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An Empirical Study of the Relationship between Job Satisfaction and Supervisor Support, Communication, Workload, Recognition, and Resources among Frontline Healthcare Workers During the Pandemic
Doctoral Study Project (DSP) Presented to the College of Health and Human Services
of Trident at American Intercontinental University
in Partial Fulfillment of the Requirements for the Degree of Doctor of Health Administration
by
Abina Riley
Chandler, Arizona
2024
Winter 2024
Dr. Faye Anderson
© 2024
Abstract
The effects of the COVID-19 pandemic have significantly impacted the job satisfaction of frontline healthcare workers. This empirical study investigates the relationship between job satisfaction and various factors: supervisor support, communication, workload intensity, recognition, and available resources among frontline healthcare professionals. Using data collected from the All-Employee Survey (AES) within the VA St. Louis Health Care System from 2018 to 2020, a quantitative cross-sectional design and logistic regression analysis will be employed to test hypotheses. The study aims to shed light on how the challenges posed by the pandemic influence frontline healthcare workers’ job satisfaction. By analyzing the data comprehensively, this study seeks to provide valuable insights for healthcare administrators and policymakers to develop targeted interventions that can enhance job satisfaction, reduce burnout, and ultimately improve the quality of patient care.
Table of Contents
List of Tables 6
List of Figures 7
Chapter 1: Introduction 8
Background 10
Problem Statement 14
Purpose Statement 17
Conceptual Model 18
Research Question(s) 19
Definition of Key Terms 20
Summary 22
Chapter 2: Literature Review 24
Literature Search Strategy 25
Synthesis of the Literature 27
Conceptual Framework 32
Summary 43
Chapter 3: Methodology 45
Research Methodology and Design 45
Role of the Researcher 47
Population and Sample Selection 48
Instrumentation 49
Variables and Operational Definitions 50
Dependent Variable 50
Independent Variables 51
Demographics and Control Variables 55
Data Collection 58
Data Analysis 60
Assumptions 64
Limitations 65
Delimitations 67
Reliability and Validity 68
Ethical Assurances 69
Summary 71
References 73
Appendix A 85
List of Tables
Table 1 34
Table 2 57
Table 3 62
List of Figures
Figure 1 19
Figure 2 28
Figure 3 33
Chapter 1: Introduction
In the wake of the COVID-19 pandemic, the global healthcare sector has encountered unparalleled challenges, casting a spotlight on the critical role of frontline healthcare workers. These professionals, who constitute the backbone of healthcare delivery, have faced increased pressures, including heightened exposure to the virus, exacerbated workloads, and the emotional toll of serving on the front lines during a global health crisis. Recognizing the significance of these developments, this study delves into an empirical analysis of the multifaceted relationship between job satisfaction and various influential factors among frontline healthcare workers during the pandemic period. Chapter 1 sets the stage for this exploration, laying the groundwork with a detailed background that contextualizes the financial and human impact of job satisfaction within the hospital setting, elucidated by Moitra et al. (2021).
Drawing upon Herzberg’s job satisfaction theory (Khanna, 2017; Rughoobur-Seetah, 2023; Barili et al., 2022), this chapter progresses to dissect the dual constituents of job satisfaction: hygiene factors and motivators, each playing a pivotal role in shaping healthcare professionals’ workplace experiences. This theoretical underpinning serves as a lens through which this research examines how aspects like workload, salary, supervisor support, recognition, and resources converge to impact job satisfaction. The ramifications of the pandemic have underscored the urgency for human resources professionals within healthcare settings to reassess and recalibrate their strategies, as underscored by McCall et al. (2021), to address the evolving hygiene and motivational needs of healthcare workers.
This introduction also brings to light the novel challenges imposed by the pandemic, such as the need for flexible work arrangements and the limited applicability of Work-From-Home (WFH) setups in direct-care roles, highlighting the work of Gigauri (2020). It emphasizes how these unprecedented circumstances demand a nuanced understanding of job satisfaction influencers to tailor effective interventions aimed at bolstering the well-being and job satisfaction of frontline healthcare workers. As such, this chapter not only paints a comprehensive picture of the current landscape but also sets a clear path for the investigation that follows, articulating the problem statement and the purpose of this study with precision.
The significance of this inquiry is further amplified by a detailed examination of various factors—supervisor support, communication, workload, recognition, and resources—through the lens of empirical evidence and theoretical frameworks. This chapter establishes a solid foundation for the research, meticulously defined key terms, and sketched out the conceptual or theoretical framework that will guide the analysis.
Thus, Chapter 1 introduces this study with a thorough and critical examination of the context, theoretical foundations, and pressing questions that frame this study. It sets a scholarly tone for a systematic investigation into how the COVID-19 pandemic has reshaped job satisfaction dynamics for frontline healthcare workers, with the ultimate goal of informing effective strategies to enhance their job satisfaction and overall well-being in these challenging times.
Background
Staff job satisfaction has a big financial influence in the hospital setting. Fatigue, burnout, tiredness, stress from the workplace, and mental health problems are signs of low job satisfaction (Moitra et al., 2021). Since they have an impact on the physical and mental health of healthcare professionals, these issues form the basis of impaired care delivery.
According to Herzberg’s job happiness theory, human resource professionals must approach job satisfaction from two anglesq1. According to the hypothesis, job happiness results from the convergence of motivational and hygienic aspects (Khanna, 2017). The elements that are likely to cause unhappiness include workload, salary/compensation/wage rates, flexible work schedules, and the general safety and security of the employees at their workplace. These concerns are included in the hygiene factors. The components that encourage workplace happiness are included in the motivational factors; these include possibilities for professional advancement, emotional support, rewards, incentives, and personalized responsive work environments. HR staff can serve as a motivational factor by enhancing job satisfaction. Enhancing job satisfaction can occur in a variety of ways (Rughoobur-Seetah, 2023). In particular, motivational factors react to hygiene factors to create a setting that encourages job satisfaction among employees (Barili, et al., 2022)
There are a number of factors such as discomfort and burnout that might limit employee happiness, which by extension, will affect job performance negatively. Job performance and happiness are typically at their highest levels when the motivators are effectively addressed. HR’s job is to analyze data about hygiene-related aspects and take the right action by including pertinent motivators. The Covid-19 pandemic has given HR staff a new way to evaluate employee work happiness. Inevitably, given how Covid-19 has affected the workload in hospitals, hygiene-related concerns have risen to the fore while new ones have evolved. It is now the responsibility of HR professionals to review the expanding hygiene and new issues and develop evidence-based strategies to respond via motivators. The low rates of re-employment and re-entry by direct care workers in the last few months, despite the decline in Covid-19 prevalence, point to the physical, psychological, and emotional demands the pandemic has placed on healthcare workers. This has particularly been due to increased workload and prolonged separation from families (McCall et al., 2021).
The requirement for flexible workspaces and work schedules is one of the effects of the Covid-19 pandemic. Healthcare personnel appear to be less eager to enter or return to the workforce in the post-pandemic era than workers in other businesses with comparable entry-level criteria (McCall et al., 2021). Healthcare workers could believe that HR staff have previously downplayed job satisfaction as a key performance indicator. According to these healthcare professionals, the pandemic may not have provided HR staff with the necessary training on how to deal with hygiene and motivational issues (Gigauri, 2020; McCall et al., 2021).
According to Gigauri (2020), the majority of organizations turned to work-from-home (WFH) programs during the pandemic, allowing employees to conduct business virtually without having to physically be present at their desks. Though it’s possible that the pandemic, not a multi-industry response to technical advancements, drove this flexibility. The WFH initiatives established a framework so that the majority of industries could continue to operate in part while also drastically lowering the rates of layoffs and dismissals caused by the pandemic. However, as noted by Gigauri (2020), the healthcare industry was unable to fully utilize the WFH programs, particularly those in direct-care roles. For this group, providing healthcare required having direct physical touch with the patients and the workplace. Thus, the flexible work times offered by WFH programs may not be very applicable for direct-care responsibilities once the post-pandemic shift gets underway. Notably, from the perspective of job satisfaction, this group of direct-care employees was and continues to be the most impacted by the pandemic (Gigauri, 2020).
For instance, according to Duarte et al. (2020), emergency department healthcare personnel had the highest prevalence of burnout. Due of the pandemic’s quick dissemination and the fast pathophysiological development rate of Covid-19, emergency rooms saw their greatest patient numbers ever. However, it should not be assumed that the burden in these settings has decreased in the post-pandemic approach to dealing with the mental health and job happiness of healthcare personnel in the emergency departments (ED). Notably, Cruz et al. (2019) found that these professionals had more than three times the amount of burnout compared to their coworkers in other units in a pre-pandemic investigation on the impact of burnout on the mental health of healthcare workers in the ED and their coping mechanisms. According to Cruz et al.’s findings from 2019, doctors and nurses were the most affected category, with considerably higher concerns about their mental health and degree of satisfaction. The same avoidance-centered coping techniques that were the most popular for dealing with burnout were also associated with adverse outcomes of social dysfunction, depression, anxiety, and somatic symptoms (Cruz et al., 2019).
According to Dreison et al. (2018), who reported the results of a meta-analysis of burnout interventions over the previous 35 years, prolonged burnout has a poor influence on healthcare workers’ mental health, which in turn has a negative impact on how well they perform at work. Person-centered and organizational-driven therapies have historically been the two main strategies used for burnout interventions. Where both person-centered and organization-driven are lacking or poorly implemented, avoidance-centered coping takes over. Person-centered approaches outperform organizational-driven approaches like job training and education in terms of improving the mental health and job happiness of healthcare personnel. In order to monitor, counsel, and treat the mental health difficulties of healthcare professionals at work, person-centered interventions largely involve the integration of mental health specialists (Dreison et al., 2018).
Few healthcare workplaces, according to Dreison et al. (2018), have mental health specialists who are solely focused on the healthcare workers. As a result, there is a substantial gap in the early detection of emotional exhaustion, burnout, weariness, and work-related discomfort among those healthcare workers in units like the ED that are prone to these conditions. As the pandemic spreads, HR managers will have to address daily concerns about burnout and job satisfaction in addition to the unresolved emotional and psychological damage the pandemic has caused in direct-care employees (Esterwood & Saeed, 2020). The necessity of person-centered approaches, such as devoted mental health professionals, for these frontline or direct-care employees may be the key to resolving the currently apparent dissatisfaction with their roles.
