The Relationship Between Emotional Intelligence and
Psychological Well-being among Employees in the Caregiving
Profession
HONOURS RESEARCH PROPOSAL
Faculty of Economic and Management Sciences
(Department of Industrial Psychology)
at the
University of the Free State
Supervisor: Dr. Harunavamwe
April 2017
NO PART OF THIS DOCUMENT MAY BE REPLICATED WITHOUT PRIOR
PERMISSION FROM UFS DEPARTMENT OF INDUSTRAIL PSYCHOLOGY.
TABLE OF CONTENTS
CHAPTER 1: GENERAL INTRODUCTION
1.1 Introduction and Problem Statement
1
1.2 Research Questions
3
1.3 Research Objectives
3
1.4 Research Hypotheses
3
1.5 Outline of the Study
4
1.6 Summary
5
CHAPTER 2: PSYCHOLOGICAL WELL-BEING
6
2.1 Introduction
6
2.2 Nature and Definition of Psychological Well-being
6
2.3 Approaches to Psychological Well-being
7
2.3.1 The Hedonic Approach
7
2.3.2 The Eudemonic Approach
7
2.4 Components of Psychological Well-being
8
2.4.1 Cognitive Components
8
2.4.1.1 Life Satisfaction
8
2.4.1.2 Domain Satisfaction
8
2.4.2 Affective Components
9
2.4.2.1 Positive Affect
9
2.4.2.2 Negative Affect
9
2.5 The Dynamic Equilibrium Theory
9
2.6 Ryff’s Multidimensional Model of Psychological Well-being
11
2.6.1 Self-Acceptance
12
2.6.2 Positive Relations with Others
2.6.3 Autonomy
12
12
2.6.4 Environmental Mastery
12
2.6.5 Purpose of Life
13
2.6.6 Personal Growth
13
2.7 Summary
13
CHAPTER 3: EMOTIONAL INTELLIGENCE
14
3.1 Introduction
14
3.2 Nature and Definition of Emotional Intelligence
14
3.3 The Components of Emotional Intelligence
15
3.4 Models of Emotional Intelligence
16
3.4.1 Bar-On’s Model of Emotional Intelligence
16
3.4.2 The Ability Model of Emotional Intelligence
17
3.5 Summary
18
CHAPTER 4: RESEARCH METHODOLOGY
19
4.1 Introduction
19
4.2 Selection of test persons
19
4.3 Data Gathering
19
4.3.1 Ryff’s Psychological Well-being Scale
19
4.3.1.1 Nature and Composition
20
4.3.1.2 Reliability
20
4.3.1.3 Validity
20
4.3.1.4 Rationale for inclusion
21
4.3.2 Mayer, Salovey and Caruso Emotional Intelligence Test
21
4.3.2.1 Nature and Composition
21
4.3.1.2 Reliability
21
4.3.1.3 Validity
21
4.3.1.4 Rationale for inclusion
22
4.4 Statistical Methods
22
4.4.1
Descriptive statistics
22
4.4.2
Inferential statistics
23
4.4.2.1
Pearson product-moment correlation
23
4.4.2.1.1
Reasons for inclusion...
23
4.4.2.1.2
Discussion of the Pearson product-moment correlation
23
4.4.2.2
T-test for independent groups /
One-way analysis of variance (ANOVA)
24
4.4.2.2.1
Reasons for inclusion of the T-test for independent groups
25
4.4.2.2.2
Discussion of the T-test for independent groups
25
4.5 Summary
26
Bibliography
27
LIST OF FIGURES
Figure 2.1: Heady and Wearing’s (1991) stocks and flows framework
10
Figure 2.2: Ryff’s Model of Psychological Well-being
11
Figure 4.1: Pearson’s Product Moment Correlation (Definitional Formula)
24
Figure 4.2: Pearson’s Product Moment Correlation (Calculation Formula)
24
CHAPTER 1
GENERAL INTRODUCTION
1.1 Introduction and Problem Statement
Caregiving is a stressful and emotionally draining profession and puts individuals employed in
such lines of work under considerable amounts of stress. Although stress may help an
individual become more focused, chronic and excessive stress has detrimental effects, such as
feeling pressured and being overwhelmed (Moss, Good, Gozal, Kleinpell & Sessler, 2016).
Psychological stress develops when individual’s external demands exceed their adaptive
abilities (Moss et al., 2016). Caregiving, especially nursing, is considered to be a stressful
profession because it requires coping with high emotional, cognitive and physical demands
(Donoso, Demerouti, Hernández, Moreno-Jiménez & Cobo, 2015). This continued exposure to
these demands can be associated with physical and psychological problems (Donoso et al.,
2015), which negatively impact a person’s psychological and overall well-being.
Internationally, the burden of caregiving is felt heaviest by individuals in the nursing
profession. Por, Barriball, Fitzpatrick and Roberts (2011) hold that in the UK, an estimate of
up to 25% of nursing students drop out of their preparation programme because of the high
demands of the occupation. Maslach and Leiter (2014), provided supporting research
showcasing that work-stress may predict psychological disability in initially healthy
employees. Additionally, Carod-Artal and Vázquez-Cabrera (2013) indicated that the demands
of caregiving have been associated with decreases in well-being, quality of care among nursing
staff and high absenteeism.
The effects of globalisation on developing countries worsen the situation, as internationally
recognised quality of care becomes the bar of measurement. This puts considerable amounts of
stress on caregivers as they attempt to meet these requirements with the little they have (CarodArtal & Vázquez-Cabrera, 2013). Research conducted in Nigeria on physiotherapists, Ibikinle,
Umeadi and Akosle (as cited in Okwaraji & Aguwa, 2014), reported that 66.2% of subjects
exhibited emotional exhaustion, 65.2% showed high levels of depersonalisation and 75.6%
displayed high levels of reduced personal accomplishment. In Malawi, maternal staff reported
high rates of burnout with close to three quarters of subjects (72%) reporting emotional
exhaustion, 43% reporting depersonalisation and 74% experienced reduced personal
accomplishment (Carod-Artal & Vázquez-Cabrera, 2013). Research seems to find a prevalence
of negative attitudes and low psychological and physical well-being among caregivers with
1
many expressing strong feelings to leave the caregiving profession (nursing) (Okwaraji &
Aguwa, 2014).
