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Predictors of psychosocial adjustment in systemic sclerosis.

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1398
ARTHRITIS & RHEUMATISM Volume 36
Number 10, October 1993, pp 1398-1405
0 1993, American College of Rheumatology
PREDICTORS OF PSYCHOSOCIAL ADJUSTMENT IN
SYSTEMIC SCLEROSIS
The Influence of Formal Education Level, Functional Ability, Hardiness,
Uncertainty, and Social Support
DEBRA K. MOSER, PHILIP J. CLEMENTS, MARY-LYNN BRECHT, and STEVEN R. WEINER
Objective. To determine predictors of psychosocial adjustment in patients with systemic sclerosis (SSc).
Methods. We surveyed 94 patients with SSc. Age,
sex, education level, marital status, work status, income, support group attendance, length of time since
diagnosis, functional status, social support, illnessrelated uncertainty, and hardiness were examined as
potential predictors of psychosocial adjustment. The
reliability and validity of the instruments used to measure these variables have been established.
ResuZts. Only education level, functional ability,
illness-related uncertainty, hardiness, and social support were predictive of psychosocial adjustment. Education level and functional ability explained 14% of the
variance in psychosocial adjustment, while illnessrelated uncertainty, hardiness, and social support increased the explained variance to 38%.
Conclusion. Although patients with relatively
poorer psychosocial adjustment to illness have lower
formal education levels and more functional disability,
the majority of the explained variance in psychosocial
From the Schools of Nursing and Medicine, University of
California, Los Angeles.
Supported in part by PHS grant M01RR-00865. Drs. Clements and Weiner are recipients of a Philip and Jane Williams
Fellowship in Scleroderrna.
Debra K. Moser, DNSc, RN: Assistant Professor, School
of Nursing, University of California, Los Angeles; Philip J. Clements, MD: Professor of Medicine, School of Medicine, University of
California, Los Angeles; Mary-Lynn Brecht, PhD: Principal Statistician, School of Nursing, University of California, Los Angeles;
Steven R. Weiner, MD: Associate Clinical Professor of Medicine,
School of Medicine, University of California, Los Angeles.
Address reprint requests to Debra K. Moser, DNSc, RN,
School of Nursing, University of California, Los Angeles, 10833 Le
Conte Avenue, Los Angeles, CA 900244918,
Submitted for publication July 7, 1992; accepted in revised
form March 30, 1993.
adjustment is ascribable to illness-related uncertainty,
low level of hardiness, and less satisfaction with social
support.
Understanding the role of psychosocial phenomena in adjustment to chronic rheumatic illnesses
such as systemic sclerosis (SSc; scleroderma) is important for several reasons. First, the process of
coping with chronic disease can take a significant
physical and psychological toll on patients and their
families. Problems with psychosocial adjustment become severe enough to be labeled clinical psychiatric
disorders in approximately 20% of patients with rheumatic diseases (1). Psychosocial distress is consequential not only because of the suffering it can cause
directly, but also because of the negative effect it can
have on work status, functional ability, assessment of
pain, perception of and preoccupation with disease,
and appraisal of the need for medical attention (2-5).
Second, although severity of disease or disability has been thought traditionally to correlate with
severity of psychosocial distress (649,newer and
more compelling evidence suggests that physical severity of disease alone is an inadequate predictor of
psychosocial adjustment (1,3,9,10). Thus, psychosocial adjustment to chronic illness is a more complex
process than was originally hypothesized.
Finally, study of psychosocial variables is essential because of their potential impact on physical
outcomes in chronic rheumatic diseases (11-13). Understanding psychosocial variables and the relationships among them is critical to an understanding of
physical disease activity.
Although SSc is associated with significant
chronic pain, disability, morbidity, early mortality,
1399
PSYCHOSOCIAL ADJUSTMENT IN SSc
and an unpredictable course (14-17), there has been
virtually no research concerning psychosocial adjustment in this disease. A review of related literature
reveals a number of sociodemographic and clinical
variables that could have an indirect effect on psychosocial adjustment because of their relationship to
disease severity and/or survival. These variables include age and sex in SSc (18), education level in
rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) (13,19,20), marital status in SLE (19),
time since diagnosis in RA (21), and functional status
in SLE (19). Social support (22,23), illness-related
uncertainty (24), and hardiness (22) have also proved
to be relevant constructs in rheumatic and other
chronic diseases.
