THE ROLES OF PSYCHOLOGICAL CAPITAL AS A PERSONAL RESOURCE IN THE JOB DEMANDS-
RESOURCES MODEL IN THAI NURSES
Korkiat Mahaveerachartkul
A Dissertation Submitted in Partial
Fulfillment of the Requirements for the Degree of Doctor of Philosophy
(Human Resource and Organization Development) School of Human Resource Development National Institute of Development Administration
2018
ABSTRACT
Title of Dissertation The Roles of Psychological Capital as a Personal Resource in the Job Demands-Resources Model in Thai Nurses
Author Mr. Korkiat Mahaveerachartkul
Degree Doctor of Philosophy (Human Resource and Organization Development)
Year 2018
The research question of the present study was what were the roles of psychological capital in the job demands-resources model with challenge-hindrance demands framework in the context of Thai nurses? In order to answer the question, this study had to accomplish two objectives - to develop and psychometrically test the new challenge-hindrance demands scale and a job resources scale among Thai registered nurses in private hospitals and to examine the possible roles of PsyCap in the job demands-resources (JD-R) model.
This work employed the exploratory sequential mixed-methods design (qualitative research followed quantitative research) to achieve the first objective. A qualitative study based on in-depth individual interviews with 11 nurses was conducted to explore what work conditions were of critical importance to job demands-resources of Thai registered nurses. The finding revealed that the nursing job demands-resources comprised certain work conditions (e.g., problematic patients), which might not be observed in other occupations. Afterward, the items and scales were developed based on the summary of the interviews. The distinctive point of the nursing challenge- hindrance demands scale was the scale format which has not yet been utilized in other existing job demands questionnaires.
The quantitative study was conducted to refine and assure the validity of the new scales. In this regards, 761 completed questionnaires from 16 private hospitals
were randomized into three different groups to use in each step of analyses – 150 for EFA, 211 for CFA, Cronbach’s alpha coefficient reliability and convergent and discriminant validity analyses, and 400 for concurrent validity analysis. Taken together, the quantitative results provided sufficient evidence for good validity and reliability of the challenge-hindrance-resource scales.
This work employed the quantitative research design to attain the second objective. The total 761 questionnaires were used to examine the roles of PsyCap in the JD-R model. The findings revealed that PsyCap was a partial mediator (CMIN/df = 4.43, CFI = .94, TLI =.93, RMSEA = .07, and SRMR = .07) and a partial antecedent (CMIN/df = 4.82, CFI = .93, TLI =.92, RMSEA = .07, and SRMR = .08) in the JD-R model. Also, PsyCap was a partial moderator in the model because it buffered the effect of job resources on work engagement. According to the model analyses, PsyCap was more important than challenge demands, hindrance demands, and job resources in influencing burnout and work engagement of Thai nurses in the private sector.
In conclusion, this study highlights the importance of PsyCap, a type of personal resources, over work environments, in dealing with burnout and increasing work engagement of Thai nurses. In addition, this research provides researchers and human resource practitioners with the valid and reliable challenge-hindrance-resource scales that could be used in future research relevant to Thai nurses.
ACKNOWLEDGEMENTS
I wish to wholeheartedly thank, first and foremost, my advisor, Associate Professor Dr. Nanta Sooraksa, for her advice, encouragement, and invaluable advice throughout the dissertation process. Thank you very much for offering me help anytime I need and usually keeping track of my dissertation progress. Next, I would like to express my deepest appreciation to Associate Professor Dr. Bung-on Sorod, the committee chairperson, for her practical advice on statistics. Her positive energy brighten my feeling whenever we have a conversation. Also, I would like to express my sincere gratitude to Dr. Niyada Chitcharat, my external committee, for her tireless efforts to help me truly understand my dissertation. Time flies whenever I work with her. This dissertation would not have been completed without strong support from the three professors.
Grateful acknowledgment is extended also to five experts who assessed the newly developed scales of this study, all nurses spending their precious time to provide both valuable personal qualitative and quantitative data, and all authorities and coordinators from 16 private hospitals participating in this study.
I would like to express my gratitude towards Dr.Sakesan Tongkhambanchong and Dr.Arnond Sakworawich for the useful advice on data analysis.
I would like to thank all faculty members of the Graduate School of Human Resource Development (SHRD), NIDA, who have groomed me throughout six great years to be entitled to use the title “Dr”. Also, I would like to give thanks to SHRD supporting staff members who always provide me with kind support and smiles and help solve all document problems.
I wish to express my sincere gratitude to Orn, P Ar, and all of my classmates from Batch3 for your emotional and intellectual support and encouragement throughout the enjoyable and difficult periods that we have encountered together throughout our study.
Finally, without the love, compassion, encouragement, and support of my mom and dad, Kolma, my aunts, and my siblings, this dissertation would not have been accomplished. Thank you for always being there for me through my ups and downs.
I thank you all very much from the bottom of my heart. Your good wishes will be with me forever.
Korkiat Mahaveerachartkul August 2018
TABLE OF CONTENTS
Page
ABSTRACT iii
ACKNOWLEDGEMENTS v
TABLE OF CONTENTS vii
LIST OF TABLES ix
LIST OF FIGURES xi
ABBREVIATIONS xii
CHAPTER 1 INTRODUCTION 1
1.1 Rationale and Problem Statement 1
1.2 Research Questions 7
1.3 Objectives of the Study 7
1.4 Significance of the Study 8
1.5 Definitions of Key Terms 9
CHAPTER 2 REVIEW OF THE LITERATURE 12
2.1 The Job Demands-Resources (JD-R) Model 12
2.2 Psychological Capital (PsyCap) 25
2.3 Conservation of Resources as a Bridge between the JD-R Model
and PsyCap 34
2.4 PsyCap as a Mediator in the JD-R Model 37
2.5 PsyCap as a Moderator in the JD-R Model 41 2.6 PsyCap as an Antecedent in the JD-R Model 44
2.7 Conceptual Frameworks 47
2.8 Hypotheses 48
CHAPTER 3 RESEARCH METHODOLOGY 50
3.1 Qualitative Method 50