Within the South African context, a cross-sectional study conducted in a public hospital
reported that physicians had higher levels of occupational stress compared to the average
working population (Carod-Artal & Vázquez-Cabrera, 2013). Further reports indicate that only
25% of registered nurses working in critical care units are qualified as critical care nurses
(Nagel, Towell, Nel and Foxall, 2016). This staff shortage leads to the employment of newly
graduated and inexperienced registered nurses who have not yet developed appropriate
knowledge and competence, or the emotional preparation needed for such a highly charged
area of practice. This lack of emotional preparedness can lead to stress, depression and
regression in psychological well-being.
Nagel et al., (2016) revealed that when faced with demands that threaten their well-being,
caregivers in the health services leave their working environments, or the profession altogether.
The solution to this problem is twofold. Firstly, it is essential that nurses continue to be
recruited to critical care units, but it is also imperative that experienced critical care nurses be
retained, as their experience is invaluable in such challenging environments (Nagel et al.,
2016). Secondly, Nagel et al. (2016) draw from De Beer, Brysiewizz and Bhengu’s (2011)
research and posit that in order to manage the demands of such taxing environments, caregivers
need a broad but specialist knowledge base and sound decision-making skills to function
appropriately. These skills, which can be summed up as emotional intelligence, can reduce the
effects of stress, burnout and psychological distress, improving feelings of ownership towards
work.
Growing interest and research into how people can manage the complex demands of their work
place has led to the identification and management of emotions. Today, researchers such as Por
et al. (2011) believe that the ability to process emotionally relevant information can have an
effect on an individual’s life outcomes such as achieving success at work and their general
well-being. This ability, termed emotional intelligence (EI), has been found to foster adaptive
methods of coping with social challenges, social stress and interpersonal conflicts; promoting
the development of supportive social networks; decreasing negative and increasing positive
emotions; and enhancing emotional regulation (Di Fabio & Kenny, 2016). EI involves a set of
emotional abilities to effectively use information from emotions, allowing people to have
adaptive coping with stressful life events (Sánchez-Álvarez, Extremera & Fernández-Berrocal,
2
2016), therefore, EI is conceived of as an indicator of psychological adjustment and a key
precursor to feelings associated with well-being.
1.2 Research Questions
From the preceding problem statement, the following research questions can be identified:
•
Primary Question:
Does a relationship exist between emotional intelligence and well-being among
employees in the caregiving profession?
•
Secondary Question:
Do differences exist in well-being among employees in the caregiving professions with
regards to gender?
1.3 Research Objectives
The following research objectives can be identified from the aforementioned research
questions:
•
Primary Objective
To determine by means of a non-experimental research design whether a relationship
exists between emotional intelligence and well-being among employees working in the
caregiving profession.
•
Secondary Objective
To determine by means of a non-experimental research design whether differences exist
between males and females working in the caregiving profession.
1.4 Research Hypothesis
Resulting from the previous research objectives, the following hypotheses will be investigated
in this study:
•
Hypothesis 1
Null Hypothesis (Ho)
3
There is no statistically significant relationship between scores achieved on emotional
intelligence and well-being among employees working in the caregiving profession.
Alternative Hypothesis (H1)
There is no statistically significant relationship between scores achieved on emotional
intelligence and well-being among employees working in the caregiving profession.
•
Hypothesis 2
Null Hypothesis (Ho)
There is no statistically significant differences with regards to gender between scores
achieved on well-being among employees working in the caregiving profession.
Alternative Hypothesis (H1)
There is a statistically significant difference with regards to gender between the scores
achieved on well-being among employees working in the caregiving profession.
1.5 Outline of the Study
Chapter 1
This chapter encapsulates the general introduction as well as the problem statement that will
be the focus of the study. The research questions, -objectives and hypotheses are outlined as
well.
Chapter 2
The first variable, emotional intelligence, is focused on, with the provision of several
definitions as well as the conceptualisation of emotional intelligence for the purposes of this
study. Emotional intelligence is then linked to the caregiving profession, and further discusses.
4
Chapter 3
The second variable, well-being, is discussed and conceptually defined. Following, is how
well-being is linked to the caregiving profession as well as the relationship between emotional
intelligence and well-being.
Chapter 4
Chapter 4 concerns itself with the research methodology. The methods that were used to
conduct the research such as the selection of research participants, data gathering and the
statistical methods employed are discussed in detail.
1.6 Summary
A general introduction along with an outline of the problem statement was provided. Explicit
focus was placed on the health of individuals employed in the caregiving profession, and how
their work exposes them to high physical and mental demands. Furthermore, focus was also
placed on the difficulty of finding a balance and maintaining that balance of well-being due to
the taxing profession of caregiving. The effects of emotional intelligence were briefly outlined
as a means of regulating the stresses of caregiving and achieving a greater sense of well-being
and health. The specific research questions, -objectives, and –hypotheses were specified. In
conclusion, the basic outline the study would follow was also included. Following in sequence
will be a focus on relevant literature, which will provide an overview of the variables:
emotional intelligence and well-being.
5
CHAPTER 2
PSYCHOLOGICAL WELL-BEING
2.1 Introduction
Seifert (2015) holds that well-being is a dynamic concept that includes subjective, social and
psychological dimensions, as well as health related behaviours. However, the question of how
well-being should be defined, let alone spelt (wellbeing or well-being) still remains largely
unresolved (Dodge, Daly, Huyton & Sanders, 2012), and has given rise to blurred and overly
broad definitions of well-being. One thing is sure though, amidst all the debates and attempts
to define the concept, there exists general consensus that it involves a state of being
comfortable, healthy or happy as well as the partial absence of illness (Rathnakana, 2014).
