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Predictors of exercise and effects of exercise on symptoms function aerobic fitness and disease outcomes of rheumatoid arthritis.

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Arthritis & Rheumatism (Arthritis Care & Research)
Vol. 57, No. 6, August 15, 2007, pp 943–952
DOI 10.1002/art.22903
© 2007, American College of Rheumatology
Predictors of Exercise and Effects of Exercise on
Symptoms, Function, Aerobic Fitness, and Disease
Outcomes of Rheumatoid Arthritis
Objective. To determine the effects of participation in a low-impact aerobic exercise program on fatigue, pain, and
depression; to examine whether intervention groups compared with a control group differed on functional (grip strength
and walk time) and disease activity (total joint count, erythrocyte sedimentation rate, and C-reactive protein) measures
and aerobic fitness at the end of the intervention; and to test which factors predicted exercise participation.
Methods. A convenience sample of 220 adults with rheumatoid arthritis (RA), ages 40 –70, was randomized to 1 of 3
groups: class exercise, home exercise using a videotape, and control group. Measures were obtained at baseline (T1), after
6 weeks of exercise (T2), and after 12 weeks of exercise (T3).
Results. Using structural equation modeling, overall symptoms (latent variable for pain, fatigue, and depression)
decreased significantly at T3 (P < 0.04) for the class exercise group compared with the control group. There were
significant interaction effects of time and group for the functional measures of walk time and grip strength: the treatment
groups improved more than the control group (P < 0.005). There were no significant increases in measures of disease
activity. Fatigue and perceptions of benefits and barriers to exercise affected participants’ amount of exercise, supporting
previous research.
Conclusion. This study supported the positive effects of exercise on walk time and grip strength, and demonstrated that
fatigue and perceived benefits/barriers to exercise influenced exercise participation. Furthermore, overall symptoms of
fatigue, pain, and depression were positively influenced in this selective group of patients with RA ages 40 –70 years.
KEY WORDS. Exercise; Rheumatoid arthritis; Exercise predictors; RA symptoms; Self-regulation.
Arthritis and other rheumatic diseases are leading causes
of disability in the US and are predicted to affect 60 million people by 2020 (1). Rheumatoid arthritis (RA) may
hasten functional decline over and above that associated
with aging. Fatigue, pain, and depression, hallmark symptoms of RA (2), may increase poor quality of life and
functional decline. Dynamic forms of exercise increase
Supported by a grant from the National Institute of Nursing Research of the NIH (R01-NR-04093).
Geri B. Neuberger, EdD, RN, Lauren S. Aaronson, PhD,
RN, FAAN, Byron Gajewski, PhD, Perri E. Cagle, PT, MS,
Janice K. Loudon, PT, PhD, Peggy A. Miller, RN, MS: University of Kansas Medical Center, Kansas City; 2Susan E.
Embretson, PhD: Georgia Institute of Technology, Atlanta.
Address correspondence to Geri B. Neuberger, EdD, RN,
University of Kansas School of Nursing, 3901 Rainbow Boulevard, Mail Stop 4043, Kansas City, KS 66160. E-mail:
Submitted for publication August 16, 2005; accepted in
revised form January 2, 2007.
muscle strength and endurance and help prevent agingrelated functional decline (3). Most persons with RA have
quite poor levels of aerobic fitness (4). In a prospective
study of older women (n ⫽ 6,632), slow gait, weak grip,
and limited exercise, all common in RA (3), were among
modifiable predictors of functional decline (5).
The Cochrane Review (6) assessed 6 randomized clinical
trials (RCTs) of dynamic exercise in persons with RA (7–
12): only 2 RCTs included fatigue (9,12) and only 2 included depression (11,12) as outcome measures. None described treatment allocation precisely, the median sample
size was 32, only 2 performed an intent-to-treat analysis
(7,12), 2 had blinded assessors (8,10), and 2 did not include full weight-bearing exercises (7,9). The Cochrane
Review concluded that dynamic exercise lasting 3 months
or less is effective in increasing aerobic capacity, muscle
strength, and joint mobility, with no detrimental effects on
disease activity or pain, and that effects of dynamic exercise on function and radiologic progression are unclear.
