1
Results
The findings of the Study Two are reported in four sections. The first section
presents the preliminary analysis of the data. This includes screening for missing
values, univariate and mulitvariate outliers, normality and examination of
relationships between variables. The reliability analyses of the scales are then
presented. In the second section, the participants' characteristics are analysed.
The third and fourth section analyse the hypotheses of the study. The third section
presents analyses of the proposed model. In the fourth section analyses based on
the adaptive outcomes of primary and secondary control are presented. Data were
analysed using SPSS Window’s version 10.0 program.
Preliminary Analyses
Each variable was screened for missing data, normality and univariate and
multivariate outliers for each of the three groups, that is, people with MS,
partners, and controls. The relationships between variables were also explored
and the scales were tested for reliability within the three groups.
The data were screened for missing values using the FREQUENCIES option in
SPSS. A small number of missing values were identified, which appeared to be
scattered randomly. Group means were calculated based on the available data and
used to replace the missing values as recommended by Tabachnick and Fidell
(1996).
Univariate outliers were identified through box plots and stem and leaf diagrams
generated using the EXPLORE option in SPSS. A small number of outliers were
identified. In accordance with the method recommended by Tabachnick and Fidell
(1996), univariate outliers were assigned a raw score on the offending variable
that was one unit larger or smaller than the next most extreme score. Multivariate
outliers were identified using Mahalnobis Distance with p < .001. One
multivariate outlier was detected and deleted from subsequent analysis.
2
The data were screened for normality using the EXPLORE option in SPSS. The
variables were screened for the three groups using measures of skewness, kurtosis,
histograms, the Kolmogorov-Smirnov statistic and the Shapiro-Wilk statistic.
Skewness and kurtosis were not extreme. However, moderate skewness was
associated with some measures. The histograms of the variables similarly
indicated normal distributions for most variables, with skewness for some. The
Kolmogrov-Smirnov statistic was calculated for people with MS and the control
group. The Shapiro-Wilk statistic was calculated for partners as the group
comprised less than fifty participants (Coakes & Steed, 1999). These statistics
were significant for most of the variables for the three groups reflecting normal
distributions. The statistics demonstrated that none of the variables were
sufficiently non-normal to compromise the subsequent analysis.
Correlation matrices were generated to explore relationships among the variables
for each group. These matrices are shown in Table 8.1 to 8.3. The Pearson
correlation co-efficient was calculated for controls and people with MS.
Spearman Rho’s coefficient was calculated for partners as recommended by
Coakes and Steed (1999) due to the small sample size. The correlation matrix
revealed that no variables were highly inter-correlated (above 0.9), thus, there was
no evidence of singularity. Some variables were inter-correlated at 0.7 and above,
these variables were closely monitored when included together in further analyses
as highly inter-correlated variables inflate the size of error terms and weaken an
analysis (Tabachnick & Fidell, 1996). Scatterplots indicated that the variables
were linearly and homoscedastically interrelated.
In summary, most of the variables were normally distributed for the three groups.
Some of the variables mildly deviated from normality, however, transformation
was not undertaken for two reasons. Firstly, none of the variables markedly
deviated from normality for all three groups. Secondly, some skewness was
considered to reflect the inherent nature of the variables and the groups. Thirdly,
all of the scales are meaningful and widely used, and some of the scales are
standardized. Tabachnick and Fiddel (1996) recommend against transformation
of such scales as it often hinders interpretation.
Table 8.1
Pearson Correlations between Variables for Controls
Personality
Variables
Neuroticism
Extraversion
Self-protective
Situation bias
Avoidant
Self-affirmative
Ventilation
Primary Control
Self-esteem
Optimism
From people
From pets
Subjective
Quality of Life
Neuroticism
1.00
-.26*
.24*
-.12
.27*
.12
.48**
-.13
-.73**
-.53**
-.09
.13
-.50**
Secondary Control
Extraversion
1.00
-.17
.22*
-.16
.22*
-.20
.18
.40*
.37**
.46**
.01
.27*
Selfprotective
Situation
bias
1.00
.36**
.46**
.47**
.25*
.32*
-.24*
-.11
-.12
-.18
-.15
1.00
.23
.47**
-.03
.68**
.15
.37**
.28*
-.06
.02
Avoidant
1.00
.40**
.21*
.12
-.36**
-.11
-.10
-.01
-.19
Positive Cognitive Bias
Selfaffirmative
1.00
.28*
.45**
-.04
.06
.46**
-.05
-.01
Ventilation
1.00
.06
-.33*
-.39**
.04
.02
-.29*
Primary
Control
Selfesteem
1.00
.16
.26*
.18
-.13
.06
1.00
.56**
.29*
-.04
.60**
Optimism
1.00
.27*
-.04
.50**
Perceived Social
Support
From
From
people
pets
1.00
.08
.38**
1.00
.05
Subjective
Quality of
Life
1.00
Two tailed correlations * p < .05, ** p < .001, n=93
3
Table 8.2
Pearson Correlations between Variables for People with MS
Personality
Variables
Neuroticism
Extraversion
Self-protective
Situation bias
Avoidant
Self-affirmative
Ventilation
Primary Control
Self-esteem
Optimism
From people
From pets
Subjective
Quality of Life
Neuroticism
1.00
-.48**
.03
-.14
.21
-.05
.46**
-.13
-.80**
-.58**
-.33*
-.17
-.60**
Extraversion
1.00
-.25
.13
-.35*
.08
.02
.06
.51**
.60**
.09
.01
.35*
Secondary Control
Selfprotective
1.00
.34*
.35*
.29*
-.08
.26*
-.16
-.05
-.10
.01
-.11
Situation
bias
1.00
.25*
.58**
-.12
.78**
.09
.26*
.01
.04
-.12
Avoidant
1.00
.21
-.29*
.18
-.25*
-.31*
-.20
-.09
-.27*
Positive Cognitive Bias
Selfaffirmative
1.00
-.12
.48**
.07
.19
-.03
.17
-.05
Ventilation
1.00
-.14
-.43**
-.25
-.17
-.09
-.38*
Primary
Control
Selfesteem
1.00
.01
.23
-.09
-.01
-.15
1.00
.64**
.48**
.22
.68**
Optimism
1.00
.23
.15
.50**
Perceived Social
Support
From
From
people
pets
1.00
.09
.53**
1.00
.25*
Subjective
Quality of
Life
1.00
Two tailed correlations * p < .05, ** p < .001, n=65
4
Table 8.3
Spearman Correlations between Variables for Partners
Personality
Variables
Neuroticism
Neuroticism
Extraversion
Self-protective
Situation bias
Avoidant
Self-affirmative
Ventilation
Primary Control
Self-esteem
Optimism
From people
From pets
Subjective Quality
of Life
1.00
-.23
.25
-.34*
.23
.17
.28
-.21
-.76**
-.52*
-.35*
-.21
-.48*
Extraversion
1.00
.09
.34*
.10
.14
-.06
.33*
.28
.38*
.23
-.14
.28
Secondary Control
Selfprotective
1.00
.29
.44*
.35*
.12
.25
-.36*
-.03
.07
-.22
-.02
Situation
bias
1.00
.18
.38*
.15
.82**
.31
.32
.26
.19
.50*
Avoidant
1.00
.21
-.10
.01
-.31
-.03
-.05
-.16
-.19
Selfaffirmative
1.00
.18
.29
-.09
-.24
.19
-.04
.14
Positive Cognitive Bias
Ventilation
1.00
.16
-.34*
-.20
-.29
-.10
-.26
Primary
Control
1.00
.23
.25
.16
.11
.43*
Self-esteem
1.00
.54*
.50*
.25
.56**
Optimism
1.00
.48*
.30
.48*
Perceived Social
Support
From
From pets
people
1.00
.42*
.59**
1.00
.44*
Subjective
Quality of
Life
1.00
Two tailed correlations * p < .05, ** p < .001, n=37
5
6
Scale Reliabilities
Although the scales of the study are widely used, it was necessary to confirm the
reliability of the scales for use with a clinical sample, namely people with MS and
partners. Based on the findings of Study One items were added to the
Comprehensive Quality of Life Scale, the Primary and Secondary Control Scale,
and the Perceived Social Support Scale. Other items in the Rosenberg SelfEsteem Inventory and the Extraversion subscale of the NEO Five-Factor
Inventory were identified as potentially biased towards people with MS.
Reliability analyses of the scales with the new items added were carried out using
Cronbach’s alpha criterion (). These are shown in Table 8.4. Cronbach’s alpha
ranges from .66 to .93. All of the scales had excellent reliability for the three
groups with the exception of the Secondary Control subscale for partners, the
Extraversion subscale for partners and the Importance subscale of the ComQol for
people with MS which all had moderate reliability (Tabacknick & Fidell, 1986).
In summary, the scales were reliable for the three comparison groups.
Table 8.4
Reliability Analyses of the Scales
People with MS
Controls
(n = 65)
Partners of People
with MS
(n = 37)
Scale
(n = 93)