The elusiveness of defining well-being comes about because of the complex and multi-faceted
nature of the construct (Pollard & Lee, 2003), and as Thomas (2009) argued, the intangibility
faced when attempting to measure it (as cited in Dodge et al., 2012). Bradburn (1969) made
one of the earliest attempts in defining well-being by shifting his focus towards the
psychological reactions of ordinary people in their daily lives (Dodge et al., 2012). Bradburn’s
interest was on how individuals coped with their daily difficulties, and highlighted how
psychological well-being, which he referred to as happiness, was the variable that stands out
as being of primary importance (Dodge et al., 2012). From this backdrop, today, psychological
well-being is a tradition centred on personal growth, on the way to manage life challenges, and
on the effort to achieve goals (Montes-Berges & Augusto-Landa, 2014).
2.2 Nature and Definition of Psychological Well-being
According to Dolan, Layard and Metcalfe (as cited in Dodge et al., 2012), the nature of
psychological well-being is multi-faceted, however, it is generally agreed that three aspects can
be distinguished;
•
Evaluative well-being, involving global assessments of how people evaluate their lives,
or their satisfaction with life.
•
Affective or hedonic well-being, involving measures of feelings such as happiness,
sadness and enjoyment.
•
Eudemonic well-being, which focuses on judgements about the meaning or purpose of
one’s life and appraisals of constructs such as fulfilment, autonomy and control.
6
From the aforementioned aspects, it becomes clear that the hedonic and eudemonic well-being
constructs seep into each other, and that complete separation of the two is an impossibility.
Due to this, defining psychological well-being, becomes ever more difficult, as researcher’s
attempts end up focused more on the dimensions or descriptions of psychological well-being
rather than on the definition (Dodge et al., 2012). Nonetheless, this has not deterred researchers
from trying with Brown (1992) defining psychological well-being as “well-being that could be
related to the quality of life, however defined, or to life satisfaction, however defined” (as cited
in Fatemi & Asghari, 2016: 189).
Brown’s (1992) definition is too broad, and provides no basis of conceptualisation and
measurement. Therefore, Chen, Jing, Hayes and Lee’s (2012) definition seems more practical
for the purposes of this study. Chen et al., (2012) hold that psychological well-being involves
perceived thriving in life in the face of existing challenges of life, such as pursuing meaningful
goals, growing and developing as a person, and establishing quality ties with others. This
definition works well as it can be aligned with Ryff’s (1989) dimensions and model of
psychological well-being which will be covered later in the study.
2.3 Approaches to Well-being
Two broad traditions have historically been employed to explore well-being, the hedonic and
eudemonic traditions.
2.3.1 The Hedonic Tradition
The hedonic tradition can be traced back to Aristippus, a Greek philosopher who believed that
the goal of life is to experience maximum pleasure (Boniwell, 2016). This view equates wellbeing with happiness and is often operationalised as the balance between positive and negative
affect (Irshad, 2015). People virtually always experience moods and emotions, which have a
hedonic component that is pleasant, signalling a positive reaction, and if unpleasant, signalling
a negative reaction (Dodge et al., 2012). Kehneman (2006) expanded on this by mentioning
that positive affects are not simply the opposite of negative affects, but rather, both should be
seen as carrying valuable information. The umbrella term used to denote hedonic measures is
subjective well-being (Samman, 2007).
2.3.2 The Eudemonic Tradition
The eudemonic perspective to a good life originated from Aristotle, the originator of
eudemonia (from daimon – meaning true nature) (Boniwell, 2016). Aristotle deemed happiness
7
to be a vulgar idea, stressing that not all desires are worth pursuing as, even though some of
them may yield pleasure, they would not necessarily produce happiness (Boniwell, 2016).
Aristotle, as Boniwell (2016) holds, believed true happiness is found by leading a virtuous life
and doing what is worth doing, and that realising human potential is the ultimate human goal.
This view was further developed throughout the centuries, with Maslow and Rogers being the
first 20th century eudaemonists. This perspective then, links itself well with humanistic
psychology and highlights positive psychological functioning and human development (Dodge
et al., 2012). The eudemonic tradition assesses how well people are living with their true selves,
emphasizing personal growth, mastery, life purpose and meaning (Di Fabio & Kenny, 2016).
Di Fabio and Kenny (2016) add that the eudemonic viewpoint holds that psychological wellbeing is derived from a sense of fulfilment, meaning and self-realisation.
2.4 Components of Psychological Well-being
Psychological well-being as posited by Diener (as cited in Irshad, 2005) has two distinct
components; cognitive and affective components. However, simplified emotional reactions
such as anger, pride or joy (affective components) usually also involve cognitive appraisals
and interpretations, thus Hansen’s (2012) assertion of unclear distinctions holds true.
2.4.1 Cognitive Components
Cognitive components have their basis on evaluative beliefs or attitudes about one’s life
(Irshad, 2015). Three aspects of cognitive well-being are reported being life satisfaction,
partnership satisfaction as well as domain satisfaction (Hansen, 2012). However, this study will
consider partnership satisfaction as part of the life satisfaction aspect.
2.4.1.1 Life Satisfaction
Life satisfaction, as Hansen (2012) explains, refers respectively to the overall assessment of
one’s quality of life and relationship(s). Better understood, Rojas (2014) explains that a
person’s evaluation of their own life involves a judgemental process. Hence life satisfaction is
an evaluation of a happy life, based on the individual’s judgement of their own life.
2.4.1.2 Domain Satisfaction
This component states that life can be approached as a general construct of many specific
domains (Rojas, 2006), and that satisfaction in the domains of life ultimately determine life
satisfaction. Consequently, a relationship between life satisfaction and domain satisfaction can
8
be assumed. In his earlier work, Rojas (2004) expanded that the domain satisfaction approach
attempts to understand a general appraisal of life as a whole, on the basis of a multidimensional
component of specific appraisals going from a small number to an almost infinite recount of
all imaginable human activities and spheres of being.
2.4.2 Affective Components
Irshad (2015) maintains that affective components reflect the amount of peasant and unpleasant
feelings that people experience in their lives. It is the frequency and intensity of positive and
negative emotions and mood (Luhmann, Hawkley, Eid & Cacoppo, 2013).
