coalition to establish the Graduate Students of Color Association (GSCA). I argue that graduate students are not only professionalizing scholars but are also often university employees. I extend conversations in the field by centering multiply marginalized or underrepresented (MMU) students' perceptions of inclusive spaces while offering a solution to Popham's (2016) argument that recruitment efforts may not be enough when trying to diversify knowledge in the workplace. Method: By taking a descriptive narrative approach to this reflection, I offer insights into the different methods to establish GSCA and the stakeholders involved. I provide readers with ways to enact transformative diversity, equity, and inclusion (DEI) in their workplaces while promoting reciprocity for all involved. Results: The continuous commitment to enhance workplace environments through social, academic, emotional, and culture-affirming support has proven to be a major impact to USU thanks to GSCA. The association has become an integral retention initiative that USU's graduate programs can promote and use alongside their recruitment efforts. Conclusion: I provide readers with insights on how to create cultural spaces for professionalizing scholars while centering their lived experiences and their need for belonging. This reflection provides readers with divergent ways to creating an infrastructure that helps MMU scholars persist in the workplace.

Critically Discuss the Policy and Research Evidence Which Examines the Role of Men in Early Childhood Education and Care

Attracting more men to balance the predominantly female workforce is one of the key issues facing the early childhood education and care (ECEC) sector. This research critically discusses the main debates regarding the issue of gendered ECEC sector, including the core concepts of childhood, masculinity and ECEC, followed by the debates about the influences of more male practitioners on both children and ECEC workforce. Although there exist some arguments against the hypothesis about men’s benefits on children and ECEC workforce, the need to get men involved in the lives of young children is reflected by government policies across different countries, such as recruitment and retention initiatives for male preschool teachers. However, most of these strategies to remove the barriers male teachers encountered, and to incorporate men and fathers, received negative results. Therefore, by building upon the need to enhance the holistic quality of ECEC workforce, new perspectives, especially from children’s perceptions, on how to change the gender imbalance in ECEC are recommended, including both the top-down policy and bottom-up strategy.

Mental health among first-generation college students: Findings from the national Healthy Minds Study, 2018-2021.

A mounting body of evidence reveals that college mental health outcomes are worsening over time. That said, little is known about the mental health needs of the nearly eight million first-generation students in U.S. postsecondary education. The present study uses population-level data from the national Healthy Minds Study to compare prevalence of mental health symptoms and use of services for first-generation and continuing-generation students from 2018-2021. The sample includes 192,202 students at 277 campuses, with 17.3% being first-generation. Findings reveal a high prevalence of mental health symptoms among both first-generation and continuing-generation students. Controlling for symptoms, FG students had significantly lower rates of mental health service use. Just 32.8% of first-generation students with symptoms received therapy in the past year, relative to 42.8% among continuing-generation students, and this disparity widened during the COVID-19 pandemic. Findings have important implications for the design and implementation of higher education policies, mental health delivery systems, college persistence and retention initiatives, and public health efforts in school settings.

Native American teacher retention initiative (ED)

Native American teacher retention initiative (ED)

What do women want? An exploration of workplace attraction and retention factors for women in construction

Increasing skill shortages in the construction industry are a concern worldwide. The industry is seeking to find effective ways to encourage more women to pursue careers in construction. This study explores the factors that attract and retain women, comparing them based on age (under 35 years, 35–44 years and 45 plus years) and role levels (managers, professionals and nonmanagers). A total of 655 responses were collected through a nationwide survey of women in construction in Australia. The findings suggest that to attract women, career opportunities must be emphasized; and that career advising, attractive salary/wages and training must be highlighted to attract young female talent. Further, working conditions are important factors considered by managerial and professional women when leaving the industry, particularly younger women. Organizational leaders and decision-makers seeking to recruit more women into construction may improve the effectiveness of their recruitment and retention initiatives by tailoring them to role level and age.

