An investigation of the relationships between
perceived age discrimination, personality
and quality of life:
Validation and implementation of the
Perceived Age Discrimination scale.
Katarzyna Banas
Dissertation presented for the
MSc in the Psychology of Individual Differences
The University of Edinburgh
2007
Acknowledgements
I would like to thank my supervisors, Dr Michelle Taylor and Dr Martha Whiteman,
who offered their help and support throughout the process of designing, carrying out,
and reporting this study. I am also very grateful to all the people who helped me in the
process of recruiting participants, especially Mr Joe Docherty from the Ageing Well
50+ Project, and the friendly staff from Café Camino and Carruber’s Café, where I
carried out my pilot study.
2
CONTENTS
LIST OF TABLES AND FIGURES
5
1. ABSTRACT
6
2. INTRODUCTION
7
2.1 DEFINITION AND EXAMPLES OF AGE DISCRIMINATION
2.2 PREVALENCE OF AGE DISCRIMINATION
2.3 NEED FOR A MEASURE OF PERCEIVED AGE DISCRIMINATION
2.4 PERSONALITY AND PERCEIVED DISCRIMINATION
2.5 CONSEQUENCES OF PERCEIVED AGE DISCRIMINATION
2.6 PERSONALITY, HEALTH AND QUALITY OF LIFE
2.7 THE PRESENT STUDY
7
9
10
11
12
13
14
3. STUDY 1: QUALITATIVE ANALYSIS
15
3.1 METHOD
16
3.1.1 PARTICIPANTS
3.1.2 PROCEDURES
3.1.3 INTERVIEW
3.1.4 CONTENT ANALYSIS
16
16
17
18
3.2 RESULTS
18
4. STUDY 2: PILOTING THE PERCEIVED AGE DISCRIMINATION AND
POSITIVE EXPERIENCE OF AGEING SCALES
21
4.1 METHOD
21
4.1.1 PARTICIPANTS AND PROCEDURES
4.1.2 SCALES
21
22
4.2 RESULTS
23
5. STUDY 3: EVALUATING THE PERCEIVED AGE DISCRIMINATION
AND POSITIVE EXPERIENCE OF AGEING SCALES
24
5.1 METHOD
24
5.1.1 PARTICIPANTS AND PROCEDURES.
5.1.2 MEASURES
5.1.2.1 Socio-demographic questions
5.1.2.2 IPIP 50-Item Personality Scale
5.1.2.3 WHOQOL-BREF
5.1.2.4 Rosenberg Self-Esteem Scale
5.1.2.5 Perceived Age Discrimination Scale
5.1.2.6 Positive Experience of Ageing Scale
24
25
25
25
26
26
27
27
3
5.1.2.7 Health index
5.1.3 STATISTICAL ANALYSES
28
28
5.2 RESULTS
28
5.2.1 DESCRIPTIVE STATISTICS
5.2.2 FREQUENCIES
5.2.3 PRINCIPAL COMPONENTS ANALYSIS
5.2.3.1 Principal Components Analysis of the Perceived Age Discrimination Scale
5.2.3.2 Principal Components Analysis of the Positive Experience of Ageing Scale
5.2.4 REVISED PERCEIVED DISCRIMINATION SCALE
5.2.5 CONSIDERATION OF PARAMETRIC ASSUMPTIONS
5.2.6 CORRELATIONS
5.2.7 REGRESSION ANALYSES
5.2.7.1 Power estimation
5.2.7.1 Regression 1: Predicting physical health
5.2.7.2 Regression 2: Predicting psychological health
5.2.7.3 Regression 3: predicting social relationships
5.2.7.4 Regression 4: predicting quality of the environment
5.2.7.5 Regression 5: predicting the health index
5.2.7.6 Generalizability of the models
28
29
30
30
35
37
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39
41
41
42
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43
44
45
45
6. DISCUSSION
46
6.1 PERCEIVED AGE DISCRIMINATION SCALE
47
6.2 PERCEIVED AGE DISCRIMINATION, SELF-REPORTED HEALTH AND QUALITY OF LIFE 47
6.3 PERSONALITY AND PERCEIVED AGE DISCRIMINATION
48
6.4 AGE AND GENDER DIFFERENCES IN PERCEIVED AGE DISCRIMINATION
49
6.5 PERSONALITY AND HEALTH OUTCOMES
49
6.6 GENDER DIFFERENCES IN PERSONALITY
50
6.7 INTERPRETATION OF THE FINDINGS
50
6.8 LIMITATIONS OF THE PRESENT STUDY
52
6.9 SUGGESTIONS FOR FURTHER RESEARCH
52
7. CONCLUSIONS
54
8. REFERENCES
55
APPENDICES
60
4
List of tables and figures
Tables
Table 1
Frequencies of reporting instances of negative
discrimination and positive experience.
Page 17
Table 2
Gender and working status of participants.
23
Table 3
Descriptive statistics.
27
Table 4
Most frequently reported types of discrimination.
27
Table 5
Percentage of variance in the 25-item scale
accounted for by the 2 factors.
30
Table 6
Rotated component matrix for the 25-item scale.
31
Table 7
Rotated component matrix.
of the Positive Experience of Ageing scale.
34
Comparison of the normality tests for Total Discrimination
and its 4th root.
36
Intercorrelations between the predictor and outcome
variables.
37
Table 10
Regression model of physical health.
39
Table 11
Regression model of psychological health.
39
Table 12
Regression model of social relationships.
40
Table 13
Regression model of the quality of environment
41
Table 14
Regression model of the health index.
42
Scree plot of the PCA on the 32-item preliminary version of
the Perceived Age Discrimination Scale.
29
Table 8
Table 9
Figures
Figure 1
5
1. Abstract
The problem of age discrimination is relatively new to psychology and is a topic
which has been under-researched. The present study aimed to provide a better
understanding of age discrimination by exploring the correlates of perceived age
discrimination including personality traits and quality of life. Currently, there is no
psychometrically sound instrument which is capable of measuring perceived age
discrimination. Therefore, a second aim of this study was to create an instrument that
would measure perceptions of age discrimination, and allow linking of perceived age
discrimination to other psychological outcomes. The final version of the Perceived
Age Discrimination (PAD) scale consisted of 25 items and had high internal
consistency (alpha = 0.90). Principal Components Analysis revealed that the scale had
two factors: General Discrimination (18 items) and Institutional Discrimination (7
items) which accounted for 41% of the total variance. A sample (N = 109) of older
adults completed the PAD scale together with measures of personality, health, and
quality of life. Multivariate analyses were carried out to explore relationships between
these variables, and to examine the predictive validity of the scale. Perceived age
discrimination was a significant independent predictor of two domains of quality of
life: social relationships and environment. The other two domains, physical and
psychological health, and self-reported health were predicted by personality variables
(self-esteem, conscientiousness, emotional stability, and intellect). Neither of the Big
Five personality traits correlated with perceived age discrimination. The study adds to
the current understanding of age discrimination by showing that the perception of
being discriminated against on the basis of one’s age is associated with reduced
quality of life.
6
2. Introduction
Age discrimination has been chronically under-researched. The number of
publications about the prevalence, nature, or possible consequences of discrimination
on the basis of age is scarce in comparison to the literature on other types of
discrimination. This study aims to contribute to a better understanding of age
discrimination by (a) creating an instrument that will help assess perceived age
discrimination among older adults; and (b) exploring potential correlates of perceived
age discrimination, such as personality traits, self-reported health, and quality of life.
An additional purpose of this investigation is to examine the relationship between
personality traits, self-reported health, and quality of life.
2.1 Definition and Examples of Age Discrimination
There have been several attempts to define age discrimination, or ageism. The
need to introduce this term arose as a consequence of the observation that people
belonging to different age groups are not treated equally. The initial definition was
provided by Butler (1975), who defined ageism as “a process of systematic
stereotyping of and discrimination against people because they are old (…)” (p. 35).
This definition was then amended by Kite and Wagner (2004), who argued that
ageism should be conceptualised in light of the three-component model of attitudes.
According to this model, ageist attitudes have an affective component, i.e. the feelings
towards older persons; a cognitive component, comprising of the “beliefs or
stereotypes about older people” (p. 131); and a behavioural component, i.e. the actual
behaviours or behavioural intentions.
The emotional component of ageism is the one that we know the least about. Still,
it seems that emotions are in many cases the factor that leads to discriminatory
attitudes or behaviours. Greenberg, Schimel and Mertens (2004) have suggested that
although older people do not pose any explicit threat to younger people, they do
represent a threat: they represent the loss of health, beauty and cognitive abilities that
people associate with ageing, and eventually, they represent the threat of death.
According to Greenberg and his colleagues (2004), in order to escape this threat,
younger people use two techniques: they either avoid older people (by literally
avoiding them in the social space, or reducing their numbers in the workplace, etc.),
7
or they create a distance between themselves and the older people by ascribing to the
older population characteristics that, according to them, the younger do not possess.
With regard to the cognitive component, there are four common beliefs about
older people: (1) that they are lonely and depressed, (2) they are all similar, (3) they
are sick and dependent, and (4) they are psychologically and cognitively impaired
(Whitbourne and Sneed, 2004). All those are stereotypes, in the meaning that, indeed,
some older people are lonely, sick, or cognitively impaired, and the proportions do
increase with age, but it is only a minority of the older population that suffer from any
of the above. There is certainly no reason to assume that an older person met on the
street would be a member of that minority. This notion becomes particularly clear if
one appreciates the fact that as people grow older, they become more different from
each other both physically and psychologically (Nelson and Dannefer, 1992).
Therefore, it is more difficult to make judgments about the health or cognitive
functioning of older people on the basis of their age than it is for younger people.
Discriminatory behaviours are normally a consequence of either attitudes or
feelings towards older people. Pasupathi and Löckenhoff (2004) defined ageist
behaviour as “a subset of age-differentiated behaviour that is either caused by
inaccurate negative attitudes and beliefs about aging or older adults or has clear
harmful impact on older adults” (p. 202). Apart from emphasising a link between the
three components of age discrimination, this definition implies that distinguishing
between ageism and age differential behaviour is not an easy matter: one would have
to know either the exact cause of that behaviour (i.e. the beliefs or feelings that led to
it), or its consequences. Both can be difficult, as people rarely reveal exact reasons for
what they do (even if asked to do so), and the consequences of many experiences are
also difficult to establish.
There are five main settings where age discriminatory behaviours occur
(Pasupathi & Löckenhoff, 2004). The first of them is healthcare, where older patients
are treated differently than younger patients: physicians spend less time with them,
they are less supportive, and give less information (Greene, Adelman, Charon, &
Hoffman, 1986). Doctors also tend to assume that conditions such as depression or
chronic pain are caused by older age, and, as a consequence, they fail to treat their
patients adequately (Pasupathi & Löckenhoff, 2004). The second environment where
older people are being discriminated against is the legal framework. What is
particularly relevant here is the legislation that promotes differential treatment based
8
on age, for example acts that set a compulsory retirement age, or allow insurance
companies to charge different rates depending on the age of the client alone. Third,
there is the workplace, where hiring older people is often avoided, and those who are
already employed and reach the age of 60 or 65 are encouraged or even forced to
retire (see for example Platman & Tinker, 1998, on the age–related policies in the
BBC in 1990s). Fourth, older people are underrepresented in the media, and when
they are portrayed, the image is not always favourable. The authors note, though, that
this pattern is changing: the image of the older population in the media used to be
much more negative in the past (Pasupathi & Löckenhoff, 2004). The last area where
age discrimination occurs is the community: whether it is between family members, or
in encounters with strangers, older people are being treated differentially: members of
the younger age groups speak slower and louder when talking to older people, and
they raise the pitch of their voice (see for example Kemper & Harden, 1999).
All in all, there is a variety of attitudes and behaviours that could be seen as ageist
and, from the outside, it seems that age discrimination is a rather widely spread
phenomenon. Before making judgements about the prevalence of ageism, it is
important to consider how older adults themselves perceive the situation. It is
important to do so for two reasons: first, knowing the consequences of certain
behaviour could help in classifying it as ageist or not, because having harmful
consequences for older people is what defines ageist behaviour (Pasupathi &
Löckenhoff, 2004). Second, for this particular study, which is concerned with the
effects of age discrimination on health and quality of life, the subjective experience of
discrimination may be more important than its objective prevalence.