2.4.2.1 Positive Affect
Positive affect, as Tran (2015) explains, refers to a trait that describes individual differences in
positive emotional experience. These emotions or feelings reflect a level of pleasurable
engagement with the environment, and can be brief, longer lasting or more stable trait-like
feelings (Cohen & Pressman, 2006). It is easy to confuse positive affect with positive emotions,
thus Miller (2011) makes the distinction that although positive affect overlaps significantly
with positive emotions, they are not identical. Positive affect is more closely related to mood
states, whereas positive emotions involve positive feelings as well as characteristic patterns of
psychological arousal, thoughts and behaviours (Miller, 2011).
2.4.2.2 Negative Affect
Since positive and negative ae opposites on a continuum, one would be justified in thinking
that the lack of positive engagement leads to negative affect, however, this is not necessarily
true (Cohen & Pressman, 2006). Negative affect as defined by Stringer (2013) is feelings of
“emotional distress” more specifically, the common variance between anxiety, sadness, fear,
anger, guilt and shame, irritability and other unpleasant emotions. Carey (1988) explains
elegantly that negative affect is a broad and pervasive predisposition to experience negative
emotions that has further influences on cognition, self-concept and worldview.
2.5 The Dynamic Equilibrium Theory
Originally proposed by Headey and Wearing in 1989, the dynamic equilibrium theory, also
known as the set-point theory, suggests links between personality, life events, well-being and
ill-being (Dodge et al., 2012). The preposition made is that individuals have unique baseline
levels of well-being that are determined by their personality (Irshad, 2015). Furthermore,
9
Headey and Wearing (1992) as cited in Irshad (2015), argued that individuals with certain
personalities are likely to experience certain types of events, and these events influence ones’
average level of well-being. Unusual events, as Irshad (2015) explains, can move a person
above or below this baseline level, however, the individual will eventually return to the
baseline, resulting in the normalisation of life events. This assertion mirrors the work of
Brickman and Campbell (1971) who built the body of theory from which the equilibrium theory
draws heavily upon.
Headey and Wearing proposed a model for equilibrium theory which is aimed at understanding
how people cope with change, and how their levels of well-being are affected as a result (Dodge
et al., 2012). The assumption then, is that change in well-being occurs only when a person
deviates from their equilibrium pattern of events, due to external forces (Irshad, 2015).
Consequently, Headey and Wearing propose a definition of well-being in which well-being is
shown “as depending on prior equilibrium levels of well-being and of life events, and also on
recent events” (Dodge et al., 2011: 227). This reflects their framework for analysing subjective
well-being which considers the relationship between stocks and flows:
Figure 2.1: Heady and Wearing’s (1991) stocks and flows framework
Using the model, Headey and Wearing proposed that differences between individuals in terms
of subjective well-being are due to “stable stocks” (stable personal characteristics), and because
of these stable stocks, each person has a level of subjective well-being which represents their
own “normal” equilibrium level (Dodge et al., 2012). Stocks, as Dodge et al., (2012) explain,
are used to deal with specific life experiences (flows) so that satisfaction is enhanced and
10
distress diminished. Consequently, the model becomes more appropriate in regarding
subjective well-being as a fluctuating state rather than a stable trait.
Though detailed and easily comprehensible, the theory and model fall short in that they treat
subjective and psychological well-being as identical and interchangeable constructs.
2.6 Ryff’s Multidimensional Model of Psychological Well-being
Ryff (1989) analysed various approaches to happiness in different subfields of psychology
(Boniwell, 2016) and came to the conclusion that research on well-being up to that time, largely
translated only into happiness (Henriques, 2014). For Ryff, well-being was more lined with
optimal psychological functionality rather than happiness, and this lead to her development of
a multidimensional model of well-being. Her model of psychological well-being includes six
related yet distinct components, and rests on the assumption that individuals strive to function
fully and realise their unique talents (Chen et al., 2012).
Personal Growth
Purpose in Life
Positive
Relationships
Self-Acceptance
Psychological
Well-Being
Autonomy
Environmental
Mastery
Figure 2.2: Ryff’s Model of Psychological Well-being
11
2.6.1 Self – Acceptance
Self-acceptance refers to the degree to which one has a positive attitude towards oneself and
one’s past life, past behaviours and choices (Irshad, 2015). Self-acceptance is the most
recurrent criterion of well-being, and previous perspectives emphasise it as well. It is a
prerequisite for mental health, as well as characteristics of self-actualisation, optimal
functioning and maturity (Henriques, 2014). Seifert (2005) maintains that high scorers possess
a positive attitude toward the self; acknowledge and accept multiple aspects of self, including
good and bad qualities and feel positive about past life. While low scorers feel dissatisfied with
their self; are disappointed with what has occurred with past life and wish to be different than
what who they are.
2.6.2 Positive Relations with Others
Many theories stress the importance of warm, trusting interpersonal relations. The ability to
love is viewed as a central component of psychological well-being (Henriques, 2014). Irshad
(2015) holds that people with high quality, satisfying relationships with others are concerned
about the welfare of others, have a capacity for strong empathy and intimacy. On the other
hand, people scoring low on this dimension have few close, trusting relationships with others,
are isolated and frustrated in interpersonal relationships and unwilling to make compromises
to sustain important ties with others.
2.6.3 Autonomy
There is considerable emphasis on such qualities such as self-determination, independence and
regulation of behaviour from within (Seifert, 2005). Self-actualisers, according to Ryff (as cited
in Irshad, 2015) show resistance to enculturation, have an internal locus of control and evaluate
the self with personal standards, as opposed to the individual who relies on others judgements
to make decisions, conforming to social pressures and is concerned with others expectations
and evaluations.
2.6.4 Environmental Mastery
This is the degree to which one feels competent to meet the demands of their situation
(Henriques, 2014), and their ability to manage life, choosing environments suitable to their
psychic conditions (Ishrad, 2005). Individuals scoring high exhibit a control over a complex
array of external activities, and are able to choose or create contexts suitable to personal needs
12
and values. However, individuals who struggle to master their environments have difficulty
managing everyday affairs and remains unaware of surrounding opportunities.