3.2 Quantitative Method 53
CHAPTER 4 RESULTS 65 4.1 Qualitative Results on Scale Development 65 4.2 Quantitative Results on Scale Validation 82 4.3 Quantitative Results on the Roles of PsyCap in the JD-R Model101
CHAPTER 5 CONCLUSION AND DISCUSSION 111
5.1 Summary 111
5.2 Discussion 114
5.3 Implications for Practice 125
5.4 Limitation & Future Studies 128
BIBLIOGRAPHY 130
APPENDICES 151
Appendix A Finalized Version of the Nursing Challenge-Hindrance Demands
Questionnaire 152
Appendix B Finalized Version of the Nursing Job Resources Questionnaire 159 Appendix C t-Test Analysis of Challenge-Hindrance Appraisals 161
BIOGRAPHY 163
LIST OF TABLES
Tables Page
3.1 Demographic Characteristics of the Key Informants and Details of the Interviews 51
3.2 Population and Expected Numbers of Participants 55
3.3 Demographic Information of Samples 60
4.1 t-Test for Item Discrimination and Corrected Item-Total Correlation of 14-
Variable Challenge Demands Scale 83
4.2 Factor Loadings of the 14-Variable Challenge Demands Scale 84 4.3 Factor Loadings of the 12-Variable Challenge Demands Scale 85 4.4 t-Test for Item Discrimination and Corrected Item-Total Correlation of 14-
Variable Hindrance Demands Scale 86
4.5 Factor Loadings of the 14-Variable Hindrance Demands Scale 87 4.6 Factor Loadings of the 13-Variable Hindrance Demands Scale 88 4.7 t-Test for Item Discrimination and Corrected Item-Total Correlation of 15-
Variable Job Resources Scale 88
4.8 Factor Loadings of the 15-Variable Job Resources Scale 89 4.9 Cronbach’s Alpha Analysis of the Four-Factor Challenge Demands Scale 92 4.10 Cronbach’s Alpha Analysis of the Four-Factor Hindrance Demands Scale 94 4.11 Cronbach’s Alpha Analysis of the Three-Factor Job Resources Scale 96 4.12 Pearson Correlation Coefficients between the Subscales of Challenge Demands,
Hindrance Demands, Work Engagement, and Burnout 98
4.13 Pearson Correlation Coefficients between the Subscales of Job Resources, Work
Engagement, and Burnout 100
4.14 Pearson Correlation Coefficients between the Subscales of Job Resources, Challenge Demands, Hindrance Demands, Work Engagement, Burnout, and
Psycap 104
4.15 Direct and Indirect Effects of the JD-R model with PsyCap as a Mediator 106 4.16 Direct and Indirect Effects of the JD-R model with PsyCap as an Antecedent 109
5.1 Summary of Hypotheses Testing 112 5.2 Summary of the Validation Analysis of the Challenge-Hindrance Demands Scale
116 5.3 Summary of the Validation Analysis of the Job Resources Scale 119
LIST OF FIGURES
Figures Page
1.1 The Revised JD-R Model with the Challenge-Hindrance Demands Framework 2 1.2 PsyCap as a Mediating Variable in the JD-R Model 4 1.3 PsyCap as a Moderating Variable in the JD-R Model 4
1.4 PsyCap as an Antecedent in the JD-R Model 4
2.1 The Original JD-R model 14
2.2 The Revised JD-R Model 17
2.3 The Hypothesized Model (PsyCap as a Mediator in the JD-R Model) 47 2.4 The Hypothesized Model (PsyCap as a Moderator in the JD-R Model) 47 2.5 The Hypothesized Model (PsyCap as an Antecedent in the JD-R Model) 48 4.1 Confirmatory Factor Analysis of Four-Factor and 12-Variable Challenge
Demands Scale (n = 211) 92
4.2 Confirmatory Factor Analysis of Four-Factor and 13-Variable Hindrance
Demands Scale (n = 211) 94
4.3 Confirmatory Factor Analysis of Three-Factor and 15-Variable Job Resources
Scale (n = 211) 95
4.4 Concurrent Validity Analysis of the Challenge-Hindrance Demands scale (n =
400) 99
4.5 Concurrent Validity Analysis of the Job Resource Scale (n = 400) 100
4.6 SEM Analysis of the JD-R Model (n = 761) 106
4.7 SEM Analysis of the JD-R Model with PsyCap as a Mediator (n = 761) 107 4.8 Interaction Effect of Job Resources and PsyCap on Engagement (n = 761)
108 4.9 SEM Analysis of the JD-R Model with PsyCap as an Antecedent (n = 761)
110
ABBREVIATIONS
Abbreviations Equivalence
AGFI Adjusted Goodness-of-Fit Index
AIC Akaike Information Criterion
AVE Average Variance Extracted
BIC Bayesian Information Criterion
BO Burnout
BOD Burnout (Disengagement)
BOE Burnout (Exhaustion)
BPNT Basic Psychological Needs Theory
CA Challenge Appraisal
CD Challenge Demands
CDI Challenge Demands (Within-
Organization Interaction)
CDJ Challenge Demands (Job Difficulty)
CDP Challenge Demands (Patients and
Relatives)
CDT Challenge Demands (Time Requirement)
CET Cognitive Evaluation Theory
CFA Confirmative Factor Analysis
CFI Comparative Fit Index
CITC Corrected Item-Total Correlation
CMIN/df Minimum Discrepancy
COR Conservation of Resources
CR Composite Reliability
EFA Exploratory Factor Analysis
GFI Goodness-of-Fit Index
HA Hindrance Appraisal
HD Hindrance Demands
HDI Hindrance Demands (Within-
Organization Interaction)
HDJ Hindrance Demands (Job Difficulty)
HDP Hindrance Demands (Patients and
Relatives)
HDT Hindrance Demands (Time
Requirement)
HR Human Resource
HRD Human Resource Development
ICU Intensive Care Unit
IOC Item-Objective Congruence
JD Job Demands
JD-R the Job Demands-Resources Model
JR Job Resources
JRO Job Resources (Organizational Support)
JRP Job Resources (Peer Support)
JRS Job Resources (Supervisor Support)
KMO Kaiser–Meyer–Olkin
M Mean
NFI Normed Fit Index
OCB Organizational Citizenship Behavior
ODBI the Oldenburg Burnout Inventory
OPD Out-Patient Department
PCE PsyCap (Efficacy)
PCH PsyCap (Hope)
PCI Psychological Capital Intervention
PCO PsyCap (Optimism)
PCQ the Psychological Capital Questionnaire
PCR PsyCap (Resiliency)
PNFI Parsimony Normed Fit Index
POB Positive Organizational Behavior
POS Positive Organizational Scholarship
PsyCap Psychological Capital
RED the Resources-Experience-Demands
Model
RMR Root-Mean-Square Residual
RMSEA Root-Mean-Square Error of
Approximation
SRMR Standardized Root Mean Square
Residual
ROI Return on Investment
SD Standard Deviation
SDT Self-Determination Theory
SEM Structural Equation Modelling
TLI Tucker-Lewis Index
US United States
UWES the Utrecht Work Engagement Scale
VIP Very Important Person
WE Work Engagement
WEA Work Engagement (Absorption)
WED Work Engagement (Dedication)
WEV Work Engagement (Vigor)
CHAPTER 1
INTRODUCTION
1.1 Rationale and Problem Statement
Based on the principle of organizational behavior and positive psychology, psychological capital (PsyCap) is a positive psychological state of development composed of self-efficacy, hope, optimism, and resilience, as a resource linkage concept and a source of competitive advantage (Hobfoll, 2002; Luthans, Youssef, &
Avolio, 2007). Because of its strong theoretical foundation and authentic impact in various types of organizations, PsyCap gained popularity in academic research which is evident in the rapid publication growth (Dawkins, Martin, Scott, & Sanderson, 2013).