2.2 Prevalence of Age Discrimination
There are few studies that have looked at rates of age discrimination, but among
those that have been published, a recent report by Age Concern England (2006) is
particularly relevant. The data for that report was collected from a representative
sample of over 1800 English residents over 16 years old (Age Concern England,
2006). According to that report, up to 30% of the adult population may be
experiencing age discrimination every year. The report does not stratify the data by
age group, but it does show that the groups which see age discrimination as the most
serious are people between 45 and 65 years old. About half of the respondents from
9
that age group reported that discrimination based on age was ‘very’ or ‘quite’ serious,
whereas most adults from other age groups perceived age discrimination as ‘not very’
or ‘not at all’ serious.
Additional evidence for the existence of ageism is provided by Palmore (2001),
who asked 84 American residents over 60 years old whether they had experienced any
of the 20 ageist behaviours specified by him. Over 77% of the respondents reported
having experiences at least one of the behaviours, which led the author to the
conclusion that “ageism is perceived as widespread and frequent” (p. 573).
2.3 Need for a Measure of Perceived Age Discrimination
The studies by Age Concern England (2006) and Palmore (2001) are the only ones
in the published literature which deal directly with the prevalence of perceived
ageism. The shortage of data on this topic may be a consequence of the lack of a
proper instrument to accurately measure the experience of age discrimination.
Palmore’s (2001) survey was created with a view of filling that gap, but it also suffers
from a number of conceptual and methodological problems. Cohen (2001) rightly
points out that it is rather a “survey of perceptions of ageism” (p. 577), in that it does
not look at the intentions behind the behaviours, thus assuming, for example, that all
jokes about older people are ageist. That is a valid point, but a survey of perceptions
of ageism may be what is needed in research on its consequences. Another problem,
which may be more important, is whether people who report experiencing those
behaviours think that they are ageist? It is conceivable that someone was told a joke
about older people (the item that was reported most frequently in Palmore’s study),
but did not feel that it was in any way offensive or discriminatory. Thus, it is
important to ask people not only whether they have experienced particular behaviours,
but also whether they felt that there was any discrimination involved.
Apart from these theoretical issues, the psychometric properties of The Ageism
Survey have not been examined to the degree that would allow the instrument to be
widely used. Most importantly, the measure has only been validated in a convenience
sample of 84 individuals, although Kline (1986) advises a sample of at least 500 in
order to reduce statistical error.
In a number of studies looking at the consequences of age discrimination, older
people were asked about their experience of ageism. For instance, Garstka, Schmitt,
10
Branscombe and Hummert (2004) asked their participants four questions about
whether they themselves, or older people as a group, are experiencing any
discrimination. Similarly, Redman and Snape (2006) asked four questions about
people’s experiences of age discrimination at work. Perrewe, Brymer, and Stepina
(1991) used a 9-item scale to measure age discrimination in the workplace. Such short
and general scales, although helpful in differentiating between those who feel
discriminated against and those who do not, are not well-suited for capturing different
degrees of perceived discrimination (Sigelman & Welch, 1994). Therefore, a new
instrument is needed that will measure the subjective experience of discrimination,
and at the same time will allow a quantifiable estimate of the scale of perceived
discrimination. The development and validation of such an instrument will be the goal
of the three studies reported in this paper.
2.4 Personality and Perceived Discrimination
The perception of age discrimination is likely to be influenced by psychological
factors such as personality variables. Studies from various areas of discrimination
have shown that personality variables are significant predictors of perceived
discrimination. Notably, in the field of gender discrimination, the willingness to risk
social disapproval and depression were significant predictors of personal
discrimination reported by women (Kobrynowicz and Branscombe, 1997). For
perceptions of the discrimination against women in general, the significant predictors
were feminism and depression.
In predicting perceived racial and ethnic discrimination, personality characteristics
were found to play a significant role. Among young immigrants in Glasgow,
depression, need for approval and low self-esteem were all related to anxiety, and
anxiety led to higher perceived discrimination (Cassidy, O’Connor, Howe, & Warden,
2005). A similar effect was observed among minority adolescents who lived in the
Los Angeles area. In that sample, lower self-esteem was indirectly related to greater
perceived racial discrimination by increasing anxiety (Phinney, Maden, & Santos,
1998). Among Indian immigrants in Portugal, lower self-esteem was an independent
and significant predictor of greater perceived racial discrimination (Neto, 2006).
The inclusion of personality variables in the present study is important in order to
provide a better understanding of why some people feel more discriminated against
11
than others. When looking at the consequences of perceived discrimination,
personality variables may be the ‘third factor’ that accounts for the apparent relation
between perceived discrimination and health or well-being outcomes.
2.5 Consequences of Perceived Age Discrimination
Apart from the moral obligation, an important reason to try to eliminate any type
of discrimination is because it tends to have a negative effect on the health and wellbeing of its victims. Krieger (2000) reviewed 20 studies of perceived discrimination
(based on race, gender, sexual orientation, and disability) and found that in only two
of them no relationship was found between the perception of prejudice and stigma,
and some measure of physical or psychological health. Her review did not include any
papers on age discrimination, but there is some evidence to show that perceived
ageism also has a detrimental effect on the victims’ well-being.
The psychological consequence of perceived age discrimination that has received
the most attention is self-esteem. Garstka and her associates (2004) found that among
older people, perceived age discrimination was inversely related to psychological
well-being- a latent factor combining self-esteem and life satisfaction. This
relationship was not present among younger adults, who also felt discriminated
against with respect to their age. The authors hypothesised that this difference may be
caused by the fact that younger age is only a transitory period, and young adults will
eventually move to the higher-status, middle-aged group. Older adults, on the other
hand, have no perspective of moving to a higher-status group, and therefore their
well-being may be more affected by the perception of being discriminated against.
Another two studies have looked at the effects of age discrimination in the
workplace, suggesting that feelings of being discriminated against do affect variables
such as job and life satisfaction. More specifically, Redman and Snape (2006) studied
the consequences of perceived age discrimination among older police officers in
England, and they found that perceived discrimination had a significant negative
influence on job satisfaction, life satisfaction, the perception of power and prestige of
the job, commitment to the job, and cognitions about withdrawal. Similarly, Perrewe
and her colleagues (1991) found that, among hotel managers, perceived age
discrimination had a negative effect on self-esteem and perceived control. Lower self-
12
esteem and perceived control led to greater burnout and job dissatisfaction, and more
somatic complaints, which resulted in an increase in turnover intentions.
At this point, it is necessary to clarify the role of self-esteem, since, in this review,
it has been included both as a cause and effect of perceived discrimination. Indeed,
the position of self-esteem in the model depends on its conceptualization. Self-esteem
has traditionally been viewed as a personality variable- a stable trait. Recently,
though, some social psychologists have started to conceptualize it as a variable index
of the quality of a person’s relationships with others, a so-called ‘sociometer’ (Leary
and Baumeister, 2000). Because there is no consensus about which definition is more
valid, self-esteem continues to be used as both. In this study, self-esteem will be
perceived as a personality variable, and thus it will be included together with the Big
Five traits, among the predictors of perceived age discrimination, quality of life, and
health.
2.6 Personality, Health and Quality of Life
The relationship between the Big Five personality traits (Extraversion, Emotional
Stability or Neuroticism, Intellect, Agreeableness, and Conscientiousness; Goldberg,
1990) and self-reported health is well-documented in the literature. Goodwin and
Engstrom (2002) found that, among participants with self-reported medical problems,
a higher score on extraversion, intellect, agreeableness or conscientiousness was
associated with better self-reported health, whereas a higher score on neuroticism was
related to worse self-reported health. The only difference in the group without any
self-reported medical problems was that agreeableness was not significantly related to
self-assessed health.
Williams, O’Brien and Colder (2004) in their study of 135 American
undergraduates found that participants who obtained higher scores on neuroticism
tended to rate their global health more poorly. Additionally, there was a marginally
significant quadratic effect of extraversion on self-reported health, meaning that
higher scores on extraversion were associated with better self-reported health up to a
certain point, but beyond that point the reverse would be true- highly extraverted
individuals rated their health poorly. This study did not examine the other personality
factors, and their relation to self-reported health. In summary, it seems that personality
traits play a role in the subjective perception of one’s own health.
13
Personality traits are also important predictors of one’s subjective well-being and
quality of life. A meta-analysis of studies looking at the relationship between the Big
Five personality traits and subjective well-being (DeNeve & Cooper, 1998) shows
that all five traits are significantly correlated with subjective well-being, with a small
to medium size effect. The two traits that contribute the most are emotional stability
(or lack of neuroticism) and conscientiousness.
A study that looked specifically into the relationship between personality traits
and four domains of quality of life (Masthoff et al., 2007) found that the significant
predictors of better perceived physical health were (in order of significance) higher
extraversion, lack of openness, and higher conscientiousness; significant predictors of
better psychological health included higher emotional stability, higher extraversion
and conscientiousness. Only conscientiousness was a significant predictor of the
reported quality of environment, and no personality trait was significantly associated
with the quality of social relationships. Although this study’s population consisted of
psychiatric outpatients, and thus its results may not be generalisable to a
psychologically healthy population, it does show an association between personality
and quality of life, and warrants inclusion of personality traits in regression models of
quality of life.
2.7 The Present Study
The present study has two goals. Firstly, because to date there is no
psychometrically sound instrument that measures the subjective experience of age
discrimination, the main objective is the development and piloting of two new scales
to assess Perceived Age Discrimination as well as Positive Experiences of Ageing.
The second goal is to use the newly created scale to identify personality and
demographic predictors of perceived age discrimination and positive experiences of
ageing, and also explore the consequences of perceived discrimination in terms of
health and quality of life. The study will be carried out in three phases: phase 1
involves the creation of the Perceived Age Discrimination scale, phase 2 involves the
piloting of the new scale, and phase 3 involves examining the new scale and using it
to predict other psychological outcomes. The hypotheses tested in phase 3 are the
following:
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(1) Women and older people will tend to report more age discrimination than men
and younger persons. For women, this would be caused by the double
jeopardy- being an older person from a disadvantaged social group is a double
disadvantage (Jackson, 1985). Regarding older people, it is conceivable that as
they grow older, their age becomes more and more visible, and thus they may
be subject to more discrimination. Also in the society, reaching a certain age is
similar to crossing a borderline: 60 is the age when one gets a free bus pass, 65
is the retirement age, etc.
(2) Perceived age discrimination will be a significant predictor of lower quality of
life in all four domains: physical health, psychological health, social
relationships, and environment.
(3) Perceived age discrimination will be a significant predictor of self-reported
health, with higher perceived discrimination leading to worse self-reported
health.
(4) Higher neuroticism, lower agreeableness, and lower self-esteem will be
significant predictors of greater perceived age discrimination. It is expected
that agreeable people would not be willing to report any discrimination events,
because they tend to comply with social norms and accept hierarchies (Costa,
McCrae, & Dye, 1991).
(5) Better self-reported health and better quality of life will be predicted by higher
extraversion, agreeableness, conscientiousness and intellect, lower
neuroticism, and higher self-esteem.
3. Study 1: Qualitative Analysis
The aim of the first study was to generate a number of items that could potentially
be used in the Perceived Age Discrimination and the Positive Experience of Ageing
scales. Because of scarce literature on age discrimination, interviews with people from
the target age group (over 55 years old) were chosen as the method of item
generation. As indicated by Dawis (1987), using items that occur naturally in an
interview, and making the wording as close as possible to the original utterances,
makes the scale more authentic and readable than it would be otherwise. This also
means that the items reflect the views of the individuals themselves and the issues
which they perceive to be most salient, rather than the researcher’s perspective.
15
3.1 Method
3.1.1 Participants
In order to generate items for the scale, 10 individuals (6 men and 4 women)
between 54 and 82 years old were invited to take part in interviews. Three methods
were used to recruit potential participants. First, the author’s personal networks were
used to contact older adults who might be willing to take part in the study. Second, the
coordinator of the Ageing Well 50+ Project in Edinburgh was contacted, and asked to
distribute the information about the study among volunteers in the project. Third,
posters and flyers about the study were placed in a Roman Catholic Church in
Edinburgh, and in two branches of the public library.
Participants who responded after being given information about the purpose of the
study were to some extent self-selected. When calling to make an appointment for the
interview, some of the participants mentioned that they found the issues of
discrimination personally relevant, because they had experienced it in the past.
Participants recruited through the personal networks, though, largely had not found
the subject of discrimination very relevant to themselves, and most of them had not
experienced any instances of it. This was later reflected in the number of items
generated in each of the sessions.
All participants were of British nationality. At the time of the interview, two of
them worked full-time, one worked part-time, and seven were retired. Although they
represented a range of occupations (from a nurse to a university lecturer), they all
belonged to the middle or upper social class groups, and it was noted that their
experiences may not be representative of the general population, especially those with
lower incomes.