Assessment of additional health status measures, including fatigue, in future exercise studies was recommended
Neuberger et al
Table 1. Eligibility criteria for inclusion in the study*
Age 40–70 years
Confirmed RA diagnosis according to ACR (formerly the ARA) 1987 criteria (23)
Able to read and speak English
No history of fibromyalgia or severe COPD
Not taking a beta-blocker or digitalis medication
Not presently performing ⱖ30 minutes of aerobic exercise ⱖ3 times weekly
Have rheumatologist/physician approval to participate
Able to meet criteria for aerobic fitness testing (no arrhythmias, recent myocardial infarction, acute infection, uncontrolled
metabolic disease, known electrolyte abnormalities, or systolic BP ⬎200 mm Hg or diastolic BP ⬎115 mm Hg)
* RA ⫽ rheumatoid arthritis; ACR ⫽ American College of Rheumatology; ARA ⫽ American Rheumatism Association; COPD ⫽ chronic obstructive
pulmonary disease; BP ⫽ blood pressure.
(6). Another review of RCTs of aerobic and strengthening
exercises also supported positive effects of exercise on RA
Little is known, however, about factors that influence
exercising in persons with RA. Some studies found that
perceived benefits of exercise and self-efficacy significantly predicted exercise among patients with RA (4,14).
Other studies found that history of exercise and the rheumatologist’s current exercise behavior (15) were exercise
predictors. Social support for exercise and prior exercise
behavior (16) and postexercise perceptions of feeling better (17) also have been found to be important for exercise
We based our study on self-regulation theory, which
posits that individuals use goals to guide their behavior. If
a discrepancy is noted between a goal and one’s present
state, behavior is adjusted. If difficulty is encountered in
adjusting behavior, one assesses whether further effort will
achieve the goal. Outcome expectancy is the term used to
describe this assessment (18). According to self-regulation
theory, psychosocial variables (social support, self-efficacy
for exercise, barriers to and benefits of exercise, and optimism) influence outcome expectancy assessments (19).
One large (n ⫽ 309) RCT of high-intensity activities
(70 –95% of maximum heart rate [MHR]) versus usual care
demonstrated greater improvement in functional ability in
exercise participants (20). In contrast to that study of highintensity exercise, our study tested predictors and effects
of low-impact aerobic exercise, which is more realistic for
individuals with RA (21). We included a third group who
exercised at home using a videotape, which if effective
may more likely result in continued exercise. No other
RCTs were found that tested outcomes of class exercise
compared with home exercise and a no-exercise control
group. Nor were any studies found that tested a theoretical
model of predictors of exercise during an exercise intervention.
Based on previous literature and a one-group pilot study
that found increased aerobic capacity and grip strength
and decreased pain, fatigue, and walk time after 12 weeks
of exercise (22), we hypothesized that compared with a
no-intervention control group, 1) participation in a class
low-impact aerobic exercise program (C-Tx) or a home
exercise program using a videotape (H-Tx) would result in
less fatigue, pain, and depression among outpatients with
RA, and 2) participation in a C-Tx program or an H-Tx
program using a videotape would improve function (grip
strength and walk time) and aerobic fitness, with no differences in disease activity (erythrocyte sedimentation
rate, C-reactive protein [CRP] level, and total joint count).
In addition, we explored the following research question:
What baseline (T1) psychosocial (optimism, exercise benefits/barriers, social support, self-efficacy for exercise),
functional, aerobic fitness, symptoms, and disease activity
factors predict exercise participation among the 2 intervention groups?
Study protocol. After institutional review board approval, participants were recruited through an arthritis
clinic, private rheumatologists, media advertisements, and
posted flyers. Between 1996 and 1999, potential participants (n ⫽ 789) were assessed for eligibility (Table 1) and
404 were invited to participate (Figure 1). The 310 who
met the inclusion criteria, gave verbal consent, and had RA
diagnosis confirmed (23) were randomly assigned to 1 of
the 3 groups, stratified by sex using an a priori list of
randomly generated permutations of 3 numbers: 1 ⫽ C-Tx,
2 ⫽ H-Tx, and 3 ⫽ control. A total of 220 participants
completed the study (68 in the C-Tx, 79 in the H-Tx, and
73 in the control group). An a priori power analysis (24)
identified 53 participants per group as sufficient to determine treatment effects using analysis of variance (ANOVA;
␣ ⫽ 0.05, medium effect 0.25, power of 0.80). This was
increased for attrition and SEM analysis, resulting in a
need for complete data on 216 participants.
Sixty-two participants dropped out or were determined
as no longer eligible before attending the first assessment
session (T1), which was scheduled several months after
initial recruitment, and 28 dropped out after T1 (Figure 1).