In general, employees who have higher PsyCap report higher levels of positive work attitudes (e.g., job satisfaction (Abbas, Raja, Darr, & Bouckenooghe, 2014), psychological well-being (Avey, Luthans, Smith, & Palmer, 2010), and work engagement (Avey, Wernsing, & Luthans, 2008)), positive work behaviors (e.g., work- life balance (Siu, 2013) and organizational citizenship behaviors (Avey, Luthans, &
Youssef, 2010; Avey, Wernsing, et al., 2008)), and positive characters and virtues (e.g., humor (Hughes, 2008) and creativity (Rego, Sousa, Marques, & Cunha, 2012)), as well as performance (Avey, Nimnicht, & Pigeon, 2010). They, also, report lower levels of undesirable affects, attitudes, and behaviors at work, such as burnout (Avey, Hughes, Norman, & Luthans, 2008; Avey, Wernsing, et al., 2008), intention to quit (Avey, Hughes, et al., 2008; Avey, Luthans, & Jensen, 2009; Avey, Luthans, & Youssef, 2010), absenteeism (Avey, Patera, & West, 2006), and deviance behaviors (Avey, Luthans, &
Youssef, 2010; Avey, Wernsing, et al., 2008).
The other significant concept based on positive psychology and stress theory in organizational context is the job demands-resources (JD-R) model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) which has been attracting widespread interest from researchers since its inception and becomes one of the prominent job stress model (Schaufeli & Taris, 2014). The first JD-R model was developed by Demerouti et al.
(2001) to understand how different types of work conditions (i.e., job demands and job resources) affects burnout (i.e., exhaustion and disengagement). The model has been revised many times and the latest JD-R model that are currently studied is composed of five main variables which are challenge demands, hindrance demands, job resources, burnout and work engagement (Crawford, Lepine, & Rich, 2010; see Figure 1.1).
Figure 1.1 The Revised JD-R Model with the Challenge-Hindrance Demands Framework
During the extension of the JD-R model, an attempt to integrate personal resources (e.g., organization-based self-esteem, extraversion, and intrinsic motivation) in the model has been made (Schaufeli & Taris, 2014). On this point, Van den Broeck, Van Ruysseveldt, Vanbelle, and De Witte (2013) suggested that future research should concentrate on the personal resources that can simply be developed from work circumstances. In responding to this suggestion, PsyCap seems to be one of the most appropriate personal resources that should be studied with the JD-R model because it is confirmed that PsyCap could be developed by a short training program (Luthans,
Avey, Avolio, & Peterson, 2010) or a counselling program (Chaleoykitti, 2014) and might be developed through on-the-job activities (Luthans, 2002a).
According to Schaufeli and Taris (2014), personal resources could become a mediating variable, a moderating variable, and an antecedent of the JD-R model. To properly explain why PsyCap could be a part of the JD-R model, certain relevant theories are provided.
The mediation role of PsyCap in the JD-R model could be supported by conservation of resources (COR; Hobfoll, 1989) theory which explains resource gain and loss from coping with stressful environment, resource caravan (Hobfoll, 2002, 2011, 2014) which describes the tendency that different types of resources are being developed together, and socialization resources theory (Saks & Gruman, 2011) which explains the utilization of socialization processes of organizations as a tool to enhance employees’ PsyCap (see Figure 1.2). In addition, COR theory, which indicates the importance of personal characteristics as general stress resistance resources, is employed to support how PsyCap can be a moderating variable in the JD-R model (see Figure 1.3). Furthermore, the resources-experience-demands model (RED; Salanova et al., 2011) which explains that personal resources influence individuals’ consideration of both positive and negative situations, and the resource caravan, are employed to justify the antecedent role of PsyCap in the JD-R model (see Figure 1.4).
To the best author’s knowledge, previous studies have only focused on the mediating role of PsyCap in the partial and full JD-R model before revision and the buffering role of PsyCap on the relationship between job demands and burnout. They failed to discover the mediating role of PsyCap in the full revised JD-R model with challenge-hindrance demands framework, nor an antecedent role of PsyCap in the model. In addition, PsyCap as a moderator between job resources and work engagement are rarely found in the literature. To fill the research gap, the main aim of this study is to examine the roles of PsyCap as a mediator, a moderator, and an antecedent in the revised JD-R model with challenge-hindrance demands framework.
Figure 1.2 PsyCap as a Mediating Variable in the JD-R Model
Figure 1.3 PsyCap as a Moderating Variable in the JD-R Model
Figure 1.4 PsyCap as an Antecedent in the JD-R Model
In order to examine the role of PsyCap in the model, the selection of an appropriate group of participants is vital. Registered nurses in private hospitals in Bangkok were selected to be the subjects of this study because of the two reasons.
First, Hinkin (2005, p. 169) argued that “it is important that the sample selected will demonstrate the behaviors or possess the attitude under examination”. In this regards, there has been some evidence that nurses demonstrated the psychological states (e.g., PsyCap, burnout, and work engagement) under study. For instance, Avey, Reichard, Luthans, and Mhatre (2011) conducted meta-analysis and suggested that the effect sizes of the relation between PsyCap and outcomes were slightly greater in employees of the service sector which may be because PsyCap seemed to be more important in jobs that required social interactions and the demonstration of positive emotions which normally lay in service work. In addition, some studies found that stress and work engagement were demonstrated by Thai registered nurses in private hospitals (Thirapatsakun, Kuntonbutr, & Mechinda, 2014; Tyson & Pongruengphant, 2004).
Second, Thailand has positioned itself to be a medical hub of Asia since 2003.
Although Thailand has been recognized as a popular tourist destination for decades, Thailand becomes well-known as medical tourism not so long ago (Bochaton, 2015).
This idea started from the attempts of private hospitals in Thailand to survive in the aftermath of the economic crisis in 1997. The visit to private hospitals of Thai people decreased so the hospitals had to change their strategies by conducting new marketing campaigns which targeted affluent societies and expatriates living in neighboring countries (e.g., Laos PDR, Myanmar, and Cambodia; Bochaton, 2015). After the success of the campaigns, the hospitals expanded the target on a global scale and brought about the phenomenon labeled medical tourism. Afterward, Thai government implemented the plan to develop Thailand into a medical hub of the region (e.g., providing attractive loans, promoting Thai healthcare excellence abroad, and holding the medical and wellness trade fair in Thailand), which involved the cooperation of several state agencies (e.g., Tourist Authority of Thailand and the Export Promotion Board; Bochaton, 2015).
Now, Thailand is renowned for providing a high quality of the medical and health services (e.g., doctors, nurses, translators, and reception staff) at a reasonable
price. Until now, in Thailand, there are 53 clinics and hospitals accredited by the Joint Commission International (Joint Commission International, 2016). Only one of them (Siriraj Piyamaharajkarun Hospital) is operated under the Faculty of Medicine, Siriraj hospital which is a public hospital. Almost all of them are private hospitals and more than half, 23 hospitals, are situated in Bangkok. According to Bloomberg and CNBC, Thailand was ranked number one in top travel destinations for medical tourism in 2013 (Robertson, 2013) and was in the top destinations for health tourism in 2014 (Barnato, 2014). In addition, Kasikorn Research (2016) predicted that medical tourism market will take a greater role in generating revenue for private hospitals in the future which is evident in the income of international patients which increase from 25% to more than 30% of private hospitals’ total revenue from 2011 to 2015.
All of this information emphasizes the importance of private hospitals to propel medical tourism in Thailand. However, Thailand has been experiencing the shortage of nurses for decades (Abhicharttibutra, Kunaviktikul, Turale, Wichaikhum, & Srisuphan, 2017). Consequently, Thai nurses in the private sector were selected to be the subjects of this study and the results of this study might suggest how hospitals could improve their work environments that contribute to the better well-being (i.e., less burnout and more engagement) of Thai nurses which might help nurses to pursue further this career.