Primary and Secondary Control
Subscales
Primary Control
Secondary Control
.76
.71
.72
.69
.75
.84
NEO Five Factor Inventory Subscales
Neuroticism
Extraversion
.86
.79
.83
.68
.89
.79
ComQOL Subscales
Importance
Satisfaction
.66
.84
.83
.88
.74
.84
Rosenberg Self-Esteem Scale
.90
.81
.86
Life Orientation Test
.84
.86
.83
Perceived Social Support Subscales
From people
From pets
.88
.93
.88
.80
.85
.86
7
Reliability Analysis of the Primary and Secondary Control Scale
Two new items were added to the Primary and Secondary Control Scale based on
the findings of Study One. These were item seventeen: ‘when I have difficulty
doing something I give up’ and item eighteen: ‘when I have difficulty doing
something I yell, scream, or cry’. A reliability analysis was undertaken to confirm
the reliability of these new items. This is presented in Table 8.5.
Table 8.5
Reliability Analysis of the Primary and Secondary Control Scale
Item
People with MS
(n= 65)
Corrected
Alpha if
Item-Total
Item
Correlation
Deleted
Partners
(n=37)
Corrected
Alpha if
Item-Total
Item
Correlation
Deleted
1. SC
.48
.76
2. SC
.44
.76
3. PC
.65
.75
4. SC
.47
.76
5. SC
.31
.77
6. SC
.58
.75
7. PC
.20
.78
8. SC
.06
.79
9. PC
.41
.76
10. SC
.13
.79
11. SC
.43
.76
12. SC
.39
.77
13. SC
.22
.78
14. SC
.59
.75
15. PC
.56
.76
16. SC
.56
.76
17. NEW
.12
.78
18. NEW
-.17
.80
Total scale
.78
alpha
NEW = New item based on study 1 findings
PC = Primary control item
SC = Secondary control item
.35
.29
.50
.41
.23
.44
.29
.46
.35
.29
.41
.40
.00
.44
.51
.62
.13
.17
.76
.76
.75
.75
.77
.75
.76
.75
.76
.76
.75
.75
.78
.75
.74
.73
.78
.77
.77
Controls
(n=65)
Corrected
Alpha if
Item-Total
Item
Correlation
Deleted
.41
.48
.44
.44
.39
.56
.43
.45
.44
.59
.46
.60
.29
.50
.48
.56
.33
.21
.84
.84
.84
.84
.84
.84
.84
.84
.84
.83
.84
.83
.85
.84
.84
.84
.85
.85
.85
Most of the items of the scale, including the new items, contributed to the
reliability of the scale. None of the items contributed significantly with decreased
reliability. One of the new items, number eighteen, was associated with decreased
reliability for people with MS only. This item was also negatively correlated with
the other items of the scale for people with MS only. Thus, the inclusion of the
new items and the reliability of the scale were confirmed.
8
Factor Analysis of Primary and Secondary Control Scale
A factor analysis was conducted on the new version of the Primary and Secondary
Control Scale to determine the validity of the factors of the scale including the two
new items. The authors of the scale recommend five factors: primary control, and
four types of secondary control: situation bias, self-protective, self-affirmative and
avoidant (Maher et al, 2000). They claim that primary control and the four types
of secondary control each serve a different purpose and as such, they do not
expect these factors to emerge from a factor analysis.
A principal components factor analysis was conducted on the entire sample
(n = 194), including an oblique rotation of the solution in order to aid the
interpretation of the factors. Table 8.6 shows the oblique rotation analysis. The
analysis produced four factors that closely resembled the factors of the scale. Few
items loaded on more than one factor. Primary control, situation bias and one selfprotective item loaded onto one factor. The remaining self-protective items
loaded onto the second factor. Self-affirmative items loaded onto the third factor.
Avoidant items loaded on the fourth factor. The other new item ‘give up’ loaded
with the avoidant secondary control items of the scale. This is inconsistent with
the proposition of the first study that this item would load with primary control
items as it reflects perceptions of primary control.
The other new item, ‘ventilation’, failed to load on any of the factors. However, it
was retained for further analysis. As discussed in study one, ventilation was
frequently mentioned as a way to cope with stressors. Following from this and the
factor analysis, it was proposed that ventilation may represent a type of secondary
control not before recognised. Thus, the item was analysed separately from the
other factors of the scale.
9
Table 8.6
Factor Analysis of the Primary and Secondary Control Scale
Items
15. Primary control
9. Primary control
7. Primary control
3. Primary control
16. Situation bias
14. .Situation bias
1. Self-protective
4. Self-protective
5. Self-protective
2. Self-protective
6. Self-affirmative
10. Self-affirmative
8. Self-affirmative
11. Self-affirmative
13. Avoidance
12. Avoidance
17. New item
18. New item
Factor 1
.81
.79
.72
.70
.67
.59
.52
Factor 2
Factor 3
Factor 4
.30
.83
.80
.66
.36
.39
.78
.75
.56
.32
-.76
-.76
.60
n = 195
In summary, the factor analysis confirmed the factor structure of control. In
further analysis, the new item ‘give up’ was categorised with the avoidant
secondary control items. The other new item, ‘Ventilation’ was analysed
separately. Factor 1 was split into primary control and situation bias, to reflect
their divergent purposes. Thus, the scale items comprised five factors based on
the hypothesised purpose of the items.
Analysis of the Domains of the ComQol
The life domain ‘independence’ was added to the ComQol based on the findings
of the first study. A reliability analysis was conducted to determine the reliability
of the scale with the new life domain. This is shown in Table 8.7. The
independence domain contributed to the reliability of the scale across the three
groups. Thus, the new ComQol scale was reliable for all three groups.
10
Table 8.7
Reliability Analysis of Comprehensive Quality of Life Scale
Domain
Importance
Possesions
Health
Achievment
Intimacy
Safety
Community
Happiness
Independence*
Total Alpha
Satisfaction
Possesions
Health
Achievment
Intimacy
Safety
Community
Happiness
Independence*
Total Alpha
People with MS
(n= 65)
Corrected
Alpha if
Item-Total
Item
Correlation Deleted
Partners
(n=37)
Corrected
Alpha if
Item-Total
Item
Correlation
Deleted
Controls
(n=65)
Corrected
Alpha if
Item-Total
Item
Correlation
Deleted
.24
.33
.53
.42
.29
.22
.33
.40
.63
.61
.54
.58
.61
.64
.60
.60
.66
.24
.50
.42
.56
.74
.57
.78
.65
.85
.80
.81
.79
.76
.79
.76
.78
.83
.51
.41
.50
.41
.46
.51
.42
.26
.70
.72
.70
.72
.71
.69
.72
.75
.74
.61
.56
.55
.69
.63
.43
.70
.44
.82
.83
.83
.81
.82
.84
.81
.84
.84
.55
.55
.70
.75
.62
.36
.81
.77
.87
.87
.56
.85
.87
.89
.84
.85
.88
.42
.53
.58
.56
.58
.57
.75
.61
.84.
.83
.82
.82
.82
.82
.80
.82
.84
* new life domain based on Study One findings
Potentially Sensitive Items of the NEO Five-Factor Inventory and the Rosenberg
Self-Esteem Inventory
Study One identified that some items of the questionnaire that might be unduly
sensitive to people with MS. These included three items of the extraversion
subscale of the NEO Five Factor Inventory namely: "I often feel as if I am
bursting with energy', 'My life is fast-paced' and 'I am a very active person'. These
items may be confounded by symptoms of MS, and may measure illness rather
than personality. A two-way ANOVA was conducted to compare the differences
between the three groups on the total extraversion score and on an extraversion
score without the three potentially biased items. This was undertaken to
determine whether differences on the subscale between people with MS and the
other two groups were unduly influenced by the three items. Box’s M was not
significant at p > .001, thus indicating that the data was suitable for the analysis.
The Pillai’s criterion revealed a significant overall effect of group,
11
F (20, 191) = 7.15, p < .001, ² = .07, p= .99. Post hoc univariate tests revealed
that people with MS were significantly less extraverted than controls on the total
extraversion (p < .001). However, they were no different from the other two
groups on the extraversion score with sensitive items removed. Thus, the
differences between the groups on the extraversion measure are attributable to the
three identified items, which likely measure MS symptoms rather than personality.
A reliability analysis was conducted using Cronbach’s alpha () to determine
whether removal of the items from the scale would detrimentally effect the
reliability of the scale. The reliability of the extraversion subscale with and
without the sensitive items is shown in Table 8.8.
Table 8.8.
Reliability Analysis of the Extraversion Subscale With and Without Sensitive
Items
Scale
Total Scale
Scale with Sensitive Items Removed
People with
MS
(n = 65)

.79
.74
Partners of People
with MS
(n = 37)

.68
.69
Controls
(n = 93)