Although we had no data on the 62 participants who
dropped out before T1, we compared the 28 who dropped
after T1 with those who completed the study on all variables. The only differences were that dropouts after T1
were more likely to be minorities (21% versus 9%), had
RA for more years (16.4 years versus 11.2 years), and took
longer to walk 50 feet at T1 (11.6 seconds versus 9.7
seconds). A check on random assignment confirmed no
significant group differences at T1 for functional, disease
activity, or aerobic fitness measures.
Exercise and RA
given their subjective exertion using the Talk Test (being
able to talk while exercising without being short of breath)
and the Borg scale (25). The instructor encouraged exercising at targeted levels, both in class and on videotape.
Participants were trained to take their pulse, prompted
when to do so, and recorded pulse rates after the aerobic
portion of each session. All participants reported the type
and amount of other exercise performed during the past
week at each assessment. The control group participated
in all assessments and was asked to keep exercise levels at
baseline amounts.
Figure 1. Flow chart of randomized clinical trial. T1 ⫽ baseline
assessment; T2 ⫽ 6-week assessment; T3 ⫽ 12-week assessment;
RA ⫽ rheumatoid arthritis; COPD ⫽ chronic obstructive pulmonary disease.
Written consent was obtained at T1. Measures were
obtained in clinic rooms at baseline (T1), midtreatment
(T2), and after the 12-week intervention (T3). All trained
assessors were blinded to participants’ group assignment.
The intervention was 12 weeks of low-impact aerobic
exercises for 1 hour 3 times a week. In low-impact aerobic
exercise one foot is always on the ground and there are no
running or jumping movements. C-Tx participants attended classes at a fitness center; H-Tx participants exercised at home using a videotape of the same exercise
program. The exercises consisted of 4 phases: warm-up,
low-impact aerobics, strengthening, and cool-down exercises. Distribution of minutes for each phase of exercise
(warm-up, aerobics, strengthening, and cool-down, respectively) was as follows: 20, 10, 20, and 10 for week 1; 15, 20,
15, and 10 for weeks 2–3; 10, 25, 20, and 5 for weeks 4 – 6;
and 10, 30, 15, and 5 for weeks 7–12.
Each treatment group participant was given their target
heart rate for 60% and 80% of their MHR and instructed to
start exercising at 60% and progress to 80% as tolerated,
Measures. Cronbach’s alpha, a measure of internal consistency reliability, was computed with T1 data for all
scales except the 1-item pain measures, and all were ⱖ0.81
(range 0.81– 0.96). All measures except social support, the
Life Orientation Test, and self-efficacy were used in our
pilot study (22).
Demographics. Information on age, sex, race, education,
income, marital status, work status, RA duration, and comorbidities were obtained at T1.
Symptoms. Fatigue was measured with the 14-item
Global Fatigue Index of the Multidimensional Assessment
of Fatigue questionnaire; a higher score indicated greater
fatigue (26). Measures of validity have been reported
Pain was measured with the Short Form of the McGill
Pain Questionnaire (28). Good reliability and validity have
been reported (29). In this study, the 1-item Present Pain
Intensity index and a 1-item pain description scale were
Depression was measured with the Center for Epidemiologic Studies Depression Scale. Responses to 20 statements were summed for a total score, with ⬎16 indicating
depressive symptoms (30). The 30-item Profile of Moods
States Short Form, a valid and reliable measure of mood
disturbance (31), was used for additional measures of depression and fatigue.
Disease activity. Disease activity was measured using
total joint count (TJC), erythrocyte sedimentation rate, and
CRP level (normal value ⫽ 0 mg/dl). TJC is the number of
tender and swollen joints (32) and is higher when RA is
active. The same trained research assistant (a clinical
nurse specialist) assessed each participant at each assessment period by palpating each joint. Erythrocyte sedimentation rate and CRP level measured RA inflammation (32)
using standard laboratory procedures (33).
Functional measures. Function was measured with grip
strength and walk time assessed by a physical therapist
(PT) or trained PT student. Grip strength, a recognized
functional measure in RA, has high test–retest reliability
and criterion validity (34). A blood pressure cuff connected to a portable sphygmomanometer was pumped to
20 mm Hg. Participants squeezed the cuff as hard as possible 3 times with each hand. A mean of the 3 measures
was used in the analyses.
Walk time, the number of seconds it takes to walk 50
feet, measured with a stopwatch, is another functional
measure in RA (35) with established reliability and validity (36). Each year a PT and trained PT students simulta-
neously assessed walk tests of 5 randomly selected participants, resulting in high interrater reliability.