Because each occupation might have specific work environments of its own that affect their well-being (Demerouti et al., 2001) and challenge-hindrance-resource scales among nurses does not yet exist in Thailand. Consequently, in order to ensure the quality of the present and future studies on the JD-R model in the Thai healthcare industry, there remains a need for the valid and reliable scales based on the Thai nurse environment.
The core problem of the existing challenge and hindrance demands scale, such as the challenge-and-hindrance-related self-reported stress measure (Cavanaugh, Boswell, Roehling, & Boudreau, 2000) or the challenge and hindrance stressors measure (Rodell & Judge, 2009) was that the work conditions of those scales were clearly categorized into challenge demands and hindrance demands, despite the fact that “many daily stressors are neither clearly positive nor negative and so are most likely to be open to personal appraisal” (Hobfoll, 1989, p. 519). Consistent with the
Hobfoll (1989)’s suggestion, Schaufeli & Taris (2014; p.56) proposed that “future research should focus on “challenges” (positively valued demands) and on “threats”
(negatively valued resources). For instance, the amount of effort (i.e., the amount of energy spend) and the appraisal (i.e., its positive or negative valence) of demands can be assessed”. Consequently, this study develops the new challenge-hindrance demands scale whose format was adapted from the suggestion of Schaufeli and Taris (2014).
In addition, unlike other studies that use certain general positive work conditions as factors of job resources, this study develops and psychometrically tests a new comprehensive job resources scale that includes the crucial factors truly representing the domain of interest tailored for Thai registered nurses in the private sector. These scales could be further used to study the JD-R model, one of the significant research topics in the field of human resources, among nurses, in the future studies.
1.2 Research Questions
In the present study, the research question is what are the roles of psychological capital in the job demands-resources model with challenge-hindrance demands framework in the context of Thai nurses?
1.3 Objectives of the Study
To answer the research question, the main objectives of this study are (a) to develop and psychometrically test the challenge-hindrance demands questionnaire and a job resources questionnaire of Thai nurses; and (b) to examine the roles of PsyCap as a mediator, a moderator, and an antecedent in the JD-R model.
1.4 Significance of the Study
This study not only fills the gaps of both the JD-R model and PsyCap but also provides the practical implications described as follows.
First, the JD-R model is one of the prominent job stress models that has been extensively used to study the phenomenon in which human resource development (HRD) researchers are interested, such as fairness, absenteeism, turnover intention, organizational commitment, or performance (see Schaufeli & Taris, 2014). This study developed and psychometrically tested (a) a new challenge-hindrance demands scale based on the suggestion of Schaufeli and Taris (2014) which addressed the issue of the existing challenge-hindrance demands scale by combining the experience of nurses with each job demand with the nurses’ appraisals of each job demand; and (b) a new comprehensive job resources scale for Thai registered nurses.
The results of this part, especially the scale validation, which relates job demands and job resources to burnout and work engagement, would ensure that the facets of those work environments (i.e., both job demands and resources) are crucial factors that private hospitals could use as a guideline for creating a better flourishing work environment. For instance, hospitals might try to provide nurses with job demands tending to be more challenging (e.g., job complexity), accompanied by appropriate job resources (e.g., training) to increase work engagement and achievement of nurses.
Hospitals could also try to decrease job demands tending to be more threatening (e.g.
conflict within organizations) to decrease burnout of nurses.
Second, this study examines the three possible roles of PsyCap in the JD-R model–the mediator, the moderator, and the antecedent. In this regards, the mediating and antecedent roles of PsyCap in the full revised JD-R model, as well as the moderating role of PsyCap in the relationship between job resources and work engagement are rarely found in previous studies.
With regard to the practical implications, if PsyCap was found to be all three roles in the JD-R model, PsyCap would be an important factor that could be influenced by work conditions, as well as could influence nurses to effectively make use of work
environments in their hospitals, in order to bolster their well-being (i.e., reducing burnout and increasing work engagement). Specifically, PsyCap as an antecedent would suggest that PsyCap could influence nurses to effectively utilize their work environments to achieve their work goals and increase their well-being. PsyCap as a mediator would suggest that there were many types of work conditions (i.e., demands and resources) that hospitals could use to promote PsyCap, which in turn promote the well-being of nurses. PsyCap as a moderator would suggest that PsyCap, as internal capacities of nurses, could intensify or mitigate the effects of external work environments on nurses’ outcome. Because of this possibly practical significance of PsyCap in influencing nurses’ burnout and engagement, providing nurses with a psychological capital development workshop or proper work conditions (e.g., adequate job resources) might be the preventive and not-very-high-cost strategies that Thai private hospitals might consider to raise nurse’ engagement and mitigate nurses’
burnout.
1.5 Definitions of Key Terms
This study focuses on six variables which are defined as follows.
1.5.1 Job Demands
Job demands refer to physical, social or organizational work conditions that demand physical and mental energy of individuals which inevitably cause a strain on them (Demerouti et al., 2001). Job demands can be classified into two dimensions: (a) challenge demands refer to work conditions that can cause stress but can help individuals to gain some benefits, and (b) hindrance demands refers to work conditions that not only can cause stress, but also can impede the individuals’ achievements of doing their jobs (Cavanaugh et al., 2000).
1.5.2 Job Resources
Job resources refer to physical, psychological, social, or organizational work conditions that can help individuals to achieve career goals or to grow and develop, as well as to mitigate the negative effects of job demands on individuals (Demerouti et al., 2001).
1.5.3 Personal Resources
Personal resources refer to psychological qualities that help individuals not only to deal with the environment effectively but also to recover from bad situations (Schaufeli & Taris, 2014).
1.5.4 Burnout
Burnout refers to a multi-dimensional construct composed of exhaustion and disengagement (Demerouti et al., 2001). Specifically, exhaustion refers to a result of putting a physical, emotional, and mental effort to deal with demands in a period of time. In addition, disengagement refers to physically or mentally distancing oneself from work and having negative attitudes towards aspects of the job (Demerouti et al., 2001).
1.5.5 Engagement
Work engagement refers to a positive and fulfilling state that individual experience at work which is composed of vigor, dedication, and absorption (Schaufeli
& Bakker, 2004). Specifically, the three dimensions of work engagement were termed by Schaufeli and Bakker (2003, 2004) as follows: (a) vigor, at the opposite end of exhaustion, means a feeling of having high levels of energy, and mental flexibility and toughness at work, not being simply worn out, being ready to direct effort to work, and persevering in handling work problems; (b) dedication, at the opposite end of cynicism, means a feeling of appreciating the significance of one’s job, being eager to work and proud about one’s duty, and being motivated and enthused by one’s work; and (c)
absorption means a feeling of being fully and happily focused on one’s work, having a feeling that time flies at work, and being inconvenient to separate oneself from work.
1.5.6 Psychological Capital
Psychological capital (PsyCap) refers to a developable positive psychological state that is composed of four main dimensions which are self-efficacy (i.e., having confidence to deal with challenging tasks successfully), optimism (i.e., having a positive explanation of success for oneself), hope (i.e., continuing trying and finding more ways to achieve goals), and resiliency (i.e., bouncing back or beyond after experiencing unsatisfactory situations in order to achieve goals) (Luthans, Avey, Avolio, Norman, & Combs, 2006).