.79
.77
The reliability of the scales was not significantly reduced due to the removal of
the three items. Therefore these items were omitted from further analysis for all
three groups.
The first study also identified one item in the Rosenberg Self-Esteem Scale as
potentially sensitive to people with MS namely: ‘I am unable to do things as well
as other people’. A two-way ANOVA was conducted as described above to
determine the validity of these items for the three groups. The three groups
differed significantly on self-esteem, despite removal of the potentially sensitive
item. Thus, this item was retained for further analysis.
12
Summary of the Preliminary Analyses
Analyses revealed that the data did not significantly deviate from normality. Some
deviations were apparent, however these were deemed to be minimal, not
common to all three groups, and an inherent nature of the sample. Thus, data
transformation was not undertaken. Some outliers were present. These were
either re-coded or deleted from subsequent analyses. The reliability and factor
structure of the scales, including the new items, were confirmed. Thus, the new
items proposed in study one were retained in the analysis of data in study two.
Three items of the extraversion scale were removed from further analyses, as it
was likely that these items were biased towards people with MS. The domains of
the ComQol and the domains differently contributed to self-esteem.
Analysis of Participant Characteristics
Table 8.9 describes the sample in terms of age, gender, years in current
relationship, and living arrangement with partner. Two-thirds of the people with
MS were female. Consistent with this, one third of partners were female. This is
consistent with estimates of the gender ration of the prevalence of MS in the
general population (MS Society Australia, 2000). In contrast, approximately half
of the controls were female. Almost all the sample lived with their partners.
Table 8.9
Participant Demographic Characteristics
People with MS
Controls
(n = 65)
Partners of People
with MS
(n = 37)
49.92
10.13
49.22
10.22
43.12
13.55
21 (32.8%)
43 (67.2%)
24 (64.9%)
13 (35.1%)
44 (47.3%)
49 (49.0%)
20.64
12.94
22.35
13.23
17.01
13.40
59 (92.2%)
34(91.9%)
78 (83.9%)
Characteristic
Age (years)
Mean
SD
Gender
Male
Female
Length of Relationship
(years)
Mean
SD
Live with Partner
(yes or no)
(n = 93)
13
Table 8.10 describes the illness characteristics of the sample.
Table 8.10
Participant Illness Characteristics
People with MS
(n = 65)
Partners (n = 37)
(responses refer to
partner’s MS)
38 (59.4%)
17 (26.6%)
3 (4.7%)
1 (1.6%)
2 (3.1)
15 (40.5%)
15 (40.5%)
1 (2.7%)
3 (8.1%)
3 (8.1%)
First diagnosed with MS (years ago)
Mean
SD
8.55
8.03
8.62
7.28
Onset of MS (years ago)
Mean
SD
13.51
8.92
10.06
7.57
Disabled by MS
(1 fully independent – 10 fully dependent on
others)
Mean
SD.
3.69
2.60
4.43
2.63
Change in MS in last year
(1 = deteriorated – 10 improved)
Mean
SD
4.93
2.15
4.70
1.81
6.05
1.99
5.69
1.67
5.67
2.85
6.00
2.90
N/A
4.13
2.39
41 (64.1%)
N/A
Characteristic
Type of MS
Relapsing-remitting
Progressive
Secondary progressive
Stable
Other
Compared to average state
(1 much worse – 10 much better)
Mean
SD
Effect of MS on life role
(1 does not effect – 10 prevents from performing
role would like)
Mean
SD
Effect of MS on partner’s Life role
(1 does not effect – 10 prevents from performing
role would like)
Mean
SD
Experience pain through MS
(yes or no)
The relative prevalence of the different types of MS evident in the sample was
consistent with estimates of the general population. As discussed in Chapter 2, 50
to 60% of people with MS in the general population have Relapsing-Remitting
14
MS, 10 to 20% have either Primary Progressive MS (or chronic progressive) or
Secondary Progressive MS and 20 to 30% have Benign MS (Rao et al, 1992).
Participants rated their current state as slightly better than their average state, and
reported only a slight deterioration in the last year. These data suggest that most
participants were in a period of illness remission rather than exacerbation at the
time of the study. There was a large variation in time since diagnosis and onset of
MS. People with MS were not fully independent on average, and rated
themselves as minimally dependent on others for care. People with MS on
average reported that their illness had moderately prevented them from
performing the role in life they would like to. Most people with MS experienced
pain through MS. Partners of people with MS rated their partners’ illness
similarly, however their partner’s MS effected their life role to a lesser extent.
The Proposed Model for the Maintenance of Subjective Quality of Life
A model was previously discussed that explains the mechanism by which
subjective quality of life is maintained in an adaptive range. It was hypothesised
that personality, positive cognitive bias of self-esteem, control, and optimism,
personality predict a significant proportion of subjective quality of life
evaluations, which differs between people with MS, partners, and controls and
that secondary control mediates between positive cognitive biases and subjective
quality of life. The model was shown previously, and is shown again in Figure
8.3.
15
FIRST ORDER
DETERMINANTS:
Personality
SECOND ORDER
DETERMINANTS:
Internal Buffers
THIRD ORDER
MEDIATING
DETERMINANT
Perceived Social
Support
Extraversion
Neuroticism
Positive Cognitive
Biases
Self-Esteem
Optimism
Primary Control
Secondary
Control
Subjective
Quality
of Life
Environmental
Factors
Figure 8.3
The proposed model for the maintenance of subjective quality of life
Unfortunately the relatively small sample size precluded the analysis of this model
through structural equation modeling (Tabachnick & Fidell, 1996). This model
was tested through a range of MANOVAs, ANOVAs, and REGRESSION
analyses. However, the shortcoming of this approach is that the proposed model
cannot be tested in its entirety and the risk of Type I errors increases. A figure of
the model is presented prior to each section with the parts of the model to be
analysed highlighted.
Differences between the Groups
Hypotheses one, four and five predicted differences between the groups in the
variables of the model. These hypotheses stated:
16
Hypothesis 1: People with MS have the lowest subjective quality of
life. Partners have a higher, and controls the highest subjective
quality of life.
Hypothesis 4: Positive cognitive biases of primary control and selfesteem are smaller for people with MS than partners and controls.
Hypothesis 5: Positive cognitive biases of optimism are larger for
people with MS than partners and controls.
A MANOVA was conducted to analyse differences between the groups on all of
the variables of the model. Box’s M indicated that the test of homogeneity of
variance had not been violated at an alpha level of .05. With the use of the Pillai’s
Trace criterion the combined dependent variables were significantly effected by
group membership, F(30, 356) = 4.03, p < .001. Table 8.11 shows the means (X),
standard deviations (SD), significance (F), power and strength of associations (²)
for each group. The mean and standard deviation are presented as a percentage of
the scale maximum, where appropriate, for ease of comparison.
17
Table 8.11
Multivariate Analysis of the Variables of the Model by Group
Variables
Age (years)
X
SD
Length of relationship(years)
X
SD
Subjective Quality of Life
X
SD
Personality
Neuroticism
X
SD
Extraversion
X
SD
Positive Cognitive Bias
Self-esteem
X
SD
Optimism
X
SD
Control
X
SD
Perceived Social Support
People
X
SD
Pets
X
SD
Secondary Control
Self-Protective
X
SD
Situation Bias
X
SD
Avoidant
X
SD
Self-Affirmative
X
SD
Ventilation
X
SD
People with
MS
(n=64)
Partners
Controls
(n = 37)
(n=93)
46.92
10.13
49.22
10.22
20.64
12.94
F
power
²
43.12
13.55
4.11*
.72
.04
22.35
13.22
17.01
13.40
2.70
.53
.03
66.81
15.35
76.26
12.91
76.57
10.42
12.45**
.99
.12
44.46
22.37
37.54
14.71
40.41
17.44
.79
.18
.01
42.22
12.98
43.50
9.26
45.13
9.87
1.73
.36
.02
66.84
20.41
75.55
13.04
76.71
12.71
7.96**
.95
.08
65.93
23.64
75.53
15.91
71.92
17.32
1.81
.38
.02
66.68
16.81
61.79
17.57
64.21
14.26
2.44
.49
.03
75.96
18.53
67.07
20.67
75.03
19.29
7.63*
.94
.07
68.72
28.13
80.26
18.93
68.39
25.73
1.98
.41
.02
53.56
16.57
46.15
13.14
46.14
12.76
2.67
.53
.03
66.57
19.92
64.25
18.99
64.51
18.53
1.22
.26
.01
36.64
12.99
33.40
12.49
31.54
10.35
4.00*
.71
.04
53.70
14.28
51.96
18.35
55.65
15.39
2.88
.56
.03
41.25
22.37
37.69
20.65
37.14
21.98
.34
.10
.01
* p < .05, ** p < .001, n = 194, ² = strength of association
18
Table 8.11 (continued)
Multivariate Analysis of the Variables of the Model by Group
People with
MS
ComQol Domains
Satisfaction:
Possessions
X
SD
Health
X
SD
Achievements
X
SD
Intimacy
X
SD
Safety
X
SD
Community
X
SD
Happiness
X
SD
Independence
X
SD
Importance:
Possessions
X
SD
Health
X
SD
Achievements
X
SD
Intimacy
X
SD
Safety
X
SD
Community
X
SD
Happiness
X
SD
Independence
X
SD
Partners of
People
with MS
Controls
78.78
21.75
81.57
17.60
76.29
15.32
49.78
20.19
76.90
18.00
64.49
20.98
Power
²
1.19
.26
.01
76.88
16.09
49.22*
1.00
.34
72.73
18.05
75.20
15.21
7.00*
.92
.07
76.91
22.93
82.84
17.75
82.02
12.92
1.98
.41
.02
75.80
19.18
83.59
19.18
82.71
12.78
4.63*
.78
.05
70.40
19.79
74.75
14.35
74.51
16.64
1.24
.27
.01
71.43
23.53
75.76
18.01
79.65
15.43
3.58*
.66
.04
68.77
22.06
76.27
18.29
79.74
15.18
6.87*
.92
.07
64.04
21.12
64.32
23.75
68.37
18.84
1.02
.27
.01
89.68
13.80
90.81
14.79
89.89
12.38
.09
.06
.34
79.20
19.86
79.19
19.20
78.37
15.90
.05
.06
.07
92.79
15.75
90.27
14.43
88.15
14.44
1.84
.38
.02
83.85
19.93
81.62
19.22
81.85
17.50
.27
.09
.05
67.40
22.23
65.68
21.80
65.43
18.38
.19
.08
.01
87.88
19.53
82.49
17.06
85.11
13.95
1.30
.28
.04
89.84
12.02
85.14
17.42
81.20
17.87
5.49*
.85
.07
F
* p <.05, ** p <.001, n = 194, ² = strength of association
19
The analysis revealed a significant effect of group for age, subjective quality of
life, self-esteem, perceived social support from people, avoidant secondary
control, satisfaction with the life domains of health, achievements, safety,
happiness, independence, and importance of the independence life domain.
Univariate tests revealed that partners were significantly older than controls,.
Consistent with hypothesis one, people with MS reported a lower subjective
quality of life than partners and controls, F(2,194) = 12.45, p < .001. Consistent
with hypothesis four, they also reported lower self-esteem than both partners (p <
.05) and controls (p < .001) In contrast with hypothesis four and five, partners did
not differ from controls in the magnitude of their positive cognitive biases, and
there was no difference between the three groups in positive cognitive biases of
optimism. Partners reported lower perceived social support than both people with
MS (p < .05) and controls (p < .05). People with MS also reported more avoidant
secondary control than controls (p < .05).
In regards to the domains of the ComQol, people with MS were less satisfied with
their health than both partners and controls (p < .001). They were also less
satisfied with what they had achieved than controls (p < .05). They were less
satisfied with how safe they felt than both partners and controls (p < .05), and less
satisfied with their happiness than controls (p < .05). Although people with MS
rated their independence as significantly more important than controls (p < .05),
they were significantly less satisfied with their independence than controls (p <
.05). The power of these tests were mostly moderate to excellent (.99). However,
the strength of associations were low (.02 to .12).
Most participants classified their or their partner’s diagnosis as either ‘relapsingremitting’ or ‘progressive’. A minority of participants reported a different
diagnosis including ‘stable’ and ‘benign’. Due to the small numbers that reported
other types of MS, only relapsing-remitting and progressive MS could be
compared. Table 8.12 shows the means, and standard deviations of subjective
quality of life for the three groups as a percentage of the scale maximum. The total
number of participants reported in the tables is more than the sum of participants
reporting relapsing-remitting MS or progressive MS as it includes those that
20
reported other types of MS. There was no difference in the subjective quality of
life of the different types of MS (i.e. progressive or relapsing-remitting) as
evidenced by a t-test. Thus, further analyses treated the group as a homogenous
sample of people with MS.
Table 8.12
The Subjective Quality of Life of Each Group and Illness Type
Group and illness type
People with MS
Relapsing-Remitting, n = 38
X
SD
Progressive, n = 17
X
SD
Total, n = 64
X
SD
Partners of People with MS
Relapsing-Remitting, n = 15
X
SD
Progressive, n = 15
X
SD
Total, n = 37
X
SD
Controls, n = 93
X
SD
Subjective quality of life
68.41
15.53
64.28
16.27
66.81
15.35
77.58
13.22
75.03
12.31
76.26
12.91
76.57
10.42
Interactions between Variables
Hypotheses two and three, below, predicted interactions between variables of the
model:
Hypothesis 2: Perceived social support and positive cognitive bias
predict subjective quality of life after personality has been controlled.
Hypothesis 3: Secondary control mediates between positive cognitive
biases and secondary control.
21
Hypothesis 2 was tested using a Hierarchical regression analyses for each group.
This analysis is represented by the bold lines in Figure 8.4.
FIRST ORDER
DETERMINANTS:
Personality
SECOND ORDER
DETERMINANTS:
Internal Buffers
THIRD ORDER
MEDIATING
DETERMINANT
Perceived Social
Support
Extraversion
Neuroticism
Positive
Cognitive Biases
Self-Esteem
Optimism
Primary Control
Subjective
Quality
of Life
Secondary
Control
Environmental
Factors
Figure 8.4
Analysis of Hypothesis 2: Interactions between Variables of the Model
Personality, perceived social support, the three positive cognitive biases,
secondary control and illness variables were entered in four steps of a hierarchical
regression analysis for each group. Further hypotheses regarding specific
interactions between variables, including the mediating role of secondary control,
the threshold effect of perceived social support, and the adaptive outcome of
primary and secondary control, were then examined through further multiple
regressions, ANOVAs, and MANOVAs.
The correlation matrices in Tables 8.1 to 8.3 were examined for evidence of
multicollinearity and singularity. Self-esteem was highly correlated with both the
22
subjective quality of life of the three groups (r2 = .60, p < .001 for controls, r2 =
.68, p < .05 for people with MS, r2 = .56, p < .001 for partners) and with
neuroticism (r2 = -.73, p < .001 for controls, r2 = -.80, p < .001 for people with
MS, r2 =-.76, p < .001 for partners). As discussed previously, the inclusion of
highly inter-correlated variables weakens statistical analyses (Tabachnick &
Fidell, 1986). Thus, self-esteem was closely monitored and the analyses were
conducted both with and without this variable to ensure that it was not negatively
effecting the regression.
Variables were entered into steps of the regression based on the order
hypothesised by the model. Specifically, extraversion and neuroticism were
entered into the first step as these were hypothesised to exert the strongest
influence on subjective quality of life. Positive cognitive bias and perceived social
support were entered into the next step. In the third step, the five types of
secondary control were added. In the final step, two illness related variables were
added for people with MS and partners to determine whether MS exerted an
influence on subjective quality of life once psychological factors were controlled
for.
With up to nine variables in the regression equation, the ratio of cases to
independent variables was sufficient for both controls and people with MS.
However, the ratio was less than the minimum five to one ratio recommended by
Coakes and Steed (1999) for partners. Using this ratio, the maximum number of
variables in the equation for partners is seven. Thus, the number of variables in
the last two steps of the analysis for partners exceeds this number and should be
interpreted with caution.
Preliminary regression analyses were conducted with the original extraversion
score, and then with the extraversion score without the three sensitive items
identified in study. There was no significant difference between the two analyses
for people with MS and partners. However, for the control group while the
original extraversion score was a significant predictor of subjective quality of life
in the regression analyses, the newly comprised score without the three items was
23
not. The two regression analyses of personality and subjective quality of life for
the control group are shown in Table 8.13
Table 8.13
Regression Analyses of the Effect of the Two Extraversion Scores on the
Subjective Quality of Life of Controls
Variables in the equation
Regression Analysis 1
Original Extraversion Score
Neuroticism
R = .53, R2 = .28
Adjusted R2 = .27
Standard error = 71.44
F(2,90) = 17.63*
Regression Analysis 2
New Extraversion Score
Neuroticism
R = .52, R2 = .27
Adjusted R2 = .25
Standard error = 72.11
F(2,90) = 16.47*
B
SE B