2.6.5 Purpose of Life
This domain deals with having life gaols and a belief that one’s life is meaningful. Furthermore,
Henriques (2014) adds that a clear comprehension of life’s purpose, a sense of directedness
and intentionality form part of the criteria of maturity. Thus one who functions positively has
goals, intentions, and a sense of direction, unlike a low scorer who experiences a lack of sense
of direction, sees no purpose to their past, and holds no sense of purpose in life (Ryff, as cited
in Seifert, 2005).
2.6.6 Personal Growth
The final facet of Ryff’s model is the continuation of developing one’s potential to grow as a
person and being open to new experiences (Irshad, 2005). While low scorers experience a sense
of personal stagnation, boredom with life and feelings of inability to develop new attitudes and
behaviours, the self-actualiser sees the self as growing and expanding, is open to new
experiences and changes in ways which reflect more self-knowledge and effectiveness
(Henriques, 2014).
2.7 Summary
This section focused on providing a comprehensive definition of psychological well-being and
outlined some issues faced when trying to define psychological well-being. Two traditions of
well-being were outlined as well as how these traditions intersect and aren’t truly separate, but
rather intertwined with each other. Furthermore, the components of psychological well-being
were briefly discussed, along with the dynamic equilibrium theory. Lastly, Ryff’s
multidimensional theory and model of psychological well-being, was touched upon.
13
CHAPTER 3
EMOTIONAL INTELLIGENCE
3.1 Introduction
Emotional intelligence is a fairly new concept that came from the acknowledgement that social
and emotional competencies are an important part of both performance effectiveness, as well
as measures of personal and professional success (Codier & Odell, 2014). The concept of
emotional intelligence, dubbed by Salovey and Mayer (1990), was initially described as being
a group of interconnected abilities that aid the processing of information regarding emotions
by acting as a guide toward cognition and behaviour (Mayer, Salovey & Caruso, 2008 as cited
by Beauvais, Stewart & DeNisco, 2014).
The concept of emotional intelligence arose from Thorndike in his theory of ‘social
intelligence’ in which he defines social intelligence as – the ability to understand and manage
men and women, boys and girls – to act wisely in human relations (Thorndike (1920) as cited
in Shaheen and Shaheen (2016)). The concept of emotional intelligence was then carried out
by Howard Gardner in his theory of Multiple intelligences, wherein he identifies interpersonal
intelligence and intrapersonal intelligence as two of the nine primary forms of intelligence
(Codlier and Odell, 2014). The research of Drs. Reuven Bar-On, John Mayer, and Peter
Salovey provide much of the theoretical foundation for the concept (Codier and Odell, 2014).
Emotional intelligence went on to gain the public’s attention and was popularised in the mid –
90’s when Dr. Dan Goleman published his best seller list book ‘’Emotional Intelligence’’, in
which he referred to emotional intelligence as a mixed model that includes social behaviours,
traits, and competencies (Beauvais, et al, 2014).
3.2 Nature and Definition
Emotional intelligence can be seen as an eye-catching term, but it is also controversial and
highly debatable. There is no consensus regarding its single definition (Irshad, 2015). Irshad
(2015) is of the opinion that emotional intelligence helps individuals in achieving the quality
of life that will make them successful and content by means of guiding the actions of
individuals. According to Meyer et al. (2008) as cited in Karimi, Leggat, Donohue, Farrell and
Couper (2013); Emotional intelligence refers to the ability to identify, assess, manage and
control oneself and one’s reactions to the emotions of others. Wolff (2005) as cited in Ackley
(2016), states that the Goleman model defines emotional intelligence as the ability to recognise
14
one’s own feelings and the feelings of others, such that emotionally intelligent individuals are
able to motivate themselves, and appropriately deal with their own emotions as well as the
emotions of others. Salovey and Mayer, (1990) as cited in Irshad (2015), define emotional
intelligence as being a form of intelligence that involves the ability to monitor one’s own and
others’ feelings and emotions, to distinguish among them and to use this information to guide
one’s thinking and actions. Mayer and Salovey (1997) as cited in Shaheen and Shaheen (2016)
further refined this definition in terms of four factors which are perceiving, using,
understanding and managing emotions. As they define “the ability to perceive accurately,
appraise and express emotion, the ability to access and/or generate feelings when they facilitate
thought; the ability to understand emotion and emotional knowledge; and the ability to regulate
emotions to promote emotional and intellectual growth” (Mayer and Salovey (1997) as cited
in Shaheen and Shaheen (2016)).
For the purpose of this study mention will be given to the definition by Mayer, Salovey and
Caruso (2004) as cited in Sharma, Dhar & Tyagi (2015) which defines emotional intelligence
as, ‘’the capacity to reason about emotions, and of emotions to enhance thinking. It includes
the abilities to accurately perceive emotions, to access and generate emotions so as to assist
thought, to understand emotions and emotional knowledge, and to reflectively regulate
emotions so as to promote emotional and intellectual growth’’.
The theoretical basis of the current study is emotional intelligence and psychological wellbeing; the aforementioned definition will lend itself to the provision of a better understanding
of the inter-relationship shared by the two constructs moderated by emotional intelligence.
Thus allowing the study to explore emotional intelligence as a solution to psychological wellbeing.
3.3 The Components of Emotional Intelligence
People who are emotionally intelligent perceive themselves to be confident and are better able
to understand, control and manage their emotions (Wilson, 2014). As such, Heffernan et al
(2010) as cited in Wilson (2014), identifies four components or determinants of emotional
intelligence:
1. Wellbeing – the degree to which one accurately perceives emotions, their level of selfesteem being it high or low, and their positive or negative outlook on life.
2. Self-control – one’s ability to access and generate emotions to assist thought in order to
regulate and control one’s own emotions and how well one deals with stress.
15
3. Emotionality – possessing emotional knowledge, understanding emotions and being
able to show empathy, and communicate one’s feelings.
4. Sociability – referring to one’s ability to reflectively regulate emotions in order to
stimulate emotional and intellectual skills and to better social skills and assertiveness
in dealing with others.
3.4 Models of Emotional Intelligence
Several models of emotional intelligence are currently used widely in organisational,
psychological, and educational research; and are all used to conceptualize, define,
operationalize and measure emotional intelligence differently (Codier and Odell, 2014). For
instance, Mayer et al, (2008) as cited in Codier and Odell (2014) give mention to Drs. Bar-On
and, Mayer and Salovey, who had different models of emotional intelligence.