CHAPTER 2
REVIEW OF THE LITERATURE
This chapter provides the review of literature relevant to the JD-R model, PsyCap, the COR theory, and the integration of PsyCap into the JD-R model, in order to indicate the hypotheses and conceptual frameworks of the present study.
2.1 The Job Demands-Resources (JD-R) Model
Since its inception, the popularity of the JD-R model among researchers has been increasing due to its flexibility in the application of a diversity of working contexts (Schaufeli & Taris, 2014). Dissimilar to the previous leading job stress models, such as job demands-control (JD-C) model (Karasek, 1979) and effort-reward imbalance (ERI) model (Siegrist, 1996), the JD-R model does not limit itself to a certain set of job demands and job resources; consequently, the model can include any variables tailored to various work settings. Due to its nature of heuristics, “there is actually no single JD- R model” (Schaufeli & Taris, 2014, p. 44).
2.1.1 The Original Job Demands-Resources Model
The first JD-R model was developed by Demerouti et al. (2001) to explain the influence of working conditions on burnout (see Figure 2.1). In their study, working conditions can be classified into two groups, job demands and job resources.
Job demands refer to “those physical, social, organizational aspects of the job that require sustained physical or mental effort and are therefore associated with certain physiological and psychological costs” (Demerouti et al., 2001, p. 501). Work conditions that fall into this group are, for instance, workload, time pressure, role
conflict, role ambiguity, or misbehaviors or harassment of and by people related to work (Schaufeli & Taris, 2014).
On the other hands, job resources refer to “those physical, psychological, social, or organizational aspects of the job that may do any of the following (a) be functional in achieving work goals; (b) reduce job demands at the associated physiological and psychological costs; (c) stimulate personal growth and development” (Demerouti et al., 2001, p. 501). Initially, job resources focused on external resources, such as social resources (e.g., colleagues, family, and supervisor support) and organizational resources (e.g., autonomy, opportunities for professional development, fairness, and task variety), rather than internal resources (Demerouti et al., 2001; Schaufeli & Taris, 2014).
The dependent variable of the first JD-R model is burnout. Burnout is a metaphor generally used to illustrate a state of mental tiredness (Schaufeli & Bakker, 2004) and refers to a multi-dimensional construct composed of exhaustion and disengagement, according to the Oldenburg Burnout Inventory (OLBI; Demerouti et al., 2001). Specifically, exhaustion refers to “a consequence of intensive physical, affective, and cognitive strain, for example as a long-term consequence of prolonged exposure to certain demands” (Demerouti et al., 2001, p. 500). In addition, disengagement refers to “distancing oneself from one's work, and experiencing negative attitudes toward the work object, work content, or one's work in general”
(Demerouti et al., 2001, p. 501).
The JD-R model suggests that different types of working conditions influence burnout in different ways and there are two distinct processes in the model (Demerouti et al., 2001). The first process termed the job demands-exhaustion path is justified by the control model of demand management of Hockey (1993). The theory argues that when an individual is influenced by stressors (e.g., workload or time pressure), they will try to maintain their performance by mobilizing their effort. This performance protection would create physiological costs and its long-term effect would lead to relentless overtaxing and, finally, cause an individual’s breakdown or exhaustion.
The second process termed the job resources-disengagement path is justified by health promotion and maintenance theories (Antonovsky, 1987). The theory emphasizes that it is more difficult for individuals who have neither important resources
(e.g., supervisor support), nor sense of coherence (i.e., a capacity to define the situation in the way that is comprehensible, manageable, and meaningful to them) to cope with job demands (e.g., workload) and achieve their goals. Moreover, to protect their selves from the predictable failure, individuals might decrease their job motivation or withdraw themselves from the job, and the long-term withdrawal leads to disengagement.
In summary, the first JD-R model is composed of three main variables which are job demands, job resources, and burnout and is based on two processes which are (a) an energetic process in which job demands leads to individual overtaxing and then drain the energy backup of an individual; and (b) a motivational process in which lacking of resources reduces individual capability to cope with high job demands and then causes an individual’s mental withdrawal and disengagement (Schaufeli &
Bakker, 2004).
Figure 2.1 The Original JD-R model
2.1.2 The Revised Job Demands-Resources Model
Schaufeli and Bakker (2004) made some revisions to the JD-R model by incorporating one more positive variable, work engagement, in the model (see Figure 2.2) under the proposition of positive psychology to shift the focus towards strengths and optimal functioning, instead of weaknesses and pathology that controlled over the psychology research for decades (Seligman & Csikszentmihalyi, 2000).
Work engagement is described as “a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption” (Schaufeli & Bakker, 2004, p. 295). Also, it refers to “a persistent and pervasive affective-cognitive state that is not focused on any particular object, event, individual, or behavior” (Schaufeli &
Bakker, 2004, p. 295).
Specifically, the three dimensions of work engagement were termed by Schaufeli and Bakker (2003, 2004) as follows: (a) vigor, at the opposite end of exhaustion, can be described by high levels of energy and mental flexibility and toughness at work, not being simply worn out, readiness to direct effort to work, and perseverance in handling work problems; (b) dedication, at the opposite end of cynicism, is described as appreciating the significance of one’s job, and being eager to work and proud about one’s duty, and being motivated and enthused by one’s work;
and (c) absorption is described as being fully and happily focused on one’s work, having a feeling that time flies at work, and being inconvenient to separate oneself from work.
Similar to the traditional model, the revised JD-R model is composed of two main processes which are the energetic process (i.e., the process that clarifies how job demands influence burnout, which in turn, affects work outcomes, such as increased health problems), and the motivational process (i.e., the process that describes how job resources influence engagement, which in turn affects work outcomes, such as decreased turnover intention) (Bakker & Demerouti, 2007).
Schaufeli and Bakker (2004) used the compensatory control in the regulation of human performance of Hockey (1997) to describe the energetic process. Hockey (1997) indicates three levels of control in response to an increasing strain. At the lower level of strain where the perceived level of trouble is slightly higher than the effort at the normal level, to maintain their performance, individuals would increase their effort within the reserve limit. This mode is referred to as an active coping mode in which effort is increased but distress has not yet created.
On the other hand, Hockey (1997) further explains that, in case of high strain where the perceived level of trouble cannot be managed by a small adjustment of increasing effort, individuals have two alternatives: (a) individuals can increase their effort until it meets the excessive demands and then try to maintain such levels of effort to accomplish the goal, and the consequence of maintaining such performance level is
distress; accordingly, this approach is referred to as a strain coping mode in which the level of effort and distress is increasing simultaneously; and (b) during the high-demand period, instead of increasing their effort, individuals can choose to maintain the energy consumption at its present level with the sacrifice of their goals and this mode is referred as a passive coping mode in which the level of effort is maintained at its usual level but the level of distress is still high, and the extreme form of such control is the complete disengagement from the goals.
The long period of the strain coping employment can explain how job demands lead to exhaustion; in addition, the extreme form of passive control can explain how job demands lead to cynicism. In addition, the strain coping mode and passive coping mode, created by job demands, are associated with the increased sympathetic activity whose overload might lead to health problems (Schaufeli & Bakker, 2004).