t
p
sr12
-4.27
2.79
.96
1.37
-.43
.20
-4.46
2.04
.00**
.04*
.18
.04
-4.60
2.56
.93
1.64
-.46
.15
-4.93
1.56
.00**
.12
.21
.03
* p < .05, ** p < .001; n = 93
The removal of items from the scale aimed to reduce potential bias towards people
with MS. However, while the analysis of differences between the three groups on
the two extraversion scores revealed that the items were likely biased towards
people with MS, the regression analysis summarised in the previous table
indicates that removal of these items did not change the relationship between
extraversion and the other variables of the model for people with MS, but did so
for controls. Therefore, the original extraversion score was used in further
regression analyses for all three groups. Analyses were also conducted with and
without self-esteem. The inclusion of self-esteem in the regression equation
resulted in some changes.
Tables 8.14 to 8.16 show the unstandardised regression co-efficients (B), the
standard error (SE B), the standardised regression co-efficients (), the semipartial correlations (sr12), the probability levels (t) and significance levels (p) of
the regression analysis including the original extraversion score for each group
both with and without self-esteem.
24
In the first step of the analyses, with personality included, R was significantly
different from zero each group (R2 = .53, adjusted R2 = .28, F(2,90) = 17.63, p <
.001 for controls. R2 = .61, adjusted R2 = .37, F(2,61) = 17.68, p < .001 for people
with MS. R2 = .53, adjusted R2 = .28, F(2,34) = 6.56, p < .05 for partners).
Neuroticism negatively predicted the subjective quality of life of all three groups
(p < .001, sr12 = .21 for controls. p < .001, sr12 = .22 for people with MS. p <
.001, sr12 = .17 for partners). In addition, extraversion positively predicted the
subjective quality of life of controls (p < .05, sr12 = .01).
The addition of positive cognitive biases and perceived social support in the
second step resulted in a significant increase in R for all three groups. Thus,
hypothesis one was supported. However, there were differences between the two
equations including and excluding self-esteem. For controls, with self-esteem
included, perceived social support from people (p < .05, sr12 = .04) and selfesteem (p < .05, sr12 = .04) positively predicted the subjective quality of life of
controls and neuroticism no longer had an effect. For people with MS,
neuroticism still negatively predicted subjective quality of life (p < .05, sr12 = .01).
Also, primary control negatively predicted (p < .05, sr12 = .03) and social support
from people positively predicted (p < .05, sr12 = .06) subjective quality of life. For
partners, at this step primary control was the only significant predictor (p < .05,
sr12 = .06).
With self-esteem excluded, there were additional predictors and also changes in
the regression weights of some variables. For controls, without self-esteem
neuroticism was a significant negative predictor (p < .001, sr12 = .08), and
optimism was a significant positive predictor (p < .05, sr12 = .04). The regression
weight for social support from people also increased. For people with MS, with
the exclusion of self-esteem there were no additional predictors. However, the
regression weights increased for extraversion, neuroticism, optimism and primary
control. For partners with self-esteem excluded, there was one additional
predictor. Perceived social support from people positively predicted subjective
25
quality of life (p < .05, sr12 = .09). Also, the regression weight for neuroticism
increased.
The addition of secondary control variables at step three did not result in a
significant increase in R for any of the three groups. Therefore this step was
removed from the analysis. This resulted in a higher case to variable ratio, which
improved the strength of the analysis for the partners group, such that the
minimum recommended five to one ratio was only exceeded in the last step of the
regression. The mediating role of secondary control will be further analysed.
The addition of illness variables at step four, resulted in a significant increase in R
for people with MS and partners. The extent to which MS was perceived to effect
their ability to live the life they would like to significantly negatively predicted
subjective quality of life with or without self-esteem included (p < .05, sr12 = .08,
and sr12 = .09 respectively) for people with MS. However, it was a significant
predictor for partners only in the analysis with self-esteem (p < .05, sr12 = .06).
The changes between the two regression equations exploring the inclusion of selfesteem suggested the presence of suppressor variable. A suppressor variable is
one that is useful in predicting the dependent variable (subjective quality of life)
and in increasing the multiple R2 solely by virtue of its correlations with other
independent variables (Tabachnick & Fidell, 1996). However, a series of
regressions, where each of the independent variables was omitted were omitted in
turn to reveal the suppressor as recommended by Tabachnick and Fidell (1996)
found no evidence of a suppressor variable. Thus, it appeared that the inclusion of
self-esteem in the equation was weakening the analysis due to its high correlation
with other variables as cautioned by Tabachnick and Fidell (1996).
Table 8.14.
Hierarchical Regression Analysis for Variables Predicting the Subjective Quality of Life of Controls
Analysis with self-esteem
Step 1
Extraversion
Neuroticism
R = .53, R2 = .28
Adjusted R2 = .27
Standard error = 71.44
F(2,90) = 17.63**
Step 2
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
R = .67, R2 = .45
Adjusted R2 = .41
Standard error = 64.23
F(5,85) = 10.00**

T
.20
-.43
-.29
1.42
-.02
-1.60
1.25
-.16
3.18
1.66
.20
-2.54
2.28
-.10
2.12
.85
.32
2.23
.86
.24
.39
.59
.06
2
R inc = 17, F(5,85) = 5.27**
B
2.79
-4.27
SE B
1.37
.96
p
sr12
2.04
-4.46
.04*
.00**
.01
.21
-.20
-1.28
1.92
-1.12
2.50
2.59
.67
.84
.20
.06
.27
.01*
.01*
.51
.01
.00
.04
.02
.01
.04
.00
Analysis without self-esteem
Step 1
Extraversion
Neuroticism
R = .53, R2 = .28
Adjusted R2 = .27
Standard error = 71.44
F(2,90) = 17.63**
Step 2
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
R = .64, R2 = .41
Adjusted R2 = .37
Standard error = 66.81
F(4,86) = 10.00**
B
SE B

t
p
sr12
2.79
-4.27
1.37
.96
.20
-.43
2.04
-4.46
.04*
.00**
.01
.21
.24
-3.53
3.98
-2.64
1.44
1.01
1.68
2.35
.02
-.35
.25
-.10
.16
-3.51
2.38
-1.12
.87
.00**
.02*
.27
.00
.08
.04
.01
2.66
.87
.29
.47
.60
.07
R inc = 13, F(4,86) = 4.74*
3.06
.77
.00*
.44
.06
.00
2
* p < .05, ** p < .001; n = 93
26
Table 8.15.
Hierarchical Regression Analysis for Variables Predicting the Subjective Quality of Life of People with MS
Analysis with self-esteem
Step 1
Extraversion
Neuroticism
R = .61, R2 = .37
Adjusted R2 = .35
Standard error = 91.19
F(2,61) = 17.68**
Step 2
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
R = .77, R2 = .59
Adjusted R2 = .41
Standard error = 83.35
F(5,56) = 11.50**
Step 3
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets.34
Years since diagnosis
Effect of MS on life role
R = .83, R2 = .68
Adjusted R2 = .63
Standard error = 74.68
F(9,54) = 12.89**
B
1.88
-6.32
SE B
1.76
1.37

t
p
sr12
.12
-.54
1.07
-4.62
.29
.00**
.17
.22
-.89
1.64
-.06
-3.47
1.57
-.29
2.87
2.32
.16
-7.26
3.42
-.19
1.40
1.03
.23
3.88
1.40
.28
1.23
.94
.12
2
R inc = 22, F(5,56) = 6.08**
-.54
-2.20
1.24
-2.13
1.37
2.78
1.31
.59
.03*
.22
.04*
.18
.01*
.20
.00
.01
.01
.03
.01
.06
.01
-.89
1.64
-.06
-3.47
1.57
-.29
.2.47
2.15
.14
-2.50
3.29
-.07
.85
.93
.14
3.21
1.27
.23
.34
.87
.03
-.21
1.33
-.01
-16.24
4.40
-.38
R2inc = 09, F(2,54) = 7.89**
-.54
-2.20
1.5
-.76
.91
2.53
.40
-.16
-3.69
.59
.03*
.26
.45
.37
.01*
.70
.87
.00**
.00
.03
.01
.00
.00
.04
.00
.00
.08
Analysis without self-esteem
Step 1
Extraversion
Neuroticism
R = .61, R2 = .37
Adjusted R2 = .35
Standard error = 91.19
F(2,61) = 17.68**
Step 2
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
R = .76, R2 = .58
Adjusted R2 = .53
Standard error = 83.99
F(4,57) = 12.90**
Step 3
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
Years since diagnosis
Effect of MS on life role
R = .82, R2 = .68
Adjusted R2 = .63
Standard error = 74.55
F(2,55) = 14.45**
B
SE B