3.1.2 Procedures
All participants were given a letter that explained the purpose of the study, and
informed that the sessions would be audio recorded and transcribed. The interview
sessions were organized as 3 mini-focus groups and 2 individual interviews. Before
each interview, participants were asked to confirm that they agreed to recording and
16
transcribing of the interview, and they were assured about the strict confidentiality of
any information obtained in the interview.
3.1.3 Interview
The semi-structured interviews were built with the view of provoking participants
to provide any instances of age discrimination that they either experienced themselves
or have heard about from others or the media. Questions included in the interview
addressed a range of topics related to the overall experience of ageing. The first few
questions were concerned with whether the participants felt that age discrimination
was a social problem (e.g. “Do you think age discrimination is a serious problem
nowadays?”), and in what areas it was the most prevalent. This was followed by a
series of questions which asked about different examples of discrimination.
Participants were encouraged to mention any situations that happened to them or that
they had heard about, that they considered discriminatory. One of such questions
was: “What are the examples of things that you would consider age discrimination?”
Some items from The Ageism Survey (Palmore, 2001) were used as examples, in
order to encourage discussion. Participants would be asked, for instance: “Have you
ever been refused promotion, on the basis of your age?” Other topics brought up in
the interviews included potential consequences of age discrimination (e.g. “Do you
think age discrimination is harmful to the people who experience it?”), gender
differences in the experience of discrimination, and other personal factors that could
change the experience of age discrimination (e.g. “Are some people more likely to
feel discriminated against, even if they are not really discriminated more than
others?”). At the end of the interview, a number of questions about the positive
aspects of being older were included (e.g. “Are there any advantages to being
older?”), and these were used later on to create the Positive Experience of Ageing
scale. A full schedule of the interviews is included in Appendix A.
17
3.1.4 Content analysis
The text of the interviews was subjected to content analysis, which is, according to
Krippendorff (2004) “a research technique for making replicable and valid inferences
from texts (…) to the contexts of their use” (p.18). By content analysing interviews
with ten participants, the researcher hoped to obtain a list of behaviours that are
considered discriminatory not only by those who were interviewed, but by the
population of older adults. Thus, the analysis was problem-driven, and an effort was
made for it to be externally valid.
A more detailed presentation of the technical side of content analysis is presented
elsewhere (Krippendorff, 2004), thus only information which is crucial for the
understanding of this study will be presented here. The first step in the analysis was
the recording of any examples of age discrimination that were presented by
participants. The next stage was to classify the examples into broader categories. The
three broadest categories were adapted from the three component model of attitudes:
the examples were classifies as stereotypes, prejudiced affect, or discriminatory
behaviours. Then, within each of these broad categories, a number of smaller groups
were identified. In case of discriminatory behaviours, they could often be grouped
with respect to the place or setting where they took place. Stereotypes were also
grouped on the basis of what they referred to: physical, psychological, or intellectual
domain.
3.2 Results
After analysing the transcripts, 12 main types of discriminatory behaviours were
identified, and the number of times that any situation of that type was mentioned, was
recorded. Thus, even if a particular situation was mentioned twice by the same person,
the frequency recorded would be 2. This method was chosen in order to reflect the
overall importance of the situations- assuming that situations that were the most
disturbing to a person would be mentioned several times.
Table 1 presents the identified types of discrimination, together with examples and
frequencies.
18
Table 1. Frequencies of reporting instances of negative discrimination
and positive experience.
Type of experience
Example
Freque
ncy
NEGATIVE DISCRIMINATION
Being forced to retire
I didn’t want to retire, and I had to retire because
4
of ageism. And I resented that.
Being denied promotion
The last selection board I went in front of, I
5
didn’t pass. And we were allowed to pass for an
interview to ask why. So I got this explanation
about different things, and then at the interview,
the last time I was interviewed, the man said:
“Of course your age went against you.”
Having difficulties finding
And when I was looking for another job I was
employment
55, and I was very concerned that my age would
4
be detrimental to the interview process. (…)I
think if I had had to offer my date of birth, I
think there would’ve been some resistance to
taking me on.
Not being able to work in other
Another area I came across, it was, I was a
institutions
member of the Children’s Panel. When you
1
reach the age of 60, you have to leave.
Having to pay higher insurance rates
I go for bus trips, and if you take their insurance,
than younger people
if you’re under 60, (…) it’s, say 42 pounds (…).
6
But because I’m older than that, it was 62
pounds.
People using patronising language
I remember a young person saying to me one
when speaking to older persons
time, I can’t remember, I think it was the dentist:
1
“Have a wee sit.”
Unpleasant remarks
And 3 years ago somebody said to me: “Don’t
5
you think it would be better when a younger
person was doing that?”
Discrimination in healthcare
In terms of health, I think there’s a fair
3
discrimination
Stereotypical image of older people
And I think there’s definitely a stereotypical
(e.g. assuming that they are
image of anyone over 55 being old, being tired,
conservative, lack energy or
being without energy and without drive.
20
ambition, look in a certain way).
19
Assumption that older people are
Like someone says to me: “Do you think you
physically or cognitively impaired
can manage these stairs?”
Assumption that older people are
My friend told me that, when I was 50, which I
“over the hill”
thought was…, “every day after this is a bonus.”
Other negative aspects (such as
Now, when there is a group of over 50s that play
fashionable clothing items being
badminton every week- we get one hall, the
targeted at younger people)
youngsters get another hall. And their hall is
9
3
4
much better than our hall. And we’ve asked:
“why can’t we have that hall?” And they’ve
said: “Oh, that’s for the young ones.”
Type of experience
Example
Freque
ncy
POSITIVE EXPERIENCE OF AGEING
Positive discrimination (bus pass,
You get your bus pass, which is very good.
3
And I think that’s something you learn as you
11
discounts)
Psychological changes
get older. You know, some things are more
important than others.
Having more time
I think the big advantage is having the time to do
2
things in case you want to do them.
Financial security
When you become that bit older you not only
1
have the time, but (…) a lot of resources with
which to enjoy the time…
Having more experience
And I think one of the great feelings of
2
satisfaction I get from my job is being able to
coach younger people.
Positive attitudes of others
I think in some circumstances older people are
2
held in some feeling of awe and respect,
certainly within my own family.
Being a grandparent
Being a grandmother is a special, special thing.
1
Much more special in many ways than being a
mother, so I love that.
20
The examples of discriminatory behaviours provided by the participants are
roughly parallel to those reviewed by Pasupathi and Löckenhoff (2004). Participants
mentioned discrimination in healthcare, in legal settings, in the workplace, in the
media (because there was only one example of that, it was classified as ‘other’) and in
the community (for example, in the family). There were also many examples of
stereotypes about older people, and participants suggested that the stereotypes may be
causing discriminatory behaviour.
Among the positive experiences related to ageing, there were two groups of
benefits: those provided by the state or other organizations (such as a free bus pass or
reduced rates for various activities), and those more psychological, such as becoming
wiser or being respected by others. Examples of negative discrimination recorded
from the interviews outnumbered the positive aspects of being older, but this is likely
to be due to a greater emphasis being put on discrimination within the interviews.
In general, a series of interviews proved to be an effective method of generating
items for the scale. In the end, 15 examples of discrimination extracted from the
content analysis, which did not appear in Palmore’s (2001) survey, were included in
the new Perceived Age Discrimination scale. Nine aspects of the positive experience
of ageing were incorporated into the Positive Experience of Ageing scale.
4. Study 2: Piloting the Perceived Age Discrimination
and Positive Experience of Ageing Scales
The main aims of the pilot study were to ensure that items in the new scales were
easily understood by participants, and that the scoring method was clear and easy to
follow.
4.1 Method
4.1.1 Participants and procedures
A questionnaire consisting of the Perceived Age Discrimination and Positive
Experience of Ageing scales, together with questions about age, gender and
occupation was distributed to a sample of 51 individuals over 55 years old.
Participants were recruited in four different ways. First, those who participated in the
21
qualitative study were asked to fill in the questionnaire, and to distribute it among
their friends: 13 questionnaires were obtained in this way. Second, a manager of a
local B&Q store was asked to distribute it among her employees. Only two
questionnaires were returned. Third, thirty older people were approached in three
cafes in Edinburgh and asked to complete the questionnaire. Four of them refused to
participate, but the other 26 completed and returned questionnaires to the author.
Fourth, a number of older employees of the University of Edinburgh were contacted
via e-mail and asked to complete the scale. Ten of them returned completed
questionnaires.
Out of the 51 individuals who completed the questionnaire, 3 did not answer all
the questions from the discrimination scale, and their data were subsequently dropped
from further analysis. In the group of 48 participants without missing data, 30 (62.5%)
were female, and 18 (37.5%) were male. The participants’ age was between 51 and 84
years, with the mean of 67, and standard deviation of 7.4 years.
4.1.2 Scales
The examples obtained from content analysis were then used to generate items for
two scales: a 35-item scale of perceived age discrimination, and a 9-item scale of
positive views of ageing. In the Perceived Age Discrimination scale, each of the 35
items was a description of a specific situation (e.g. “I was forced to retire because of
my age”), and for each item two questions were asked:
Has it ever happened to you? With scores 0 = Never, 1 = Once, and 2 = More than
once (scoring adapted from Palmore, 2001)
and
Did you feel discriminated against when this happened? With 0 = the situation did not
happen, and a scale from 1 to 5, with 1 = not at all, 3 = depends on the circumstances,
and 5 = very much.
The scoring method was chosen to account for the fact that often people do
experience different forms of discrimination, but do not recognise it as discrimination.
22
For example, someone may be asked to retire when he or she reaches 65, and be
unhappy about it, but not perceive it as discrimination, but rather as the normal order
of things.
The Positive Experience of Ageing scale consisted of descriptions of potential
positive aspects of growing older. It was scored on a 5-point Likert scale, ranging
from 1 “strongly disagree” to 5 “strongly agree”. Three items were negatively worded
to account for the complicance effect (a tendency to agree with items). These three
items were reverse scored.
The full pilot version of the Perceived Age Discrimination scale is included in
Appendix B, and the Positive Experience of Ageing scale can be found in Appendix
D.
4.2 Results
Similar to Palmore’s (2001) results, only a minority of participants did not report
experiencing any instance of ageism. In fact, only 3 (6.25%) participants reported that
they had never experienced any of the situations presented in the scale. The most
frequently reported type of a discriminatory behaviour was having been told a joke
that pokes fun at older people, which was reported by almost 67% of participants.
Interestingly, this was also the most frequently reported discriminatory event in
Palmore’s (2001) study. Nevertheless, only 10% said that they felt discriminated
against when hearing that joke. Other frequently reported situations included “I was
sent a birthday card that pokes fun at older people,” reported by 67% of participants,
or “When I went shopping for clothes, I felt that there was less choice of clothes for
people of my age, than there was for younger people,” and “Someone assumed I am
not interested in certain activities, because of my age,” each reported by 54% of
participants.
Independent of prevalence rates, it is important to examine which situations were
considered to be the most discriminatory. Thus, the lack of choice of clothing for
older people was considered to be “very discriminatory” by 31% of participants
(meaning that 31% of participants have both experienced it and found it very
discriminatory), having to pay higher insurance rates was regarded as serious
discrimination by 17% of participants, and other people assuming that older people
23
could not remember well was considered very discriminatory by 10% of the
participants.
There were 5 items that were not reported by any of the participants (numbers 17,
19, 23, 30, 34). Items 19 (“refused rental housing”), 23 (“denied medical treatment”),
and 34 (“house was vandalised”) were then removed from the scale, because they
were considered to be very extreme situations that are unlikely to happen frequently in
Great Britain. Items 17 (“assumed not to make enough contribution at work”), 30
(“denied a position of leadership”) were left in the scale. In a predominantly female
sample, as is this one, events of work-related discrimination (such as items 17 and 30)
may rarely be reported. Therefore, these items were retained and their frequencies
examined in the main study sample.
Apart from removing the items that yielded no variance, a slight change was made
in the scoring method of the scale. Because in the “Did you feel discriminated
against?” question participants only chose 0, 1, 3, or 5 (although it was possible to
choose any number between 0 and 5), the scoring was changed to a simple 0, 1, 2 or
3.
Analysis of the Positive Experience of Ageing scale showed that all nine items
discriminated between participants. Principal Components Analysis and reliability
analysis could not be performed due to the small number of participants who took part
in the pilot study. Therefore, this scale will be analysed further in the third phase of
the study.