Aerobic fitness level. Bicycle ergometer testing, using
the Astrand-Rhyming protocol, provided data for calculating estimated maximum oxygen consumption (VO2max) for
each participant (25). Estimated VO2max and maximal testing are highly correlated (r ⫽ 0.94) (37). The protocol,
conducted at T1 and T3 by a PT, involved pedaling on the
cycle for 6 minutes or until a steady-state heart rate was
achieved. A cardiac monitor with 5 electrodes monitored
heart rates. Either an all-extremity cycle or an arm cycle
test was used for 12 participants who had difficulty cycling. The all-extremity cycle also correlates highly (r ⫽
0.91) with maximal testing (38) whereas the arm cycle is
25% lower than maximal testing (39).
Psychosocial measures. Expectations about positive
outcomes in life were measured with the Life Orientation
Test at T1 and T3 (40). A higher score indicates greater
optimism and acceptable internal consistency (40) and
test–retest reliability have been reported (41).
The 43-item Exercise Benefits/Barriers Scale (42) measured perceived benefits (29 items) and barriers (14 items)
to exercising. With reverse scoring barrier items, a higher
total score indicates more perceived benefits and fewer
perceived barriers.
Social support was measured with the Medical Outcomes Social Support Survey, an 18-item questionnaire
that measures functional social support and has demonstrated validity (43). Self-efficacy was measured with the
mean of 2 confidence measures, a 9-item exercise selfefficacy scale with reported concurrent validity (44) and a
5-item measure of confidence in one’s ability to persist
with exercising when potential barriers exist (45). Construct validity has also been reported (45). Higher scores
indicate greater self-efficacy.
Exercise. For the treatment groups, amount of exercise
was calculated by summing mean minutes per week of the
aerobic portion of the intervention (half of each 1-hour
session completed) and the mean minutes per week of
other aerobic exercise reported at T2 and T3. Control
group participants also reported the number of minutes of
aerobic exercise per week at T2 and T3.
Medications. Participants reported all medications at
T1 and any medication changes at subsequent assessments. Arthritis medications were coded as either nonsteroidal antiinflammatory drugs or disease-modifying antirheumatic drugs (DMARDs).
Statistical analysis. Intent-to-treat was used in all analyses. Descriptive statistics were obtained for all variables
using SPSS software, version 8.0 (SPSS, Chicago, IL). Chisquare or ANOVA was used to test for differences in baseline variables among the groups. Missing data were limited
and random. In all cases, at least 80% of the items were
needed to calculate scale scores. Occasionally, participants’ mean scores on a daily measure (completed 1 week
following each assessment but not otherwise used in this
study) were used to replace a missing value. Means, standard deviations, medians, and ranges by group at all assessments are shown in Tables 2 and 3.
Neuberger et al
Structural equation modeling (SEM), a specialized parametric regression technique (46), was used to answer the
first hypothesis. Quantile-quantile plots confirmed normal
distribution of data. Each of the 3 symptoms was assessed
with 2 measures so that a latent variable for each symptom
was estimated. The overall fit of the SEM model was assessed using the Confirmation of Fit Index (CFI) (46). A CFI
score ⬍0.90 is considered inadequate, 0.90 – 0.94 is considered adequate, and ⬎0.95 is considered very good.
The advantage of SEM is that it accommodates multiple
measures of concepts and generates latent or unmeasured
variables. For example, instead of determining the effects
of 2 measures of depression, or deciding between them or
how to combine them if they are highly correlated (as
would be likely), the 2 measures serve as indicators of a
latent variable for depression in the model. This is a stronger measure of the concept of interest because it takes
advantage of more than 1 empirical measure and adjusts
for measurement error when calculating relationships involving the latent variable. Finally, latent variables for
overall symptoms were estimated combining fatigue, pain,
and depression. The overall symptoms score is essentially
a weighted average of the individual symptom scores. The
weights and calculation of overall symptoms are automatically determined in SEM. Group assignment was dummy
To answer the second hypothesis, after determining normality of data, repeated-measures ANOVA was conducted
to determine if there were significant group differences in
the functional, disease activity, and aerobic fitness measures over time, or for the interaction of time and group.
Repeated-measures ANOVA was used because we did not
have multiple measures of these variables in order to take
advantage of and use SEM as in the first hypothesis.
A classification and regression tree (CART) analysis was
used to answer the research question about predictors of
exercise. CART is a nonparametric regression model that
makes no assumptions about distribution of errors (47). It
provides a flexible exploratory analysis and allows identification of interactions among variables. CART does not
provide typical inferential measures such as P values.