Accordingly, the present study was undertaken
to determine predictors of psychosocial adjustment to
SSc from among a variety of potentially pertinent
sociodemographic, clinical, and psychosocial variables. We hypothesized that while better functional
ability would contribute to the prediction of better
psychosocial adjustment to illness, the psychosocial
variables of satisfaction with social support, presence
of hardiness, and less uncertainty regarding illness
would provide predictive power, beyond that of functional status, to the explanation of psychosocial adjustment to illness.
PATIENTS AND METHODS
Study sample. A convenience sample of 146 patients
who met the American College of Rheumatology (formerly,
the American Rheumatism Association) criteria for SSc (25)
was recruited over a 6-month period. Patient recruitment
was by referral from systemic sclerosis clinics or privatepractice physicians in southern and northern California, and
by announcements in scleroderma newsletters. Both in
referred patients and in those responding to newsletter
announcements, the diagnosis of SSc was confirmed by their
physician. Potential subjects were mailed a questionnaire
containing all of the instruments used in this study (see
below). Ninety-four patients (64%) completed and returned
the questionnaire. Reflective of the prevalence of SSc in the
population, the sample was predominantly female. The mean
SD age was 55 & 12 years, and the mean SD time since
diagnosis was 8 7 years. Characteristics of the group are
presented in Table 1.
Variables. Independent variables examined in this
study were as follows: current or past attendance at a
support group, time since diagnosis, age, sex, yearly household income, marital status, work status, formal education
level, functional status, satisfaction with social support,
hardiness, and illness-related uncertainty. The dependent
variable was psychosocial adjustment to illness.
*
*
*
Table 1. Characteristics of the 94 systemic sclerosis patients*
Mean f SD age, years
Mean SD years since diagnosis
Early disease (<I8 months since diagnosis)
Female
Marital status
Married
Unmarried
Education
Less than high school
Completed high school
Beyond high school
Work status
Disabled
Working part- or full-time outside home
Homemaker
Retired
Total annual household income
<$20,000
$20,000--39,999
$40,00040,000
>$60,000
Insurance status
Private insurance
Medicare
Medi-Cal
None
Have attended support group
Currently attending support group
*
5s 5 12
827
19 (20.3)
83 (88.3)
72 (76.6)
21 (22.3)
4 (4.3)
36 (38.3)
52 (55.2)
23 (24.5)
24 (25.5)
17 (18.1)
27 (28.7)
14 (16.0)
27 (28.7)
17 (18.1)
21 (22.3)
71 (75.5)
19 (20.2)
3 (3.2)
l(1.1)
58 (61.7)
41 (43.6)
* Except for age and years since diagnosis, values are the number
(%) .
Instruments. Dependent variable. Psychosocial adjustment to illness was measured by the Psychosocial Adjustment to Illness Scale (PAIS). The PAIS consists of 46
questions divided among 7 domains of adjustment to illness:
health care orientation, vocational environment, domestic
environment, sexual relationships, extended family relationships, social environment, and psychological distress (26).
Subjects check 1 of 4 choices ranging from no change, or
improvement related to illness, to markedly negative change
related to illness. In this study, the total PAIS score was
used to represent psychosocial adjustment to illness. Higher
scores signify poorer adjustment to illness. Construct, convergent, and predictive validity, and internal consistency
reliability have been established for the PAIS in cancer,
cardiac, and renal dialysis patients (26-28). In addition, the
PAIS has been widely used to measure psychosocial adjustment to illness in patients with a variety of chronic diseases
including SLE (19).
Independent variables. Data concerning current or
past attendance at a support group, time since diagnosis,
age, sex, marital status, income, work status, and formal
education level were collected from a self-report sociodemographic questionnaire.
Functional status was measured by the disability
section of the Health Assessment Questionnaire (HAQ) (30).
The disability section of the HAQ is a 24-item questionnaire
in which subjects rate their ability to perform activities of
daily living on a 4-point scale from 0 (no difficulty) to 3
(unable to do) for each item. An overall (average) disability
MOSER ET AL
1400
score was calculated by adding the item scores and dividing
by the number of items answered. Higher scores represent
higher disability. The level of test-retest reliability for the
HAQ disability scale in arthritis patients has been reported
to be 0.98 (31). Validity of the HAQ disability scale has been
established in patients with arthritis (29-31), SLE (19), and
SSc (32).
Satisfaction with social support was measured by the
Personal Resources Questionnaire-85, Part 2 (PRQ) (33).