5. Study 3: Evaluating the Perceived Age Discrimination
and Positive Experience of Ageing Scales
5.1 Method
5.1.1 Participants and Procedures.
After the pilot study, a battery of self-administered questionnaires which included
the adapted Perceived Age Discrimination scale and the Positive Experience of
Ageing scale was distributed to a sample of 150 older individuals who were part of
the Psychology Department’s Volunteer Panel at the University of Edinburgh. In total,
one-hundred nine questionnaires were returned, giving a 72.6% response rate.
24
Socio-demographic characteristics of the sample that returned the questionnaires
are given in Table 2. The majority of the participants were female, and retired. The
age of participants was between 56 and 86 years, with mean of 68, and a standard
deviation of 7.9 years.
Table 2. Gender and working status of participants
Count
Percent
Male
28
25.7%
Female
81
74.3%
Employed full-time
16
14.7%
Employed part-time
21
19.3%
Retired
70
64.2%
Unemployed
2
1.8%
5.1.2 Measures
5.1.2.1 Socio-demographic questions
All participants were asked to report their gender, year of birth, occupation and
working status (whether they were working full-time, working part-time, unemployed,
or retired).
5.1.2.2 IPIP 50-Item Personality Scale (Goldberg, 2001)
Fifty items from the International Personality Item Pool were used as a measure of
the Big Five personality factors: Extraversion (e.g. “I am the life of the party”),
Agreeableness (e.g. “I am interested in people”), Conscientiousness (e.g. “I pay
attention to details”), Emotional Stability (e.g. “I seldom feel blue”), and Intellect
(e.g. “I have a rich vocabulary”). There were 10 items measuring each factor, and
participants responded by saying how accurately or inaccurately the item described
themselves, on a 1 (very inaccurate) to 5 (very accurate) Likert-type scale. The scores
25
for each personality trait were then computed by adding the scores from the 10
individual items associated with that trait. As a result, each personality trait was
scored on a scale from 10 to 50. The mean coefficient alpha for the five personality
scales was found to be 0.84, and the mean correlation between the scores on the IPIP
50-item scale and the NEO-PI-R Personality Inventory is 0.77 (Goldberg, 1990). In
this sample, all scales had very good internal consistency reliability, with the average
alpha score of 0.82.
5.1.2.3 WHOQOL-BREF (WHO, 1996)
The World Health Organization Quality of Life Scale Brief Version was used as
the measure of quality of life. The scale has two separately scored general items, and
the other 24 items are arranged to measure quality of life in four domains: physical
health (7 items, e.g. “How much do you need any medical treatment to function in
your daily life?”), psychological health (6 items, e.g. “How much do you enjoy
life?”), social relationships (3 items, e.g. “How satisfied are you with your personal
relationships?”), and environment (8 items, e.g. “How healthy is your physical
environment?”). The participants respond on a 1 to 5 Likert-type scale, and the
response categories are different for different questions. The scale has been shown to
have excellent reliability and good validity across age and cultural groups
(Skevington, Lofty, & O’Connell, 2004). Specifically in this sample, the average
alpha coefficient of the four scales was 0.80.
5.1.2.4 Rosenberg Self-Esteem Scale (Rosenberg, 1965)
Participants’ self-esteem was measured using the 10-item Rosenberg Self-Esteem
scale (Rosenberg, 1965). This scale consists of 5 positively (e.g. “On the whole, I am
satisfied with myself.”), and 5 negatively worded items (e.g. “At times, I think I am
no good at all.”). Each item was rated on a 1 (strongly disagree) to 4 (strongly agree)
Likert-type scale. The scores on the negatively worded items were reversed, and the
scores were then added to obtain an overall self-esteem score. The alpha coefficient
was 0.87.
26
5.1.2.5 Perceived Age Discrimination Scale
The scale developed in the two previous studies (see Study 1 and 2) was used to
measure perceived age discrimination. The scale included 32 items, and each item
was a description of a discriminatory event, e.g. “Someone assumed that I cannot hear
well because of my age.” Each item was then rated on two scales. First, participants
were asked if they have ever experienced such event, and they replied on a 3-point
scale, where 0 = never, 1 = once, and 2 = more than once. Second, they were asked
whether they felt discriminated against as a result of that situation, and they responded
on a 4-point scale, filling in a 0 if the event had never occurred, 1 = not at all, 2 =
somewhat, 3 = very much. The number of items and the range of scores that would
characterize the final version of the scale were not clear at this point, therefore that
information is presented in the results section.
5.1.2.6 Positive Experience of Ageing Scale
Apart from the experience of discrimination, a finding from the interviews (Study
1) and from the Pilot (Study 2) was that some people report positive aspects of ageing.
Therefore, 9 items derived from the interviews (Study 1) and describing positive
consequences of ageing were included in the questionnaire. Six items were positively
worded (e.g. “Because I am older, I have a better understanding of what is really
important in life.”), and three were negatively worded (e.g. “Being older does not
make you wiser.”). The scale included both psychological (e.g. wisdom) and practical
(e.g. a bus pass) advantages of being older. The scores from the negatively worded
items were transformed, and the total score of the 9 items was computed. In the pilot
version of this scale, scores ranged from 9 to 45 with higher scores indicating a more
positive experience of ageing. After performing the Principal Component Analysis,
the number of items included in the scale and its range of scores may change. The
changes will be reported in the results section.
27
5.1.2.7 Health index
Two questions asked about people’s perceptions of their own health:
In general, would you say your health is…? (rated on a 5-point scale, from 1 = poor,
to 5 = excellent).
Compared to one year ago, how would you rate your health in general now? (rated on
a 5-point scale, from 1 = Much worse than one year ago, to 5 = Much better now than
one year ago).
Both items were adapted from the SF-36 (McHorney, Ware, & Raczek, 1993), a
measure of health-related quality of life. The scores on these two items were then
added to obtain a health index. The health index provides a global measure of selfrated health.
5.1.3 Statistical Analyses
Data were analysed using the Statistical Package for the Social Sciences (SPSS)
version 13.0 for Windows. There were two types of analyses used in this study. First,
Principal Components Analysis (PCA) was used in order to detect patterns within
participants’ responses. More specifically, it was expected that participants may be
sensitive to some types of discrimination but not to others, and thus a pattern of
responses would form. Second, multiple regression was used to test models predicting
the relationship between perceived age discrimination and different aspects of quality
of life and health.
5.2 Results
5.2.1 Descriptive statistics
Means and standard deviations for each of the variables of interest are shown in
Table 3. Because 9 participants did not provide an answer to one or more questions in
the questionnaire, their data was not included in the regression analyses. It was,
however, used for the PCA, provided that they answered all questions in the Perceived
Age Discrimination scale. Descriptive statistics for the perceived age discrimination
28
and the positive experience of ageing are not included, because the scales measuring
those outcomes will be modified as a result of the analyses performed in this study.
Table 3. Descriptive statistics
N
Mean
Std. Deviation
Age
109
67.57
7.86
Physical health
106
27.15
5.20
Psychological health
106
22.37
3.16
Social relationships
108
11.19
2.44
Environment
106
33.30
4.58
Extraversion
106
32.23
7.21
Agreeableness
106
41.95
4.96
Conscientiousness
107
37.48
5.95
Emotional stability
107
32.75
8.15
Intellect
107
36.62
4.25
Health index
109
6.39
1.51
Self-esteem
107
31.88
4.54
Note: Valid N (listwise) = 100.
5.2.2 Frequencies
The data from the pilot study and from the main study was merged into one data
file. As a result, frequency analysis and the Principal Component Analysis included
data from 157 participants. Frequencies of reporting the items in the Perceived Age
Discrimination were recorded in order to identify the discriminatory behaviours that
occurred most frequently. Items with the highest frequencies are presented in Table 4.
29
Table 4. Most frequently reported types of discrimination.
Item no.
Situation
Frequency
(%)
Item 1
I was told a joke that pokes fun at older people.
70
Item 2
I was sent a birthday card that pokes fun at older people.
53
Item 31
When I went shopping for clothes, I felt that there is less
49
choice of clothes for people of my age, than there is for
younger people.
Item 4
Someone assumed that I could not remember well because of
43
my age.
Item 21
A doctor or nurse assumed my ailments were caused by my
42
age.
Item 8
Someone assumed I am not interested in certain activities,
42
because of my age.
The situations that were considered most discriminatory included “felt that there is
less choice of clothing for older people than there is for the younger people” (reported
as ‘very discriminatory’ by 21% of participants), “had to pay higher insurance rates
because I am older” (reported as ‘very discriminatory’ by 12% of participants), and
“doctor or nurse assumed my ailments were caused by my age” (reported as ‘very
discriminatory’ by 10% of participants). A full frequency analysis is presented in
Table 4, Appendix E.
5.2.3 Principal Components Analysis
5.2.3.1 Principal Components Analysis of the Perceived Age Discrimination Scale
Because the sample size was relatively small for a PCA, the Kaiser-Meyer-Olkin
measure of sampling adequacy was calculated, in order to assess whether PCA was an
appropriate technique to use. The value obtained was 0.781, which is considered
acceptable (Hutcheson and Sofroniou, 1999). Also Bartlett’s test of sphericity, which
tests the hypothesis that there is no relationship between the items, was significant,
indicating that there were significant relationships between the items, and so Principal
Components Analysis was appropriate.
30
The variables included in this PCA were the participants’ responses to the second
question of the Perceived Age Discrimination Scale, i.e. “Did you feel discriminated
when this happened?” Thus, participants who did not report experiencing a particular
situation would get a score of 0, and other participants had scores of either 1, 2, or 3.
By factor analysing answers to the second question only, I hoped to obtain
components which explain variance in perceived discrimination rather than
components which describe discriminatory behaviours.
First, a scree plot was made. Inspection of the scree plot (see Figure 1) shows a
break after the first factor and a further break after the fourth factor suggesting that the
first four factors were meaningful. However, when four factors were extracted, only 2
or 3 items loaded on the last two factors. If one factor was extracted, on the other
hand, several items would have to be dropped from the scale, because their loading on
the first factor did not exceed the pre-specified criterion of 0.4.
Figure 1. Scree plot of the PCA on the 32-item preliminary version of the Perceived Age
Discrimination Scale.
Scree Plot
10
Eigenvalue
8
6
4
2
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Component Number
Similar observations were made by inspecting eigenvalues: 10 components had
eigenvalues over 1, and the ten of them taken together accounted for 70% of the total
variance (see Appendix E, Table 1 for the percentage of total variance accounted for
by each of the components). However, the variance accounted for by the first
component was 25% of the total variance, but individual contributions of the other
components were not higher than 10%. Moreover, there were very few items loading
31
on components other than the first or second one (see Appendix E, Table 2). On the
basis of this information, only two components were extracted.
After inspecting the factor loadings (see Appendix E, Table 3), a theoretical basis
was found for the extraction of two components: the first component represented
general perceived discrimination, and the items which loaded on the second
component appeared to represent work/institution related discrimination. Principal
Components Analysis was repeated specifying two factors in order to identify items
that did not load above the criterion of 0.4 on either of the components. The two
components accounted for 34% of the total variance.
Items 2, 18, 25, 27, 29, 31, and 32 did not load above 0.4 on any of the two
factors. These items were subsequently dropped from the analysis, leaving 25 items in
the scale.
After removing these 7 items, the KMO statistic increased slightly to 0.816. A
Principal Components Analysis with 2 forced factors was then performed on the 25
remaining items. In order to make the interpretation of factors easier, the solution was
rotated and the factors were allowed to correlate using Oblimin rotation.
Extracting two factors resulted in a decrease in the values of communalities, and
none of them reached 0.6 (see Appendix F, Table 5). However, the two factors did
account for over 40% of the total variance in the 25-item scale (see Table 5).
Table 5. Percentage of variance in the 25-item scale
accounted for by the 2 factors.
Component
Initial Eigenvalues
Total
% of Variance
Cumulative %
1
7.71
30.84
30.84
2
2.51
10.03
40.87
The final rotated factor loadings are presented in Table 6. By examining the
loadings from the oblique rotation of the two components the items that loaded
uniquely on each were identified.
32
Component 1 had loadings on 18 items and accounted for 31% of the total
variance. The highest loading items included:

Someone assumed that I lack energy because of my age.

Someone assumed I could not understand because of my age.

Someone assumed that I could not remember well because of my age.
Because the first component had loadings on items that did not represent any
particular type or setting of discrimination, it was called General Discrimination. The
18 items loading on this component formed the General Discrimination subscale of
the Perceived Age Discrimination scale.
Component 2 had loadings on 7 items, and thus accounted for 10% of the total
variance. The items that loaded most highly on this component were:

I had difficulty getting a loan because of my age.

I was denied promotion because of my age.