t
p
sr12
1.88
-6.32
1.76
1.37
.12
-.54
1.07
-4.62
.29
.00**
.17
.22
1.22
-3.86
3.74
-8.05
1.76
1.33
2.25
3.39
.08
-.33
.21
-.22
.69
-2.89
1.66
-2.37
.49
.00*
.10
.02*
.00
.06
.02
.04
4.61
1.30
.34
1.42
.93
.13
R inc = 21, F(4,57) = 7.02**
3.55
1.52
.00**
.13
.09
.02
2
-.74
-4.39
2.99
-2.80
1.63
1.19
2.07
3.27
-.05
-.37
.17
-.08
.45
-3.68
1.45
-.86
.65
.00**
.15
.40
.00
.08
.01
.00
3.62
1.18
.26
.43
.86
.04
-.29
1.32
-.02
-16.71
4.37
-.39
R2inc = 10, F(2,55) = 8.67**
3.07
.50
-.22
-3.83
.00*
.62
.83
.00**
.06
.00
.00
.09
* p < .05, ** p < .001; n = 65
27
Table 8.16.
Hierarchical Regression Analysis for Variables Predicting the Subjective Quality of Life of Partners
Analysis with self-esteem
Step 1
Extraversion
Neuroticism
R = .53, R2 = .28
Adjusted R2 = .24
Standard error = 90.24
F(2,34) = 6.56*
Step 2
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
R = .76, R2 = .57
Adjusted R2 = .47
Standard error = 75.33
F(7,29) = 5.15**
Step 3
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets.
Years since diagnosis
Effect of MS on life role
R = .79, R2 = .63
Adjusted R2 = .51
Standard error = 72.54
F(9,27) = 5.10**
B
3.74
-6.02
SE B
3.07
2.10

t
p
sr12
.19
-.44
1.22
-2.87
.23
.00*
.03
.17
-.98
3.05
-.05
-1.14
2.75
-.08
1.83
3.67
.08
8.67
4.29
.28
1.67
1.70
.21
3.27
1.64
.33
1.10
1.22
.13
2
R inc = .29, F(5,29) = 3.96*
-.32
-.41
.50
2.02
.98
2.00
.90
.75
.68
.62
.05*
.34
.06
.37
.00
.00
.00
.06
.01
.06
.01
-2.08
3.17
-.10
.46
2.82
.03
2.72
3.58
.13
6.71
4.24
.21
2.19
1.69
.28
2.93
1.59
.29
.90
1.18
.11
.49
1.86
.03
-12.36
5.98
-.29
R2inc = 06, F(2,27) = 2.14**
-.65
.17
.76
1.58
1.30
1.84
.76
.26
-2.07
.52
.87
.45
.13
.21
.08
.46
.80
.05*
.01
.00
.01
.03
.02
.05
.01
.00
.06
Analysis without self-esteem
Step 1
Extraversion
Neuroticism
R = .53, R2 = .28
Adjusted R2 = .24
Standard error = 90.24
F(2,34) = 6.56**
Step 2
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
R = .75, R2 = .56
Adjusted R2 = .47
Standard error = 75.28
F(6,30) = 6.28**
Step 3
Extraversion
Neuroticism
Optimism
Primary Control
Self-Esteem
Social support from people
Social support from pets
Years since diagnosis
Effect of MS on life role
R = .78, R2 = .61
Adjusted R2 = .49
Standard error = 73.42
F(2,28) = 5.40**
B
SE B

t
p
sr12
3.74
-6.02
3.07
2.10
.19
-.44
1.22
-2.87
.23
.00*
.03
.17
-.63
-2.98
2.02
8.58
3.03
2.01
3.67
4.29
-.03
-.22
.09
.27
-.21
-1.48
.55
2.00
.84
.15
.59
.05*
.00
.03
.00
.06
3.82
1.54
.38
1.09
1.22
.13
R inc = 28, F(4,30) = 4.71*
2.48
.90
.02*
.38
.09
.01
2
-1.29
-2.10
2.80
6.81
3.15
2.04
3.62
4.29
-.06
-.15
.13
.22
-.41
-1.03
.77
1.59
.69
.31
.45
.12
.06
.01
.01
.04
3.67
1.51
.37
.93
1.19
.11
.86
1.86
.06
-11.19
5.98
-.26
R2inc = .05, F(2,28) = 1.77
2.43
.78
.46
-1.87
.02*
.44
.65
.07
.08
.01
.00
.05
* p < .05, ** p < .001; n = 37
28
29
In summary of the Hierarchical regression analyses, as hypothesised the variables
of the model predicted a significant portion of the subjective quality of life of each
group (R2 = .45 for controls, R2 = .68 for people with MS, R2 = .63 for partners).
As predicted personality, specifically neuroticism, was a consistent predictor of
subjective quality of life. Extraversion positively predicted the subjective quality
of life of controls only. After personality was controlled for, perceived social
support from people consistently predicted subjective quality of life across the
three groups as hypothesised.
The influence of positive cognitive bias was less consistent between the three
groups and was effected by self-esteem. As discussed, self-esteem was highly
correlated with the subjective quality of life of the three groups. Regression
analyses were run both with and without self-esteem. While self-esteem was not
acting as a suppressor variable, it nevertheless suppressed some of the variance in
other variables of the model. With self-esteem removed from the regression
analysis, perceived social support positively predicted the subjective quality of life
of the three groups. In addition, primary control negatively predicted for people
with MS, and positively predicted the subjective quality of life of partners.
Optimism was a positive predictor for controls. The analysis also revealed that the
effect of MS on life role predicted the subjective quality of life of people with MS
when the other psychological variables of the model were controlled.
Influence of Life Domains on Subjective Quality of Life
Regression analyses were undertaken in order to determine the relative
contribution of each domain to subjective quality for each group. Subjective
quality of life could not be used as the dependent variable in this analysis as the
life domains are components of the ComQol scale that measures subjective quality
of life. Self-esteem was selected as a substitute dependent variables as it correlates
highly with subjective quality of life (R2 = .60, p < .001 for controls, R2 = .68, p <
.001 for people with MS, R2 = .56, p < .001 for partners). Correlation matrices
were then generated for each group for the domains of ComQol and self-esteem to
test for the presence of multicollinearity and singularity. Pearson’s correlation coefficient was calculated for people with MS and controls. Spearman Rho’s co-
30
efficient was calculated for partners. The correlation matrices are shown in Table
8.17 to 8.19.
Most of the life domains were significantly correlated with other domains and
with self-esteem. There was some evidence of multicollinearity that weakens
regression analyses (Tabacknick & Fidell, 1996). ‘Happiness’ was removed from
the regression analyses due to the high correlation with self-esteem and other
domains. With seven independent variables, the ratio of cases to independent
variables in the analysis was low, especially for partners. However, the ratio was
greater than the minimum five to one ratio recommended by Coakes & Steed
(1999). Thus, the data were suitable for regression analyses.
Table 8.17.
Pearson Correlations between Satisfaction with ComQol Domains and Self-Esteem for Controls
Variables
Possessions
Health
Achieve
Intimacy
Safety
Community
Happiness
Independence
Self Esteem
Possessions
Health
Achieve
Intimacy
Safety
Community
Happiness
Independence
Self-Esteem
1.00
.40**
.38**
.18
.12
.24*
.39**
.38*
.35**
1.00
.31**
.26*
.37**
.30*
.50**
.45**
.31**
1.00
.45**
.35**
.28*
.65*
.45*
.45*
1.00
.50**
.46**
.58**
.33*
.37**
1.00
.69**
.50**
.32**
.46**
1.00
.42**
.48**
.41**
1.00
.53*
.52*
1.00
.03
1.00
* p < .05, ** p < .001, n = 93.
Table 8.18.
Pearson Correlations between Satisfaction with ComQol Domains and Self-Esteem for People with MS
Variables
Possessions
Health
Achieve
Intimacy
Safety
Community
Happiness
Independence
Self-esteem
Possessions
Health
Achieve
Intimacy
Safety
Community
Happiness
Independence
Self-esteem
1.00
.53**
.41**
.58**
.45**
.27*
.50**
.20
.44**
1.00
.58**
.33**
.36**
.27*
.34**
.33**
.42**
1.00
.34*
.34*
.23
.52*
.28*
.60**
1.00
.58**
.49**
.68*
.29*
.58**
1.00
.69**
.47*
.46**
.46**
1.00
.33*
.18
.30*
1.00
.45*
.63*
1.00
.30*
1.00
* p < .05, ** p < .001, n = 64.
31
Table 8.19.
Spearman Correlations between Satisfaction with ComQol Domains and Self-Esteem for Partners
Variables
Possessions
Health
Achieve
Intimacy
Safety
Community
Happiness
Independence
Self-esteem
Possessions
Health
Achieve
Intimacy
Safety
Community
Happiness
Independence
Self-esteem
1.00
.35*
.60**
.32
.46**
.46**
.37*
.45**
.32
1.00
.42**
.50**
.39*
.09
.52**
.51**
.62**
1.00
.50**
.30
.47**
.53**
.49**
.35*
1.00
.62**
.20
.80**
.64**
.58**
1.00
.46**
.58**
.58**
.38*
1.00
.24
.18
.19
1.00
.80**
.52**
1.00
.40*
1.00
* p < .05, ** p < .001, n = 37.
32
33
For controls, there was a significant R2 of .35 and an adjusted R2 of .30, F(7,85) =
6.61, p < .001. This indicates that the regression model accounted for 35% of the
variance in self-esteem. There was one significant predictor, satisfaction with
achievements positively influenced the self-esteem of controls (p < .05, sr12 = .03).
Table 8.20 shows the unstandardised regression co-efficients (B), the standard
error (SE B), the standardised regression co-efficients (), the semi-partial
correlations (sr12), the probability levels (t) and significance levels (p) for each
variable.
Table 8.20
Regression Analysis of the Effect of the Domains of ComQol on the Self-Esteem
of Controls
Variables in equation
Possessions
Health
Achieve
Intimacy
Safety
Community
Independence
R = .59, R2 = .35
Adjusted R2 = .30
Standard error = 10.64
F(7,85) = 6.61**
B
1.39
.27
1.76
.55
2.24
.76
-.21
SE B
.78
.77
.84
.97
1.20
.93
.88

.19
.04
.23
.06
.25
.11
-.03
t
1.80
.35
2.10
.57
1.86
.82
-.24
p
.08
.72
.04*
.57
.07
.41
.81
sr12
.03
.00
.03
.00
.03
.01
.00
* p < .05, ** p < .001; n = 93
For people with MS, There was a significant R2 of .53 and an adjusted R2 of .47,
F(7,56) = 8.93, p < .001. This indicates that the regression model accounted for
53% of the variance in self-esteem. There were two significant predictors. This
regression indicates that satisfaction with achievements (p < .001, sr12 = .12) with
close relationships (p < .05, sr12 = .07) positively influenced the self-esteem of
people with MS. This analysis is summarised in Table 8.21.
34
Table 8.21
Regression Analysis of the Effect of the Domains of the ComQol on the SelfEsteem of People with MS
Variables in equation
Possessions
Health
Achieve
Intimacy
Safety
Community
Independence
R = .73, R2 = .53
Adjusted R2 = .47
Standard error = 14.88
F(7,56) = 8.93**
B
-.01
.11
3.80
3.18
.75
-.27
.30
SE B
1.08
1.15
1.02
1.09
1.21
1.00
.90