3.4.1. Bar-On’s Model of Emotional Intelligence
Dr. Reuven Bar-On based his model on his own rigorous research wherein he views the factors
he identified as skills that can be learned and improved (Ackley, 2016). According to Bar-On’s
model as defined by Ackley (p274, 2016), emotional intelligence comprises of the follow five
components:
1. Self-perception which consist of self-regard, self-actualization, and emotional selfawareness.
2. Self-expression is comprised of emotional expression, assertiveness, and
independence.
3. Interpersonal is comprised of interpersonal relationships, empathy, and social
responsibility.
4. Decision making is comprised of problem solving, reality testing, and impulse
control.
5. Stress management is comprised of flexibility, stress tolerance, and optimism.
In the application of this model Dr. Bar-On made use of a self-report personality test by
developing the concept of emotional intelligence as a personality construct which he measured
using the Emotional Quotient Inventory (EQ-I). The Emotional Quotient Inventory is a selfreport test consisting of 133 questions on a 5-point Likert scale, that evaluates emotional and
social functioning. The instrument is used to decipher emotional intelligence, personal
development, and emotional and social competencies by specifically measuring intrapersonal,
interpersonal, stress management, adaptability, and general mood skills (Statistic Solutions,
2016).
16
3.4.2. The Ability Model of Emotional Intelligence
Drs. John Mayer and Peter Salovey on the other hand established a model of emotional
intelligence that describes emotional intelligence as a set of abilities that can be measured using
a performance instrument (Mayer et al (2008) as cited in Cordier and Odell, 2014). Ackley
(2016) explains that Salovey and Mayer see emotional intelligence as being a form of inherent
intelligence, a largely inborn set of abilities that impact the ways in which people manage their
own emotions and understand and influence emotions in others.
Salovey and Mayer identify four branches within their overall concept of emotional
intelligence (Mayer, Salovey, & Caruso, 2002 as cited in Ackley, 2016). The following
branches describe how people recognize and manage their own emotions and how people may
try to influence the emotions of others:
1. The perceiving emotions branch involves the ability to identify emotions within the
self, others, and as represented by objects, such as pictures, as well as the ability to
express emotions accurately.
2. The emotional facilitation of thought branch involves the use of emotions to prioritize
thought and utilizes feelings as aids to judgment. Changes in mood lead to changes in
perspective.
3. The understanding and analysing emotions branch involves the accurate labelling of
emotions, understanding emotions and relationships, understanding complex feelings,
and understanding transitions between emotions.
4. The reflective regulation of emotion branch involves the ability to stay open to
feelings, reflectively engaging and detaching from feelings as appropriate, and
managing emotions in oneself and attempting to influence them in others.
According to Codier and Odell (2014), the above mentioned models differ widely in their
definition of the nature of emotional intelligence, the type of measurement they utilize (selfreport vs performance criteria) and the validity and reliability of the instruments used to
measure them.
For the purpose of this study the ability model of emotional intelligence will be used. This
study has distinguished emotional intelligence as consisting of four components; these being
well-being (the ability to identify emotions in self and others), self-control (the ability to use
emotions to reason), emotionality (the ability to understand emotions) and sociability (the
ability to manage emotions in self and in emotional situations).
17
According to the Universal Class (2017), the ability model supports the above definition by
recognising that emotional intelligence includes four distinct types of ability:
1. Emotional perception. The ability to identify emotions in self and others Through
facial expression, body language, pictures, voices, and so on, a person can identify
the emotions of others.
2. Use of emotion. The ability to use emotions to reason. The second activity which
proposed by the Ability Model relates to a person's ability to use emotions -whether it is their own emotions or another person's emotions -- in order to achieve
a desired outcome or to reason.
3. Understanding emotions. The ability to understand emotions. This ability is built
upon an understanding of the complexity of emotions.
4. Managing emotions. The ability to manage emotions in self and in emotional
situations. Someone's ability (or lack thereof) to regulate emotions in both
themselves and others.
The instrument most commonly used to measure ability emotional intelligence
according to Codier and Odell (2014), is the Mayer, Salovey and Caruso Emotional
Intelligence Test, version 2 (MSCEITv2), an instrument with rigorously established
validity and reliability. Based on the belief that emotional intelligence is an inherent
intelligence or ability, the MSCEIT attempts to measure one’s capacity for learning
emotional intelligence competencies (Ackley, 2016). The MSCEITv2 measures
emotional intelligence ability by evaluating the performance of emotional tasks, and
has been used widely in the general emotional intelligence research literature as well as
in numerous nursing emotional intelligence research studies (Mayer et al, 2008, as cited
in Codier and Odell, 2014).
3.5 Summary
Provided in this chapter were various definitions of emotional intelligence. The one which will
be used for the purpose of this study is the definition by Mayer, Salovey and Caruso (2004).
The four components of emotional intelligence which are; well-being, self-control,
emotionality and sociability were discussed. Finally, different models of emotional intelligence
were provided with specific focus on the ability model of emotional intelligence.
18
Chapter 4
Research Methodology
4.1 Introduction
This chapter will outline the research methodology that will be used for the purpose of this
study. The framework of this chapter will comprise; the selection of respondents and a
discussion of the data gathering methods that will be used. Lastly, a description of the statistical
methods which will be used in data analysis for testing the research hypotheses, will be
provided.
4.2 Sample Selection
The data for this study will be collected from a sample of 81 registered nurses drawn from the
population of at least 270 Post-basic nursing students enrolled at the University of the Free
States’ School of Nursing (Idalia Loots), in Bloemfontein. This sampling frame is in
accordance with Sekaran’s rule of thumb for determining sample size, wherein, he states that
the minimum size of the sample should be 30% of the population (Slideshare, 2014). A selfreport questionnaire will be used to capture demographic characteristics (age, gender); and
nursing related details (location of work: rural/metropolitan, years of experience in nursing,
qualification etc.). This study will make use of probability sampling where all elements in the
population have an equal chance of being chosen for the sample. The simple random method
of sampling will be used. This entails assigning numbers per element, distributing these
numbers on a table and then selecting the numbers at random.