Fitting a CART model results in a large tree with sets of
nodes. Each node represents a partition of the dependent
variable from binary cut points in the independent variables. Iterative process reduces the number of nodes, resulting in a more parsimonious model. In the CART
analysis, T1 measures of symptoms (fatigue, pain, depression), psychosocial measures (social support, self-efficacy
for exercise, perceived benefits of exercise, and optimism),
demographics (age, education, sex, duration of RA, number of comorbidities), functional measures (grip strength,
walk time), aerobic fitness, and disease activity measures
(erythrocyte sedimentation rate, CRP level, total joint
count) were examined as predictors of minutes of exercise.
The median age of the 220 participants was 55.5 years
(range 40 –70 years) and the median years with RA was 8.0
(range 0.5–50). Participants were predominantly white
* Values are the mean ⫾ SD (actual range). Sample sizes varied slightly due to missing values. Numbers for the C-Tx group were 66 – 68, for the H-Tx group were 75–79, and for control group were 68 –73.
MAF ⫽ Multidimensional Assessment of Fatigue; POMS ⫽ Profile of Mood States form; CES-D ⫽ Center for Epidemiological Studies Depressions Scale; ESR ⫽ erythrocyte sedimentation rate; CRP ⫽
C-reactive protein.
Global fatigue
24.91 ⫾ 10.25
20.08 ⫾ 10.15
21.88 ⫾ 9.80
23.38 ⫾ 11.57
19.52 ⫾ 9.11
20.04 ⫾ 11.34
20.74 ⫾ 11.61
19.23 ⫾ 10.55
20.88 ⫾ 11.20
(MAF) (possible
range 3–50)
POMS fatigue
1.53 ⫾ 0.98
1.16 ⫾ 0.81
1.52 ⫾ 0.82
1.61 ⫾ 1.05
1.29 ⫾ 0.81
1.42 ⫾ 0.92
1.35 ⫾ 1.08
1.23 ⫾ 0.91
1.37 ⫾ 1.03
(possible range
McGill Pain
4.67 ⫾ 2.14
3.88 ⫾ 1.90
4.14 ⫾ 2.31
4.98 ⫾ 2.34
4.56 ⫾ 2.12
4.49 ⫾ 2.26
4.05 ⫾ 2.24
4.15 ⫾ 1.94
4.34 ⫾ 2.25
(possible range
McGill description
2.00 ⫾ 1.02
1.71 ⫾ 0.84
2.01 ⫾ 1.11
2.16 ⫾ 1.14
1.87 ⫾ 0.90
2.07 ⫾ 0.95
1.67 ⫾ 1.13
1.78 ⫾ 0.88
1.95 ⫾ 1.03
of pain today
(possible range
CES-D depression
14.81 ⫾ 8.12
10.62 ⫾ 7.74
12.86 ⫾ 8.57
13.74 ⫾ 8.17
10.49 ⫾ 7.67
12.79 ⫾ 8.30
13.74 ⫾ 9.46
10.45 ⫾ 8.16
11.65 ⫾ 9.00
(possible range
POMS depression
0.59 ⫾ 0.67
0.46 ⫾ 0.59
0.62 ⫾ 0.63
0.47 ⫾ 0.58
0.44 ⫾ 0.60
0.42 ⫾ 0.53
0.49 ⫾ 0.62
0.36 ⫾ 0.67
0.42 ⫾ 0.62
(possible range
Total joint count
32.16 ⫾ 29.07
29.04 ⫾ 23.09
37.14 ⫾ 25.13
32.81 ⫾ 31.68
23.19 ⫾ 21.90
32.99 ⫾ 25.76
31.04 ⫾ 29.21
23.71 ⫾ 23.07
35.14 ⫾ 26.72
(possible range
ESR (mm/hour)
32.47 ⫾ 22.71
23.68 ⫾ 25.57
27.59 ⫾ 24.09
30.78 ⫾ 22.10
24.19 ⫾ 24.73
29.68 ⫾ 25.59
31.99 ⫾ 24.17
21.90 ⫾ 21.85
26.79 ⫾ 23.43
CRP (mg/dl)
1.33 ⫾ 2.00
1.25 ⫾ 1.58
1.30 ⫾ 1.76
1.20 ⫾ 1.47
1.07 ⫾ 1.25
1.14 ⫾ 1.42
1.13 ⫾ 1.36
0.86 ⫾ 1.03
1.02 ⫾ 1.21
Left grip strength 117.40 ⫾ 46.82 134.65 ⫾ 59.42 134.84 ⫾ 56.56 131.44 ⫾ 52.71 142.23 ⫾ 61.09 139.63 ⫾ 60.74 138.82 ⫾ 54.58 144.67 ⫾ 63.78 138.07 ⫾ 59.51
(mm hg;
possible range