The PRQ is constructed based on a multidimensional model
of social support which includes the following: 1) provision
for attachment and intimacy, 2) social integration, 3) opportunity for nurturant behavior, 4) reassurance of worth, and 5 )
availability of informational, emotional, and material assistance. This instrument is a 25-item questionnaire employing
a 7-point Likert scale. Higher scores on the PRQ indicate
greater availability of and satisfaction with social support.
Reliability has been demonstrated to be 0.87-0.91 (Cronbach’s alpha) in healthy adults and in spouses of multiple
sclerosis (MS) patients (33,34). Content, predictive, and
construct validity have been established in large samples of
healthy subjects (33,34).
Hardiness was measured by the Health-Related Hardiness Scale (HRHS) (35,36). Hardiness is a personality
style, and researchers believe that individuals who have a
high level of hardiness assess stressful situations optimistically, believe that they can change adverse situations, and
view changes as stimulating challenges (37). Individuals with
low hardiness have few resources to buffer stressful situations and are thus more vulnerable to the adverse effects of
stressful life events. The HRHS consists of 40 items requiring responses rated on a 6-point Likert scale. In the present
study the total score was used to represent the relative level
of the hardiness characteristic. Lower scores indicate higher
levels of hardiness.
The HRHS was developed specifically to measure
health-related hardiness in chronically ill subjects (35); the
Hardiness Scale originally developed by Kobasa (37) was
constructed for use in healthy individuals. The HRHS, as
does Kobasa’s Hardiness Scale, assesses health-related hardiness as a characteristic consisting of the elements of
commitment, control, and challenge. Health-related hardiness, however, differs from hardiness as defined by Kobasa
in that health-specific definitions for control, commitment,
and challenge form the construct. Additionally, construction
of the HRHS as a direct measure of health-related hardiness,
and use of positive and negative indicators for individual
items on the scale, successfully address some of the criticisms of Kobasa’s original scale.
The internal consistency reliability of the HRHS was
high in a mixed sample of adult patients with either MS, RA,
or hypertension (Cronbach’s alpha 0.89) (36), and the HRHS
demonstrated higher internal consistency when compared
with Kobasa’s Hardiness Scale. Test-retest reliability at 2
weeks was 0.90 in diabetes patients (36). Content and
construct validity for the HRHS have been established in
patients with diabetes, RA, hypertension, and MS (35,36).
Illness-related uncertainty was measured by the
Mishel Uncertainty in Illness Scale (MUIS) (38,39). Patients
experience uncertainty in illness when the meaning or significance of circumstances surrounding their illness is un-
Table 2. Mean scores, possible score ranges, and coefficient alphas for the instruments administered to the 94 systemic sclerosis
patients
Instrument
Mean rf: SD
Range
in study Possible in study Coefficient
sample
range sample
alpha
Mishel Uncertainty in
98 f 12 34-170 68-138
Illness Scale*
Health-Related
93 t 18 40-240 53-149
Hardiness Scale?
Personal Resources
144 2 20 25-175 52-92
Questionnaire-85t
0-3
Health Assessment
1.2 f 0.8 0-3
Questionnaire:
disability sections
0-138
5-78
Psychosocial Adjustment 36 -t 16
to Illness Scalell
0.84
0.77
0.86
0.87
0.84
* Mean 2 SD scores in other groups reported in the literature were
as follows: multiple sclerosis 89 2: 16, back pain 103 t 16, various
cancer diagnoses 77 t 16, and ischemic heart disease 93 t 15 (41).
t Mean ? SD score in a previously reported group of patients with
various chronic illnesses including rheumatoid arthritis 94 t 23 (36).
$ Mean 2 SD scores in other groups reported in the literature were
as follows: multiple sclerosis 141 2 17 (62), and healthy adults 142 2
17 (33).
8 Mean ? SD scores in other groups reported in the literature were
as follows: systemic sclerosis 0.92 f 0.05 (32), rheumatoid arthritis
0.82 (32), and systemic lupus erythematosus 0.66 (19).
7 Mean i SD scores in other groups reported in the literature were
as follows: heart transplant patients pretransplant 50 t 14 and heart
transplant patients 6 months posttransplant 36 f 18 (63).
clear and when ambiguities concerning diagnosis, prognosis,
symptoms, treatment, andlor relationships with caregivers
are present (24). The MUIS consists of 34 items rated on a
6-point Likert scale, and is composed of the 4 subscales of
ambiguity, complexity, deficient information, and unpredictability. The subscale scores are summed to obtain a total
scale score. Higher scores signify higher uncertainty. All
questions on the MUIS refer to attitudes and feelings regarding specific aspects of the illness and its treatment, prognosis, expected course, and symptoms.