Problem Statement
The COVID-19 pandemic has presented issues like restricted travel, lockdowns, and extra workload, especially for healthcare workers, with far-reaching consequences for healthcare systems worldwide due to the shifting environment of healthcare delivery (Ardebili et al., 2021). Healthcare providers providing frontline treatment have been among those hit hardest by the pandemic. Their jobs have changed drastically, exposing them to greater dangers and increasing their stress levels (Chen, et al., 2020). An important question emerges in this setting: to what degree is the pandemic affecting the happiness of frontline healthcare workers? It is impossible to exaggerate the importance of job satisfaction in determining the health, engagement, and ultimately the quality of treatment provided to patients by healthcare professionals. It is crucial to objectively examine how factors like supervisor support, communication, workload, recognition, and available resources affect these professionals’ job satisfaction as they handle the many obstacles posed by the pandemic. This study will focus on these factors to see how they affect frontline healthcare professionals’ happiness on the job. Workloads were increased, resources were depleted, infection risks were raised, and staff had to spend more time away from their families than ever before because of pandemic. The research aims to specifically examine the extent to which the challenges posed by the COVID-19 pandemic, such as heightened infection risks, increased workloads, decreased resources, and disrupted work-life balance, impact the job satisfaction and overall well-being of frontline healthcare workers within the VA St. Louis Health Care System. Previous investigations have not comprehensively explored the measurements of these difficulties and their direct correlation with workers’ satisfaction in this context. This research aims to fill this knowledge vacuum by providing concrete numbers for the effects of these factors on work satisfaction, thereby illuminating the relationships between them and the sizes of their effects. Employee satisfaction, wellness, organizational success, and patient outcomes have all been linked in the existing research. However, in the case of a catastrophe like the COVID-19 pandemic, the precise numeric consequences are unknown at this time. In order to improve work satisfaction, reduce burnout, and eventually improve patient care quality, this study aims to offer empirical information that healthcare administrators, policymakers, and stakeholders may use to develop targeted interventions, support systems, and resource allocations.
Nearly every economic sector has been profoundly impacted by the Covid-19 pandemic at the local, national, and international levels (International Labor Organization, 2020). A sudden pandemic, with its rapid spread and high mortality rate, nearly brought down the whole world economy. The healthcare sector experienced a difficult time marked by an increase in patient volumes and complex cases including the Covid-19 infections, whilst the bulk of industries shut down during the pandemic (International Labor Organization, 2020). Additionally, the lack of effective pharmacological therapies combined with the scant information available on the pathophysiology and epidemiology of the illness called for a community-driven strategy for virus containment (Hamaguchi, 2021; International Labor Organization, 2020).
Prior studies have shown that healthcare employees in the US had a higher prevalence of low job satisfaction than workers in other professions (Alpern et al., 2013; Cruz et al., 2019; Dreison et al., 2018). Since March 2020, a small number of research have examined job satisfaction in the setting of a pandemic that is fast developing, nevertheless (Bajrami et al., 2021). Even so, the main emphasis has been on work performance in studies that have previously examined job satisfaction in the context of the pandemic. Previous research has not attempted to generalize its findings to identify the cleanliness and motivators of the work environment that may be changed to enhance job satisfaction and lower the associated turnover/attrition rates. Prior studies have highlighted the importance of both personal and work-related issues (Dreison et al., 2018; Blanco‐Donoso et al., 2022; Luo et al., 2020). Age, education, gender, and degree of education are a few examples of such personal characteristics. The workload, type of occupation, work environment, salary and compensation, resource sufficiency, professional status, career advancement, relationship with coworkers and managers, and performance evaluation, on the other hand, are job-related factors, and particularly institutional factors. Healthcare employees’ job satisfaction was unquestionably significantly predicted by the pandemic’s quickly changing nature (Blanco-Donoso et al., 2022; Luo et al., 2020). Infection risk, workload, worry about infecting family members, inadequacy of personal protective equipment (PPE), disrupted work-life balance, increased weight of mental health concerns, and limited support are a few variables that contribute to this (Zhang et al., 2022; Blanco‐Donoso et al., 2022; Luo et al., 2020). The unexpected pandemic and its quick spread increased turnover rates in a workforce already experiencing shortage concerns. In the midst of the pandemic, a poll of nurses in the US revealed that three out of every five nurses intended to leave the field, which was supported by their experiences with the pandemic’s effects on work conditions (Zhang et al., 2022). The healthcare industry may collapse in the next years if the high turnover rates are not handled or catered to. These worries highlight how important and urgent it is to look at job satisfaction in light of the pandemic. Furthermore, little research has looked into the precise hygienic and modifiable incentive aspects that human resource professionals in hospital settings may prioritize to increase job happiness and lessen the otherwise overwhelming and attrition rates in the post-pandemic work (Bajrami et al., 2021; Zhang et al., 2022).
Purpose Statement
Healthcare employees’ performance in their responsibilities is largely dependent on how satisfied they are with their jobs (Dreison et al., 2018; Caligiuri et al., 2021). Addressing the hygiene and motivational aspects that affect healthcare employees’ mental health and, in turn, their capacity to perform to their full potential in their professions will be the first step in improving job satisfaction among these workers (Cruz et al., 2019; Dreison et al., 2018). Within the context of the Covid-19 outbreak, the research presented here focuses on examining job satisfaction among frontline/direct care healthcare personnel. The difficulty for modern HR is that a historically difficult pandemic that profoundly changed the workplace is slowly coming to an end. The modern and future HR will need to address historical issues that have an impact on job happiness while also examining brand-new issues brought up by the pandemic (International Labor Organization, 2020).
This research intends to measure the links between Herzberg’s job satisfaction theory and supervisor support, communication, workload, recognition, and resources during the pandemic. Furthermore, the research intends to use quantitative indicators to examine any changes in work satisfaction levels between 2018 and 2020. Norful et al (2021), in their investigation of the primary drivers, as well as the psychological manifestations of stress among American frontline workers quality communication and better supervisor support had significant positive impacts on job satisfaction, even during the difficult period when the frontline workers risked their lives to offer critical services. Rehder, Adair, and Sexton (2021), consistent with Norful et al (2021), also established that increased workload (which was a major issue during the pandemic, especially among healthcare workers), had an inevitable negative impact on work-life balance, which in turn affects job satisfaction negatively. A combination of poor work-life balance, increased workload, and uncertainty about the employees’ own safety also had a negative impact on their emotional wellbeing, which in turn had a negative impact on their happiness, as explained by (Ingusci, et al., 2021).
Conceptual Model
The conceptual model of this study offers a thorough theoretical foundation that directs the investigation of factors that affect job satisfaction of frontline workers, and their general well-being. The conceptual model aims to provide light on the underlying mechanisms and elements that affect the job satisfaction of healthcare workers during times of crisis. It does this by drawing on well-established ideas and concepts from the domains of healthcare management, psychology, and organizational behavior (Bieńkowska et al., 2022).
The conceptual model is developed based on the AES Framework, which is shown in the figure below. This is the framework that produced the All-Employee Survey (AES), which was used to collect the AES data that will be used to answer the overarching research question in this study. Under behavior, the elements studied are Supervisor tasks, Supervisor relationships, Workgroup tasks, and Workgroup relationships. Under Environment, the elements studied are Relationships and Workplace characteristics. Under Feelings, the elements studied are Attitudes towards work environment, Attitudes towards leaders, and Employee withdrawal.
Figure 1. The conceptual Model
Research Questions
The research herein seeks to explore on the factors that affect job satisfaction among frontline healthcare workers and further identify applicable recommendations for HR personnel to ensure swift adaptation to the new normal within the healthcare settings. The research applies a quantitative approach guided by the following research questions and Herzberg’s job satisfaction theory;
To what extent does supervisor support influence job satisfaction among frontline healthcare employees during the pandemic?
How does effective communication impact the job satisfaction of frontline healthcare workers amidst the challenges posed by the pandemic?
What is the relationship between workload intensity and job satisfaction among frontline healthcare employees during the pandemic?
How does recognition from supervisors and peers contribute to the job satisfaction of frontline healthcare workers during the pandemic?
In what ways do available resources (equipment, staffing, etc.) influence the job satisfaction of frontline healthcare workers during the pandemic?
Definition of Key Terms
All-Employee Survey (AES). An All-Employee Survey encompasses a comprehensive range of questions specifically designed to evaluate overall employee satisfaction within an organization. Beyond providing insights into employee satisfaction, AES surveys delve into leadership and management practices that play a crucial role in organizational performance (Perla & Barry & Grunberg, 2023 May).
Behaviors. Within the context of this study, behavior is examined through the lens of supervisor tasks, supervisor relationships, workgroup tasks, and workgroup relationships. These components collectively provide a framework for understanding the dynamics and interactions within the workplace environment (Perla & Barry & Grunberg, 2023 May).
Environment. For the purposes of this study, ‘environment’ encompasses two main elements: Relationships and Workplace characteristics. This term refers to the composite of physical, social, and psychological factors that define the workplace setting and significantly influence employee experiences and job satisfaction (Perla & Barry & Grunberg, 2023 May).
Feelings. This term is used to describe employees’ Attitudes towards their work environment, their leaders, and inclinations towards employee withdrawal. Feelings encapsulate the emotional responses and perceptions that employees hold concerning various aspects of their job and workplace (Perla & Barry & Grunberg, 2023 May).
Frontline healthcare workers. Frontline healthcare workers are defined as professionals armed with formal training, skills, and knowledge necessary for delivering direct care services to populations. They play a pivotal role in the healthcare system, interacting directly and frequently with patients, families, and communities. These workers are synonymous with direct-care workers and are characterized by their engagement in direct, predominantly physical, interactions with patients (Esterwood & Saeed, 2020).