Right grip strength 121.37 ⫾ 52.35 130.94 ⫾ 58.72 133.38 ⫾ 58.65 134.89 ⫾ 57.09 141.39 ⫾ 61.54 141.09 ⫾ 62.04 141.84 ⫾ 56.63 144.81 ⫾ 64.86 142.95 ⫾ 60.31
(mm hg;
possible range
Walk time
10.04 ⫾ 3.11
9.64 ⫾ 5.19
9.36 ⫾ 2.83
9.57 ⫾ 2.60
9.09 ⫾ 2.93
10.08 ⫾ 4.68
9.33 ⫾ 2.81
9.40 ⫾ 4.37
9.97 ⫾ 3.88
Table 2. Measures of symptoms, disease activity, and function at baseline (T1), 6-week (T2), and 12-week (T3) assessments for class treatment (C-Tx), home treatment
(H-Tx), and control group*
Exercise and RA
29.81 ⫾ 33.22
22.71 ⫾ 7.85
92.54 ⫾ 45.37
24.58 ⫾ 8.07
* Values are the mean ⫾ SD (actual range). Sample sizes varied slightly due to missing values. Numbers for the C-Tx group were 66 – 68, for the H-Tx group were 75–79, and for the control group were
68 –73. NA ⫽ not assessed; NC ⫽ not calculated (total mean minutes of aerobic exercise calculated only at T3); VO2max ⫽ estimated maximum oxygen consumption.
4.80 ⫾ 1.31
5.13 ⫾ 0.99
2.86 ⫾ 0.57
2.67 ⫾ 0.60
133.02 ⫾ 16.34 127.32 ⫾ 14.62
(94.19–169.00) (87.00–172.00)
Optimism (possible
2.71 ⫾ 0.67
2.76 ⫾ 0.61
2.66 ⫾ 0.61
2.76 ⫾ 0.61
range 0–4)
Exercise benefits
130.43 ⫾ 13.35 130.95 ⫾ 15.81 127.25 ⫾ 14.49 136.27 ⫾ 14.72 134.98 ⫾ 16.56 127.41 ⫾ 17.14 135.75 ⫾ 13.51
and barriers
(104.00–167.90) (102.00–166.00) (89.00–167.00) (100.68–172.00) (102.38–171.00) (86.00–169.00) (100.33–170.00)
(possible range
5.04 ⫾ 1.33
5.38 ⫾ 0.98
4.87 ⫾ 1.16
5.35 ⫾ 1.10
5.30 ⫾ 1.01
4.86 ⫾ 1.26
5.31 ⫾ 1.05
(possible range
Amount of exercise
85.45 ⫾ 36.30
aerobic exercise)
22.50 ⫾ 9.15
23.32 ⫾ 7.19
21.10 ⫾ 8.15
25.09 ⫾ 9.25
Aerobic fitness
(VO2max in ml/kg/
Neuberger et al
Table 3. Measures of psychosocial variables, exercise, and aerobic fitness at baseline (T1), 6-week (T2), and 12-week (T3) assessments for class treatment (C-Tx), home
treatment (H-Tx), and control group*
(85%), 9.5% were African American, 4.1% were Hispanic,
and 1.4% were Native American. The median education
category was some college, 82.7% were women, most
(70%) were married, 40% worked full time and 15.9%
worked part time, and the median income level was
$40,000 –$49,999. The only significant group differences
in demographics were for race (␹2 ⫽ 22.16, P ⬍ 0.001;
more minorities in the C-Tx group than in the H-Tx group)
and educational level. The H-Tx group had higher education than the control group (␹2 ⫽ 15.34, P ⬍ 0.001) but did
not differ from the C-Tx group. There were no significant
group differences in sex, age, duration of RA, number of
comorbidities, or number and type of medication changes
from T1 to T3. However, the control group had fewer
participants receiving DMARDs compared with the C-Tx
group at T1 (␹2 ⫽ 8.34, P ⬍ 0.02) and at T3 (␹2 ⫽ 6.06, P ⬍
0.05). Participation in the exercise intervention was similar (both the C-Tx and H-Tx groups completed a median of
30 of the 36 exercise sessions) with similar ranges (4 –36
for C-Tx, 3–36 for H-Tx).