-.00
.01
.43
.39
.08
-.03
.04
t
-.01
.09
3.72
2.93
.62
-.27
.34
p
.99
.93
.00**
.01*
.54
.79
.74
sr12
.00
.00
.12
.07
.00
.00
.00
* p < .05, ** p < .001; n = 64
For partners, there was a significant R2 of .47 and an adjusted R2 of .34, F(7,29) =
3.63, p < .05. This indicates that the regression model accounted for 47% of the
variance in self-esteem. There were two significant predictors. Satisfaction with
one’s health (p < .05, sr12 = .09) and close relationships (p < .05, sr12 = .10)
positively influenced the self-esteem of partners. This analysis is summarised in
Table 8.22.
Table 8.22
Regression Analysis of the Effect of the Domains of the ComQOL on the SelfEsteem of Partners
Variables in equation
Possessions
Health
Achieve
Intimacy
Safety
Community
Independence
R = .68, R2 = .47
Adjusted R2 = .34
Standard error = 10.61
F(7,29) = 3.63*
* p < .05, ** p < .001; n = 37
B
.12
2.59
-.71
3.65
-1.03
1.48
-.40
SE B
1.24
1.14
1.55
1.60
1.75
1.52
1.42

.02
.39
-.11
.55
-.13
.18
-.06
t
.10
2.26
-.46
2.28
-.59
.97
-.28
p
.92
.03*
.65
.03*
.56
.34
.78
sr12
.00
.09
.01
.10
.01
.02
.00
35
In summary, in regards, to the influence of the life domains on self-esteem, which
is highly related to subjective quality of life, satisfaction with happiness was
highly correlated for each of the groups. In addition, satisfaction with
achievements positively predicted the self-esteem of controls and people with MS.
Satisfaction with close relationships predicted the self-esteem of people with MS
and partners. Satisfaction with health predicted the self-esteem of partners.
Life Circumstances and Stressors
The stress caused by MS was assessed by asking ‘how severely does your/ or your
partner’s condition effect your ability to perform the role you would like to in
life?’ It was hypothesised that personality and perceived social support effect
perceptions of MS as a stressor. Specifically, that high neuroticism, low
extraversion, and low perceived social support correlate positively with the
perceived extent to which MS effects life roles.
In order to assess the influence of neuroticism, extraversion, and perceived social
support on this assessment of stress, these variables were entered into a multiple
regression with effect on life role as the independent variable for both people with
MS and partners.
For people with MS, there was a significant R2 of .20 and an adjusted R2 of .15,
F(4,59) = 3.72, p < .05. This indicates that the regression model accounted for
20% of the variance in the extent to which people perceived that MS effected their
life role. There were two significant predictors. Extraversion (p < .05, , sr12 = .09)
and perceived social support from pets (p < .05, , sr12 = .07) negatively predicted
the extent to which MS was perceived as effecting life roles. Table 8.23 shows the
unstandardised regression co-efficients (B), the standard error (SE B), the
standardised regression co-efficients (), the semi-partial correlations (sr12), the
probability levels (t) and significance levels (p) for each variable.
36
Table 8.23.
Regression Analysis of the Effect of Personality and Perceived Social Support on
Assessment of Life Role for People with MS
Variables in equation
Neuroticism
Extraversion
Perceived Social Support from people
Perceived Social Support from Pets
R = .45
R2 = .20
Adjusted R2 = .15
F (4,59) = 3.72*
B
-.03
-.14
-.07
-.07
SE B
.04
.06
.04
.03

t
p
-.10
-.32
-.23
-.27
-.69
-2.37
-1.87
-2.24
.49
.02*
.07
.03*
Sr12
.01
.09
.05
.07
* p < .05, n = 64.
The regression model was not significant for partners, indicating that neither
personality nor social support influenced the extent to which they perceived that
their partner’s MS influenced their ability to live the life they would like to.
The Mediating Role of Secondary Control
Hypothesis 3 predicted that secondary control mediates between positive
cognitive bias and subjective quality of life. The mediating role of secondary
control was tested through a series of regressions as recommended by Baron and
Kenny (1986). In order to test for mediation, three regression equations are
recommended. Firstly, the mediator (secondary control) is regressed on the
independent variable (positive cognitive bias). The dependent variable (subjective
quality of life) is then regressed on the independent variable (positive cognitive
bias). Finally, the dependent variable (subjective quality of life) is regressed both
on the independent variable (positive cognitive bias) and the mediator (secondary
control). Mediation is evidenced by an effect of the independent variable in both
the first equation and second equation, and an effect of the mediator on the
dependent variable in the third equation. If these conditions all hold, then the
effect of the independent variable on the dependent variable must be less in the
third equation than in the second. The analysis based on this hypothesis is
represented by the bold lines in Figure 8.5.
37
FIRST ORDER
DETERMINANTS:
Personality
SECOND ORDER
DETERMINANTS:
Internal Buffers
THIRD ORDER
MEDIATING
DETERMINANT
Perceived Social
Support
Extraversion
Neuroticism
Positive
Cognitive Biases
Self-Esteem
Optimism
Primary Control
Subjective
Quality
of Life
Secondary
Control
Environmental
Factors
Figure 8.5
Analysis of Hypothesis 3: The Mediating Role of Secondary Control
In order to undertake these analyses, the three positive cognitive biases: selfesteem, primary control and optimism were summed to form one total positive
cognitive bias score. In order for a total secondary control score to be generated
for each group, regression analyses were undertaken to determine which of the
five types of secondary control influenced subjective quality of life. Tables 8.24 to
8.26 shows the unstandardised regression co-efficients (B), the standard error (SE
B), the standardised regression co-efficients (), the semi-partial correlations
(sr12), the probability levels (t) and significance levels (p) for each group.
For controls, there was a significant R2 of .13 and an adjusted R2 of .08, F(5,87) =
2.49, p < .05. This indicates that the regression model accounted for 8% of the
variance in subjective quality of life. There was one significant predictor.
Ventilation (p < .05, , sr12 = .07) negatively predicted subjective quality of life.
38
Table 8.24.
Regression Analysis of the Effect of the Five Types of Secondary Control on the
Subjective Quality of Life of Controls
Variables in equation
Ventilation
Self-Protective Secondary Control
Situation Bias Secondary Control
Avoidant Secondary Control
Self-Affirmative Secondary Control
R = .35
R2 = .13
Adjusted R2 = .08
F (5,87) = 2.49*
B
-22.72
-2.83
-.17
-6.62
3.83

t
p
-.28
-.09
-.00
-.16
-.18
-2.61
-.73
-.03
-1.38
1.39
.01*
.47
.97
.17
.17
SE B
8.70
3.86
5.12
4.79
2.75
sr12
.07
.01
.00
.02
.02
* p < .05, ** p < .001; n = 93.
For people with MS, there was a significant R2 of .31 and an adjusted R2 of .25,
F(5,58) = 5.16, p < .05. This indicates that the regression model accounted for
25% of the variance in subjective quality of life. There were two significant
predictors. Ventilation (p < .001, sr12 = .23) and avoidant secondary control (p <
.05, sr12 = .12) negatively predicted subjective quality of life.
Table 8.25.
Regression Analysis of the Effect of the Five Types of Secondary Control on the
Subjective Quality of Life of People with MS
Variables in the equation
Ventilation
Self-Protective Secondary Control
Situation Bias Secondary Control
Avoidant Secondary Control
Self-Affirmative Secondary Control
R = .56
R2 = .31
Adjusted R2 = .25
F (5,58) = 5.16*
B
SE B

t
p
-56.70
.24
-6.13
-19.76
.92
12.85
4.29
9.00
6.13
4.97
-.50
.01
-.09
-.39
.03
-4.41
.06
-.68
-3.23
.19
.00**
.96
.50
.00**
.85
sr12
.23
.00
.01
.12
.00
* p < .05, ** p < .001; n = 65.
For partners, there was a significant R2 of .43 and an adjusted R2 of .33, F(5,31) =
4.62, p < .05. This indicates that the regression model accounted for 33% of the
39
variance in subjective quality of life. There were two significant predictors.
Ventilation (p < .05, sr12 = .14) negatively predicted and situation bias secondary
control (p < .001, sr12 = .31) positively predicted subjective quality of life.
Table 8.26.
Regression Analysis of the Effect of the Five Types of Secondary Control on the
Subjective Quality of Life of Partners
Variables in the equation
Ventilation
Self-Protective Secondary Control
Situation Bias Secondary Control
Avoidant Secondary Control
Self-Affirmative Secondary Control
R = .65
R2 = .43
Adjusted R2 = .33
F (5,31) = 4.62*
B
SE B

t
p
-44.92
-2.39
37.22
-13.00
.27
16.50
5.32
9.09
6.69
3.78
-.40
-.07
.66
-.30
.01
-2.72
-.45
4.09
-1.94
.07
.01*
.66
.00**
.06
.94
sr12
.14
.00
.31
.07
.00
* p < .05, ** p < .001; n = 65.
In summary, while ventilation negatively predicted the subjective quality of life of
the three groups, avoidant secondary control negatively predicted the subjective
quality of life of people with MS, and situation bias secondary control positively
predicted the subjective quality of life of partners.
A total secondary control score was generated for each of the groups based on
these regressions. For people with MS this score comprised of the sum of the
ventilation and avoidant secondary control scores. For partners this comprised the
sum of the ventilation score and the inverse of the situation bias secondary control
score. For controls this comprised the ventilation score only. The series of three
regressions recommended by Baron and Kenny (1986) were then undertaken for
each of the three comparison groups to test for the mediating role of secondary
control.
For controls, the analyses revealed that secondary control mediated between
positive cognitive biases and subjective quality of life. This was evidenced by the
40
three significant regression equations, and the reduced impact of positive
cognitive bias in the third equation (sr12 = .29) compared to the second (sr12 = .36).
These regression analyses are summarised in Table 8.27.
Table 8.27
Regression Analysis of the Mediating Effect of Secondary Control for Controls
Regressions
1. Regression of total secondary control on
total positive cognitive bias
R = .35
R2 = .12
Adjusted R2 = .11
F (1,91) = 12.80**
2. Regression of subjective quality of life on
total positive cognitive bias
R = .60
R2 = .36
Adjusted R2 = .36
F (1,91) = 51.99**
3. Regression of subjective quality of life on:
total positive cognitive bias
total secondary control
R = .61
R2 = .37
Adjusted R2 = .36
F (2,90) = 26.48**
* p < .05, ** p < .001, n = 93
B
-.02
SE B
.01

t
p
-.35
-3.58
.00**
.12
sr12
2.93
.41
.60
7.21
.00**
.36
2.78
-7.10
.43
7.17
.57
-.09
6.40
-.99
.00**
.33
.29
.01
41
For people with MS, the analyses revealed that secondary control mediated
between positive cognitive biases and subjective quality of life. This was
evidenced by the three significant regression equations, and the reduced impact of
positive cognitive bias in the third equation (sr12 = .27) compared to the second
(sr12 =.43). These regression analyses are summarised in Table 8.28.
Table 8.28
Regression Analysis of the Mediating Effect of Secondary Control for People with
MS
Regressions
1. Regression of total secondary control on
total positive cognitive bias
R = .46
R2 = .21
Adjusted R2 = .20
F (1,62) = 16.56**
2. Regression of subjective quality of life on
total positive cognitive bias
R = .66
R2 = .43
Adjusted R2 = .42
F (1,62) = 46.80**
3. Regression of subjective quality of life on:
total positive cognitive bias
total secondary control
R = .68
R2 = .46
Adjusted R2 = .44
F (2,61) = 25.81**
* p < .05, ** p < .001, n = 65
B
SE B