I was forced to retire because of my age.
Because the items loading on this component were related to work or other
institutional settings, the second component was named Institutional Discrimination.
The 7 items loading on this component formed the Institutional Discrimination
subscale of the Perceived Age Discrimination scale.
Table 6. Rotated component matrix for the 25-item scale.
Item 1
I was told a joke that pokes fun at older people.
Item 3
Someone assumed that I am not physically fit
because of my age.
Someone assumed that I could not remember well
because of my age.
Someone assumed that I cannot hear well
because of my age.
Someone assumed I could not understand
because of my age.
People raised their voice and slowed down when
speaking to me, because of my age.
Someone assumed I am not interested in certain
activities, because of my age.
Someone assumed that, because of my age, I
must look in a certain way (e.g. wear glasses or
have grey hair).
Item 4
Item 5
Item 6
Item 7
Item 8
Item 9
Components
1
2
0.464
0.714
0.740
0.530
0.743
0.527
0.627
0.479
33
Item 10
0.649
Item 11
Someone made unpleasant remarks about my
age.
Someone assumed that I am ‘over the hill.’
Item 12
Someone said to me: “Aren’t you too old for that?”
0.603
Item 13
I was forced to retire because of my age.
0.641
Item 14
I was denied promotion because of my age.
0.668
Item 15
I had difficulty finding employment, because of my
age.
I was employed in a lower status job than I used
to, because of my age.
At work, my colleagues assumed that I couldn't
make enough contribution to the company,
because of my age.
I had difficulty getting a loan because of my age.
0.641
Item 16
Item 17
Item 19
Item 20
Item 21
Item 22
Item 23
Item 24
Item 26
Item 28
Item 30
A waiter or waitress ignored me because of my
age.
A doctor or nurse assumed my ailments were
caused by my age.
Someone assumed that I lack energy because of
my age.
Someone assumed that I am conservative in my
views because of my age.
Someone assumed that I lack ambition because of
my age.
Someone used patronizing language when
speaking to me, because of my age.
I was denied a position of leadership because of
my age.
I was treated with less dignity and respect because
of my age.
0.708
0.582
0.570
0.676
0.400
0.508
0.766
0.690
0.588
0.576
0.632
0.427
Note: Items belonging to the institutional subscale in italics.
5.2.3.1.1 Internal consistency of items in the Perceived Age Discrimination scale
Internal consistency was computed both for the entire scale, and for the two
subscales. For the entire scale, Cronbach’s alpha was equal to 0.901, for the general
subscale it was also 0.901, and for the institutional subscale 0.771. All values were
relatively close to one, and thus strongly suggested that the scale is internally
consistent.
34
5.2.3.1.2 Analysis of the dropped items
After performing the PCA, the list of items that remained in the scale was
compared with the frequency tables. Three items that had relatively high rates of
occurring (i.e. more than 20% participants indicated that they have experienced a
given situation) did not load on any of the two factors, and were therefore excluded
from the scale:

I was sent a birthday card that pokes fun at older people (reported by 70% of
participants).

I had to pay higher insurance rates because of my age (reported by 31% of
participants).

When I went shopping for clothes, I felt that there is less choice of clothes for
people of my age, than there is for younger people (reported by almost 50% of
participants).
The reason why these items, although frequently reported, did not load on any of
the factors, could be that these items are different in nature from the others: they do
not reflect the views of any particular person, or they are not related to any particular
institution (as the work-related items are), but they seem to reflect views present in the
society as a whole that find their way to everyday culture. For instance, the societal
stereotype that older people do not pay much attention to clothing can be reflected in
there not being a wide variety of clothing options available. Bearing in mind that
those items could perhaps form a separate factor if a larger sample was studied, I
would advise any researchers who may want to use this scale to keep these items in
the questionnaire, and only decide whether they should remain or be dropped after
performing a Principal Components Analysis of their own data. For the purpose of
this study, though, I decided to drop those items from further analysis.
5.2.3.2 Principal Components Analysis of the Positive Experience of Ageing Scale
This Positive Experience of Ageing scale consisted of 9 items which were created
based on information obtained in the interviews, and included any positive aspects of
being older that were brought up by the participants. A PCA was performed on the
scores to detect potential patterns in the data. It was expected that if the scale
35
measures the overall positive experience of ageing, all items would load highly on a
single factor.
Before looking at the extracted factors, the data’s suitability for Principal
Components Analysis was examined. Two methods were used: inspecting the KaiserMeyer-Olkin measure of sampling adequacy, and examining the communalities, i.e.
the proportion of variance shared between the items. The KMO statistic of this dataset
was 0.577, which is mediocre according to Kaiser (1974), and indicates that Principal
Components Analysis may not be the most appropriate technique in this case. Indeed,
with 9 items it may be difficult to detect any patterns. The communalities were also
relatively low, with only three of them above 0.6 (see Appendix G, Table 6).
Nevertheless, the Principal Components Analysis was performed. Inspection of
the eigenvalues (see Appendix G, Table 7) and the Scree plot (see Appendix G,
Figure 1) suggested extraction of 3 factors. The unrotated component matrix (see
Appendix G, Table 8) was then inspected, showing that the factors did have a simple
structure. Next, an oblique (Oblimin) rotation was performed, but because the
intercorrelations between factors were low (-0.075, -0.048, and -0.168), Varimax
rotation was chosen as a more appropriate method. Factor loadings after the Varimax
rotation are presented in Table 7.
After rotating the factors, only three items loaded on the second factor, and only
two loaded on the third factor. With such a small number of items loading on the
factors, it would be difficult to interpret the factors, and also the scale would be
unlikely to be internally consistent.
36
Table 7. Rotated component matrix
of the Positive Experience of Ageing scale.
Components
1
2
Item 1
3
0.639
Item 2
0.776
Item 3
0.656
Item 4
0.594
Item 5
0.926
Item 6
0.924
Item 7
0.511
Item 8
0.448
Item 9
0.746
Note. Rotation performed: Varimax with Kaiser normalisation.
In order to further examine the internal consistency reliability of the scale, the
Cronbach’s Alpha was computed, and was found to be 0.531. In light of this low
value and a small number of items loading into each factor in the Principal
Components Analysis, the scale was considered unreliable, and this data was not
analysed further. Nevertheless, because there are a number of positive aspects of
growing older that people consistently report, it would be recommended for
researchers to develop this scale further by adding more items and administering it to
a larger group of participants.
5.2.4 Revised Perceived Discrimination Scale
In further analysis, three scales measuring perceived age discrimination were
used. Firstly, the adapted Perceived Age Discrimination scale, consisting of 25 items,
gave scores between 0 and 75. Higher scores on this scale indicated higher overall
perceived discrimination. Secondly, the scale could be divided into two subscales: the
General Discrimination scale, measuring the experience of discrimination not linked
to any specific setting, consisted of 18 items and was scored between 0 and 54; and
the Institutional Discrimination subscale consisted of 7 items referring to the
experience of discrimination related to work and other institutional settings, and gave
37
scores between 0 and 21. On both subscales, higher scores indicated that a person
perceived more age discrimination in his or her life. Initially, scores on the two
subscales were computed and used in the analysis, as they provided more specific
information about the type of discrimination experienced.
5.2.5 Consideration of Parametric Assumptions
Field (2005) speaks of four assumptions that need to be met in order for
parametric tests’ outcomes to be meaningful: normal distribution of data, interval
data, independence of the observations, and homogeneity of variance. The first three
assumptions were tested before performing the regression analyses. The assumption
of homogeneity of variance was tested after performing the analysis, and is reported
in section 5.2.7.6.
Normal distribution of the data was examined in two ways: by inspecting the
histograms of all the variables, and by computing the Kolmogorov-Smirnov and
Shapiro-Wilk tests of normality. The variables whose distribution was most severely
skewed was Total Discrimination, General Discrimination, and Institutional
Discrimination. This was not surprising, bearing in mind that most instances of
discrimination were reported by a minority of the participants only.
The Institutional subscale had the most skewed distribution and had to be dropped
from further analysis. Because scores on the General Discrimination subscale and the
entire Perceived Age Discrimination scale were highly correlated (r > 0.9), only the
score on the entire scale was used. In order to further normalize its distribution, all
questionnaires with scores of 0 on the Perceived Age Discrimination scale were
discarded (valid N = 93), and the fourth root was taken of the total Perceived Age
Discrimination score. Table 8 compares results on the normality tests between the
Total Discrimination score, and its 4th root, both after excluding cases with a score of
0. There is a clear improvement in the values of the normality statistics, suggesting
that taking the fourth root of the Total Discrimination score improves the distribution
of that variable. In all further analysis, the label ‘Total Discrimination’ will be used to
denote the fourth root of the score on the Perceived Age Discrimination scale.
38
Table 8. Comparison of the normality tests for Total Discrimination
and its 4th root.
Tests of Normality
Kolmogorov-Smirnov(a)
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
Total Discrimination
0.205
99
0.000
0.765
99
0.000
4th root of Tot. Disc.
0.092
99
0.039
0.956
99
0.002
A number of other variables also had skewed distributions, but the deviations from
normality were not very severe. Basing on the finding that multiple regression is
robust to deviations from normality (Box & Watson, 1962), the analysis was
performed without any further transformations.
All variables in the study were measured on interval scales, and all observations
were independent.
5.2.6 Correlations
Before fitting any models into the data, a series of correlations was computed in
order to find any significant relationships between the predictor and outcome
variables (see Table 9).
39
Table 9. Intercorrelations between the predictor and outcome variables.
Correlations
Physical
Psychological
Social
Environment
Health
health
health
relationships
Gender
-0.098
-0.041
-0.183
-0.115
-0.110
Age
0.083
0.205*
0.323**
0.215*
0.025
Extraversion
0.031
0.340**
0.190
0.019
0.060
Agreeableness
0.284**
0.346**
0.233*
0.184
0.343**
Conscientiousness
0.307**
0.220*
0.006
0.080
0.267*
Emotional stability
0.335**
0.592**
0.337**
0.189
0.214*
Intellect
0.028
0.218*
0.091
0.077
0.073
Self-esteem
0.405**
0.693**
0.464**
0.517**
0.299**
Total discrimination
-0.156
-0.096
-0.283**
-0.282**
-0.043
Index
Note: N = 93. ** Correlation significant at the 0.01 level. * Correlation significant at the 0.05 level.
As expected, the Big Five personality traits correlated significantly with quality of
life. In particular, emotional stability and self-esteem correlated with all four quality
of life domains, and also with the health index. Correlations that came out significant
are explored further, after controlling for other factors, in the regression analysis.
Other correlations that were looked at included correlations between gender and
personality, and between personality and perceived age discrimination.
There was a significant gender difference in Agreeableness, with men scoring
lower on that trait than women t (104) = 2.93, p < 0.01, which represented a medium
sized effect r = 0.28, but there was no significant gender difference on any other Big
Five trait. This may be due to the fact that the sample in this study consisted in 74% of
women, and thus did not have a fair gender representation.
None of the Big Five personality traits correlated significantly with the perceived
age discrimination score. The only personality variable whose correlation coefficient
came close to significance was self-esteem, with r = -.193, p > .05, which shows that
40
individuals with higher self-esteem tended to report less perceived age discrimination
than those with lower self-esteem.
The four domains of quality of life were all highly intercorrelated, with the r
coefficient between 0.471 and 0.680.
Because of performing a large number of univariate correlations, the number of
correlations that were significant at the 0.05 level was relatively high, and some of
them could have been falsely flagged as significant (Type I error). This is not a major
problem in this analysis, because the main goal of performing the univariate
correlations was to look for patterns in the data and inform the regression analyses,
rather than look for significant relationships. However, in order to partially alleviate
this problem, in finding variables to be included in the regressions, a cut-off point of
0.2 for the correlation coefficient was used instead of the 0.05 significance criterion.
Thus, predictors whose correlations with the outcome variables were above 0.2 will
be included in the regression analyses.
Regression was performed for the whole sample, without splitting it to gender
groups. There were two main reasons for this. First, the only variable that
significantly correlated with gender was Agreeableness, and second, because of the
small number of males in the sample (N = 28), the regression analyses would not have
enough power to detect any effects.
5.2.7 Regression analyses
5.2.7.1 Power estimation
Before performing the regression analysis, an estimate of the power available for
detecting a medium effect size was made. The maximum number of predictors for a
given outcome variable was 7 (seven variables correlated significantly with the
psychological health quality). According to Cohen (1992), the number of participants
needed to detect a medium effect size in a multiple regression analysis with 7
predictors at power equal to 0.8 is 102. The actual number of participants whose data
was analysed in multiple regressions was 93 and thus, the regressions with 6 or 7
predictors are slightly underpowered. This should be taken into consideration when
interpreting the results.