Electrolytes, blood chemistries, hemoglobins, and hematocrits, obtained only to screen for other health problems,
were within normal limits or remained stable for all participants at all assessments. Thyroid-stimulating hormone
was measured at T1 to rule out hypothyroidism, which
could affect symptoms. There were no significant group
differences in number of participants needing thyroid replacement medication (␹2 ⫽ 0.202, P ⫽ 0.90) and no significant differences between cases and noncases on study
outcomes. Therefore, changes in rheumatology medications or other health problems were unlikely to affect
study outcomes.
For the first hypothesis, the model in Figure 2 is adequate (CFI ⫽ 0.91). Both overall symptoms at T1 and the
C-Tx/control group contrast were significant predictors of
overall symptoms at T3. Specifically, after controlling for
T1 overall symptoms, the C-Tx group was significantly
different from the control group (␤ ⫽ ⫺0.108, P ⬍ 0.04) on
overall symptoms at T3. There were no statistically significant differences in overall symptoms for the H-Tx group
compared with the control group.
For the second hypothesis, a Bonferroni correction for
10 repeated-measures ANOVAs resulted in setting a P
value ⱕ 0.005 for statistical significance (Table 4). The
second hypothesis was supported. There were significant
interaction effects for walk time (F ⫽ 4.52, P ⬍ 0.005) and
left grip strength (F ⫽ 3.84, P ⬍ 0.005). Significant time
effects were found for right grip strength (F ⫽ 28.42, P ⬍
0.005) and aerobic fitness (F ⫽ 27.84, P ⫽ 0.005). Although
not statistically different, the C-Tx group improved their
aerobic fitness level by 12%, the H-Tx group improved by
10%, and the control group improved by 7%. No detrimental effects of exercise on disease activity were found.
For the research question, CART was used to determine
the level of scores on all predictor variables that were most
predictive of exercise minutes. This analysis identified an
interaction of the Global Fatigue Index and the Exercise
Benefits/Barriers Scale scores. Participants with a global
fatigue score ⱖ31 exercised an average of 62 minutes per
week, whereas those with a global fatigue score ⬍31 exercised an average of 85 minutes each week. Among partic-
Exercise and RA
Figure 2. Structural equation modeling testing of effects of class exercise group or home
exercise group versus control group on fatigue, pain, and depression from baseline (T1) to
postintervention (T3). T1 or T3 after each measure ⫽ time period measure obtained either at
T1 or T3; Mafglob ⫽ Multidimensional Assessment of Fatigue Global Index Score; Poms-F ⫽
Profile of Mood States Fatigue subscale; McG-D ⫽ McGill Pain Questionnaire Description of
Pain; McG-I ⫽ McGill Pain Questionnaire Intensity of Pain; CESD ⫽ Center for Epidemiologic Studies Depression Scale; Poms-D ⫽ Profile of Mood States Depression subscale;
depress ⫽ depression. *P ⬍ 0.04; ** P ⬍ 0.001.
ipants with low fatigue, those with a score ⬍117 on the
Exercise Benefits/Barriers Scale exercised an average 62
minutes weekly, whereas those with a score ⱖ117 exercised an average of 95 minutes weekly.
The C-Tx group experienced a significant reduction in
overall symptoms after 12 weeks of exercise, whereas the
H-Tx group did not, despite participation in similar numbers of exercise sessions. The self-reported heart rates provide a plausible explanation. For the last 6 weeks of the
exercise intervention, 72% of the C-Tx participants were
exercising at 60% of their MHR and 16% were exercising
at 80% of their MHR. In contrast, only 45% of the H-Tx
group met the 60% criterion and only 4% met the 80%
criterion. Thus, the H-Tx group exercised at a lower intensity than the C-Tx group, despite participating in the same
number of sessions, and this may have contributed to less
symptom improvement. Other researchers report positive
effects for any amount of exercise and exercise intensity
when compared with a sedentary lifestyle (48). Additional
studies need to explore this possible intensity dose effect
of exercise on symptoms. Other factors, such as the interaction of the C-Tx group with the exercise instructor and
class participants, may have influenced ratings of symptoms in this study.
Both intervention groups decreased their walk time and
increased their left grip strength. These data support use of
the videotape by the H-Tx group as effective for functional
improvements and these improvements are consistent
with an earlier RCT (11) and our pilot study findings (22).