t
p
-.04
.01
-.46
-4.07
.00**
.21
3.11
.46
.66
6.84
.00**
.43
2.70
-9.75
.50
5.47
.57
-.19
5.37
-1.78
.00**
.08
.27
.03
sr12
42
For partners, the analyses revealed that secondary control mediated between
positive cognitive biases and subjective quality of life for the control group. This
was evidenced by the three significant regression equations, and the reduced
impact of positive cognitive bias (sr12 = .18) in the third equation compared to the
second (sr12 = .44). The regressions are summarised in Table 8.29.
Table 8.29
Regression Analysis of the Mediating Effect of Secondary Control for Partners
Regressions
1. Regression of total secondary control on
total positive cognitive bias
R = .56
R2 = .32
Adjusted R2 = .30
F (1,35) = 15.31**
2. Regression of subjective quality of life on
total positive cognitive bias
R = .66
R2 = .44
Adjusted R2 = .42
F (1,35) = 27.50**
3. Regression of subjective quality of life on:
total positive cognitive bias
total secondary control
R = .72
R2 = .51
Adjusted R2 = .48
F (2,34) = 16.75**

t
.02
.56
-3.91
.00*
.32
3.94
.75
.66
5.24
.00**
.44
3.09
-16.42
.90
8.64
.52
-.28
3.45
-1.90
.00*
.07
.18
.06
B
.05
SE B
p
sr12
* p < .05, ** p < .001, n = 37
In summary, consistent with hypothesis three, secondary control was found to
mediate between positive cognitive biases and subjective quality of life for each of
the three groups but to unequal extents. The reduction in the influence of positive
cognitive bias on subjective quality of life from the second regression equation to
the third was the most for people with MS (.26), then partners (.16), and least for
controls (.07).
43
The Role of Perceived Social Support
It was hypothesised that effect of perceived social support on subjective quality of
life is subject to a threshold effect such that it is more strongly associated with the
subjective quality of life for people under stress. The hypothesis stated:
Hypothesis 6: Perceived social support is more strongly correlated
with subjective quality of life for people with MS than partners and
controls.
The analysis based on this hypothesis is represented by the bold lines in Figure
8.6.
FIRST ORDER
DETERMINANTS:
Personality
SECOND ORDER
DETERMINANTS:
Internal Buffers
THIRD ORDER
MEDIATING
DETERMINANT
Perceived Social
Support
Extraversion
Neuroticism
Positive Cognitive
Biases
Self-Esteem
Optimism
Primary Control
Subjective
Quality
of Life
Secondary
Control
Environmental
Factors
Figure 8.6
Analysis of Hypothesis 6: The Threshold Effect of Perceived Social Support
44
In order to address this hypothesis, participants were categorised as perceiving
either high or low levels of social support. By doing so, interaction effects
between group membership and levels of perceived social support could be
explored through an ANOVA. The means (X) and standard deviations (SD) of
subjective quality of life at the two levels of perceived social support are shown in
Table 8.30.
Table 8.30.
Subjective Quality of Life by Group Membership and Level of Perceived Social
Support.
People with MS
Perceived Social Support
High Perceived Social Support
X
SD
Low Perceived Social Support
X
SD
Controls
N = 36
57.31
15.27
Partners of People
with MS
N= 21
68.78
13.84
N= 28
73.65
13.07
N= 16
81.25
11.39
N= 41
78.79
10.00
N = 52
72.93
12.22
In order to determine whether the effect of perceived social support on subjective
quality of life varied according to group membership, a two-way ANOVA of
subjective quality of life by group membership (i.e. person with MS, partner of a
person with MS, control) and perceived social support (i.e. high and low) was
undertaken seeking interaction effects. Levene’s Test was not significant at
p > .05, indicating that the data were suitable for the analysis. This analysis is
shown in Table 8.31.
45
Table 8.31
Analysis of Variance Examining the Interaction between Subjective Quality of
Life, Group Membership and Perceived Social Support
Source
Perceived Social Support
Group Membership
Perceived Social Support*Group Membership
F
36.22**
16.52**
3.88*
Power
1.00
1.00
1.00
²
.16
.15
.04
* p < .05. ** p < .001, ² = strength of association, n = 194
The analysis demonstrated a significant main effect for group membership,
perceived social support, and an interaction effect F(2,193) = 3.88, p < .05. The
interaction effect is shown in Figure 8.7
The
700
600
Subjective
Quality of
Life
500
PERSON WITH MS
PARTNER OF PWMS
400
Low
CONTROL
High
Perceived Social Support
Figure 8.7
The Interaction between Perceived Social Support, Group Membership and
Subjective Quality of Life
ANOVAs with subjective quality of life as the dependent variable were carried
out to explore the simple effects of the interaction between group membership,
46
level of perceived social support, and subjective quality of life. ANOVAs were
conducted to determine whether there was a main effect for level of social support
for each group. These are summarised in Table 8.32. Consistent with previous
analysis, high levels of perceived social support were associated with significantly
higher subjective quality of life than low levels of perceived social support for
each group.
Table 8.32
Univariate Analyses of Variance Examining the Difference in Subjective Quality
of Life between the Two Levels of Perceived Social Support
Source
People with MS
Partners of People with MS
Controls
F
21.76**
8.83**
6.16*
power
.99
.82
.69
²
.26
.20
.06
* p < .05, ** p < .001, ² = strength of association.
ANOVAs were also undertaken at each level of perceived social support (high and
low) to determine whether there was a main effect for group. These analyses
revealed a main effect of group at both low and high levels of perceived social
support. These two analyses are summarised in Table 8.33.
Table 8.33
Simple Effects of Group Membership at the Two Levels of Perceived Social
Support
Source
Low Perceived Social Support
High Perceived Social Support
F
14.47**
3.67*
power
.99
.66
²
.26
.07
* p < .05, ** p < .001, n = 194, ² = strength of association
Univariate tests revealed that in the low perceived social support condition the
subjective quality of life of people with MS was significantly lower than both
partners (p < .05) and controls (p < .001). In the high perceived social support
47
condition the subjective quality of life of people with MS was significantly lower
than partners (p < .05).
In summary, these findings support Hypothesis 6. Perceived social support
effected subjective quality of life differently between the three groups. People
with MS reported a lower subjective quality of life than the other two groups at
levels of low perceived social support. At levels of high perceived social support
their subjective quality of life differed only from partners.
It was hypothesised that perceived social support from pets is similarly more
strongly associated with subjective quality of life for people with MS than
partners and controls. An ANOVA revealed no significant difference in the
amount of perceived social support from pets between the three groups. Analyses
similar to that undertaken to explore the relative influence of perceived social
support from people, and primary and secondary control were not possible as
substantially fewer people responded to the questionnaire items pertaining to pets.
Specifically, 58 (of 93) controls, 26 (of 37) partners, and 48 (of 64) people with
MS responded to the items pertaining to pets. Splitting of perceived social
support from pets into levels (e.g. high and low) was not viable as it yielded too
few cases in each cell of the analysis. Thus, in order to determine the unique
effect of this support on subjective quality of life, a correlation matrix was
generated. The means (X), standard deviations (SD), and correlation co-efficients
of perceived social support from pets and subjective quality of life are shown in
Table 8.34.
48
Table 8.34.
Correlations between Perceived Social Support from Pets with Subjective Quality
of Life
Total Perceived
Social Support
from Pets
X 68.72
SD 28.13
Correlation with
Subjective Quality
of Life
.25*
Partners of People with MS
X 80.26
SD 18.93
.44**
Controls
X 68.39
SD 25.73
.05
Group
People with MS
* p < .05, ** p < .001.
While the control group reported no association between perceived social support
from pets and their subjective quality of life, people with MS reported a
significant positive association. In contrast with the hypothesis, partners reported
an even stronger positive association between perceived social support from pets
and their subjective quality of life.
The Adaptive Function of Primary and Secondary Control
Integral to the adaptive functioning of the model is the adaptive functioning of
primary and secondary control. It was hypothesised that:
Hypothesis 7: The use of secondary control is positively associated
with the subjective quality of life of people with MS and partners, but
not controls. The use of primary control is negatively associated with
the subjective quality of life of people with MS and partners, but not
controls.
Hypothesis 8: Individuals with high levels of both primary and
secondary control have a higher subjective quality of life than those
who exhibit a preference for either primary or secondary control.
49
The analysis based on this hypothesis is represented by the bold lines in Figure
8.8.
FIRST ORDER
DETERMINANTS:
Personality
SECOND ORDER
DETERMINANTS:
Internal Buffers
THIRD ORDER
MEDIATING
DETERMINANT
Perceived Social
Support
Extraversion
Neuroticism
Positive
Cognitive Biases
Self-Esteem
Optimism
Primary Control
Secondary
Control
Subjective
Quality
of Life
Environmental
Factors
Figure 8.8
Analysis of Hypothesis 7 and 8: The Adaptive Outcome of Primary and
Secondary Control
In order to explore the adaptive outcome of a balance between primary and
secondary control for the three groups a strategy similar to that utilised to explore
the effect of perceived social support and group membership on subjective quality
of life was undertaken. Similarly, the sample was split into groups based on
primary and secondary control levels. The sample was initially split into four
groups representing the four possible combinations of primary and secondary
control: high primary, high secondary; high primary, low secondary; low primary,
high secondary; low primary, low secondary. Unfortunately, this split yielded
groups with as few as four participants in some cells. Therefore, three groups
were retained for the analysis: high primary, high secondary; low primary, low
50
secondary; and a group called ‘unbalanced control’, which was a combination of
the two groups high primary, low secondary and low primary, high secondary.
The means and standard deviations of subjective quality of life for these three
groups are shown in Table 8.35.
Table 8.35.
Subjective Quality of Life by Group Membership and Relative Levels of Primary
and Secondary Control.
Levels of Control
People with MS
High Primary, High Secondary
X
SD
N = 25
62.86
13.14
Partners of People
with MS
N=8
85.63
7.10
Controls
Low Primary, Low Secondary
X
SD
N = 15
74.58
16.90
N = 16
71.72
15.77
N = 37
76.99
10.61
Unbalanced Control
X
SD
N = 24
64.69
17.49
N = 13
74.94
12.07
N = 37
74.73
12.05
N = 28
76.65
11.86
In order to determine whether the levels of primary and secondary control exerted
a different effect on subjective quality of life between the three groups, a two-way
ANOVA was conducted seeking interactions with subjective quality of life as the
dependent variable, and group membership (person with MS, partner, or control),
and levels of primary and secondary control as the factors. Levene’s was not
significant at p> .001 indicating that the data were suitable for this analysis. The
analysis is summarised in Table 8.36.
51
Table 8.36
Analysis of Variance Examining the Interaction between Subjective Quality of
Life and Levels of Control
Source
Levels of Control
Group Membership