The Impact of Leadership Models on the Performance of Employees in the Private Sector in the Eastern Province in Kingdom of Saudi Arabia

This paper looks for leadership models on the performance of workers in the private sector in the eastern region, and whether leadership models in the private sector can be considered a catalyst for creating a good environment or not. Listing and classifying the character, characteristics and impact of leadership models was one of our top priorities in this research. The results showed that there are many leadership models on the performance of workers in the private sector in the eastern region, because of the suspicions it bears and the lack of centralization to predict the increase in productivity and increase efficiency.Furthermore, these findings can help supervisors identify which leadership style suits their situation, allowing them to adjust their leadership styles to be more successful and results-oriented. According to the results of this study, democratic leadership styles are superior to autocratic and laissez-faire leadership styles for boosting organizational performance and employee retention. The business may achieve its goals by keeping talented and experienced service people through a suitable leadership style lastly, the study's findings have several consequences for research and practice. The results may aid in improving corporate practices by giving executives knowledge on retaining the best employees and increasing employee performance. A manager in the manufacturing business might utilize the information to enhance individual employee performance, investigate probable reasons for employee turnover, and adopt retention initiatives.

Barriers to international physician recruitment in Nova Scotia, Canada.

A healthcare staffing crisis has been brewing in Canada since 1993. Recently worsened by the COVID-19 pandemic and increasing immigration, it has severely impacted rural and remote areas of the country like the province of Nova Scotia. Researchers have considered international physician recruitment as a long-term solution, but it comes with its own challenges. In addition to an extensive literature search, qualitative interviews were conducted with various representatives from the Nova Scotia health ecosystem as part of this article. Identifying challenges to international physician recruitment from different perspectives, recommendations include bringing legislative and/or policy changes to increase candidate seats and developing new pathways to bring international medical graduates to Nova Scotia from other countries. The article includes interview responses from official authorities involved in physician recruitment, author recommendations to remove barriers to international physician recruitment, and recruitment and retention initiatives currently being implemented in the province.

Leveraging AI and Machine Learning in Salesforce for Predictive Analytics and Customer Insights

Today's data-driven business climate is driving companies to use AI and ML to achieve a competitive advantage. Salesforce is a major CRM platform that uses AI and ML for predictive analytics and customer insights. This abstract discusses how Salesforce's AI and ML integration can transform company operations with actionable insight and prediction. Salesforce's Einstein AI framework leads this integration. Einstein integrates AI into Salesforce's technologies so organizations may use predictive analytics without data science knowledge. Einstein helps enterprises automate data analysis, predict patterns, and get insights from massive data sets.AI and ML in Salesforce improve consumer insights. AI-driven analytics can better segment clients, discover behavior trends, and forecast requirements. Segmentation allows individualized marketing, better customer service, and targeted sales. Businesses may use predictive algorithms to target at-risk clients with retention initiatives. Additionally, AI and ML provide sophisticated lead scoring and opportunity management. Machine learning algorithms can grade leads for accuracy and anticipate which opportunities will close by analyzing previous data and present interactions. Sales procedures are streamlined and revenue increases. Sales teams may prioritize high-value prospects and concentrate on high-probability opportunities by integrating these tools into Salesforce. AI-powered automation streamlines corporate operations too. Salesforce's Einstein automates data input, reminders, and reporting. This boosts operational efficiency and frees up staff time for strategic projects. AI automation keeps data current and accurate, improving business choices.

E-commerce customer churn prevention using machine learning-based business intelligence strategy

Businesses in the E-Commerce sector, especially those in the business-to-consumer segment, are engaged in fierce competition for survival, trying to gain access to their rivals' client bases while keeping current customers from defecting. The cost of acquiring new customers is rising as more competitors join the market with significant upfront expenditures and cutting-edge penetration strategies, making client retention essential for these organizations. The best course of action in this circumstance is to detect prospective churning customers and prevent churn with temporary retention measures. It's also essential to understand why the customer decided to go away to apply customized win-back strategies. Each customer's information, including searches made, purchases made, frequency of purchases, reviews left, feedback is given, and other data, is kept on file by the e-commerce company. Machine learning and data mining may be aided by examining this enormous quantity of data, analysing customer behaviour, and seeing potential attrition opportunities. The support vector machine is a popular supervised learning method in machine learning applications. Predictive analysis uses the hybrid classification approach to address the regression and classification issues. The process for forecasting E-Commerce customer attrition based on support vector machines is presented in this paper, along with a hybrid recommendation strategy for targeted retention initiatives. You may prevent future customer churn by suggesting reasonable offers or services. The empirical findings demonstrate a considerable increase in the coverage ratio, hit ratio, lift degree, precision rate, and other metrics using the integrated forecasting model. To effectively identify separate groups of lost customers and create a customer churn retention strategy, categorize the various lost customer types using the RFM principle.