Increased grip strength is likely due to the strengthening
exercises of the intervention, which included work with
elastic exercise bands. Interpretation of the left grip
strength effect is tempered by the fact that the C-Tx group
had lower left grip strength at T1, although not a statistically significant effect. Right grip strength was nonsignificant for the interaction and may have occurred due to less
margin for improvement in the dominant right hand.
Functional improvements are important because slow gait
and weak grip are significant predictors of functional decline among elderly women in general (5), and among
persons with RA specifically (49).
Although improvement in aerobic fitness did not reach
statistical significance, the C-Tx group had the highest
percentage improvement (12%). Larger improvements
might have emerged if more participants in the treatment
groups actually exercised at their target heart rate or if the
exercise intervention continued beyond 12 weeks (3).
Other researchers (50) suggest that it may be helpful to
advise persons with low levels of activity to perform moderate-intensity exercise using 2 or 3 short bouts during the
day instead of 1 longer session. The fact that some of our
participants did not exercise at the intended intensity, or
for the entire 30 minutes of the aerobic phase, suggests this
may be a reasonable recommendation.
Fatigue and perceived benefits/barriers to exercise affected the amount of exercise performed. Participants with
lower fatigue participated in more minutes of exercise.
However, those with low fatigue who also had higher
(better) scores on perceptions of benefits/barriers engaged
in the most exercise. Perceptions of benefits and barriers
did not affect amount of exercise among those with high
fatigue. While we found an interaction of perceived benefits/barriers with fatigue, others have found perceived benefits alone to be a predictor of exercise in patients with RA
(4,14). Our findings reinforce the need for health providers
to educate patients with RA about the many benefits of
exercise, how to overcome barriers to exercise, and ways to
manage fatigue. Part of fatigue in patients with RA may be
due to a deconditioned state and regular aerobic exercise
may decrease the detrimental effects of fatigue.
Limitations of this study include self-reported data, the
fact that not all measures had been tested for reliability
and validity in patients with RA, and possible selection
bias from the convenience sample. Furthermore, absence
of data on the 62 participants who dropped out prior to T1
precluded comparing them with participants who completed the study. Therefore, our sample may be biased
Neuberger et al
Table 4. Analysis of variance for the main effect of time period, group, and interaction of time period with group on various
measures at baseline (T1), 6-week (T2), and 12-week (T3) for class treatment (C-Tx), home treatment (H-Tx), and
control group*
Exercise group
Aerobic fitness
Left grip strength
Right grip strength
Walk time
Total joint count
F values
Interaction of time
ⴛ exercise group
* NA ⫽ not assessed; ESR ⫽ erythrocyte sedimentation rate; CRP ⫽ C-reactive protein.
† P ⱕ 0.005.
toward more highly motivated participants. Lastly, with
respect to limitations, the control group may have been
less ill because fewer were receiving DMARDs.
In summary, this RCT, which used a larger sample than
any RCT in the Cochrane Review, supported the positive
effects of C-Tx and H-Tx exercise on walk time and grip
strength, and found that fatigue and perceived benefits/
barriers influenced exercise participation. Furthermore,
overall symptoms for fatigue, pain, and depression were
positively influenced in this selective group of patients
with RA. However, given the differences found between
the C-Tx and H-Tx groups, future studies should test use of
an exercise videotape in combination with some in-class
sessions. Our results also confirmed findings of 2 RCT
reviews of RA exercise (6,13) that exercise does not increase disease activity.
We acknowledge Herbert B. Lindsley, MD, and David Wilson, MD, who served as medical consultants, and Marian
Minor, PT, PhD, who served as an exercise consultant. We
also acknowledge the following former students who contributed to various aspects of this study: Marian Jamison,
Ruthellyn Hinton, Sandra David, Kathleen Thornton,
Mary Turnbull, Robert Spaniol, and Pat Twenter. Lastly,
we wish to thank the men and women who generously
gave their time and energy to participate in this study.
Dr. Neuberger had full access to all of the data in the study and
takes responsibility for the integrity of the data and the accuracy
of the data analysis.
Study design. Neuberger, Aaronson, Embretson, Cagle.
Exercise and RA
Acquisition of data. Cagle, Loudon.
Analysis and interpretation of data. Neuberger, Aaronson, Gajewski, Embretson, Miller.
Manuscript preparation. Neuberger, Aaronson, Gajewski, Embretson, Cagle, Loudon, Miller.
Statistical analysis. Aaronson, Gajewski, Embretson, Miller.
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