Reliability of the MUIS has been demonstrated repeatedly through calculation of high levels of internal consistency (38-41). The standardized coefficient alpha for the
total scale has been reported to be 0.88 in a group of 202
subjects with a variety of chronic illness diagnoses (41), 0.90
in a group of 1,075 adult patients with a variety of diagnoses
(41), and 0.93 in cancer patients (40). Construct and convergent validity have been demonstrated in patients with a
variety of medical and surgical diagnoses and in cancer
patients (38).
Reliability. To establish\ the reliability of the standardized instruments used in the current study, internal
consistency was determined using Cronbach’s coefficient
alpha (42). Means, standard deviations, possible ranges, and
coefficient alphas for the instruments administered are presented in Table 2. Coefficient alpha in this study ranged from
0.77 to 0.87, indicating acceptable reliability for all instruments. To afford some perspective on the means reported in
PSYCHOSOCIAL ADJUSTMENT IN SSc
1401
this study, Table 2 also provides published means from other
patient groups. Caution must be used, however, in directly
comparing the means from different research studies.
Validity. Because there is limited psychosocial research in SSc, very few instruments have had their validity
established for use in these patients. To provide initial
evidence for the construct validity of each standardized
instrument used in this sample of SSc patients, we conducted the following analyses. Utilizing the contrasted
groups approach (43), we compared the HAQ scores of
patients who stated that they were disabled (n = 23) with
those of patients who were still working either full-time or
part-time (n = 24), using Student’s t-test. Disability was
defined as the inability to perform usual job activities due to
the effects of SSc. Subjects who were not working for
reasons other than disability were specifically distinguished
from disabled subjects. Disabled subjects reported significantly higher HAQ scores than subjects who were employed
(mean 5 SD 1.72 0.73 versus 1.06 k 0.82; P = 0.0005),
providing evidence for the construct validity of the HAQ.
Again using the contrasted groups approach, we
compared the MUIS scores in subjects for whom the time
since diagnosis was <12 months (n = 18) versus those for
whom it was >10 years (n = 31). The expectation based on
uncertainty theory (24) was that newly diagnosed patients
wouId exhibit significantly higher MUIS scores. As predicted, newly diagnosed patients did demonstrate significantly more illness-related uncertainty (mean
SD score
107.5 e 12.3 versus 95.2 16.9; P = 0.002), lending support
for the construct validity of the MUIS.
In the absence of other theoretically sound contrasting groups about whom assumptions could be made with
confidence (a prerequisite for the use of the contrasted
groups approach), we used convergent validity principles
(43) to supply evidence of the construct validity of the PAIS,
the HRHS, and the PRQ. Several predictions were made
concerning expected correlations among the instrument
scales, based on the theoretical constructs upon which they
were developed. The PRQ score, as a measure of perceived
social support, should correlate (inversely, due to the scoring direction) with scores on the domestic environment and
extended family relations subscales of the PAIS. Indeed, the
PRQ score was found to correlate with the domestic environment score (r = -0.36, P = 0.0006) and the extended
family relations score (r = -0.50, P = 0.0001). Scoring on
the HRHS, which draws upon items concerning attitudes
toward health and illness, should be correlated to the health
care orientation subscale score of the PAIS, and such was
found to be the case (r = 0.33, P = 0.001). The demonstrated
correlations were low to moderate, as would be expected for
instruments that measure related, but not identical, constructs. Taken together, these correlations support the constructs as defined and lend beginning support for the validity
of these instruments in this patient population.
Data analysis. Data are presented as the mean SD.
Multiple regression analysis was used to determine which of
the independent variables was predictive of psychosocial
adjustment to illness. Correlations between the continuous
independent variables (age, education level, length of diagnosis) and psychosocial adjustment to illness were calculated. The associations of the remaining noncontinuous
independent variables (sex, income, work status, marital
status, and support group attendance) with psychosocial
adjustment to illness were determined using Student’s t-test
or analysis of variance (ANOVA), where appropriate. Independent variables not correlated or associated with the
dependent variable were not included in the regression
model. Significance was set at P I0.01 to correct for the use
of multiple statistical tests.