Hygiene factors. Stemming from Herzberg’s Motivator-Hygiene theory of job satisfaction, hygiene factors, also known as dissatisfiers, underscore the extrinsic elements within the work environment that can lead to job dissatisfaction. Addressing and moderating these factors are essential for maintaining or enhancing levels of job satisfaction (Khanna, 2017).
Motivator factors. Drawn from Herzberg’s Motivator-Hygiene theory, motivator factors refer to the intrinsic elements inherent to the work environment that can significantly elevate or lead to job satisfaction. The enhancement of these factors is closely linked to achieving high levels of job satisfaction (Khanna, 2017).
Performance Promoter Score (PPS). PPS is introduced as an innovative metric designed to evaluate employee performance, especially during unforeseen crises such as a pandemic. Unlike traditional performance metrics that lean heavily on Key Performance Indicators (KPIs), PPS adopts a broader perspective by acknowledging various tasks and their contextual relevance. This approach allows for an inclusive measurement of performance, recognizing contributions beyond a worker’s formally defined scope of work (Aguinis & Burgi-Tian, 2020).
WFH (Work-From-Home). The WFH acronym stands for work-from-home, a concept that allows employees to execute their roles and responsibilities remotely, without the need for a centralized physical office space. Although the WFH model had been existing, its prominence and application surged remarkably during the COVID-19 pandemic (Gigauri, 2020).
Summary
Chapter 1 has laid a solid foundation for the understanding of the profound financial and operational impacts of staff job satisfaction in hospital settings. Through an in-depth exploration, we have identified key stressors such as fatigue, burnout, tiredness, workplace stress, and mental health issues that significantly affect healthcare professionals’ job satisfaction. The background discussion has illuminated the intricate relationship between these stressors and job satisfaction, highlighting the repercussions on both individual healthcare workers and the broader hospital operational efficacy. The importance of delving into these dimensions cannot be overstated, especially in the context of the recent COVID-19 pandemic, which has further exacerbated the challenges faced by frontline healthcare staff.
The examination of these critical issues sets the stage for a more detailed exploration of existing literature on the topic. As we transition into the next chapter, the focus will shift towards a comprehensive literature review. This review aims to contextualize the study within the broader academic discourse, drawing parallels and distinctions between the findings of previous research and the objectives of the current study. The literature review will explore various theoretical frameworks, empirical studies, and scholarly debates that inform our understanding of job satisfaction among healthcare workers. It will critically analyze existing knowledge, identify gaps in the literature, and lay the groundwork for the empirical investigation that this study proposes.
In essence, Chapter 2 will build upon the foundational insights provided in this opening chapter, weaving them into a broader scholarly tapestry. It will set the theoretical and conceptual parameters for the study, guiding the research design and methodology in a coherent and informed manner. This scholarly transition ensures a logical flow and continuity in the dissertation, facilitating a deeper understanding of the complexities surrounding job satisfaction in the healthcare sector.
Chapter 2: Literature Review
The literature review serves as a comprehensive exploration into the multifaceted domain of job satisfaction and its critical importance for healthcare workers, focusing specifically on the unique circumstances presented by pandemics such as COVID-19. This chapter methodically delves into various thematic areas pivotal to understanding the complex interactions between healthcare workers’ well-being and their work environment. These themes encompass job satisfaction, frontline healthcare workers’ experiences during pandemic conditions, the pivotal roles of supervisor support, effective communication practices, workload management, the significance of recognition, and the availability of resources within healthcare settings. The onset of the COVID-19 pandemic ushered in unprecedented operational and performance management challenges within healthcare organizations, highlighting the limitations of traditional Key Performance Indicator (KPI)-based performance management systems in adapting to the swift and severe shifts in working conditions (Aguinis & Burgi-Tian, 2020). Frontline healthcare personnel found themselves bearing the brunt of these challenges, facing increased responsibilities, extended working hours, and heightened risks of infection. These conditions rendered conventional pre-pandemic performance metrics inadequate for a comprehensive evaluation of job performance and satisfaction. Through a critical examination of empirical and theoretical literature, this chapter seeks not only to review existing knowledge but to uncover gaps in the literature where further research could contribute significantly to our understanding. By providing a detailed conceptual framework towards the chapter’s conclusion, it effectively lays the groundwork for the subsequent analysis and discussion, establishing a scholarly basis for the study’s pursuit of new insights and contributions to the field.
Literature Search Strategy
To undertake a thorough examination of job satisfaction among frontline healthcare workers during the COVID-19 pandemic, a detailed literature search strategy was meticulously developed and executed. This strategy encompassed a wide range of databases and sought to incorporate a broad spectrum of interdisciplinary research to provide a well-rounded analysis of the topic.
Database Selection and Search Execution. The primary databases selected for the initial search were PubMed and Cochrane, known for their comprehensive coverage of medical and health-related literature. Recognizing the interdisciplinary nature of job satisfaction, the search was expanded to include Web of Science, PsycINFO, Scopus, and Google Scholar. This expansion aimed to capture pertinent research across psychological, management, and healthcare disciplines.
Keyword Identification and Search Terms. The search began with identifying key terms relevant to the study’s focus. These included “frontline healthcare workers,” “direct-care workers,” “job satisfaction,” “COVID-19,” “pandemic,” “mental health,” “human resource performance management,” and “workplace policies.” Additional keywords related to the nuanced aspects of job satisfaction during the pandemic, such as “resilience,” “occupational stress,” “organizational support,” and “work-life balance,” were also incorporated.
Search Refinement. Boolean operators (AND, OR, NOT) were employed to create comprehensive and nuanced search strings. Initially, phrases like ‘frontline healthcare workers AND job satisfaction’ and ‘pandemic AND human resource AND job satisfaction’ were used. The search criteria were further refined by focusing on articles published between 2018 and 2023 to ensure the discussion’s timeliness and relevance, although seminal works outside this window were considered for foundational insights.
Screening and Selection Process. The initial search yielded hundreds of articles, which were then subjected to a rigorous screening process. Titles and abstracts were reviewed for relevance, with a focus on peer-reviewed research, systematic reviews, and guidelines. A full-text review followed to ensure each article’s alignment with the research questions and theoretical framework. Ultimately, 25 articles meeting these criteria were selected for in-depth analysis.
Quality Assessment and Bibliography Screening. To maintain a high evidence quality, articles underwent a standardized quality assessment. Furthermore, the bibliographies of selected articles were screened for additional relevant sources, a technique known as snowballing, which helped in identifying seminal works and emerging trends.
Ongoing Updates and Record Keeping. Acknowledging the evolving nature of COVID-19 research, the search strategy included provisions for periodic updates to capture new findings. Detailed records of search terms, databases, and outcomes were meticulously maintained, ensuring transparency and the reproducibility of the search process.
Transition to Methodology. Armed with a comprehensive understanding gleaned from the literature review, the next chapter will delve into developing a nuanced research methodology. This approach will be guided by the identified research gaps and insights from the reviewed literature, laying a solid foundation for theoretical and conceptual study development.
Synthesis of the Literature
Theoretical Orientation
Kurt Lewin’s Change Theory.
Kurt Lewin’s Change Theory has gained widespread recognition, especially during the Covid pandemic as a useful paradigm for navigating the changes that companies must inevitably undergo. Businesses, during this period, faced a unique set of challenges, and the adjustments it imposed were fundamental ones, not just on people’s ways of life, but also on service delivery and professional experiences. Transformational changes demand a more targeted approach on particular areas that have been impacted and need quick adaptation to prosper in the future business landscape, as contrast to ordinary transactional changes that affect the corporation as a whole (Bhattacharyya, 2020).
The connection between HR departments and employees has been strained as a result of these developments. HR professionals now have to carefully balance organizational goals with the expectations and worries of the workforce, which has more negotiating power as a result of the pandemic’s effects. In this situation, Kurt Lewin’s change model offers HR staff a useful and efficient framework for navigating these difficulties and ensuring smooth operations within healthcare institutions.
The analogy of reshaping an ice block is frequently used to illustrate Lewin’s transformation model (Figure 1). Three steps make up the process: unfreezing, altering, and refreezing. An ice block must first be defrosted in order to become pliable enough to be shaped into a cone. Similar to this, firms need to foster an environment that is change-friendly by addressing employee reluctance and encouraging readiness. The genuine transformation can start if the workforce is open to it. In order to address the post-pandemic requirements and concerns of the healthcare employees, HR personnel can then adopt the necessary improvements to job satisfaction initiatives, including new policies, support systems, and incentives.
Finally, to sustain the improvements made by HR professionals, the ice block must be refrozen, much as the changes made by HR personnel must be ingrained into the organization’s culture and procedures. In order to maintain the positive improvements in job satisfaction and workforce dynamics, it is necessary to integrate the new techniques into daily operations and to ensure continued support and communication (Bhattacharyya, 2020). Healthcare workers’ job satisfaction can be increased, the organization’s relationship with its workforce can be improved, and Lewin’s change model can be used by HR people to strategically handle the pandemic’s transformative issues. In the post-pandemic era, a more robust and successful organization will result from the model’s logical and structured approach, which guarantees that changes are well-planned, well implemented, and long-lasting. (Bhattacharyya, 2020).
Figure 2
Kurt Lewin’s Change model cycle
Unfreezing
Unfreezing
Refreezing
Refreezing 3
1
Transition/Change
Transition/Change 1
2
Herzberg Theory of Job Satisfaction.
Healthcare organizations faced similar extraordinary difficulties as other industries as a result of the Covid-19 pandemic. The pandemic has a severe negative influence on front-line healthcare personnel’ job satisfaction in addition to disrupting healthcare operations. Organizations and human resource (HR) staff had to adjust and plan in response to this crisis to satisfy the changing demands and concerns of the workforce. In the current study, the pandemic and the post-pandemic phases are used to illustrate how Herzberg’s theory of job satisfaction might be applied in a time of crisis.