4.3 Data Gathering
In order to measure psychological well-being, Ryff’s Psychological Well-being Scale
(RPWBS) will be utilised, while the Mayer, Salovey and Caruso Emotional Intelligence Test
(MSCEITv2) will assist with the assessment of emotional intelligence trait in the subjects.
4.3.1 Ryff’s Psychological Well-being Scale
This section focuses on the dimensions of Ryff’s Psychological Well-being Scale (RPWBS),
paying particular attention to its nature and composition, reliability, validity and the rationale
for inclusion.
19
4.3.1.1 Nature and Composition
The RPWBS was developed by Carol Ryff, who believed that pervious perspectives on
operationalising well-being were a theoretical (independent of theory) and decentralised
(Springer & Hauser, 2006). To address this shortcoming, Ryff (1989) suggested a
multidimensional model of psychological well-being, compromised of six psychological
dimensions (Lee & Taniguchi, 2014); self-acceptance, positive relations with others,
autonomy, environmental mastery, purpose of life and personal growth (Kállay & Rus, 2014),
it is these dimensions that the scale measures.
4.3.1.2 Reliability
A variety of versions of the RPWBS ranging from short-item scales to long and extensive ones
are available (Lee & Taniguchi, 2014). While the scale is highly acclaimed, many a researcher,
Kafka and Kozma (2002); Van Dierendonck (2004), have questioned the reliability of the scale
(Springer & Hauser, 2006). However, Akin (2008) refers back to Ryff’s own attempts in
assessing the reliability of her scale, reporting internal consistency reliability coefficients of:
.80 for autonomy, .90 for environmental mastery, .87 for personal growth, .91 for positive
relations with others, .90 for purpose in life, and .93 for self-acceptance, through test-retest.
Despite this doubt, researchers (Villar, Triadó & Celdrán, 2010; Akin, 2008; and Chen & Chan,
2005) have reported Cronbach alphas along the same ranges with only slight variation, largely
attributable to demographic characteristics (Kálly & Rus, 2014).
According to Burns and Machin (2009), the use of the larger 84- and 54-item scales is an
improvement on previous validation and reliability studies that have used the shorter scales.
4.3.1.3 Validity
While some studies (Kitamura et al., 2004; Fernandes, Vasconcelos-Raposo & Teixeira, 2010)
have shown an acceptable level of factorial validity, others such as Kim, Kim, Cha and Lim
(2007) (as cited in Lee & Tanguchi, 2014) showed lower validity. However, it should be noted
that this difference is due to demographical characteristics, and that evidence on factorial
validity of the instrument was provided by empirical studies that used exploratory factor
analysis (EFA) and confirmatory factor analysis (CFA) (Kállay & Rus, 2014). Overall, the
scale is limited and as Springer and Hauser (2006) hold, “it would appear that the structure of
PWB is limited to face validity” (p. 9).
20
4.3.1.4 Rationale for inclusion
Satisfactory internal consistencies ranging from .86 to .93 have been reported for the RPWBS.
This internal consistency, coupled with the lack of scale application in the South African
context, are sufficient reason to conduct the study using this particular measuring instrument.
4.3.2 Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT v2.0)
This section focuses on the dimensions of Mayer-Salovey-Caruso Emotional Intelligence Test
(MSCEIT v2.0), paying particular attention to its nature and composition, reliability, validity
and the rationale for inclusion.
4.3.2.1 Nature and Composition
The MSCEIT V2.0 is a newly developed, 141-item scale designed to measure the following
four branches (specific skills) of EI: (a) perceiving emotions, (b) using emotions to facilitate
thought, (c) understanding emotions, and (d) managing emotions. Each of the four branches
is measured with two tasks. Perceiving emotions is measured with the faces and pictures
tasks; facilitating thought is measured with the sensations and facilitation tasks;
understanding emotions is measured with blends and changes tasks; and managing emotions
is measured with emotion management and emotional relationships tasks (Mayer. J, Salovey.
P, Caruso. R, and Sitarenios. G, 2003).
4.3.2.2 Reliability
Codier. E, and Odell. E (2013) confirm that the MSCEIT v2.0 has undergone rigorous
reliability and validity testing and that significant evidence exists that it has a factor structure
reflective of the ability emotional intelligence model. The split-half reliability coefficient for
the total emotional intelligence score is reported to be 0.94. The split half reliability for the
total score is 0.94. Reliability scores for the sub-scores range from 0.65 to 0.78. Test–retest
reliability for the MSCEIT is r − .86, p < .001 ( Brackett et al., 2006; Brackett and Mayer,
2003 ; Mayer et al., 2003 as cited in Codier. E & Odell. E, 2013).
4.3.2.3 Validity
Validity evidence is presented that pertains to the MSCEIT's test content, its factorial
structure, its convergence and divergence with other measures, and its predictions of
important life criteria (Mayer. J, Salovey. P, & Caruso. D, 2017). Additionally, Mayer et al
(2017) emphasise that Validity data provide empirical justification for MSCEIT’s use in that:
21
-
Face validity is readily apparent in the tasks employed by the test
-
Content validity is also strong, as the scale items provide a good representation of the
Four Branch Model
-
Findings to date point to suitable construct validity and unique predictive validity
4.3.2.4 Rationale for inclusion
The validity and reliability of the MSCEIT v2.0 are considered acceptable and its’ face and
construct validity do not overlap with personality construct models. Also, the MSCEIT v2.0 is
the only test that measures the entire four-branch ability model which will be used for the
purpose of this study. For these reasons mentioned above; the study will draw on the MSCEIT
v2.0 for measuring emotional intelligence as defined by Mayer, Salovey and Caruso (2004) as
cited in Sharma, Dhar & Tyagi (2015) earlier in the proposal.
4.4
Statistical Methods
4.4.1 Descriptive Statistics
Bless, Smith and Sithole (2015) provide a definition for descriptive statistics as procedures for
summarising information about a set of data or measurements. The aim is to acquire a holistic
idea of the data distribution by summarising large data amounts in order to draw useful
conclusions.