Levels of Control*Group Membership
F
1.30
10.87**
3.29*
²
.01
.11
.07
power
.28
.99
.83
* p < .05. ** p < .001, n = 194, ² = strength of association
The analysis revealed a significant main effect for group membership, F(2,193) =
10.87, p < .001 and an interaction effect between levels of primary and secondary
control and group membership F(4,193) = 3.29, p < .05. The interaction is shown
in Figure 8.9.
700
600
Subjective
Quality
of Life
500
PERSON WITH MS
PARTNER OF PWMS
400
low primary
low secondary
CONTROL
unbalanced
hi primary
hi secondary
Figure 8.9
Interaction Between Relative Levels of Primary and Secondary Control and Group
Membership on Subjective Quality of Life.
52
ANOVAs with subjective quality of life as the dependent variable were carried
out to explore the simple effects of the interaction between group membership and
level of primary and secondary control. ANOVAs were conducted within each
group to determine whether the three levels of primary and secondary control
exerted an effect on subjective quality of life. There was no effect for each of the
three groups. Thus, subjective quality of life did not differ within the three groups
based on the relative use of primary and secondary control.
ANOVAs were also undertaken to determine whether there were differences
between the three groups on subjective quality of life at each level of control.
These analyses revealed a main effect of group at conditions of both high
primary/high secondary and unbalanced control for the three groups. Univariate
tests demonstrated that in the high primary/high secondary condition the
subjective quality of life of people with MS was significantly lower than both
partners and controls (p < .001). In the unbalanced control condition the subjective
quality of life of people with MS was also significantly lower than controls (p <
.05). The three analyses are summarised in Table 8.37.
Table 8.37
Simple effects of Group membership and Levels of Primary and Secondary
Control
Source
High Primary High Secondary
Unbalance
Low Primary Low Secondary
F
15.99**
3.95*
.79
Power
.99
.69
.18
²
.36
.11
.02
* p < .05, ** p < .001, n = 194, ² = strength of association
In summary, while the relative use of primary and secondary control did not differ
between controls and partners, people with MS reported a significantly lower
subjective quality of life than partners and controls in the unbalanced control and
high primary/high secondary control condition.
53
In order to determine whether primary and secondary control individually
interacted with group membership to influence subjective quality of life, the above
analysis was repeated examining separately levels of primary and secondary
control separately. The means (X) and standard deviations (SD) of subjective
quality of life for the three groups at the various levels of primary and secondary
control are shown in Table 8.38.
54
Table 8.38.
Subjective Quality of Life by Group Membership and Levels of Primary and
Secondary Control.
Levels of Control
People with MS
Partners of People
with MS
N = 13
84.65
7.86
Controls
High Primary
X
SD
N = 34
63.10
16.31
N = 40
76.34
12.18
Low Primary
X
SD
N = 30
69.92
15.69
N = 24
71.09
14.12
N = 53
76.11
10.80
High Total Secondary
X
SD
N = 40
63.77
13.09
N = 16
77.73
12.08
N = 49
75.72
11.60
Low Total Secondary
X
SD
N =24
70.52
20.00
N = 21
74.43
15.15
N = 44
76.65
11.23
High Ventilation
X
SD
N= 38
63.18
17.22
N = 21
72.26
15.79
N = 48
74.25
12.44
Low Ventilation
X
SD
N = 26
70.86
13.86
N = 16
80.58
9.17
N = 45
78.30
9.78
High Situation Bias
X
SD
N = 38
63.98
15.53
N = 16
82.08
11.89
N = 54
76.69
11.45
Low Situation Bias
X
SD
N = 26
69.71
16.97
N = 22
71.62
13.67
N = 39
75.55
11.34
High Self-Protective
X
SD
N = 32
64.31
14.01
N = 16
76.75
14.24
N = 28
75.19
11.76
Low Self-Protective
X
SD
N = 32
68.32
18.17
N = 21
75.25
13.84
N = 65
76.65
11.24
High Avoidant
X
SD
N = 36
63.15
14.56
N = 21
72.98
13.80
N = 37
75.20
8.13
Low Avoidant
X
SD
N = 27
70.60
17.66
N = 16
79.64
13.34
N = 56
76.88
13.09
High Self-Affirmative
X
SD
N =28
65.80
13.78
N = 16
76.95
12.67
N = 55
76.89
11.23
Low Self-Affirmative
X
SD
N = 35
66.79
18.18
N = 21
75.03
14.89
N = 38
75.23
11.62
55
In order to determine whether the effect of either primary or secondary control on
subjective quality of life varied according to group membership, a three-way
ANOVA of subjective quality of life by group membership (i.e. person with MS,
partner, or control), level of primary control, total secondary control level and the
levels of the five types of secondary control was undertaken seeking interaction
effects. Levene’s test was not significant at p> .001 indicating that the data were
suitable for this analysis. The analysis is shown in Table 8.39.
Table 8.39
Analysis of Variance Examining the Interaction between Subjective Quality of
Life and Levels of Primary and Secondary Control
F
10.73**
Power
.99
²
.11
Levels of Primary Control
Levels of Primary Control*Group Membership
1.92
5.51*
.28
.85
.01
.06
Levels of Secondary Control
Levels of Secondary Control*Group Membership
1.24
.87
.20
.20
.01
.01
12.91**
1.25
.95
.27
.07
.01
Levels of Situation bias
Levels of Situation bias*Group Membership
1.19
3.77*
.19
.68
.01
.04
Levels of Self-Protective
Levels of Self-Protective*Group Membership
.01
.06
.05
.06
.00
.01
7.85*
1.31
.80
.28
.04
.02
.46
.35
.10
.11
.01
.01
Source
Group Membership
Levels of Ventilation
Levels of Ventilation*Group Membership
Levels of Avoidant
Levels of Avoidant*Group Membership
Levels of Self-Affirmative
Levels of Self-Affirmative*Group Membership
* p < .05. ** p < .001, n = 194, ² = strength of association.
Consistent with previous analyses, there was a significant effect of group
membership. There was also a main effect for ventilation and avoidant secondary
control, with lower subjective quality of life associated with higher levels of both.
There was no significant effect for levels of secondary control, no significant
56
effect for levels of primary control and no interaction effect between secondary
control and group membership. However, there were two significant interaction
effects. There was an interaction effect between levels of primary control and
group membership F(2,188) = 6.34, p < .05, and one between levels of situation
bias secondary control and group membership F(2,188) = 3.77, p < .05 . The
simple effects of both are now analysed in turn. The interaction between primary
control and group membership is analysed first and is shown in Figure 8.10
700
600
Subjective
Quality of
Life
PERSON WITH
MS
PARTNER OF
PWMS
500
Low Primary Control
CONTROL
High Primary Control
Figure 8.10
The Interaction between Primary Control, Group Membership and Subjective
Quality of Life
ANOVAs were carried out to explore the simple effects of group membership of
the interaction between primary control and subjective quality of life. ANOVAs
were conducted for each group to determine whether there was a difference in
subjective quality of life between the two levels of primary control. The two
levels of primary control were associated with a significant difference in the
subjective quality of life of partners, F(3,33) = 9.80, p < .001, but not of the other
57
two groups. Partners reported a higher level of subjective quality of life at high
levels of primary control compared to low levels.
ANOVAs were also undertaken at each level of primary control (high and low) to
determine whether there were differences in subjective quality of life between the
three groups. These two analyses are summarised in Table 8.40.
Table 8.40.
Simple Effects of Group Membership on Subjective Quality of Life
Source
High Primary
Low Primary
F
16.88**
2.90
power
1.00
.56
²
.29
.05
* p < .05, ** p < .001, n = 194, ² = strength of association
In the high primary condition there was a significant effect of group on subjective
quality of life. Univariate tests revealed that in the high primary condition the
subjective quality of life of people with MS was significantly lower than both
partners and controls (p < .001).
The interaction between group membership, situation bias secondary control, and
subjective quality of life is now analsyed. This interaction is shown in Figure
8.11.
58
700
600
Subjective
Quality of
Life
PERSON WITH MS
PARTNER OF PWMS
500
Low Situation Bias
CONTROL
High Situation Bias
Figure 8.11
The Interaction between Situation Bias Secondary Control, Group Membership
and Subjective Quality of Life
ANOVAs were carried out to explore the simple effects the interaction between
group membership, situation bias secondary control and subjective quality of life.
ANOVAs were conducted for each group to determine whether there was a
difference in subjective quality of life between the two levels of situation bias
secondary control. The was a significant difference in subjective quality of life
between the two levels of situation bias secondary control for partners, F(3,33) =
5.82, p < .05, but not for the other two groups. Partners reported a higher level of
subjective quality of life at high levels of situation bias control compared to low
levels.
ANOVAs were also undertaken at each level of situation bias secondary control
(high and low) to determine whether there were differences in subjective quality
of life between the three groups. These three analyses are summarised in Table
8.41
59
Table 8.41.
Simple Effects of Group Membership, Situation Bias, and Subjective Quality of
Life
Source
High Situation Bias
Low Situation Bias
F
16.09**
1.79
power
1.00
.36
²
.24
.04
* p < .05, ** p < .001, n = 194, ² = strength of association
In the high situation bias condition there was a significant effect of group on
subjective quality of life. Univariate tests revealed that in the high situation bias
condition the subjective quality of life of people with MS was significantly lower
than both partners and controls (p < .001).
In summary, the adaptive outcome of primary and secondary control differed
between the three groups. There were no differences in subjective quality of life
within the groups based on relative levels of total primary and secondary control, .
However, when the three groups were compared it was apparent that people with
MS fared worse than the other two groups at balanced levels of control, and worse
still at levels of high primary and secondary control.
In regards to the use of secondary control, there were no differences in subjective
quality of life based on absolute levels of secondary control and there was no
interaction with group membership. However, when the five types of secondary
control were separately analysed, some differences between the groups were
evident. Ventilation negatively predicted the subjective quality of life of the three
groups, avoidant secondary control negatively predicted the subjective quality of
life people with MS, and situation bias secondary control positively predicted the
subjective quality of life of partners. There was one interaction effect that was
between situation bias secondary control and group membership. Partners
reported a higher subjective quality of life at conditions of high situation bias
secondary control. Also when the three groups were compared people with MS
60
fared significantly worse than the other two groups at high levels of situation bias
secondary control.
There was also an interaction between group membership and levels of primary
control. Partners were the only group who differed in their subjective quality of
life based on levels of primary control. They reported a higher subjective quality
of life at high levels of primary control. When the three groups were compared, it
was apparent that primary control effected subjective quality of life differently
between the three groups. Specifically, people with MS reported a lower
subjective quality of life compared to the other two groups, at levels of high
primary control.