Crisis Period and Diversified Hygiene Factors:
Healthcare employees had particular difficulties during the Covid-19 crisis era, which changed the dynamics of hygienic concerns at work. Due to the virus’s high level of contagiousness and the unpredictability of its epidemiological patterns, healthcare practitioners faced increased safety and security hazards (Alrawashdeh et al., 2021). The pandemic also reduced organizational resources, necessitating significant budgetary allocations to deal with new complications and pandemic-related demands. HR staff had to deal with a crisis period with a variety of hygienic problems as a result.
Integration with Kurt Lewin’s Change Model:
Figure 2’s representation of Kurt Lewin’s change model provides an organized method for handling change inside businesses. Unfreezing, altering, and refreezing are the three phases of the model. The emphasis is on combining methods to improve interpersonal relationships, provide reward and incentive programs, and introduce chances for career progression during the transition and refreezing stages (Hussain et al., 2018). These components emphasize the value of fostering job happiness and are closely related with Herzberg’s motivational factors.
Integrating Herzberg’s hygiene aspects is essential in Lewin’s second and third phases, which represent the change process. Human resources professionals must address the various hygiene issues brought on by the crisis to make sure that healthcare employees feel supported and well-equipped to operate at their best. Strategies may include improving working conditions, offering fair compensation packages, and providing resources to bolster employee well-being during these challenging times.
The rationale for the choice of Kurt Lewin’s and Herzberg’s theories
According to Herzberg’s thesis, employees and employers in any business will show signs of unhappiness over pay, benefits, and management (Khanna, 2017). Workers will, nevertheless, show signs of contentment as a result of motivating elements like achievement and acknowledgment. In order to satisfy the demands of the healthcare system during a pandemic, HR was forced to manage and optimize the workforce under extremely difficult circumstances because to the Covid-19 pandemic (Alrawashdeh et al., 2021). High rates of mortality and morbidity were characteristics of the pandemic (Rana et al., 2022). To ensure that even with the social distance regulations, these workers remained productive to the organization, the initial approach across most HR departments was to extend the working hours for healthcare workers and implement WFH programs.
HR professionals and their employers must plan a smooth transition back to work during the post-pandemic period. The healthcare environment has emerged as a workplace with a high workload, hazards to safety and security, is emotionally taxing, and has the potential to hinder career growth. This is a reality that the post-pandemic period cannot ignore (Rana et al., 2022). In addition, for jobs with comparable entry-level criteria, healthcare workers have been found to have the lowest rates of re-employment and re-entry in comparison to employees in other sectors of the economy (McCall et al., 2021). The fact that HR staff is still reluctance to raise the motivators and hygiene aspects is the cause of these poor re-employment and re-entry rates in healthcare (Figure 2). Instead of being governed by the actions of the HR staff, the workforce must believe that the rules or procedures that address their motivators and hygiene elements are their own (Khanna, 2017).
In all three phases of Lewin’s change model, communication and negotiation are highlighted by Herzberg’s theory (Rana et al., 2022). Lewin’s model’s initial phase of communication focuses on persuading the workforce to support the proposed change. The workforce is informed of their new roles in the new system or culture during the second phase of communication. The third phase of communication focuses on negotiating an acceptable work environment, culture, and workforce training and education, in addition to the parameters of the new workplace that have been agreed upon. Herzberg’s theory aims to use the workforce’s knowledge and experiences on the difficulties of the work environment in the current crisis time that the study analyzes in order to improve the hygiene and motivational aspects. Therefore, Herzberg’s theory continues to place emphasis on the need of communication in this improving process (Khanna, 2017; Hussain et al., 2018).
Conceptual framework
The conceptual framework of this study offers a thorough theoretical foundation that directs the investigation of factors that affect job satisfaction of frontline workers, and their general well-being. The conceptual framework aims to provide light on the underlying mechanisms and elements that affect the job satisfaction of healthcare workers during times of crisis. It does this by drawing on well-established ideas and concepts from the domains of healthcare management, psychology, and organizational behavior (Bieńkowska et al., 2022).
The conceptual framework is developed based on the AES Framework, which is shown in the figure below. This is the framework that produced the All-Employee Survey (AES), which was used to collect the AES data that will be used to answer the overarching research question in this study. Under behavior, the elements studied are Supervisor tasks, Supervisor relationships, Workgroup tasks, and Workgroup relationships. Under Environment, the elements studied are Relationships and Workplace characteristics. Under Feelings, the elements studied are Attitudes towards work environment, Attitudes towards leaders, and Employee withdrawal.
The conceptual framework developed from this survey is as shown in Figure 3 below.
This framework demonstrates how addressing the research questions related to supervisor support, effective communication, workload intensity, recognition, and available resources serves as crucial factors influencing job satisfaction among frontline healthcare workers. By examining these aspects within the context of Herzberg’s job satisfaction theory and considering their effects on mental health and well-being, HR personnel can develop strategies to enhance job satisfaction and adapt to the new challenges posed by the COVID-19 pandemic in healthcare settings.
The hypotheses that the study seeks to test are as follows:
H1: Supervisor support is positively associated with the job satisfaction of frontline healthcare workers, as influenced by the challenges of the pandemic.
H2: Effective communication has a positive impact on the job satisfaction of frontline healthcare employees amidst the pandemic-related difficulties.
H3: Increased workload intensity is linked to a decrease in job satisfaction among frontline healthcare workers during the pandemic.
H4: Recognition from supervisors and peers positively contributes to the job satisfaction of frontline healthcare workers facing pandemic-related challenges.
H5: The availability of resources (such as equipment and staffing) positively influences the job satisfaction of frontline healthcare workers during the pandemic.
Table 3
Table of Hypotheses
Research Question
Hypothesis
Primary Theory
1.To what extent does supervisor support influence job satisfaction among frontline healthcare employees during the pandemic?
1. Supervisor support is positively associated with the job satisfaction of frontline healthcare workers, as influenced by the challenges of the pandemic.
Social Exchange Theory (Khan & Ashraf, 2023)
2. How does effective communication impact the job satisfaction of frontline healthcare workers amidst the challenges posed by the pandemic?
2. Effective communication has a positive impact on the job satisfaction of frontline healthcare employees amidst the pandemic-related difficulties.
Communication Theory (Alegre et al., 2016)
3. What is the relationship between workload intensity and job satisfaction among frontline healthcare employees during the pandemic?
3. Increased workload intensity is linked to a decrease in job satisfaction among frontline healthcare workers during the pandemic.
Job Demand-Resources (JD-R) Model (Toon & Schaufeli, 2015)
4. How does recognition from supervisors and peers contribute to the job satisfaction of frontline healthcare workers during the pandemic?
4. Recognition from supervisors and peers positively contributes to the job satisfaction of frontline healthcare workers facing pandemic-related challenges.
Herzberg’s Two-Factor Theory (Alrawahi, Sellgren, Altouby, Alwahaibi, & Brommels, 2020)
5. In what ways do available resources (equipment, staffing, etc.) influence the job satisfaction of frontline healthcare workers during the pandemic?
5. The availability of resources (such as equipment and staffing) positively influences the job satisfaction of frontline healthcare workers during the pandemic.
Conservation of Resources (COR) Theory (Hobfoll, Halbesleben, Neveu, & Westman, 2018)
This alignment provides a structured approach to understanding the theoretical foundations that underpin the hypotheses.
Hypothesis 1 (H1): Supervisor Support and Job Satisfaction.
Primary Theory: Social Exchange Theory.
Rationale: This theory suggests that relationships (including those between supervisors and subordinates) are based on reciprocal exchanges. Positive exchanges, such as support and understanding from supervisors, are expected to enhance job satisfaction.
Hypothesis 2 (H2): Effective Communication and Job Satisfaction
Primary Theory: Communication Theory
Rationale: Central to this theory is the idea that effective communication within organizations is key to job satisfaction. Clear, timely, and effective communication helps in clarifying roles, reducing uncertainties, and enhancing employee satisfaction.
Hypothesis 3 (H3): Workload Intensity and Job Satisfaction.
Primary Theory: Job Demand-Resources (JD-R) Model.
Rationale: This model posits that while job demands (such as high workload) can lead to burnout and decreased job satisfaction, the availability of job resources can buffer these negative effects. The hypothesis directly aligns with the job demands aspect of this theory.
Hypothesis 4 (H4): Recognition and Job Satisfaction.
Primary Theory: Herzberg’s Two-Factor Theory.
Rationale: According to Herzberg, recognition is a ‘motivator’ that positively affects job satisfaction. This theory distinguishes between hygiene factors, which can cause dissatisfaction when absent but don’t necessarily motivate when present, and motivators like recognition that enhance job satisfaction.
Hypothesis 5 (H5): Availability of Resources and Job Satisfaction
Primary Theory: Conservation of Resources (COR) Theory
Rationale: COR theory posits that individuals strive to obtain, retain, and protect their resources. In a healthcare setting, resources such as adequate equipment and staffing are crucial. Their availability is likely to reduce stress and increase job satisfaction among healthcare workers.
In any firm, employee productivity and well-being depend heavily on job satisfaction. Frontline personnel’ job satisfaction is crucial in the healthcare industry since it has a direct impact on the standard of patient care. The Covid-19 pandemic substantially changed the working environment and impacted the job satisfaction of healthcare professionals, posing hitherto unheard-of issues for healthcare institutions. With an emphasis on how the pandemic has affected the job happiness of healthcare workers, this study examines the various expressions of job satisfaction and the factors that influence it. The study also provides a framework for HR professionals to solve the issues and give healthcare workers’ job satisfaction a priority.
Manifestations of Job Satisfaction
Job satisfaction is a multifaceted concept impacting not only professional performance but also personal well-being. Various external and internal factors contribute to one’s sense of job satisfaction. Externally, aspects such as interpersonal relations with colleagues and supervisors, the balance of workload, the level of organizational support, and opportunities for career growth play a crucial role (Rana et al., 2022). These elements can significantly influence an employee’s engagement, motivation, and overall satisfaction with their job.
Further, internal manifestations of job satisfaction or the lack thereof, can lead to profound psychological and physical responses. Employees experiencing low job satisfaction may suffer from energy depletion, increased negativism, cynicism towards their job, a diminished sense of accomplishment, and even serious health implications as a result of persistent stress and unfavorable job perceptions (Khanna, 2017). These inner turmoil manifestations are critical indicators that need addressing for maintaining a healthy work environment.