41
5.2.7.1 Regression 1: Predicting physical health
Only conscientiousness and self-esteem were significant predictors of physical
health, and the regression model explained 27% of variance in the outcome variable
(see Table 10 for model coefficients). Contrary to this study’s hypothesis, perceived
age discrimination was not a significant independent predictor of physical health
quality.
Table 10. Regression model of physical health.
Coefficients
B
Std. Error
Beta
(Constant)
-0.671
5.320
Agreeableness
0.163
0.103
0.151
Conscientiousness
0.203
0.083
0.230*
Emotional Stability
0.081
0.071
0.127
Self-esteem
0.330
0.134
0.276*
Note R2 = 0.27. * p < 0.05.
5.2.7.2 Regression 2: Predicting psychological health
Table 11. Regression model of psychological health.
Coefficients
B
Std. Error
Beta
(Constant)
-6.467
3.433
Agreeableness
0.063
0.046
0.098
Conscientiousness
0.080
0.037
0.152*
Emotional stability
0.107
0.032
0.282**
Extraversion
0.024
0.031
0.055
Intellect
0.176
0.049
0.244**
Self-esteem
0.333
0.058
0.469**
Age
0.029
0.029
0.325
Note: R2 = 0.65. * p < 0.05. ** p < 0.01.
Here, the model explained 65% of variance in psychological health, and the
significant predictors were, in descending order of importance, self-esteem, emotional
stability, intellect, and conscientiousness (see Table 11). This finding is in line with
42
previous research (see for example DeNeve & Cooper, 1998), where personality has
been shown to predict subjective well-being. Again, perceived age discrimination did
not account for a significant portion of variance in psychological health.
5.2.7.3 Regression 3: predicting social relationships
Table 12. Regression model of social relationships.
Coefficients
B
Std. Error
(Constant)
-2.187
3.011
Emotional stability
0.012
0.033
0.039
Agreeableness
0.089
0.045
0.175
Self-esteem
0.177
0.061
0.314**
Age
0.086
0.030
0.266**
-1.443
0.512
-0.248**
Total discrimination
Beta
2
Note R = 0.36. ** p < 0.01.
Significant predictors of social relationships were, in order of significance, selfesteem, age, and general discrimination (see Table 12). Somewhat surprisingly, older
people reported better satisfaction with their social relationships than younger
participants. An explanation could be that when people are retired for a longer time,
they learn how to organize their social life outside the framework of work- for
example, they may join activity groups or other clubs, and socialize there. Indeed, a
study of American nurses found that women over 60 years old were more likely to
participate in religious and voluntary group activities than women under 60 (Michael,
Colditz, Coakley, & Kawachi, 1999). Another explanation could be that as people
grow older, they receive more social support than they used to, because their families
and friends perceive older people as particularly vulnerable and deserving special
care.
43
5.2.7.4 Regression 4: predicting quality of the environment
Table 13. Regression model of the quality of environment
Coefficients
B
Std. Error
Beta
(Constant)
16.189
4.581
Age
0.081
0.054
0.133
Self-esteem
0.487
0.095
0.458**
Total discrimination
-2.414
0.973
-0.217*
Note: R2 = 0.33. * p < 0.05. ** p < 0.01.
As expected, perceived age discrimination had a significant negative impact on
the participants’ satisfaction with the quality of their environment (see Table 13). This
relationship can be explained by the fact that this domain of quality of life includes
questions about the outside world: the quality of healthcare, transport, access to
leisure activities. Thus, individuals who felt discriminated against in those areas of
life were also likely to report lower satisfaction when responding to those questions.
As for the significant relationship between self-esteem and quality of the
environment, it could be that people who are more satisfied with themselves are also
more satisfied with their environments. That would mean that self-esteem is not
related to the quality of environment as such, but rather to the perception if that
quality. Another explanation could be that self-esteem affects the quality of the
environment itself- the assumption being that people with higher self-esteem earn
more, can afford better healthcare and transport options, etc.
Because of the correlational design of this study, the possibility that it is the
quality of environment that affects self-esteem and perceived discrimination cannot be
excluded. Indeed, especially with regard to perceived discrimination, perhaps people
whose quality of the environment is poor (e.g. they lack financial resources) are more
discriminated against within the society than those whose quality of life is better.
44
5.2.7.5 Regression 5: predicting the health index
Table 14. Regression model of the health index.
Coefficients
B
Std. Error
Beta
(Constant)
-1.145
1.579
Agreeableness
0.078
0.031
0.250*
Conscientiousness
0.047
0.025
0.185
Emotional stability
0.007
0.021
0.036
Self-esteem
0.070
0.040
0.204
Note: R2 = 0.21. * p < 0.05.
The only significant predictor of the health index, after controlling for other
variables, is Agreeableness (see Table 14 for the regression coefficients). It seems
possible that Agreeableness is not related to health itself, but rather to the manner of
reporting it, so that people who are more agreeable tend to report better health
regardless of their objective health status. Further implications of this finding will be
presented in the discussion section.
It is also important to note that predictors of self-reported health are different than
the predictors of the quality of physical health. It suggests that the psychological
processes involved in assessing one’s health are different from those involved in
judging whether somebody is satisfied with their health.
5.2.7.6 Generalizability of the models
In order to decide whether five regression models presented above are
generalizable to the population, a series of assumptions was assessed. First, the
assumption of no multicollinearity was tested. Inspection of correlations between
predictor variables showed that there were no correlations higher than 0.8, which,
according to Field (2005), would be a cause for concern. Additionally, the variance
inflation factor (VIF), which is one of the multicollinearity diagnostics provided by
SPSS, provided values between 1.0 and 1.7, which is well below the value of 10 that,
according to Myers (1990), would indicate a serious violation of the assumption of no
multicollinearity.
45
Second, the assumption of independent errors was tested using the Durbin-Watson
statistic. For all regression models, value of the Durbin-Watson statistic was between
1.7 and 2.2. Thus, as for all models this statistic was relatively close to 2, the
assumption of independent errors has been met (Field, 2005).
Third, in order to assess the assumptions of linearity and homoscedasticity, a plot
of the standardized residuals against the standardized predicted values was created for
each model (results not presented). In each model, points of the scatterplot were
randomly and evenly dispersed, indicating that these two assumptions have been met
(Field, 2005).
Finally, normality of residuals was assessed by inspecting histograms and normal
probability plots of residuals in each of the five models. In each case, residuals were
roughly normally distributed.
The regression models of quality of life and self-reported health meet the
necessary assumptions, and can therefore be generalized to the population of older
adults.
6. Discussion
Perceived Age Discrimination scale, consisting of 25 items, was piloted and
subsequently employed in the current investigation. The scale had sufficient internal
consistency reliability and predictive validity to be used in research on age
discrimination. Perceived age discrimination was found to negatively affect two
domains of quality of life: social relationships and environment. It showed, however,
no association with the other two domains of quality of life or with self-reported
health. Third, perceived age discrimination was not significantly associated with any
of the Big Five personality traits. Though, there was a marginally significant
correlation between self-esteem and the perception of age discrimination.
In addition to the primary concerns of this study, several important findings
emerged in the statistical analyses. There were no age and gender differences in
perceived age discrimination. Conscientiousness and agreeableness were the main
predictors of health-related quality of life and self-reported health, whereas emotional
stability was only significant in the univariate correlations. Finally, there was a
significant difference between men and women in agreeableness, but no gender
difference in emotional stability or the other Big Five personality traits.
46
6.1 Perceived Age Discrimination scale
The Perceived Age Discrimination scale was shown to have satisfactory levels of
validity and reliability. Discriminatory behaviours presented in the scale belong to
either of two domains, or factors: general discrimination and institutional/workrelated discrimination. The institutional/work-related domain included discriminatory
behaviours that either occurred at work (e.g. being denied promotion), or were related
to another institutional setting (e.g. having difficulty getting a loan). The general
discrimination domain included instances of stereotypes and discriminatory
behaviours that occurred in all other contexts: in the family, community, healthcare,
etc.
After validating the scale in a sample of 160 people, it seems that majority of
older people in Scotland have experienced at least one instance of discrimination or
stereotyping. Many potentially discriminatory events, however, were not interpreted
as discriminatory. For example, having been told a joke that pokes fun at older people,
although reported very frequently, often was not perceived as an instance of
discrimination. It seems that Perceived Age Discrimination scale is an extension and
improvement of Palmore’s (2001) Ageism Survey, because it allows distinguishing a
mere experience of an event from its classification as discriminatory. It is possible
that only experiences perceived as discriminatory influence people’s health and
quality of life.
6.2 Perceived age discrimination, self-reported health and quality of life
The perception of discrimination negatively affected quality of life in two
domains: social relationships and environment, but did not influence the quality of
physical and psychological health. It was also not associated with poorer self-reported
health.
This pattern of associations suggests that perceived age discrimination influenced
quality of life in those domains that were most directly affected by it. For instance,
being discriminated against by a doctor because of one’s age may lead directly to a
lower perceived quality of healthcare. The relationship between perceived age
discrimination and health-related quality of life or self-reported health is much less
47
direct. One model suggests that prejudice causes stress, and excessive stress increases
the likelihood of both physical and psychological health problems (Meyer, 2003b). It
is well-known, however, that stress does not directly cause illness, and that a number
of psychological variables, such as social support or coping, moderate the stressillness relationship (Steptoe, 1991). Therefore, even though older people experience
and perceive discrimination against them, they may have the appropriate personal
resources to successfully cope with that stressor, and prevent it from affecting their
health.
Alternatively, one can reverse the causal relationship and conclude that different
levels of quality of life make people go through different amounts of discrimination,
and also perceive it differently. Thus, it is possible that people in more disadvantaged
environments, or those with less social support available, are more likely to encounter
age discrimination in the first place, and are also more likely to be negatively affected
by it. This relationship may not be as pronounced in case of physical and
psychological health differences. Independent of their health quality, people often
engage in the same social interactions, and may perceive situations similarly.
6.3 Personality and perceived age discrimination
Contrary to this study’s hypothesis, personality traits were not associated with
perceived age discrimination. One reason for this finding may be that the score on the
Perceived Age Discrimination scale is a reflection of the amount of discrimination
experienced by a person, and does not depend on personality variables. Thus, it could
suggest that the differences in the Perceived Age Discrimination scores are
differences in the discrimination experienced, and not merely differences in
perception.
However, previous research has shown that perceived discrimination is
significantly correlated with personality variables other than the Big Five. For
example, Kobrynowicz and Branscombe (1997) found an association between
perceived gender discrimination, self-esteem and need for approval. Although these
variables share variance with personality traits (Watson, Suls, & Haig, 2002; Dunkley,
Sanislow, Grilo, & McGlashan, 2004), they are conceptualized as distinct and more
specific than the Big Five. In the present study, perceived age discrimination was
marginally negatively correlated with self-esteem, which suggests that individual
48
differences variables other than personality traits may influence the perception of
discrimination.
6.4 Age and gender differences in perceived age discrimination
The hypothesis about age and gender differences in the perception of age
discrimination was not supported: perceived age discrimination did not depend on
gender and age. In interpreting this result, one should consider that although the
experience of age discrimination of men and women, or older and younger people,
may be qualitatively different, it is likely that these differences did not show in a
quantitative index, such as the Perceived Age Discrimination scale. A thorough
analysis of specific answer patterns for each of the groups in question will be needed
in order to clarify aspects of age or gender differences.
6.5 Personality and health outcomes
There are only few papers examined the relationship between all Big Five traits
and health outcomes (e.g. Jerram & Coleman, 1999). Most investigations focused
exclusively on neuroticism and extraversion (e.g. Williams et al., 2004). However, the
studies that looked at agreeableness and conscientiousness in relation to health, did
find a significant association. Agreeableness has been shown to influence a number of
medical outcomes, such as perceived general health and vitality, especially in women
(Jerram & Coleman, 1999). Moreover, it is related to better health behaviour (BoothKewley & Vickers, 1994). Apart from its actual association with health,
Agreeableness also influences how people report their health. For example, Jerram
and Coleman (1999) suggested that agreeable women attempt to have a positive
outlook on life and avoid health complaints. Thus, they are likely to report fewer
medical problems and make less frequent visits to the GP.