The motivational process, the second process of the revised JD-R model, explains how job resources influence engagement which, in turn, leads to work outcomes (e.g., decreased turnover intention). To explain this process, Schaufeli and Bakker (2004) refer to self-determination theory (Deci & Ryan, 1985) and effort- recovery model (Meijman & Mulder, 1998).
First, self-determination theory (SDT) is “an empirically based theory of human motivation, development, and wellness” (Deci & Ryan, 2008, p. 182) which elaborates basic issues, for instance, motivation, self-regulation, and basic psychological needs.
SDT has been developed through the combination of five mini-theories but only two of them, cognitive evaluation theory (CET; i.e., the topic of intrinsic motivation) and basic psychological needs theory (BPNT; i.e., the topic of psychological needs comprising autonomy, competence, and relatedness), and their direct connection to psychological health and well-being (Ryan, 2009), are employed to explain a part of the motivational process of the revised JD-R model. These mini-theories suggest that positive work conditions (e.g., job resources, such as rewards, feedback, and social supports) can increase the individuals’ level of the three basic psychological needs and intrinsic motivation, then promote individuals’ well-being, as well as learning and development, and finally promote positive organizational outcomes (e.g., job competence) (Ryan, 2009; Schaufeli & Bakker, 2004).
Second, effort-recovery model could explain the relationship between workload and capacity provided that when challenged by certain demands, individuals will attempt to intervene actively in their work conditions by adopting a certain work procedure which in turn leads to two results, the product, which is the tangible outcomes of activities related to work, and the temporarily emotional, mental and physical responses (Meijman & Mulder, 1998). Nevertheless, work conditions that provide individuals with several resources can promote individuals’ preparedness to dedicate their efforts and abilities to the task (Meijman & Mulder, 1998; Schaufeli & Bakker, 2004). To put it another way, job resources can foster the willingness to put effort into managing job demands and promote goal attainment (Schaufeli & Taris, 2014) and this explanation can support the motivational process of the revised JD-R model.
To conclude, both paths, the satisfaction of basic needs and the willingness to devote effort, can lead to engagement which, in turn, lead to a high tendency of positive work outcomes (e.g., job performance ) and a low tendency of negative work outcomes (e.g., turnover intention) (Schaufeli & Bakker, 2004).
Figure 2.2 The Revised JD-R Model
The revised JD-R model, in which different sets of job demands and job resources impact different groups of health impairments and work outcomes, has been studied and confirmed in various groups of population in some countries and the results appear just as if it is predicted by the model. Schaufeli and Bakker (2004) found that among employees from organizations in the service sector in The Netherlands (i.e., an insurance firm, a health and safety corporation, a pension fund enterprise, and a home-
care agency), job demands (i.e., workload and emotional demands) predicted burnout, which in turn led to health problems, and job resources (i.e., colleague support and supervisory coaching) predicted engagement, which in turn resulted in lower turnover intention. In line with the previous studies, Schaufeli, Bakker, and Rhenen (2009) conducted 1-year longitudinal study and revealed that among telecom managers in The Netherlands, the increase in job demands (i.e., work overload, emotional demands, and work-home interference), from Time1 to Time2, predicted burnout, and the decrease and the increase in job resources predicted burnout and work engagement respectively.
Not only the full model but its parts have been studied. With regard to longitudinal studies, among Finnish healthcare personnel, Mauno, Kinnunen, and Ruokolainen (2007) found that both job demands and job resources at Time1 predicted work engagement at Time2; in addition, job resources could predict engagement stronger than job demands. Hakanen, Perhoniemi, and Toppinen-Tanner (2008) conducted cross-lagged panel analysis among dentists in Finland and found that job resources at Time1 had a positive effect on work engagement at Time2.
Regarding Thai research studies on the revised JD-R model, Thirapatsakun et al. (2014) found that among registered nurses of private hospitals in Thailand, job demands (e.g., psychological and physiological demands, and job insecurity) and job resources (i.e., perceived organizational support) had negative and positive effects on work engagement respectively. In addition, both independent variables had an indirect effect on turnover intention via work engagement. The results are compatible with those of Boonpun (2011) which indicated that job demands (i.e., perceived workload) and job resources (i.e., autonomy, coworker support, supervisor coaching, and performance feedback) had both direct and indirect effect on turnover intention via work engagement among the officers of The Secretariat of the Senate. The similar results are found in the study of Yodrakang (2011) which revealed that job resources (e.g., career advancement opportunity, coworker support, and supervisor support) had a direct effect on work engagement among section chiefs of the Provincial Electricity Authority. In addition, Kleebbua (2009) found that among Thai employees, job demands (i.e., workload) predicted burnout.
2.1.3 The Revised JD-R Model with the Challenge-Hindrance Demand Framework
Due to its popularity, the JD-R model has been studied, investigated, extended, and refined progressively. A number of refinements are, for instance, to reveal the roles of personal resources, such as extraversion, optimism, hope, or self-esteem, as an antecedent, a moderator, or a mediator in the revised JD-R model, and to include a variety of work outcomes beyond performance, such as innovativeness (Huhtala &
Parzefall, 2007) and safety behavior (Nahrgang, Morgeson, & Hofmann, 2011), into the revised JD-R model (see Schaufeli & Taris, 2014, for discussion).
Apart from those contributions, one of the outstanding model refinements is from the study of Crawford et al. (2010) whose attempt was to address the results’
inconsistency between job demands and work engagements that were found in a number of previous studies. Some found only positive relationships (e.g., Schaufeli, Taris, & van Rhenen, 2008); some found both positive and negative relationships depending on each work condition (e.g., Bakker, van Emmerik, & Euwema, 2006;
Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2007). The other found no significant relationship (e.g., Schaufeli & Bakker, 2004). In this regards, Crawford et al. (2010) separated job demands in the JD-R model into hindrance demands and challenge demands based on the study of Cavanaugh et al. (2000).
Cavanaugh et al. (2000)’s study attempted to discover why the relationship between work stress associated with certain stressors and work outcomes (e.g., job satisfaction, job search, and intention to quit) had not been found in several previous studies. The authors discussed that one practical explanation might be the existence of the relationship depending on types of stressors. Specifically, items of work stress from different types of stressors in a single scale might possibly cancel out the actual effects of work stress on work outcomes. Accordingly, it would be more beneficial to classify work stress into two dimensions: (a) challenge stressors refers to “work-related demands or circumstances that, although potentially stressful, have associated potential gains for individuals”; and (b) hindrance stressors refers to “work-related demands or circumstances that tend to constrain or interfere with an individual’s work achievement and that do not tend to be associated with potential gains for the individual” (Cavanaugh et al., 2000, p. 68). The authors further revealed that stress related to challenge stressors
(e.g., job overload, time pressures, and high level of responsibilities) is positively related to job satisfaction and negatively associated with job search because individuals considered pressure and stress relevant to these demands as rewarding work experience that led to growth and development so it is worth facing uneasiness to experience goal achievement afterward. The significant opposite results were found in stress related to hindrance demands (e.g., politics, role ambiguity, red tape, or lack of job security).