One of the most telling signs of job dissatisfaction is a high employee turnover rate. Specifically, within the healthcare sector, the Covid-19 pandemic has exacerbated the turnover phenomenon, with fundamental issues such as inadequate compensation, overwhelming workloads, and concerns over personal safety being cited as primary reasons for leaving the profession (Bieńkowska et al., 2022). This situation underscores the urgent need for strategic interventions.
To counteract these challenges, Barili et al. (2022) suggest that human resource managers should prioritize establishing robust recruitment and retention strategies. Improving the quality of the work environment, offering competitive compensation, and enhancing organizational support are key areas of focus. Moreover, instituting comprehensive support systems that address the overall wellness of healthcare workers could significantly improve job satisfaction and, consequently, lower turnover rates (Rana et al., 2022). By investing in workers’ job satisfaction, healthcare institutions can not only retain but also attract quality professionals, forming a resilient workforce capable of delivering superior patient care.
Influence of Personal Factors
The nexus between personal traits and job satisfaction has been a focal point of research within occupational psychology, particularly in high-stress sectors like healthcare. Personal traits—including age, gender, marital status, race/ethnicity, education level, years of service, and type of employment—play a substantial role in shaping an individual’s experience of job satisfaction. This complex interaction is further influenced by job-related elements, creating a multifaceted framework for understanding employee contentment. According to research by Blanco-Donoso et al. (2022), individual characteristics profoundly interact with work environments to influence satisfaction levels. Similarly, Luo et al. (2020) highlight the interplay between personal and work-related issues, pinpointing how variables such as age, gender, and education level intersect with occupational demands and settings.
Job-related factors, indeed, hold significant sway over job satisfaction levels. Workload, occupation type, work environment, salary and compensation packages, availability of resources, professional status, opportunities for career advancement, relationships with coworkers and managers, as well as performance evaluation mechanisms, are central to this discussion. In the context of the recent pandemic, these aspects have come under severe strain. Zhang et al. (2022) emphasize that the Covid-19 pandemic revealed and exacerbated underlying challenges within healthcare settings, influencing job satisfaction negatively. The pandemic’s role as a catalyst for increased workload, alongside the disruption of work-life balance, underscores the crucial need for robust support systems and adaptive work policies to safeguard healthcare workers’ job satisfaction during and beyond crises.
This evidence suggests a compelling argument for healthcare institutions, and HR professionals specifically, to adopt a holistic approach in addressing job satisfaction. Understanding the nuanced influences of personal and occupational factors is key to devising and implementing effective strategies aimed at fostering a supportive and satisfying work environment for healthcare professionals.
Impact of the Pandemic on Job Satisfaction
The global disruption caused by the Covid-19 pandemic has brought unprecedented challenges to healthcare operations, significantly altering the work landscape for frontline healthcare professionals. The intensification of workloads, coupled with the high-risk environment, has unequivocally affected job satisfaction levels within this cohort. McCall et al. (2021) highlighted that the pandemic’s onset saw a discernible decline in re-employment rates and willingness to re-enter the healthcare field, a trend not as evident in other industries. This downturn can largely be attributed to the pandemic’s exhaustive physical, mental, and emotional demands placed on healthcare workers.
Kolakowski (2020) emphasizes the imperative need for HR professionals to consider the mental and emotional wellbeing of employees with utmost importance. The backdrop of the pandemic has seen a significant rise in workplace burnout and stress, particularly pronounced among those engaging in remote work or telemedicine programs – a swift pivot many healthcare organizations had to make. The suggestion here points towards the critical need for HR departments to implement comprehensive support mechanisms, such as work-life balance initiatives, stress management programs, and direct mental health support, to mitigate these pandemic-induced challenges.
Additional studies reinforce the notion that the psychological wellbeing of healthcare staff is intricately linked to their overall job satisfaction. For instance, Lever et al. (2022) found that healthcare workers who reported higher levels of support from their organization exhibited lower levels of stress and higher job satisfaction ratings. Such findings argue for an organizational culture that places a premium on caring and support, encapsulating emotional, psychological, and logistical aspects of the work environment.
To steward healthcare organizations through this crisis and beyond, there’s a compelling argument for adopting a holistic approach to employee wellbeing. Integrating stress-reduction techniques, ensuring adequate access to mental health resources, and fostering a culture of transparency and support are pivotal strategies. Such an approach not only ameliorates the adverse impacts on job satisfaction triggered by the pandemic but also enhances overall employee performance, resilience, and commitment to the organization (Singh & Nayak, 2021).
In conclusion, the Covid-19 pandemic has undeniably revolutionized the landscape of healthcare work, underscoring the critical correlation between employee wellbeing and job satisfaction. The literature suggests that for healthcare organizations to navigate out of the pandemic-induced crisis effectively, a significant reevaluation of HR policies towards more supportive and employee-centered practices is indispensable. Through prioritizing mental and emotional wellbeing, healthcare organizations can foster a more resilient, satisfied, and high-performing workforce, ready to face the challenges of the future.
A Framework for HR Personnel
In the challenging times presented by the global health crisis, HR professionals are tasked with the crucial role of ensuring the well-being and job satisfaction of healthcare workers, a task that carries with it the weight of not only maintaining but also enhancing the quality of healthcare services. Central to this effort is the application of Herzberg’s Two-Factor Theory of job satisfaction, which posits that true employee motivation is achieved through the enrichment of ‘motivator’ factors such as opportunities for professional development, recognition of achievements, and meaningful work that challenges and fulfills (Khanna, 2017). Simultaneously, HR must attend to ‘hygiene’ factors, including but not limited to, the work environment, salary, and job security, which, though they do not in themselves motivate employees, can lead to significant dissatisfaction if neglected.
In parallel, the incorporation of Kurt Lewin’s Change Management Model underscores the necessity for HR personnel to undertake changes in a structured manner, emphasizing the importance of effective communication and employee involvement in the change process (Hussain et al., 2018). This approach becomes particularly salient in the context of a pandemic, where rapid adaptations to working conditions, policies, and procedures are commonplace. As such, engaging the workforce through clear, empathetic communication and allowing for feedback and dialogue is imperative in navigating these changes successfully.
Further strengthening this framework, research conducted by Alrawashdeh et al. (2021) and Rana et al. (2022) has underlined the importance of dynamic and flexible HR strategies in responding to the fluctuating demands of the healthcare sector during times of crisis. These studies advocate for a strategic approach to HR management that is not only reactionary but anticipatory, allowing HR professionals to allocate and optimize resources effectively, even under the pressure of increased demand and constrained supply typical of pandemic situations. This includes innovative staffing strategies, robust support systems for mental health, and initiatives aimed at enhancing job satisfaction and overall wellbeing among healthcare workers.
By synthesizing the theoretical foundations laid by Herzberg and Lewin with contemporary research insights, HR professionals are better equipped to navigate the intricate challenges of managing healthcare workforces during times of crisis. This approach not only facilitates a more resilient and responsive healthcare system but also contributes to a work environment where healthcare professionals feel valued, supported, and motivated. As this chapter unfolds, the interplay between theory and practice reveals the complexity of ensuring job satisfaction among healthcare workers in the face of a pandemic, highlighting the pivotal role HR personnel play in fostering an environment conducive to high morale and optimal performance.
Summary
In this comprehensive literature review, we delved into the complex and multi-dimensional nature of job satisfaction within the healthcare sector, with a particular focus on the pivotal role frontline healthcare workers have played during the COVID-19 pandemic. Through the synthesis of current research and theoretical frameworks, we identified key factors influencing job satisfaction, including supervisor support, communication, workload, recognition, and resource allocation. These elements have been critically analyzed to understand their impact on healthcare workers’ mental and emotional well-being, as well as on their overall job performance and retention rates.
Significant points highlighted include the crucial role of effective communication and robust supervisor support in enhancing job satisfaction. Additionally, the literature underscores the negative implications of excessive workload and inadequate resources on healthcare professionals’ job satisfaction, pointing to an urgent need for systemic changes within healthcare organizations.
As we transition to Chapter 3, the focus will shift towards outlining the methodology used in further investigating the relationship between job satisfaction and its various influencing factors among frontline healthcare workers during the pandemic. This upcoming chapter will detail the research design, sampling techniques, data collection methods, and analytical strategies employed to provide empirical insights into enhancing job satisfaction levels within this critical workforce segment. The methodological framework outlined in Chapter 3 will bridge the theoretical insights from the literature review with practical research, aiming to offer evidence-based recommendations to improve job satisfaction among frontline healthcare professionals.
Chapter 3: Methodology
The problem this study investigates is the unparalleled challenges faced by the global healthcare sector in the wake of the COVID-19 pandemic, with a focus on the critical role of frontline healthcare workers within this context. The purpose of this research is to explore the impact of supervisor support on the psychological well-being of frontline healthcare workers, incorporating factors such as job satisfaction, burnout, and available resources. This chapter outlines the methodological framework adopted to address the research problem and achieve the study’s objectives. It details the research model, encompassing the study design, population, sample selection, data collection methods, and the approach for data analysis. Additionally, this chapter discusses the ethical considerations inherent in conducting research within a healthcare context. By providing a comprehensive overview of the methodology, this chapter sets the foundation for understanding how the study aims to contribute valuable insights into the support systems for healthcare professionals during crises.
Research Methodology and Design
The chosen research methodology for this study is quantitative using secondary data, leveraging a comprehensive approach to examine the intricate dynamics of job satisfaction among frontline healthcare workers during the COVID-19 pandemic. This methodology was selected for its robustness in allowing for a precise, numerical analysis of data related to job satisfaction, supervisor support, communication, workload, recognition, and available resources. Quantitative research is instrumental in identifying patterns and correlations between variables, providing a solid foundation for drawing generalizable conclusions (Creswell & Creswell, 2018). While qualitative methods offer depth in understanding individual experiences, the quantitative approach’s ability to analyze large data sets through statistical methods makes it particularly suited for this study, which aims to explore broad patterns and make predictions based on secondary data obtained from the All-Employee Survey (AES). The decision to use a quantitative methodology over a qualitative one is underpinned by the study’s objective to quantify the extent to which various factors influence job satisfaction, rather than to explore these factors’ nuanced, subjective experiences.