Staffing rural emergency departments in Ontario: The who, what and where.

The emergency department (ED) in rural communities is essential for providing care to patients with urgent medical issues and those unable to access primary care. Recent physician staffing shortages have put many EDs at risk of temporary closure. Our goal was to describe the demographics and practices of the rural physicians providing emergency medicine services across Ontario in order to inform health human resource planning. The ICES Physician database (IPDB) and Ontario Health Insurance Plan (OHIP) billing database from 2017 were used in this retrospective cohort study. Rural physician data were analysed for demographic, practice region and certification information. Sentinel billing codes (i.e., a billing code unique to a particular clinical service) were used to define 18 unique physician services. A total of 1192 physicians from the IPDB met inclusion as rural generalist physicians out of a total of 14,443 family physicians in Ontario. From this physician population, a total of 620 physicians practised emergency medicine which accounted for 33% of their days worked on average. The majority of physicians practising emergency medicine were between the ages of 30 and 49 and in their first decade of practice. The most common services in addition to emergency medicine were clinic, hospital medicine, palliative care and mental health. This study provides insight into the practice patterns of rural physicians and the basis for better targeted physician workforce-forecasting models. A new approach to education and training pathways, recruitment and retention initiatives and rural health service delivery models is needed to ensure better health outcomes for our rural population.

Resource management for full paying patient service in Malaysia: issues and challenges

Full paying patient service (FPP) in the Ministry of Health Malaysia (MOH) hospitals was established as one of the specialist retention initiatives in 2007. FPP hospitals experience significant challenges in managing their resources while serving the public as their utmost priority. A semi-structured guide was used in 17 focus group discussions and 12 in-depth interviews with specialists, hospital directors, and supporting staff exploring issues and challenges in managing hospitals' resources. Four sub-themes were identified (ward/facility, medical equipment, drugs/consumable, workforce). Some of the issues include no dedicated FPP ward/equivalent ward, sharing of medical equipment and specialists' medication quota between public and FPP patients, inability to charge unlisted drug/consumables in the Fee Act. Limited human resources, especially among the support group to run FPP, lead to an increase in workload and dissatisfaction. Proper planning and close monitoring by MOH and individual hospitals are crucial to overcome these issues and improve the service.

Customer churning analysis using machine learning algorithms

Businesses must compete fiercely to win over new consumers from suppliers. Since it directly affects a company's revenue, client retention is a hot topic for analysis, and early detection of client churn enables businesses to take proactive measures to keep customers. As a result, all firms could practice a variety of approaches to identify their clients early on through client retention initiatives. Consequently, this study aims to advise on the optimum machine-learning strategy for early client churn prediction. The data included in this investigation includes all customer data going back about nine months before the churn. The goal is to predict existing customers' responses to keep them. The study has tested algorithms like stochastic gradient booster, random forest, logistics regression, and k-nearest neighbors methods. The accuracy of the aforementioned algorithms are 83.9%, 82.6%, 82.9% and 78.1% respectively. We have acquired the most effective results by examining these algorithms and discussing the best among the four from different perspectives.

Dynamic Behavior-Based Churn Forecasts in the Insurance Sector

In the insurance sector, a massive volume of data is being generated on a daily basis due to a vast client base. Decision makers and business analysts emphasized that attaining new customers is costlier than retaining existing ones. The success of retention initiatives is determined not only by the accuracy of forecasting churners but also by the timing of the forecast. Previous works on churn forecast presented models for anticipating churn quarterly or monthly with an emphasis on customers’ static behavior. This paper’s objective is to calculate daily churn based on dynamic variations in client behavior. Training excellent models to further identify potential churning customers helps insurance companies make decisions to retain customers while also identifying areas for improvement. Thus, it is possible to identify and analyse clients who are likely to churn, allowing for a reduction in the cost of support and maintenance. Binary Golden Eagle Optimizer (BGEO) is used to select optimal features from the datasets in a preprocessing step. As a result, this research characterized the customer's daily behavior using various models such as RFM (Recency, Frequency, Monetary), Multivariate Time Series (MTS), Statistics-based Model (SM), Survival analysis (SA), Deep learning (DL) based methodologies such as Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Customized Extreme Learning Machine (CELM) are framed the problem of daily forecasting using this description. It can be concluded that all models produced better overall outcomes with only slight variations in performance measures. The proposed CELM outperforms all other models in terms of accuracy (96.4).