*
*
*
*
RESULTS
Univariate analyses using t-tests, or ANOVA
when appropriate, were conducted to investigate associations between the noncontinuous independent
variables and the dependent variable of psychosocial
adjustment to illness as measured by the PAIS. There
were no differences in PAIS scores based on any of the
noncontinuous variables: prior or current support
group attendance versus never having attended a
support group (35.8 versus 36.2; P = 0.91), female
versus male (36.0 versus 36.1; P = l.O), married
versus unmarried (36.3 versus 35.4; P = O X ) , yearly
income categorized as <$20,000 versus $20,00140,000 versus $40,001-60,000 versus >$60,000 (37.9
versus 39.7 versus 34.6 versus 28.3; P = 0.09), and
work status defined as disability versus working fullor part-time outside the home versus homemaker
versus retired (38.2 versus 34.3 versus 34.1 versus
33.9; P = 0.43).
Correlation coefficients among the continuous
independent variables and the PAIS were calculated.
Patient age (r = -0.03, P = 0.75) and length of time
since diagnosis (r = -0.02, P = 0.87) were not
significantly correlated with the PAIS score. Education, functional status as measured by the HAQ,
satisfaction with social support as measured by the
PRQ, hardiness as measured by the HRHS, and illnessrelated uncertainty as measured by the MUIS were
significantly correlated with the PAIS score (Table 3).
For proper interpretation of these coefficients it is important to keep in mind the scoring direction of the
various instruments. Relatively better psychosocial adjustment to illness (lower PAIS score) was correlated
with higher education levels, better functional ability
(lower HAQ score), more satisfaction with social support (higher PRQ score), less illness-related uncertainty
(lower MUIS score), and higher levels of hardiness
(lower HRHS score).
Multiple regression analysis was used to determine predictors of psychosocial adjustment to illness
as measured by PAIS score from among the variables
correlated with or related to the PAIS in univariate
MOSER ET AL
1402
analysis: education level, functional status as measured by the HAQ, satisfaction with social support as
measured by the PRQ, hardiness as measured by the
HRHS, and illness-related uncertainty as measured by
the MUIS. The variables that were not correlated with
the PAIS on univariate testing were not included in the
regression model.
In order to test the hypothesis that the variables
of social support as measured by the PRQ, hardiness
as measured by the HRHS, and illness-related uncertainty as measured by the MUIS would provide predictive power to the explanation of psychosocial adjustment to illness beyond that of functional status as
measured by the HAQ, the HAQ score was entered
into the equation in a controlled manner. Education
level, as a preexisting characteristic, was also controlled in the analysis. MUIS, HRHS, and PRQ scores
were then entered into the equation in a stepwise
manner. The resulting model was statistically significant (F[5,80])= 9.84, P < 0.01). Education level was
entered first and was found to explain 6% of the
variance in the PAIS. HAQ score was entered second
and increased the explained variance to 14%. The
subsequent entry of MUIS, HRHS, and PRQ scores
increased the explained variance to 38%: PRQ score
entered the equation first after the controlled variables, followed by MUIS score and then HRHS score
(Table 4).
DISCUSSION
Poor psychosocial adjustment to chronic illness
can lead to increased perception of pain, increased
Table 3. Correlation coefficients between Psychosocial Adjustment to Illness Scale (PAIS) score and education level, Health
Assessment Questionnaire (HAQ) score, Personal Resources Questionnaire (PRQ) score, Mishel Uncertainty in Illness Scale (MUIS)
score, and Health-Related Hardiness Scale (HRHS) score in the 94
systemic sclerosis patients*
Independent
variable
Education
HAQ
PRQ
MUIS
HRHS
PAIS
(dependent
variable)
Education
-0.29t
0.36t
-0.43t
0.321
0.30t
-0.25$
0.14
-0.10
-0.01
HAQ
PRQ
0.03
0.04 -0.17
0.13 -0.32t
MUIS
0.31t
* The PAIS measures psychosocial adjustment to illness; the HAQ
measures functional ability; the PRQ measures presence of, and
satisfaction with, social support; the MUIS measures illness-related
uncertainty; the HRHS measures hardiness.
t P 5 0.005.
-tP 5 0.01.