The research design adopted for this study is a cross-sectional survey design, which involves collecting data at a single point in time to analyze the relationship between job satisfaction and several independent variables among frontline healthcare workers. This design was chosen for its efficiency in data collection and its effectiveness in facilitating the investigation of multiple variables simultaneously (Bryman, 2015). The cross-sectional design allows for a broad understanding of the factors influencing job satisfaction during the specific period of the COVID-19 pandemic, providing a snapshot of the experiences and perceptions of healthcare workers. Although longitudinal designs could offer insights into how these relationships change over time, a cross-sectional approach was deemed more appropriate for this study given the logistical constraints and the need to assess the impact of the pandemic during a defined time frame. Furthermore, this design aligns with the study’s goals to evaluate the current state of job satisfaction and its determinants, making it a practical and relevant choice. The ability to use existing secondary data from the AES simplifies the process of gathering a wide range of information without the lengthy timeline and higher costs associated with longitudinal studies.
Role of the Researcher
As the principal researcher of this study, my role encapsulates several key responsibilities and ethical obligations, primarily geared towards objectively examining the relationship between job satisfaction and various influencing factors among frontline healthcare workers within the context of the St. Louis VA Health Care System. My position as a Health System Specialist on the executive team at the St. Louis VA Health Care System places me in a unique vantage point to conduct this research, providing me with an intimate understanding of the organizational culture, operational dynamics, and the potential challenges and stressors that frontline healthcare workers may face.
Given my role within the organization, it is imperative to acknowledge and strategically navigate any relationships that may exist with participants or the broader organization that could impact the study’s objectivity. My professional standings within the healthcare system afford me the capability to facilitate the efficient use of the All-Employee Survey (AES) and ensure a high response rate due to established trust and credibility. However, it also necessitates the implementation of rigorous measures to mitigate bias and maintain the integrity of the research process.
To address these concerns, several strategies will be employed:
Anonymity and Confidentiality. The responses to the AES are completely anonymous and that the data is reported in aggregate form to protect the identities of individual participants. This will help in alleviating any apprehensions among the staff regarding potential reprisals for their feedback, thereby encouraging more honest and forthright responses.
Objective Data Analysis. Utilizing statistical methods and software to analyze the survey data impartially, thereby minimizing the influence of my own biases or preconceptions on the study’s findings.
Transparency. Being open about my position within the organization and how it may relate to the research, while also maintaining a strict separation between my duties as a Health System Specialist and my responsibilities as a researcher to avoid any conflicts of interest.
In summary, my role as a researcher in this study involves not only designing and overseeing the collection and analysis of data but also being acutely aware of the potential impacts of my organizational role on the research process. By implementing measures to safeguard the integrity of the research and maintain the trust of the participants, this study aims to contribute valuable insights into the dynamics of job satisfaction among frontline healthcare workers, with potential implications for improving workplace environments within the VA healthcare system and beyond.
Population and Sample Selection.
In this study, the overarching population of interest is comprised of frontline healthcare workers serving within the St. Louis VA Healthcare System. This targeting responds directly to the heightened pressures and unique challenges faced by this group during the COVID-19 pandemic. There will be no sample selection as this study will use secondary data focusing specifically on employees who have direct patient contact and are therefore more likely to experience factors affecting job satisfaction, such as supervisor support, workload, and communication efficacy. To accurately gauge the sentiments and experiences of these individuals, the study will rely on the All-Employee Survey (AES), a standardized and validated tool, administered by the VA St. Louis Health Care System’s administration. This methodological choice not only leverages existing infrastructures but also aligns with the study’s commitment to ethical and effectual data collection.
Aiming for robust statistical power and meaningful effect sizes, a power analysis will be conducted to determine the requisite size for this research. This analysis will be foundational in ensuring that the study is adequately equipped to identify significant relationships within the data, thus enhancing the reliability and validity of the findings. Detailed results of this power analysis will be included in the appendices of the study to ensure transparency and replicability. No active participant recruitment will be conducted with the St. Louis VA Healthcare System employees. Given the study’s setting and population, necessary permissions will be sought from both the healthcare system’s administration and its ethics review board.
Instrumentation
This study will be based on the AES survey questionnaire, which is divided into three sections, with the first section on basic/demographic information, the second section is the closed-ended questions based on SIJS (Short Index of Job Satisfaction), and part 3 is based on open-ended questions. The PHQ-2 (Patient Health Questionnaire) and the SEHC (Satisfaction of Employees in Health Care) Survey are also included to complement the SIJS to assess job satisfaction levels more fully.
Adapting the SIJS is tailored to align with the particular variations in the healthcare context, which ensures relevance and accuracy, especially in the assessment job satisfaction. The open ended in Part 3 gives the respondents to express themselves and offer explanations while responding to the questions in the survey. To augment the assessment of job satisfaction levels, the PHQ-2 and SEHC Survey are integrated with the SIJS. The PHQ-2, a validated instrument for measuring depression, is incorporated to account for its potential impact on job satisfaction. The SEHC Survey, tailored for healthcare settings, captures additional dimensions of satisfaction related to the work environment, thereby offering a comprehensive evaluation of job satisfaction among frontline healthcare workers.
Variables and Operational Definitions
Dependent Variable: Job Satisfaction
Operational Definition: Job satisfaction in this study is defined as an employee’s affective and cognitive appraisal of their job as a whole, including aspects like work environment, role clarity, supervisor support, and remuneration. It reflects the extent to which employees feel content with their job and its various components.
Operationalization: To measure job satisfaction, we will employ the Job Satisfaction Survey (JSS) developed by Paul E. Spector (1985). The JSS is a widely used diagnostic instrument designed to assess employee satisfaction with various facets of their job, including pay, promotion, benefits, supervisor, coworkers, work conditions, communication, nature of work, and job in general. The survey consists of 36 items, with each facet of job satisfaction being addressed by four items. Responses are recorded on a 6-point Likert scale ranging from “Disagree Very Much” (1) to “Agree Very Much” (6).
Measurement: Participants’ responses to the JSS items will be summed to create a composite score for each facet of job satisfaction, with higher scores indicating greater satisfaction. A total job satisfaction score will also be calculated by summing the scores of all facets, providing a comprehensive measure of the employee’s overall job satisfaction.
Source and Reliability: The JSS was developed by Paul E. Spector in 1985 and has been used in numerous research studies across different industries and countries, establishing its applicability and reliability across diverse work settings. The scale has demonstrated good reliability, with Cronbach’s alpha coefficients reported in the range of .70 to .90 for the different facets of job satisfaction.
Independent Variables
Supervisor Support. Operational Definition: Supervisor support is defined in this study as the extent to which supervisors provide guidance, resources, emotional support, and constructive feedback to frontline healthcare workers. This includes accessibility of supervisors, availability of support in stressful situations, and the adequacy of communication between supervisors and employees regarding job expectations and performance.
Operationalization: Supervisor support will be operationalized using specific items from the All-Employee Survey (AES). Questions related to “Support from Supervisor,” such as “My supervisor is available when I need help,” “My supervisor provides constructive feedback,” and “I feel supported by my supervisor in my work,” will be used.
Measurement: Responses to these items will be on a Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The scores will be averaged to create a composite score for supervisor support for each respondent.
Scale Source and Reliability: The AES, developed by the VA Health Care System’s administration. Previous iterations of the AES have reported Cronbach’s alpha coefficients for the “Support from Supervisor” scale in the range of 0.85 to 0.90, indicating high reliability.
Effective Communication. Operational Definition: Effective communication is defined as the clarity, frequency, and quality of the exchange of information between healthcare workers and their supervisors, colleagues, and the organization at large. This includes timely updates on changes in procedures, availability of resources, and responses to inquiries.
Operationalization: Measured by AES items such as “I am well-informed about important changes in my work environment,” “Communication between staff is effective in my unit,” and “My team regularly discusses ways to improve patient care.” Responses will be rated on a Likert scale from 1 (Strongly Disagree) to 5 (Strongly Agree).
Measurement: A composite score for effective communication will be created by averaging respondents’ scores on the related items.
Scale Source and Reliability: Derived from the All-Employee Survey (AES) with reported Cronbach’s alpha coefficients for communication-related items typically ranging from 0.80 to 0.88.
Workload Intensity. Operational Definition: Workload intensity refers to the volume and complexity of tasks that frontline healthcare workers are expected to manage within their work hours, including patient care responsibilities, administrative tasks, and any additional duties stemming from the COVID-19 pandemic.
Operationalization: Assessed using AES items that query respondents about their perceptions of workload, such as “I have a manageable workload,” “The amount of my work is reasonable,” and “My workload corresponds appropriately with my role.” Ratings are based on a 1 (Strongly Disagree) to 5 (Strongly Agree) Likert scale.
Measurement: The individual responses will be averaged to yield a workload intensity score for each participant.
Scale Source and Reliability: Sourced from the All-Employee Survey, with previous reports indicating a reliability measure (Cronbach’s alpha) for workload-related items around 0.82.
Recognition and Rewards. Operational Definition: Recognition and rewards are defined as formal and informal recognitions, incentives, and acknowledgments of employees’ efforts, accomplishments, and contributions to the organization and patient care.
Operationalization: Evaluated through AES items such as “My contributions are valued by the organization,” “I receive recognition for doing my job well,” along with questions assessing satisfaction with rewards and incentives. Responses are given on a Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree).
Measurement: A composite recognition and rewards score will be calculated by taking the mean of relevant item scores.
Scale Source and Reliability: Obtained from the All-Employee Survey, with reliability measures (Cronbach’s alpha) for recognition-related items typically above 0.80.
Available Resources. Operational Definition: Available Resources for frontline healthcare workers encompasses the spectrum of both tangible (e.g., personal protective equipment, medical supplies) and intangible resources (e.g., informational support, training opportunities) that are necessary and accessible for performing their duties effectively. This includes resources allocated for prevention, diagnosis, treatment, and general patient care.