Following the work of Cavanaugh et al. (2000), Crawford et al. (2010) classified job demands into challenge and hindrance and tested them with the revised JD-R model in the meta-analysis study. The results revealed the significant relationship between job resources and burnout, and job resources and engagement as predicted by the previous JD-R model. Importantly, challenge demands were positively associated with engagement while hindrance demands were negatively related to engagement. In addition, both challenge and hindrance demands were positively associated with burnout. The authors further discussed that the underlying reasons might be challenge demands activated positive feelings and thoughts, which in turn led to problem-focused coping styles and then triggered engagement; on the other hand, hindrance demands activated negative feelings and thoughts, which in turn led to emotion-focused coping styles and then lowered engagement (Cavanaugh et al., 2000).
In the last few years, there has been a growing interest in testing the revised JD-R model with challenge-hindrance stressor framework; nevertheless, very few publications that discuss this issues can be found because the model with both types of demands has been established quite recently. Interestingly, many results of those studies are inconsistent with the findings reported in the meta-analysis study of Crawford et al. (2010) which might be because of the difference in the number of participants. The number of participants in the meta-analysis study is from 64 samples of 55 articles and in such a large sample size, even small differences can be detected.
In recent years, the whole model with the different sets of challenge demands, hindrance demands, and job resources has been studied in several publications. Van den Broeck, De Cuyper, De Witte, and Vansteenkiste (2010) tested the model comprising challenge demands (i.e., workload and cognitive demands), hindrance demands (i.e., emotional demands), job resources (i.e., autonomy and social support), vigor (i.e., the main component of engagement), and exhaustion (i.e., the main
component of burnout) in two samples (i.e., Dutch call center agents and Belgian police officers) and revealed results as follows: challenge demands were positively and not significantly related to vigor and exhaustion respectively; hindrance demands were negatively and positively associated with vigor and exhaustion respectively; and job resources were positive and negatively associated with vigor and exhaustion respectively.
In addition, Lin, Siu, Shi, and Bai (2009) tested the model in the sample of nurses in Beijing and discovered that challenge demands (e.g., quantitative workload) were positively related to vigor and emotional exhaustion. Hindrance demands (i.e., office politics) were negatively and positively associated with vigor and emotional exhaustion respectively. However, job resources (i.e., autonomy) were not significantly related with both constructs. This might be because, among Beijing nurses, other job resources (e.g., supervisor or colleague supports or rules and standards) might affect work engagement and burnout stronger than did autonomy.
Moreover, Searle and Lee (2015) discovered that, in the convenient samples, challenge demands (i.e., workload, time urgency, job responsibility and job complexity) were positively related to engagement but not burnout; conversely, hindrance demands (i.e., red tape, role ambiguity, role conflict and hassles) had no significant relationship with both variables. While job resources (i.e., perceived coworker support, supportive and non-controlling supervision and role autonomy) were positively and negatively related to engagement and burnout respectively.
Ventura, Salanova, and Llorens (2015) tested the model in two samples (i.e., teachers of secondary schools and users of information and communication technology) and discovered that hindrance demands (i.e., role conflict, lack of autonomy, and lack of social support) were positively and negatively related to burnout and engagement respectively. While challenge demands (i.e., mental overload) were positively related to only engagement but not burnout.
Regarding the Thai context, Seeda (2012) found that among employees in both private and public sectors, challenge demands and job resources had positive effects on work engagement while hindrance demands and job resources had positive and negative effects on burnout respectively. In addition, Sapyaprapa (2012) examined the model in employees of private organizations in Bangkok Metropolitan Region and found that
challenge demands and job resources were positively related to work engagement and the opposite result was found in the relationship between hindrance demands and work engagement.
According to the previous studies having been noted, it is obvious that those results cannot reach a consensus; however, some basic patterns emerge from the results which are as follows: challenge demands are positively related to work engagement;
hindrance demands are negatively and positively related to work engagement and burnout respectively; and job resources are positively and negatively related to work engagement and burnout.
2.1.4 Challenge-Hindrance Demands Measures
Most challenge-hindrance demands studies in general or in the JD-R model (see Crane & Searle, 2016; Lepine, Podsakoff, & Lepine, 2005; Podsakoff, LePine, &
LePine, 2007; Rodell & Judge, 2009; Searle & Auton, 2015) usually follow the concepts of job demands of Demerouti et al. (2001) and challenge-hindrance demands of Cavanaugh et al. (2000) which explain the certain properties of work conditions that could be categorized as job demands in general or as a specific kind of job demands (i.e., challenges and hindrances). The newly developed challenge-hindrance demands scale of this study, also, were founded on these concepts
In addition, in order to gain basic knowledge of the potential work environmental factors which could adequately represent the nursing job demands, as well as the nursing challenge-hindrance demands, previous relevant demands instruments, as well as factors that influenced stress of international and Thai nurses, were studied.
First, regarding the relevant existing scales, Sundin et al. (2008) developed and validated a job demands scale among a nursing profession which resulted in a four dimension scale; coping with patients’ pain and death, handling patient and relative needs, experiencing and managing threats and violence from patients, and feeling worries inherent in work. However, its dimensions and items were not categorized into challenge and hindrance demands. In contrast, Cavanaugh et al. (2000) and Rodell and Judge (2009) developed and psychometrically tested instruments that clearly separated
stressors into challenge stressors (i.e., workload, job responsibility, time pressure, and job complexity), and hindrance stressors (i.e., hassles, politics, role ambiguity, role conflict, red tape, job insecurity, no career advancement). Nevertheless, the work aspects in the scales have not explicitly based on nursing experiences.
Second, concerning the studies on stresses of nurses in the international perspective (e.g., USA, South Africa, UK, Germany, Israel, Taiwan, China, Australia, and Thailand) both in specific countries (Boamah, Read, & Spence Laschinger, 2017;
Van der Colff & Rothmann, 2014; Wu, Fox, Stokes, & Adam, 2012; Yau et al., 2012) and across countries (Admia & Eilon-Mosheb, 2016; Chang, Hancock, Johnson, Daly,
& Jackson, 2005; Lambert & Lambert, 2001; McVicar, 2016), the common work environmental factors that caused nursing stress were, for instance, patient and family complaints, the threat of litigation, conflicts with co-workers, lack of support and resources, poor quality of nursing staff members, understaffing, responsibility (e.g., workload, variety, complexity), role ambiguity, time pressures, long working hours, shift rotation, work-life imbalance, restrictions of the hospitals, dealing with death and dying, lack of job security, career stalled, lack of fair remuneration, and lack of skills and knowledge of using new equipment.
The list of nursing stress factors in the international perspective does not much different from that of Thai nurses (Nantsupawat et al., 2011; Raungsrijan &
Suppapitiporn, 2011; Tyson & Pongruengphant, 2004). In this regard, it was the recent study of Pumfang and Srisatidnarakul (2015) that comprehensively summarized factors that affected job stress of Thai nurses which were demands of patients and relatives (e.g., fast and accurate service), work-life balance (e.g., unstable work schedule), leader behaviors (e.g., less autonomy at work), unsafe work environment (e.g., risk of infection), over workload, insufficient benefits and compensation, poor relationship with co-workers (e.g., other nurses, doctors, or pharmacists) and co-workers disapproval, and lack of career progression and job security.
In conclusion, the probable work aspects that cause stress of nurses are very diverse and it remains unclear that which work conditions rightfully belong to either challenge or hindrance category. Consequently, there remains a need for a further empirical investigation of the actual job demands facets crucial to Thai nurses.