Table 4. Multiple regression analysis of predictors of Psychosocial
Adjustment to Illness Scale (PAIS) score in the 94 systemic sclerosis
patients*
~
~~
Step
Variable
Cumulative
multiple RZ
b
SE
/3
1 (forced)
2 (forced)
3 (stepwise)
4 (stepwise)
5 (stepwise)
Education
HAQ
PRQ
MUIS
HRHS
0.06
0.14
0.32
0.37
0.38
-2.05
5.67
-0.29
0.27
0.08
1.4
1.7
0.08
0.12
0.09
-0.14
0.31
-0.37
0.21
0.09
* See Table 3 for definitions and explanations of PAIS and of the
instruments studied as independent variables.
preoccupation with disease, more frequent clinic visits, and increased functional disability in patients with
RA (1). Although these relationships have yet to be
demonstrated in systemic sclerosis, there is reason to
believe that they will hold true for this disease as well.
Identification of variables predictive of psychosocial
adjustment in SSc can be used to develop interventions to improve psychosocial adaptation to this potentially devastating chronic illness. In the present
study, education level, functional ability (as measured
by the HAQ), illness-related uncertainty (as measured
by the MUIS), hardiness (as measured by the HRHS),
and social support (as measured by the PRQ) were
predictive of, and explained 38% of the variance in,
psychosocial adjustment to illness as measured by the
PAIS. The variables of age, sex, income, marital
status, work status, time since diagnosis, and attendance at a support group were not related to psychosocial adjustment to illness. In interpreting these findings, one must keep in mind the usual caution
regarding the results of cross-sectional, correlational
studies; only relationships between variables are postulated, and causation cannot be evaluated.
Lower education level contributed a small, but
significant amount to the prediction of poorer psychosocial adjustment as assessed by total PAIS score.
Lower education level was also correlated with increasing functional disability as demonstrated by
higher HAQ score. The relationship of lower formal
education level to mortality and morbidity, including
functional status, in RA and SLE has been welldocumented (13,19,20). The mechanism whereby education predicts mortality and morbidity is unclear,
but several hypotheses have been advanced (44).
Many investigators believe that education acts as a
"surrogate" variable for socioeconomic status (13). In
this context, those with higher education levels may
have access to resources (better health care, material
and emotional assistance, better education about their
disease, less financial stress if disabled) which ulti-
PSYCHOSOCIAL ADJUSTMENT IN SSc
1403
mately have a positive impact on disease progression.
In the same way, higher education level may contribute to better psychosocial adjustment. Although the
finding of no relationship between income and PAIS
score may appear to be evidence against this explanation, income alone is not fully representative of socioeconomic status. Further research is needed to unravel the connection between education level and
psychosocial adjustment.
Functional status as measured by the HAQ
accounted for an additional 8% of the explained variance in PAIS score. The further addition of the variables of hardiness (HRHS score), illness-related uncertainty (MUIS score), and social support (PRQ
score) to the regression equation more than doubled
the variance explained by functional status and education level. The current results suggest that psychosocial adjustment in SSc cannot be explained by
characteristics of the disease alone. These findings
have been reflected in other studies on RA (45).
The psychosocial variables of illness-related
uncertainty as assessed by the MUIS, social support
as assessed by the PRQ, and hardiness as assessed by
the HRHS may exert their effects on overall psychosocial adjustment both directly and indirectly. Illnessrelated uncertainty may be particularly relevant to
psychosocial adjustment to SSc because of the diverse
and unpredictable course of the disease and the lack of
definitive information concerning treatment. Illnessrelated uncertainty has been associated with psychological distress in a variety of patient populations
(24,39,46) and with lower quality of life in RA patients
(47). Fortunately, illness-related uncertainty is modifiable through the use of interventions such as educational strategies, assistance to the individual in changing his or her appraisal of uncertainty, availability of
supportive health care providers, and strengthening of
the individual’s sources of social support (24,48).
Several investigators have identified social support as an important variable in determining physical
and psychological adaptation to chronic illness. There
is extensive evidence that social support buffers the
stress associated with illness, effectively mitigates
many of the consequences of physiologic and psychologic stressors, and positively influences health outcomes (49-52). Although social support has not been
studied in individuals with SSc, satisfaction with social
support has been correlated with psychological wellbeing in women with RA (23). Additionally, the combination of social support and the personality characteristic of hardiness is predictive of psychological
well-being in RA, regardless of the severity of the
illness (22). Subjective pain, observed pain behaviors,
and grip strength in RA patients are improved by
interventions that address social stress and lack of
social support (233). The strong relationship between
PRQ score as a measure of social support and PAIS
score as a measure of psychosocial adjustment to
illness demonstrated in the current study suggests that
attention to social support in SSc patients may yield
similar results.