Operationalization: The measurement of ‘Available Resources’ will be realized through a self-reported questionnaire that assesses the perception of adequacy and accessibility of both tangible and intangible resources. Items will cover aspects such as the sufficiency of protective gear, availability of necessary medical equipment, access to up-to-date medical information, and availability of training and support.
Measurement: To measure ‘Available Resources,’ a modified version of the Health Work Environment Scale (HWES) will be utilized, focusing specifically on the scale items related to resource availability. Respondents will rate their agreement with statements on a Likert scale from 1 (Strongly Disagree) to 5 (Strongly Agree).
Source and Reliability: The original Health Work Environment Scale was developed by Smith et al. (2012) and has demonstrated good psychometric properties in various settings. The Cronbach’s alpha for the original scale was reported as .89, indicating high reliability. The modification for this study will maintain the core items related to resources while ensuring the context aligns with the current healthcare setting. Prior to the main study, a pilot test will be conducted to confirm the reliability of the modified scale within the targeted population.
Demographics and Control Variables
Age. Justification: Age is collected to examine the potential influence of generational differences on perceptions of supervisor support and psychological outcomes. Different age groups may have diverging expectations and experiences in the workplace, potentially affecting their responses to supervisory practices.
Gender. Justification: Collecting data on gender is vital to explore if there are any gender-based differences in the perception of supervisor support and its impact on job satisfaction and psychological well-being. It helps in identifying if tailored interventions are needed for different gender groups within the healthcare sector.
Years of Experience in Healthcare – Justification: The duration of experience in the healthcare sector is an important variable that can influence the impact of supervisor support. More experienced professionals may have different expectations, coping mechanisms, and support needs compared to their less experienced counterparts.
Role in Healthcare (e.g., Nurse, Doctor, Administrative Staff). Justification: This variable allows for the analysis of whether perceptions of supervisor support and its effects differ across various roles within the healthcare sector. Understanding these differences is critical for implementing role-specific support mechanisms.
Educational Level – Justification: Educational level is collected to explore if there are variations in the perception of supervisor support and its outcomes across different levels of educational attainment. This information can inform targeted educational programs or interventions.
Work Shift (Day/Night) – Justification: The nature of the work shift (day or night) could influence the perception and effects of supervisor support due to the unique challenges and dynamics of night shifts. Identifying differences based on work shift can help in designing shift-specific support strategies.
Type of Employment (Full-time/Part-time). Justification: This variable is important to understand if there are differences in experiencing supervisor support and its associated outcomes between full-time and part-time workers. It could highlight the need for different approaches in managing part-time employees.
Ethnicity. Justification: Ethnicity is collected to explore cultural differences in the perception of supervisor support and its impact on psychological well-being and job satisfaction. This aids in creating culturally sensitive support programs.
By collecting these demographic and control variables, the study aims to provide a comprehensive understanding of how supervisor support operates within the diverse workforce of frontline healthcare workers. This nuanced approach can contribute to developing more effective and inclusive support strategies, enhancing the well-being of healthcare professionals.
Table 2
Summary of Variables
Data Collection
The current study utilizes secondary data obtained from the administration of the All Employee Survey (AES) by the VA St. Louis Health Care System. This data collection focuses on surveys conducted over a three-year period, from 2018 to 2020. The AES serves as a comprehensive tool designed to evaluate aspects of workplace environment and employee engagement within the system. Its deployment across these years offers a rich dataset to analyze trends, shifts, and patterns in employee perspectives and job satisfaction.
Description of Collection Method
The AES employs a standardized questionnaire that is both validated and tailored to gauge various dimensions of the workplace experience. The survey encompasses a wide array of topics including interpersonal relationships at work, perceptions of leadership, feelings of achievement, and overall job satisfaction. Items within the survey are crafted to maintain succinctness, clarity, and direct relevance to the organizational context of the VA St. Louis Health Care System. The questionnaire skillfully balances the collection of quantitative data through structured queries and qualitative insights via open-ended questions, allowing for a nuanced exploration of the workforce’s sentiment and engagement levels.
Employees participating in the AES were assured anonymity, encouraging candor in their responses and thus enhancing the validity of the collected data. The administration of the survey adhered to stringent protocols to ensure confidentiality and protect the privacy of all respondents. Personal identifiers were removed or masked before the dataset was made available for analysis, safeguarding participant privacy while maintaining the integrity and utility of the data for research purposes.
Validity and Reliability
The AES as an instrument has undergone rigorous validation processes to ensure its questions are both reliable and valid measures of the constructs they aim to assess. Its standardized format is the result of methodical development involving pilot testing, feedback revisions, and iterative refinement to enhance its overall reliability. This ensures that the survey accurately captures the nuanced dynamics of workplace satisfaction and engagement among healthcare personnel.
In utilizing this secondary data, the study inherits the AES’s established validity and reliability, providing a strong foundation for the examination of employee job satisfaction within the VA St. Louis Health Care System. The consistent application of the survey across multiple years further bolsters the reliability of the data, offering a temporal depth that enriches the analysis and interpretation of the findings according to the research questions at hand.
The comprehensive approach taken in the AES’s design and implementation, coupled with the rigorous attention to validity and reliability, ensures that the secondary data acquired for this study are both robust and highly credible, enabling a detailed exploration of workplace dynamics and employee satisfaction within the healthcare setting.
Data Analysis
To ensure the integrity and validity of our research findings, the data analysis process for this study will be conducted meticulously, with a methodical approach to prepare, clean, and analyze the data.
The steps outlined below detail our comprehensive strategy for data analysis:
Data Cleaning: The initial step involves a thorough examination of the dataset for any missing values, outliers, or inconsistencies. We will employ missing value analysis to determine the extent and pattern of missing data. Appropriate strategies, such as imputation or case exclusion, will be considered based on the nature and amount of missing data. Duplicate entries will be identified and removed to ensure the uniqueness of each data point.
Data Coding (if applicable): For qualitative variables or open-ended survey responses, a coding scheme will be developed. This involves assigning numerical values to categories or themes to facilitate quantitative analysis. The coding scheme will be tested on a subset of data to ensure its reliability, with adjustments made as necessary.
Validity and Reliability Testing: To assess the validity of the survey instruments or data collection tools, factor analysis may be used for scale validation. This helps in confirming that the questions measure the constructs they are intended to measure. Reliability testing, through Cronbach’s alpha or inter-item correlation, will be performed to evaluate the consistency of responses across similar items in the survey.
Hypothesis Testing: For each research question and corresponding hypothesis, appropriate statistical tests will be selected based on the nature of the data and the specific hypothesis being tested. Logistic regression will be the primary method for testing hypotheses involving categorical dependent variables (e.g., job satisfaction) and one or more independent variables (e.g., supervisor support, effective communication). Before conducting logistic regression analyses, assumptions such as the absence of multicollinearity among predictor variables will be checked. The Hosmer and Lemeshow test may be used to assess the goodness-of-fit for the logistic regression models. Results will be interpreted based on the odds ratios, confidence intervals, and significance levels obtained from the logistic regression analyses.
Descriptive Statistics: Descriptive statistics will be employed to provide an overview of the sample demographics and main variables of interest. Measures such as means, standard deviations, frequencies, and percentages will be used to summarize the data.
Data Interpretation and Discussion: The findings from the logistic regression analyses and descriptive statistics will be interpreted in the context of the existing literature and theoretical frameworks outlined in earlier chapters. Limitations of the analysis, potential biases, and implications for future research will be discussed.
Each step in the data analysis process will be carefully documented, ensuring transparency and reproducibility of the findings. The SPSS software (version 25) will be utilized for both descriptive and inferential statistical analyses, facilitating a detailed exploration of the relationships between variables and testing of the study’s hypotheses.
Table 3: Summary of hypotheses, variables, and statistical methods.
RQ
Hypotheses
Statistical Method
Qualitative or Quantitative
Data Source
Data Type
Dependent Variable
Independent Variables
1.To what extent does supervisor support influence job satisfaction among frontline healthcare employees during the pandemic?
H1: Supervisor support is positively associated with the job satisfaction of frontline healthcare workers, as influenced by the challenges of the pandemic.
Logistic Regression
Quantitative
AES Survey
Secondary
Job Satisfaction
Supervisor Support
2. How does effective communication impact the job satisfaction of frontline healthcare workers amidst the challenges posed by the pandemic?
H2: Effective communication has a positive impact on the job satisfaction of frontline healthcare employees amidst the pandemic-related difficulties.
Logistic Regression
Quantitative
AES Survey
Secondary
Job satisfaction
Effective Communication
3. What is the relationship between workload intensity and job satisfaction among frontline healthcare employees during the pandemic?
H3: Increased workload intensity is linked to a decrease in job satisfaction among frontline healthcare workers during the pandemic.
Logistic regression
Quantitative
AES Survey
Secondary
Job Satisfaction
Workload Intensity
4. How does recognition from supervisors and peers contribute to the job satisfaction of frontline healthcare workers during the pandemic?
H4: Recognition from supervisors and peers positively contributes to the job satisfaction of frontline healthcare workers facing pandemic-related challenges.
Logistic regression
Quantitative
AES Survey
Secondary
Job satisfaction
Recognition and Rewards
5. In what ways do available resources (equipment, staffing, etc.) influence the job satisfaction of frontline healthcare workers during the pandemic?
H5: The availability of resources (such as equipment and staffing) positively influences the job satisfaction of frontline healthcare workers during the pandemic.
Logistic regression
Quantitative
AES Survey
Secondary
Job Satisfaction
Available Resources
Assumptions
In this study, several critical assumptions have been identified to underpin the research design, population, and the methodological approach for evaluating the impacts of various factors on frontline healthcare workers during the pandemic. These assumptions are imperative to acknowledge as they help in understanding the boundaries and the interpretative lens through which the findings should be viewed.
Independence of Observations. It is assumed that the data collected from participants are independent of each other. Rationale: The independence assumption is crucial for statistical tests to yield valid results, as it ensures that the outcome of one observation does not influence another. Scale of Measurement: It is assumed that the data collected will be at an interval or ratio level of measurement, which is necessary for the application of parametric tests.