2.1.5 Job Resources Measures
Most studies relevant to the JD-R model usually follow the concept of job resources of Demerouti et al. (2001). To discover the potential work conditions that could represent nurse job resources, remaining job resources scales, as well as work environmental factors that previous nursing studies used as job resources were reviewed.
First, to the best author’s knowledge, no single job resources scale exists.
However, job resources were found as part of the job demands-resources scale (Rothmann, Mostert, & Strydom, 2006), which could be utilized to measure the domains in different occupations. The scale comprises both job demands and job resources factors and the latter is composed of three dimensions which are growth opportunities (i.e., having sufficient opportunities to learn and to be self-reliant at work, such as job variety), advancement (i.e., the progress within one’s work, such as training and career opportunities), and organizational support (i.e., social support and the opportunities to relate to others in organizations).
Second, previous job resources studies among nurses usually selected some work aspects to represent the domain of interest. Among these studies, the most frequently used factors are social support (e.g., supervisor and coworker support;
Blanco-Donoso, Garrosa, Moreno-Jimenez, de Almeida, & Villela-Bueno, 2017;
Shahpouri, Namdari, & Abedi, 2016; Sundin, Hochwälder, & Lisspers, 2011; Zito, Cortese, & Colombo, 2016). The second group of factors frequently employed is opportunities to learn and grow (e.g., training and career advancement; Q. Hu, Schaufeli, & Taris, 2017; Moloney, Boxall, Parsons, & Cheung, 2018; Vander Elst et al., 2016). Apart from those commonly used variables, other possible nurse job resources are senior management support (Moloney et al., 2018), organizational justice (Shahpouri et al., 2016), relationship with physicians and patients (Jourdain &
Chênevert, 2010), teamwork (Montgomery, Spânu, Băban, & Panagopoulou, 2015), access to information via computer appliances (D'Emiljo & du Preez, 2017), and job security (Bhatti, Hussain, & Al Doghan, 2018).
In conclusion, the potential work conditions that could become factors of the nursing job resources might be categorized into two groups which are person-related
factors (e.g., supervisor, peer support, and relationship with doctors and patients) and organization-related factors (e.g., professional training, opportunities of career advancement, and job security). Because the previously mentioned studies among nurses have been based on an international context, not all results could be applied to Thai nurses and there remains a need for a further investigation of the actual facets of Thai nurses’ job resources.
2.2 Psychological Capital (PsyCap)
Rooted in the field of positive psychology and positive organizational behavior, PsyCap, or “who you are”, focuses on a group of individual strengths that are sources of competitive advantage which lies beyond other familiar capitals which are economic capital (i.e. “what you have”), human capital (i.e., “what you know”), social capital (i.e., “who you know”) (Luthans, Luthans, & Luthans, 2004, p. 46; Luthans & Youssef, 2004). Similar to the JD-R model, PsyCap has existed not long ago and is required more rigorous studies to uncover its value in the organization (Min, Kim, & Lee, 2015).
2.2.1 The Origin of PsyCap
According to Luthans et al. (2004) and Luthans and Youssef (2004), the PsyCap concept was firstly drawn from the disciplines of positive psychology and positive organizational behavior by the University of Nebraska’s Gallup Leadership Institute which concentrates on human functioning in the individual level and deals with the construct that is developable and related to performance (Luthans & Youssef, 2007).
Since becoming the president of the American Psychological Association, Martin Seligman has been propelling the wheel of positive psychology by encouraging researchers to invest their resources more on the studies relevant to the positive human functioning or factors that support flourishment in the individual, organizational, and societal levels. Positive psychology was seriously suggested to address the problem of the psychology field since World War II which had focused more excessively on
pathologies, psychological disorders, or the negative outcome of environmental stressors (Seligman & Csikszentmihalyi, 2000).
Luthans, Youssef, and Avolio (2007) suggest that although the problem-focused approach attempting to mitigate what is wrong in human and organization is important, such method does not initiate better understanding of human strengths, happiness, flourishing, and optimal functioning. The authors go on to make the idea clearer by comparing it with the famous theory in the field of human resources and organizational behavior, the motivation-hygiene theory (Herzberg, 1965). The theory suggests that job satisfaction and job dissatisfaction are two separate constructs which have their own set of antecedents. For instance, professional growth and achievement recognition are the contributions towards job satisfaction called “motivators” while working conditions and status are the forerunners of job dissatisfaction called “hygiene factors” (Herzberg, 1965, p. 369). The author further suggests that to meet the demands of hygiene factors can only prevent individuals from job dissatisfaction but has little to do with job satisfaction. Similarly, studies about psychological disorders can alleviate negative symptoms but might not help individuals, organizations, or societies to flourish.
Consequently, positive psychology calls for more studies of positive sides of human, organization, and community that focuses on strengths and resilience to shift the focus of the field from cures for suffering to development of flourishing (Seligman &
Csikszentmihalyi, 2000).
A few years after the formal origin of positive psychology, the studies that applied positivity and strength-based management in organizational contexts were developed and the two well-known positive organizational theories are positive organizational scholarship (POS), and positive organizational behavior (POB) (Luthans
& Youssef, 2004). The latter concept is the foundation of PsyCap (Luthans & Youssef, 2007).
2.2.2 Theoretical Foundation of PsyCap
2.2.2.1 Positive Organizational Behavior (POB)
Positive organizational behavior (POB) is “the study and application of positively oriented human resource strengths and psychological capacities that can be
measured, developed, and effectively managed for performance improvement in today’s workplace” (Luthans, 2002b, p. 59). In other words, the strengths or capacities that will be included in POB must be positive, connected to the area of organizational behavior, research-based, assessable, developable, and involving with performance (Luthans, Youssef, et al., 2007). Some of the criteria are clarified in the following paragraphs.
1) Valid measurement criterion
Because prediction and control is achievable when valid scales exist, the constructs included in POB must be reliably and validly measurable and these standard measurements will shift organizational behavior from “philosophical metaconstructs” to the state of science that can be operationalized and assessed (Luthans, Youssef, et al., 2007, p. 13).
2) The state-like criterion
There are several psychological traits in the field of organizational behavior, such as big five personality traits, core self-evaluations, talents and strengths, the locus of control, cognitive abilities, and emotional stability that have relationships with job performance (Luthans, 2002a). However, Luthans, Youssef, et al. (2007) caution that these traits have a tendency to demonstrate stability over time within the realm of the workplace and can be developed over one’s lifetime by optimal situational factors or extensive psychotherapy but are difficult to change in a training program. Consequently, they are more important for human resource management (e.g., recruitment, selection, and placement, or “selecting the right people and placing them in the right roles”) (Luthans, Youssef, et al., 2007, p. 14). On the other hand, state-like capacities are allowed to develop and improve based on training programs, micro- interventions, or on-the-job activities (Luthans, 2002a). Therefore, opportunities are open to human resource (HR) practitioners to use human resource development (HRD) processes, especially, training and development, to increase employees’ level of those state-like capacities.
3) The performance impact criterion
To gain acceptance from both public and private organizations, the constructs included in POB are required to create a significant impact on work-
related outcomes, especially performance. To put it in another way, utilizing POB ensures the organizations’ sustainable g