Hardiness is believed to influence psychosocial
adjustment indirectly by mediating the effects of
stressful events associated with chronic illness. Work
by Kobasa and associates (3734) established the relationship between the presence of the hardiness characteristic and increased physical and psychological
well-being in individuals without chronic illness. Extending this work, Pollock et a1 (36) and others (22)
have demonstrated that hardiness promotes psychological and physical adaptation in chronic illness.
Hardiness may be used as a predictor of psychological
and physical adjustment to illness so that high-risk
patients can be targeted for early intervention. In
addition, preliminary research suggests that hardiness
can be taught and that such instruction results in
improved health outcomes (55).
The relationship between sociodemographic
variables and psychosocial adjustment has been explored frequently. The presumed assumption is that
variables such as age, sex, and work status indirectly
reflect disease activity. Although some investigators
have documented a relationship between various sociodemographic variables and physical measures of SSc,
RA, and SLE disease activity (18-20,56-58), the relationship does not extend to psychosocial adjustment
(19). Our finding that no relationship existed between
sociodemographic characteristics and psychosocial adjustment as measured by the PAIS is consistent with
previous work. Similarly, the finding that length of time
since diagnosis is unrelated to psychosocial adjustment
has been documented in RA (45).
Ours was not a controlled trial of support group
interventions, and it is likely that the various groups
involved were heterogeneous with regard to format
and patient contact. Despite this limitation, the finding
of no relationship between past or current attendance
at a support group and psychosocial adjustment to
illness is intriguing. Typically, support group activities
consist of a combination of patient education and
psychological support, and one of their aims is to
promote psychological adjustment. Numerous studies
have demonstrated the effectiveness of psychoeducational interventions in improving knowledge and
1404
health outcomes and positively affecting behavior in
RA (1239). However, not all support groups are
created equal, and there is wide variation in their
composition and objectives. Not all programs have
their intended effect, and the failure of some psychoeducational interventions highlights the importance of
ensuring that a given group has the requisite components to be effective (60).
Another point that must be considered when
evaluating the effectiveness of support groups is the
potential negative effects of these interventions, which
can attenuate any positive effects. Patients not as
severely disabled or affected as others in the group
may, when confronted with these more severe conditions that they may possibly face in the future, experience adverse effects. Depression, increased helplessness and fear, confusion, and an inappropriate sense of
personal responsibility for the disease have been documented in some patients participating in psychoeducational intervention programs (60). Thus, special
thought must be given to the elements of psychoeducational interventions, or even the appropriateness of
some group interventions, for certain patient groups.
Research regarding the content, timing, and appropriateness of support group interventions for SSc patients
should be undertaken before the general recommendation of support group participation is made.
Lack of a direct measure of disease severity in
this study may be a limitation. Investigators studying a
variety of chronic illness populations have demonstrated that severity of disease does not generally
correlate with psychosocial adjustment to illness, and
that relationships between psychosocial factors and
adjustment to illness are sustained after controlling for
severity of disease (1,3,9,10). However, it is still
conceivable that severity of disease may be an important factor in psychosocial adjustment to SSc, and
future investigations into psychosocial adjustment in
this illness should include a direct measure of disease
severity. Although the HAQ was not used in this study
as an indirect measure of disease severity, a recent
report suggests that the HAQ score correlates strongly
with the total skin score and with the presence of
visceral involvement in SSc (61).
In summary, although patients with relatively
poorer psychosocial adjustment to illness as demonstrated by higher PAIS scores have lower formal
education levels and more functional disability (higher
HAQ scores), the majority of the explained variance in
psychosocial adjustment is ascribable to illness-related
uncertainty (higher MUIS score), low level of hardiness (higher HRHS score), and less satisfaction with
MOSER ET AL
social support (lower PRQ score). Knowledge of factors that contribute to psychosocial adjustment to SSc
is vital in the development and testing of appropriate
interventions. The results of this study suggest that
treatment strategies aimed at improving illness-related
uncertainty, hardiness, and satisfaction with social
support may have a salutary effect on psychosocial
adjustment in SSc. It is also important to note that the
variables examined herein explained only 38% of the
variance in PAIS score as an indicator of psychosocial
adjustment to illness. Although this is significant, it
still leaves a majority of the variance unexplained.
Further investigation of the factors contributing to
psychosocial adjustment in systemic sclerosis is warranted.
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