Impact of the Pandemic. It is assumed that the COVID-19 pandemic has had a significant impact on the job satisfaction levels of participants, sufficient to be detected through our data collection methods. Rationale: This assumption is based on existing literature and research findings suggesting widespread effects of the pandemic on healthcare workers’ job satisfaction and overall wellbeing.
Effects of Variables on Frontline Workers. Variables such as quality of communication, supervisory support, and resource availability are presumed to have a significant impact on the frontline workers. Rationale. Prior research and theoretical frameworks suggest these factors play crucial roles in employee satisfaction and engagement, especially in high-stress environments.
Demographic Variability. The use of demographic variables as covariates is based on the assumption that these factors will reveal variations in employees’ workplace experiences. Acknowledging and transparently discussing these assumptions not only identifies the study’s theoretical and methodological underpinnings but also enhances the credibility and reliability of the research findings.
Limitations
In conducting this quantitative study, it is vital to openly acknowledge and address the inherent limitations that could potentially impact the interpretation, validity, and generalizability of the findings. The following outlines these limitations and the strategies employed to mitigate their effects where feasible.
Data Availability and Accessibility. As noted, obtaining historical AES data requires permissions and data sharing agreements, which may limit the scope of data accessible for analysis. To mitigate this limitation, the study will seek to establish early communication with relevant authorities and organizations to outline the necessity and potential benefits of the research. Additionally, the study will explore alternative datasets that could provide supplementary insights if access to preferred data is restricted.
Sample Representativeness. There is a risk that the sample may not fully represent the broader population of frontline healthcare workers, particularly if participant recruitment encounters challenges such as low response rates or selection bias. To address this, the study will deploy stratified sampling methods whenever possible to ensure a diverse and representative sample. Recruitment efforts will also include multiple channels and strategies to enhance participation rates across different demographics and professional categories.
Participant Honesty and Response Bias. The integrity of self-reported data may be compromised by social desirability bias or inaccuracies in participant responses. To mitigate this, the study will emphasize the confidentiality and anonymity of the survey process in recruitment and data collection materials. Additionally, the survey will be designed to include indirect questioning and validated scales to reduce the likelihood of biased responses.
Missing Data and Nonresponse. Missing data and nonresponse can significantly impact the analysis and interpretation of results. The study will employ multiple imputation techniques and sensitivity analyses to handle missing data effectively, thereby preserving the robustness of the study findings. Efforts to minimize nonresponse will include follow-up reminders and incentives for survey completion.
Threats to Validity. Potential threats to internal and external validity, such as measurement error, confounding variables, and generalizability issues, will be rigorously evaluated. The study design includes pre-testing of the survey instrument to ensure its reliability and validity. Additionally, statistical controls for confounding variables will be applied during data analysis to address potential biases.
while these limitations present challenges to the study’s design and outcomes, acknowledging and proactively addressing them strengthens the research process. By implementing these mitigating strategies, the study aims to enhance the reliability, validity, and usefulness of its contributions to the literature on frontline healthcare workers during the COVID-19 pandemic.
Delimitations
This study is explicitly delimited to frontline healthcare professionals, including nurses, doctors, and pharmacists, who were actively engaged in patient care during and subsequent to the COVID-19 pandemic. This delineation ensures that the data collected reflects the experiences and viewpoints of those directly confronted with the myriad challenges presented by the pandemic. By focusing on this specific cohort, the research aims to distill the unique stressors, supports, and job-related sentiments experienced by these vital healthcare providers, thereby offering nuanced insights into factors influencing their job satisfaction and overall wellbeing during an unprecedented global health crisis.
Moreover, the study is limited by its exclusive reliance on survey questionnaires as the primary data collection instrument. Despite potential pitfalls such as common-method bias and recall bias, this method was chosen for its efficiency and uniformity, providing a structured means for participants to convey their experiences comprehensively. Furthermore, the utilization of a Likert scale to gauge responses is a deliberate decision to capture the gradations in participants’ attitudes, perceptions, and satisfaction levels effectively. This methodological approach aligns with the study’s objectives to explore the complex interplay of job-related factors impacting frontline healthcare workers, framed within the broader literature and theoretical paradigms addressing job satisfaction and employee wellbeing in high-stress professions. By acknowledging these delimitations, the study delineates its scope in accordance with its problem statement and research questions, mapping a focused investigation into the repercussions of the pandemic on a critically impacted segment of the healthcare workforce.
Reliability and Validity
To ensure the reliability and validity of this study, several strategies will be rigorously implemented across both quantitative and, if applicable, qualitative components. For the quantitative aspect, reliability will be ascertained through the use of established, validated measurement instruments wherever possible. Piloting of the survey instrument among a small subsection of the target population will be carried out to test for consistency and repeatability of responses. Any adjustments needed will be made based on this pilot test to enhance reliability. For validity, careful attention will be paid to content, criterion, and construct validity. Content validity will be addressed by ensuring that the survey items comprehensively cover the concepts being measured. Criterion validity will be evaluated by comparing the outcomes with relevant benchmarks or outcomes known from previous research, while construct validity will be assessed through factor analysis to verify that the measures accurately reflect the theoretical constructs.
In potential qualitative components, credibility will be established through prolonged engagement and member checking, where participants will have the opportunity to review and provide feedback on the findings. Dependability will be addressed by maintaining a clear and detailed audit trail of the research process, allowing for replication. Confirmability will be ensured through triangulation, using multiple data sources, methods, or investigators to cross-verify findings, thereby reducing bias. Transferability, though limited in qualitative research due to the specificity of contexts, will be facilitated by providing a detailed description of the research context and participants, allowing others to evaluate the applicability of findings to their situations.
Overall, attention to bias will be paramount across all stages of the research. Efforts to mitigate bias include blind data analysis, where the researcher is unaware of the participant’s group allocations during the processing and analysis of data, and ensuring diversity in participant selection to avoid over-representation of specific groups. By adhering to these strategies, the study aims to enhance the reliability and validity of its findings, contributing valuable insights into the impact on frontline healthcare workers during and after the COVID-19 pandemic.
Ethical Assurances
This study is committed to upholding the highest standards of research ethics, in strict accordance with the Helsinki Declaration, and will proceed only after obtaining formal approval from the Trident University International Institutional Review Board (IRB). Prioritizing the rights, safety, and wellbeing of participants, the study design includes comprehensive ethical assurances tailored to the specific needs of the proposed research and its participants.
Informed consent procedures are a cornerstone of our ethical considerations. Although this study primarily utilizes secondary data from the All-Employee Survey (AES), the original data collection ensured all participants provided informed consent, understanding the scope of the research and their role within it, including assurances regarding anonymity and confidentiality. For any potential primary data collection, informed consent will be rigorously sought, clearly communicating the study’s purpose, the voluntary nature of participation, risks, benefits, and the right to withdraw at any time without penalty.
Confidentiality and anonymity are paramount. The study employs several measures to maintain the highest level of data privacy and participant confidentiality. Each participant’s information is assigned a unique, system-generated code, eliminating direct links between data and personal identifiers. This approach significantly minimizes any possible risk or discomfort participants might experience from their involvement. Data security is further ensured through the use of password-protected computer systems and secure, encrypted data storage solutions. According to Trident University International guidelines and ethical standards, all collected data will be meticulously managed, stored securely during the research process, and appropriately disposed of or permanently anonymized one year post-study completion, safeguarding against unauthorized access or disclosure.
The role of the researcher is clearly defined to maintain objectivity and mitigate any potential bias. Aware of the inherent biases and personal experiences that may affect the study, strategies including method triangulation, peer debriefing, and reflexive journaling will be employed to ensure these do not influence data analysis or findings. The researcher’s engagement with the topic, problem, or context has been critically reflected upon to preemptively address any potential influence on the study’s objectivity.
Finally, obtaining ethical assurances and formal IRB approval is a meticulous process that involves detailing the study’s adherence to ethical guidelines, demonstrating comprehensive measures for participant protection, and outlining the researcher’s commitment to ethical integrity throughout the research process. A confirmation statement assures that no data collection or analysis will commence until Trident University International’s IRB approval is granted, ensuring that the study meets all requisite ethical standards set forth by the institution and the broader research community.
Summary
This chapter meticulously outlines the methodology adopted in this study, beginning with a restatement of the problem: the significant challenges encountered by the global healthcare sector, particularly highlighting the imperative role of frontline healthcare workers during and post the COVID-19 pandemic. It underscores the purpose of the study, which is to explore how factors such as supervisor support, job satisfaction, mental health outcomes, and available resources impact these workers within their professional capacities.
The research design specified is quantitative, employing a cross-sectional survey methodology aimed at capturing a snapshot of frontline healthcare workers’ experiences and perceptions. A comprehensive description of the population, sample size, sampling methods, and inclusion criteria ensures a clear understanding of who the participants are and how they were selected. Data collection instruments, specifically designed surveys, and measurement scales for variables like job satisfaction and mental health, are thoroughly vetted for reliability and validity, guaranteeing that data gathered will be both accurate and relevant.
Data analysis procedures are detailed step-by-step, explaining how the data will be prepared, cleaned, and analyzed using statistical software. Emphasis is placed on strategies for dealing with missing data and ensuring the integrity of the dataset. Furthermore, the chapter discusses assumptions made during the study, highlighting how these assumptions could influence interpretations of the data.
Ethical assurances and compliance with established ethical standards for conducting research provide the framework within which the study operates, ensuring the protection of participants’ rights and well-being throughout the research process.
In summary, This chapter offers a comprehensive view of the research methodology, laying a solid foundation for the study’s execution. It ensures that the research is conducted systematically, ethically, and with rigorous adherence to established scientific principles. As we transition to the next chapter, we will delve into the results obtained from applying these methodologies, analyzing the data collected to provide insights into the study’s hypotheses and research questions.
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Appendix
A. C:UsersabinaOneDriveDesktopVASTLHCS 2020 AES Results – Printer Friendly.pdf
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