Conscientiousness is also a predictor of health behaviours (Booth-Kewley &
Vickers, 1994). Perhaps conscientious older people take better care of themselves, and
thus have better health. Interestingly, conscientiousness has been shown to be a
significant predictor of health outcomes predominantly among men (Jerram &
Coleman, 1999; Artistico, Baldassarri, Lauriola, & Laicardi, 2000). The significant
link between conscientiousness and quality of physical health in this, predominantly
49
female sample, is an extension of the previous findings, and suggests that the effect of
conscientiousness on health is not yet fully understood.
The reason why emotional stability did not predict better self-reported health in
the multivariate analysis remains unclear. Most previous studies did show a
relationship between neuroticism/emotional instability and self-reported health (Smith
& Williams, 1992; Goodwin & Engstrom, 2002), and Duberstein and colleagues
(2003) noted that this relationship becomes even more pronounced in older age.
However, in the studies that looked only at neuroticism and extraversion, the effects
of conscientiousness and agreeableness are not controlled for. Therefore, the exact
pattern of relationships between the Big Five personality traits and health outcomes is
not entirely clear.
On the whole, this study offers support to Booth-Kewley and Vickers’ (1994)
observation that agreeableness and conscientiousness are significant predictors of
health outcomes, and that they have been unjustly neglected in recent research on
personality predictors of health.
6.6 Gender differences in personality
In line with previous research (see for example Costa, Terracciano, & McCrae,
2001, for a meta-analysis; or Chapman, Duberstein, Sörensen, & Lyness, 2007, for a
study of an elderly sample), men who participated in this study scored lower on
agreeableness than women. The lack of significant gender differences in emotional
stability, however, contradicted previous findings (Costa et al., 2001; Chapman et al.,
2007). This may be due to the uneven gender distribution of this sample, or to the fact
that participants in this study were on average more emotionally stable than the
general population. A comparison of means and standard deviations of the Big Five
personality traits in this sample and the Scottish validation sample (Gow, Whiteman,
Pattie, & Deary, 2005) shows that the average scores on all five personality traits were
substantially higher in this group than in the validation sample.
6.7 Interpretation of the findings
Predictors of quality of life show an interesting pattern. The Big Five personality
traits predicted the quality of physical and psychological health, whereas perceived
50
age discrimination was associated with the quality of social relationship and
environment. This suggests that health is largely affected by a person’s internal
resources, such as personality, whereas the quality of social relationships and
environment depends more on how a person functions in the social world.
Although it has been found that social functioning, including the experience of
discrimination, may affect physical and psychological health (for reviews see Krieger,
2000; Williams, Beighbors, & Jackson, 2003; Meyer, 2003a; and Paradies, 2006),
there are studies showing that it is not always the case. Some members of
disadvantaged groups manage to sustain high levels of self-esteem and psychological
well-being, even though they are being discriminated against (see for example Frable,
Wortman, & Joseph, 1997).
Two models have been proposed to explain the coping strategies used by members
of underprivileged groups to cope with the stress caused discrimination. The
rejection-identification model (Branscombe, Schmitt, & Harvey, 1999) proposes that
being rejected by the dominant group leads to greater identification with one’s own,
disadvantaged group. The increase in identification leads to improved psychological
well-being, and that can partially or completely alleviate the negative effect of
discrimination on well-being. Evidence to support this model has been found among
African Americans (Branscombe et al., 1999), and among older people (Garstka et al.,
2004).
The balanced identity model suggests that older individuals successfully cope with
ageing and age discrimination by using two mechanisms: identity assimilation and
identity accommodation (Whitbourne & Sneed, 2004). In the process of growing
older, people often lose certain skills or abilities, and some of those may have been
central to their identities. Successful ageing often amounts to being able to distinguish
between things that can be changed (such as a decrease in fitness, which can be
reduced by taking up exercise), and those that cannot be altered and should therefore
be accepted (for example, not being able to lift very heavy objects). Thus, older
people have to find a balance between assimilating the changes into their identity, or
accommodating to them.
The present study does not provide direct evidence to support any of these models,
but the lack of relationship between age discrimination of physical and psychological
health strongly suggests that some protective mechanism helps older people to cope
with discrimination.
51
6.8 Limitations of the present study
Although the present study provided new insights into the nature and
consequences of perceived age discrimination, it has a few limitations. First, because
of controlling for a relatively large number of variables, some of the analyses were
slightly underpowered, and their results should thus be interpreted with caution.
Moreover, gender distribution was highly skewed towards females and did not allow
performing separate analysis for males and females. The age group of 55-65 years
was underrepresented, which may have resulted in lower reporting of work-related
discrimination and perhaps also other types of discrimination.
The study did not control for social class and education, which have been shown
to influence perceived discrimination (Pavalko, Mossakowski, & Hamilton, 2003).
Also, age-group identification, which has been shown to partially alleviate the
negative effect of perceived discrimination on well-being, was not examined.
Finally, a self-reported index of health was used, which may have led to a
reporting bias. I believe, however, that self-reported health, because of its subjective
nature, may be more influenced by the experience of discrimination than objective
health status. Therefore, if self-reported health was not influenced by perceived
discrimination, it is unlikely that objective health would be.
6.9 Suggestions for further research
The Perceived Age Discrimination scale should be administered to a larger,
younger, and more gender-balanced sample to allow further examination of its
validity and reliability. Also, further work is needed to improve the psychometric
qualities of the Positive Experience of Ageing scale. The positive aspects of growing
older have been somewhat neglected by researchers, who tend to focus on negative
outcomes. Therefore, it has been interesting to see that older people do see a number
of advantages of their age, and it would be worthwhile to further explore that field.
Assessment of the effects of perceived age discrimination and its relation to
personality traits has only been started in this study. Further research is needed to
confirm whether the experience of discrimination truly does not influence physical
52
and psychological health and, if so, what are the mechanisms that allow older people
to ward off the potentially stressful impact of discrimination.
Ideally, a longitudinal research design should be employed to examine the
influence of perceived discrimination on physical and psychological health of older
adults, after controlling for health in younger age. It may be that the experience of
discrimination makes successful ageing more difficult, and that the process could be
observed in longitudinal design.
53
7. Conclusions
To the author’s knowledge, this is the first study that looked at perceived age
discrimination in the broad context of personality, health and quality of life. This
comprehensive approach allowed making inferences about the personal characteristics
that moderate older people’s perception of discrimination against them, and about the
consequences that perceived age discrimination has on people’s lives. The lack of
relationship between personality and perceived age discrimination, together with
reports of discriminatory practices in a variety of settings, proves that age
discrimination is a real and relatively widespread social phenomenon. The finding that
perceived age discrimination lowers quality of life is yet another argument in favour
of introducing policies and campaigns aimed at reducing age discrimination. The
author hopes that the scale developed in this study will help generate more research
on this topic and that findings of the multivariate analyses will be replicated and
extended by future studies.
54
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59
Appendices
Appendix A. Schedule of the semi-structured interviews.
Introductory question: tell us your name and what you do (occupation).
Do you think age discrimination is a serious problem nowadays?
What is the age group concerned?
What are the areas of life in which age discrimination may take place?
Examples: work, shops, community activities, travel agencies, hotels,
healthcare, etc.
What are the examples of things that you would consider age discrimination?
Examples from Palmore (2001):








Being told a joke that pokes fun at old people
Being ignored or not taken seriously
Being patronized
Being refused rental housing
Having a difficulty with getting a loan
Being denied medical treatment
Being denied promotion
Somebody assuming that I couldn’t hear or understand well because of my age
Can you think of any other examples of age discrimination?
Attitudes that people have (e.g. patronizing)
Stereotypes (older people aren’t competent, etc.)
Specific discriminatory behaviours
Do you think age discrimination is harmful to the people who experience it? What
could the negative consequences be?
Examples:
 poorer health because of discrimination in health services
 fewer opportunities to engage in activities, because they are aimed at younger
people
Are some people more likely to feel discriminated against, even if they are not really
discriminated more than others?
Is it because they are more sensitive, or is there another reason?
What could help people not to suffer so much because of the perceived
discrimination?
Would having a lot of support from friends and family help? What else could help?
60
Would you say that there are some gender differences in the experience of
discrimination?
Would you say that ageing is more difficult for women than it is for men?
Are there any advantages to being older (e.g. you get a seat in the bus)?
Are there any other issues associated with age discrimination that you think are
important?
61
Appendix B. Pilot version of the Perceived Age Discrimination scale.
In this questionnaire, you will read a number of descriptions of situations. Please
indicate in the column next to each situation how often it has happened to you: Never
= 0, Once = 1, More than once = 2. Then, please also indicate whether, as a result of
that situation, you felt discriminated against because of your age. Please give your
answers on a scale between 1 and 5, where 1 means that you did not feel
discriminated with respect to age, and 5 means that you felt very much discriminated
against, on the basis of your age. If the situation did not occur, please enter 0.
Situation
1
I was told a joke that pokes fun at older people.
2
I was sent a birthday card that pokes fun at older people.
3
10
Someone assumed that I am not physically fit because of
my age.
Someone assumed that I could not remember well
because of my age.
Someone assumed that I cannot hear well because of my
age.
Someone assumed I could not understand because of my
age.
People raised their voice and slowed down when
speaking to me, because of my age.
Someone assumed I am not interested in certain activities,
because of my age.
Someone assumed that, because of my age, I must look in
a certain way (e.g. wear glasses or have gray hair).
Someone made unpleasant remarks about my age.
11
Someone assumed that I am ‘over the hill.’
12
Someone said to me: “Aren’t you too old for that?”
13
I was forced to retire because of my age.
14
I was denied promotion because of my age.
4
5
6
7
8
9
Has it ever
happened to
you?
0- never
1- once
2- more
than once
Did you feel
discriminated
against when this
happened?
0- did not happen
1- not at all
3- it depends on
the circumstances
5- very much
62
Situation
15
I had difficulty finding employment, because of my age.
16
18
I was employed in a lower status job than I used to,
because of my age.
At work, my colleagues assumed that I couldn’t make
enough contribution to the company, because of my age.
I had to pay higher insurance rates because of my age.
19
I was refused rental housing because of my age.
20
I had difficulty getting a loan because of my age.
21
22
A waiter or waitress ignored me because of my age.
A doctor or nurse assumed my ailments were caused by
my age.
I was denied medical treatment because of my age.
Someone assumed that I lack energy because of my age.
17
23
24
25
26
27
28
29
30
31
32
33
34
35
Has it ever
happened to
you?
0- never
1- once
2- more
than once
Did you feel
discriminated
against when this
happened?
0- did not happen
1- not at all
3- it depends on
the circumstances
5- very much
Someone assumed that I am conservative in my views
because of my age.
Someone assumed that I lack ambition because of my
age.
I was denied access to some facilities, because of my age.
Someone used patronizing language when speaking to
me, because of my age.
I was called an insulting name relating to my age.
I was denied a position of leadership because of my age.
I was rejected as unattractive because of my age.
I was treated with less dignity and respect because of my
age.
When I went shopping for clothes, I felt that there is less
choice of clothes for people of my age, than there is for
younger people.
My house was vandalized because of my age.
I was victimized by a criminal because of my age.
Note: Items that remained in the final version of the scale are marked in grey.
63
Appendix C. Final version of the Perceived Age Discrimination scale.
In this questionnaire, you will read a number of descriptions of situations. Please
indicate in the column next to each situation how often it has happened to you: Never
= 0, Once = 1, More than once = 2. Then, please also indicate whether, as a result of
that situation, you felt discriminated against because of your age. Please give your
answers on a scale between 1 and 3, where 1 means that you did not feel
discriminated with respect to age, and 3 means that you felt very much discriminated
against, on the basis of your age.
Situation
Has it ever
happened to
you?
0- never
1- once
2- more than
once
Did you feel
discriminated
against when
this happened?
0- did not
happen
1- not at all
2- somewhat
3-very much
1 I was told a joke that pokes fun at older people.
2 Someone
1
assumed that I am not physically fit because of
my age.
3 Someone
2
assumed that I could not remember well
because of my age.
4 Someone
3
assumed that I cannot hear well because of my
age.
5 Someone
1
assumed I could not understand because of my
age.
6 People raised their voice and slowed down when
speaking to me, because of my age.
7 Someone assumed I am not interested in certain
activities, because of my age.
8 Someone assumed that, because of my age, I must look
in a certain way (e.g. wear glasses or have gray hair).
9 Someone made unpleasant remarks about my age.
10 Someone assumed that I am ‘over the hill.’
11 Someone
1
said to me: “Aren’t you too old for that?”
12 I1was forced to retire because of my age.
13 I1was denied promotion because of my age.
14 I had difficulty finding employment, because of my age.
15 I was employed in a lower status job than I used to,
because of my age.
64
Situation
Has it ever
happened to
you?