Descriptive statistics employ the use of frequency distributions in order to describe variables.
Frequency distribution is a statistical table that indicates how many individuals in a sample fall
into each set of categories. They can be displayed visually as a bar or as a graph. Furthermore,
descriptive statistics also contain measures of Central Tendency, which is the point in the
distribution of a variable on which data are central. Three major types of estimates of central
tendency exist; (a) Mean = the average ;(b) the median = the score found at the exact middle
of the set of values (distribution); (c) the mode – the most frequently occurring value in the set
of scores (Stagnor, 2015). Measures of dispersion are also part of descriptive statistics.
Dispersion refers to the extent to which the observations (scores in a sample) are spread out
around the measures of central tendency (Stagnor, 2015). The common measures of dispersion
are the range and standard deviation. By definition, the range is a measure of dispersion equal
to the maximum observed score minus the minimum observed score on a variable (the highest
value minus the lowest value). The standard deviation is a measure of dispersion equal to the
22
square root of the variance, it is a more accurate and detailed estimate of dispersion because an
outlier can greatly exaggerate the range (Stagnor, 2015).
4.4.2 Inferential Statistics
These are mathematical techniques, or statistical tests, which allow the researcher to make
statements about populations based on data retrieved from samples (Bless et al, 2015). Stagnor
(2015) supports the above stance in his definition of inferential statistics; as numbers that are
used to specify the characteristics of a population on the basis of the data in a sample. These
numbers are p-value. The techniques to be applied in this study are the Pearson’s product
moment correlation and t-test for independent groups.
4.4.2.1 Pearson’s Product Moment Correlation
The Pearson’s product-moment correlation is a measure of the linear dependence between two
variables, giving a value between +1 and -1 where 1 is total positive linear correlation, 0 is no
linear correlation and -1 is total negative linear correlation
4.4.2.1.1 Reasons for use of the Pearson’s Product Moment Correlation
Since the studies sample size is n>30(n=81), this correlation coefficient is best suited in
providing conclusive results. Sudbury, Steyn and Wessel’s (2008) hold that if n>30, the scores
of the variables of the target population tend towards a normal distribution and a parametric
statistical method is implied. Moreover, the Pearson’s product-moment correlation provides a
single, objective measure of the direction, as wells as the strength of a relationship between
two variables, and in this case, burnout and personality characteristics.
4.4.2.1.2 Discussion of the Pearson’s Product Moment Correlation
The Pearson’s product-moment correlation coefficient (r) focuses on the relationship between
variables and looks to find a relationship between variable X and Y. Since the correlation will
be applied on a sample, the study will use the sample correlation coefficient. Sudbury et al
(2008) assert that the size of r is indicative of the strength of the relationship, while the positive
sign of r indicates a direct correlation while a negative sign is symptomatic of an inverse
correlation (Sudbury et al., 2008). To determine the Pearson’s product moment correlation, the
following formula can be used:
Definitional Formula:
23
Figure 4.1: Pearson’s Product Moment Correlation (Definitional Formula)
Where:
rxy = the correlation coefficient between variables x and y
Zx and Zy = individual’s standard scores on the variables x and y
N = Sample size
Calculation Formula:
Figure 4.2: Pearson’s Product Moment Correlation (Calculation Formula)
Where:
rxy = the correlation coefficient between variable x and y
Σx = the sum of the scores of the variable x
Σy = the sum of the scores of variable y
Σxy = the sum of the product of the scores for variables
N = Sample size
4.4.2.2 T-test for independent groups/One-way analysis of Variance (ANOVA)
A T-test is a statistical test used to determine whether the observed means are statistically
different (Stagnor, 2015)
24
The One-way Analysis of Variance (ANOVA) is a statistical procedure designed to compare
the means of the dependent variable across the conditions of an experimental research design.
(Stagnor, 2015)
Given these definitions, the use of the t-test for independent groups is best suited because of
the independence between the units to be measured, bearing in mind that the objective is
determining whether or not differences in well-being exist with regards to gender.
4.4.2.2.1 Reasons for inclusion of the t-test for independent groups
The t-test for independent groups compares the means between two unrelated groups on the
same continuous, dependent variable (Statistics.laerd.com). The decision to use the t-test for
independent groups stems from the fact that the two groups (male and female) to be tested on
the same continuous, dependent variable (psychological well-being) are independent (gender).
4.4.2.2.2 Discussion of the t-test for independent groups
The t-test for independent groups as mentioned above, determines whether there is a
statistically
significant difference between
the means
in
two
unrelated
groups
(statistics.laerd.com). Independent groups, are groups in which the participants in each group
are different, this means that an individual in one group cannot also be a member of the other
group and vice versa. Since the secondary objective of the study focuses on gender, which
classifies an individual as either male or female – not both, this test is best suited.
A few assumptions are met when deciding to work with the t-test for independent groups.
However, it is not uncommon with real-world data that a few of these assumptions are violated
(statistics.laerd.com):
1. The independent variable should be measured on a continuous scale (measured at the
internal or ratio level)
2. The independent variable consists of two categorical, independent groups
3. There should be independence of observations – there is no relationship between the
observations in each group or between the groups themselves
4. There should be no significant outliers – data points that do not follow the usual pattern
25
5. The dependent variable should be approximately normally distributed for each group
of the independent variable
6. There needs to be homogeneity of variables
When reporting the result of an independent t-test, included must be the t-statistic value, the
degrees of freedom (df) and the significance value of the test (p-value). The format of the test
result is: t(df) = t-statistic, p = significance value.
For the purpose of this study, the statistical computer program (SPSS program) will be used to
process the data.
4.5 Summary
This chapter paid attention to the proposed research methodology for the study. Focus was on
the selection of a sample and how data would be collected from said sample. The RPWBS and
MSCEITv2 were identified as the most appropriate methods of gathering data, after which a
discussion of statistical techniques to be used in order to test the hypotheses was provided. The
Pearson product moment correlation is proposed to address the question pertaining to the
relationship between burnout and personality traits, while the t-test for independent groups will
address the differences in well-being with regards to gender.
26
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