0- never
1- once
2- more than
once
Did you feel
discriminated
against when
this happened?
0- did not
happen
1- not at all
2- somewhat
3- very much
16 At work, my colleagues assumed that I couldn’t make
enough contribution to the company, because of my age.
17 I had difficulty getting a loan because of my age.
18 A
1 waiter or waitress ignored me because of my age.
19 A
1 doctor or nurse assumed my ailments were caused by
my age.
20 Someone
1
assumed that I lack energy because of my age.
21 Someone
1
assumed that I am conservative in my views
because of my age.
22 Someone
1
assumed that I lack ambition because of my
age.
23 Someone
1
used patronizing language when speaking to
me, because of my age.
24 I1was denied a position of leadership because of my age.
25 I1was treated with less dignity and respect because of my
age.
65
Appendix D. Positive Experience of Ageing scale
Please indicate to what extent you agree or disagree with the following statements:
1. Because I am older, I have a better understanding of what is really important in life.
strongly agree
agree
neither agree
nor disagree
disagree
strongly
disagree
disagree
strongly
disagree
disagree
strongly
disagree
disagree
strongly
disagree
2. Because I am older, people respect me less.
strongly agree
agree
neither agree
nor disagree
3. Because I am older, people come to me for advice.
strongly agree
agree
neither agree
nor disagree
4. Because I am older, I have less self-confidence.
strongly agree
agree
neither agree
nor disagree
5. I think getting a bus pass is a great advantage of being older.
strongly agree
agree
neither agree
nor disagree
disagree
strongly
disagree
6. I think having concession rates for various activities is a great advantage of being
older.
strongly agree
agree
neither agree
nor disagree
disagree
strongly
disagree
7. I think being a grandparent is a great advantage of being older.
strongly agree
agree
neither agree
nor disagree
disagree
strongly
disagree
8. I think having more time to spend on my hobbies and interests is a great advantage
of being older.
strongly agree
agree
neither agree
nor disagree
disagree
strongly
disagree
disagree
strongly
disagree
9. Being older does not make you wiser.
strongly agree
agree
neither agree
nor disagree
66
Appendix E. Additional tables for the 32-item pilot scale
Table 1. Total variance in the 32-item pilot scale
explained by 10 factors.
Component
Total
8.15
2.64
2.24
1.92
1.47
1.34
1.29
1.16
1.12
1.04
1
2
3
4
5
6
7
8
9
10
Initial Eigenvalues
% of Variance
Cumulative %
25.48
25.48
8.24
33.72
6.99
40.71
6.00
46.71
4.59
51.30
4.18
55.48
4.04
59.52
3.62
63.14
3.49
66.63
3.24
69.87
Table 2. Factor loadings for the 10 extracted components in the 32-item pilot scale.
Item
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
1
0.510
2
3
4
Component
5
6
7
8
9
10
0.435
0.675
0.662
0.446
0.685
0.515
0.687
0.588
0.603
0.695
0.647
0.471
0.577
-0.540
-0.423
0.573
0.554
0.492
0.418
0.411
-0.488
0.429
0.549
0.640
0.402
0.519
0.663
0.573
0.642
0.526
0.413
0.419
67
26
0.589
27
28
0.480
0.499
29
0.555
0.407
30
0.591
31
32
0.443
Note: Loadings below 0.4 were suppressed.
0.539
0.424
0.409
Table 3. Factor loadings for 2 extracted components (32-item pilot scale).
Factor loadings for specific items
Components
1
2
0.510
1
I was told a joke that pokes fun at older people.
2
10
I was sent a birthday card that pokes fun at older
people.
Someone assumed that I am not physically fit
because of my age.
Someone assumed that I could not remember well
because of my age.
Someone assumed that I cannot hear well because
of my age.
Someone assumed I could not understand because
of my age.
People raised their voice and slowed down when
speaking to me, because of my age.
Someone assumed I am not interested in certain
activities, because of my age.
Someone assumed that, because of my age, I must
look in a certain way (e.g. wear glasses or have
grey hair).
Someone made unpleasant remarks about my age.
11
Someone assumed that I am ‘over the hill.’
0.695
12
Someone said to me: “Aren’t you too old for that?”
0.647
13
I was forced to retire because of my age.
0.573
14
I was denied promotion because of my age.
0.554
15
I had difficulty finding employment, because of my
age.
I was employed in a lower status job than I used to,
because of my age.
At work, my colleagues assumed that I couldn’t
make enough contribution to the company,
because of my age.
I had to pay higher insurance rates because of my
age.
0.492
3
4
5
6
7
8
9
16
17
18
0.675
0.662
0.446
0.685
0.515
0.687
0.588
0.603
0.471
0.418
0.577
0.411
68
19
I had difficulty getting a loan because of my age.
20
A waiter or waitress ignored me because of my
age.
A doctor or nurse assumed my ailments were
caused by my age.
Someone assumed that I lack energy because of
my age.
Someone assumed that I am conservative in my
views because of my age.
Someone assumed that I lack ambition because of
my age.
I was denied access to some facilities, because of
my age.
Someone used patronizing language when
speaking to me, because of my age.
I was called an insulting name relating to my age.
0.402
I was denied a position of leadership because of
my age.
I was rejected as unattractive because of my age.
0.480
0.591
31
I was treated with less dignity and respect because
of my age.
When I went shopping for clothes, I felt that there is
less choice of clothes for people of my age, than
there is for younger people.
32
I was victimized by a criminal because of my age.
21
22
23
24
25
26
27
28
29
30
0.640
0.519
0.663
0.573
0.642
0.589
0.499
69
Table 4. Frequencies of reporting instances of discrimination in the 32-item scale.
Has it ever happened to you?
0
1
2
%
%
%
30.19
13.21
56.60
46.54
15.09
38.36
Did you feel discriminated against?
0
1
2
3
%
%
%
%
30.19
58.49
9.43
1.89
46.54
47.17
5.03
1.26
1
2
I was told a joke that pokes fun at older people.
I was sent a birthday card that pokes fun at older
people.
3
Someone assumed that I am not physically fit because
of my age.
62.89
16.98
20.13
62.89
20.75
11.95
4.40
4
Someone assumed that I could not remember well
because of my age.
57.23
13.21
29.56
56.60
23.90
11.95
7.55
5
Someone assumed that I cannot hear well because of
my age.
74.36
5.13
20.51
73.72
12.82
12.82
0.64
6
Someone assumed I could not understand because of
my age.
82.17
7.64
10.19
82.17
5.73
7.64
4.46
7
People raised their voice and slowed down when
speaking to me, because of my age.
89.10
2.56
8.33
89.10
4.49
3.85
2.56
8
Someone assumed I am not interested in certain
activities, because of my age.
57.69
11.54
30.77
57.96
23.57
12.10
6.37
9
Someone assumed that, because of my age, I must
look in a certain way (e.g. wear glasses or have grey
hair).
75.80
5.10
19.11
75.16
15.29
5.73
3.82
10
Someone made unpleasant remarks about my age.
88.54
3.82
7.64
88.54
5.10
3.82
2.55
11
12
Someone assumed that I am ‘over the hill.’
Someone said to me: “Aren’t you too old for that?”
77.71
61.15
14.65
17.83
7.64
21.02
77.71
61.15
8.28
23.57
9.55
9.55
4.46
5.73
13
I was forced to retire because of my age.
86.62
12.10
1.27
86.62
5.73
3.18
4.46
70
Has it ever happened to you?
0
1
2
%
%
%
91.72
7.01
1.27
82.17
8.28
9.55
Did you feel discriminated against?
0
1
2
3
%
%
%
%
91.72
1.27
2.55
4.46
82.17
2.55
9.55
5.73
14
15
I was denied promotion because of my age.
I had difficulty finding employment, because of my age.
16
I was employed in a lower status job than I used to,
because of my age.
87.90
6.37
5.73
87.90
3.82
3.18
5.10
17
At work, my colleagues assumed that I couldn’t make
enough contribution to the company, because of my
age.
94.90
1.91
3.18
94.90
0.00
1.91
3.18
18
I had to pay higher insurance rates because of my age.
68.15
12.74
19.11
68.15
6.37
13.38
12.10
19
20
I had difficulty getting a loan because of my age.
A waiter or waitress ignored me because of my age.
97.47
93.67
1.90
2.53
0.63
3.80
97.47
93.67
0.63
0.63
2.53
1.27
3.80
21
A doctor or nurse assumed my ailments were caused by
my age.
57.59
22.15
20.25
58.23
19.62
12.03
10.13
22
Someone assumed that I lack energy because of my
age.
65.61
16.56
17.83
65.82
17.72
11.39
5.06
23
Someone assumed that I am conservative in my views
because of my age.
72.78
9.49
17.72
72.78
13.92
7.59
5.70
24
Someone assumed that I lack ambition because of my
age.
89.31
5.66
5.03
88.61
3.80
3.80
3.80
25
I was denied access to some facilities, because of my
age.
93.71
3.14
3.14
93.71
3.14
0.63
2.52
26
Someone used patronizing language when speaking to
me, because of my age.
80.50
9.43
10.06
80.50
2.52
8.18
8.81
71
Has it ever happened to you?
Did you feel discriminated against?
0
1
2
0
1
2
3
%
89.31
%
5.66
%
5.03
%
89.31
%
3.14
%
1.89
%
5.66
27
I was called an insulting name relating to my age.
28
I was denied a position of leadership because of my
age.
94.97
3.77
1.26
94.97
0.00
1.26
3.77
29
I was rejected as unattractive because of my age.
98.10
1.27
0.63
98.10
0.63
0.63
0.63
30
I was treated with less dignity and respect because of
my age.
86.08
3.80
10.13
86.08
3.16
5.06
5.70
31
When I went shopping for clothes, I felt that there is less
choice of clothes for people of my age, than there is for
younger people.
51.27
5.06
43.67
51.27
7.59
20.25
20.89
32
I was victimized by a criminal because of my age.
98.10
1.27
0.63
98.10
0.63
0.63
0.63
72
Appendix F. Additional tables for the 25-item adapted Perceived Age Discrimination
scale.
Table 5. Communalities of the 25-item scale.
Item 1
Item 3
Item 4
Item 5
Item 6
Item 7
Item 8
Item 9
Item 10
Item 11
Item 12
Item 13
Item 14
Item 15
Item 16
Item 17
Item 19
Item 20
Item 21
Item 22
Item 23
Item 24
Item 26
Item 28
Item 30
Communalities
Initial
Extraction
1
0.249
1
0.498
1
0.512
1
0.258
1
0.544
1
0.304
1
0.452
1
0.336
1
0.425
1
0.512
1
0.419
1
0.381
1
0.457
1
0.447
1
0.451
1
0.486
1
0.419
1
0.158
1
0.265
1
0.546
1
0.439
1
0.416
1
0.357
1
0.464
1
0.421
73
Appendix G. Additional tables and figures for the Positive Experience of Ageing
scale.
Table 6. Communalities extracted from items of the scale.
Item
Because I am older, I have a better understanding of what
is really important in life.
Initial
1
Extraction
.476
Because I am older, people respect me less.
1
.716
Because I am older, people come to me for advice.
1
.555
Because I am older, I have less self-confidence.
1
.405
I think getting a bus pass is a great advantage of being
older.
1
.861
I think having concession rates for various activities is a
great advantage of being older.
1
.855
I think being a grandparent is a great advantage of being
older.
1
.415
I think having more time to spend on my hobbies and
interests is a great advantage of being older.
Being older does not make you wiser.
1
.303
1
.556
Figure 1. Scree plot of the Positive Experience of Ageing scale.
Scree Plot
2.5
Eigenvalue
2.0
1.5
1.0
Table 6. Percentage of variance accounted for by factors.
0.5
0.0
1
2
3
4
5
6
7
8
9
Component Number
74
Table 7. Eigenvalues and variance accounted for by the components
in the Positive Experience of Ageing scale.
Factor
1
2
3
4
5
6
7
8
9
Total
2.361
1.540
1.243
0.942
0.865
0.792
0.619
0.531
0.107
% of Variance
26.233
17.108
13.813
10.468
9.606
8.801
6.882
5.899
1.189
Cumulative %
26.233
43.341
57.154
67.622
77.228
86.029
92.911
98.811
100.000
Note: Three factors with eigenvalues over 1 are in bold.
Table 8. Unrotated component matrix after extracting 3 factors.
1
Item 1
Item 2
Item 3
Item 4
Item 5
Item 6
Item 7
Item 8
Item 9
Component
2
0.423
0.495
0.734
0.613
3
0.686
0.860
0.873
0.610
0.503
-0.604
75