1. Symptom Cluster as a Predictor of Physical Activity in Multiple Sclerosis: Preliminary Evidence 
Robert W. Motl, PhD, Edward McAuley, PhD 
Journal of Pain and Symptom Management 
Volume 38, Issue 2, Pages (August 2009)
DOI: /j.jpainsymman
Copyright © 2009 U.S. Cancer Pain Relief Committee Terms and Conditions

2. Fig. 1
Single-factor model tested using confirmatory factor analysis for establishing the symptom cluster of fatigue, depression, and pain in the sample of 292 individuals with multiple sclerosis. All coefficients are standardized estimates.
Journal of Pain and Symptom Management  , DOI: ( /j.jpainsymman )
Copyright © 2009 U.S. Cancer Pain Relief Committee Terms and Conditions

3. Fig. 2
Mean scores and standard errors for the measures of fatigue, depression, and pain based on the low, moderate, and high symptom clusters identified in the cluster analysis with the sample of 292 individuals with multiple sclerosis.
Journal of Pain and Symptom Management  , DOI: ( /j.jpainsymman )
Copyright © 2009 U.S. Cancer Pain Relief Committee Terms and Conditions

4. Fig. 3
Model tested using covariance modeling for understanding the association between symptom cluster and physical activity behavior in a sample of 292 individuals with multiple sclerosis. All coefficients are standardized estimates. Accel = accelerometer counts.
Journal of Pain and Symptom Management  , DOI: ( /j.jpainsymman )
Copyright © 2009 U.S. Cancer Pain Relief Committee Terms and Conditions

5. Fig. 4
Mean scores and standard errors for the accelerometer counts and GLTEQ scores across the three groups of individuals with low, moderate, and high symptom experiences identified in the cluster analysis. Accelerometer data are expressed in units of original values × 10−4 so that the units are easily graphed and compared in magnitude with GLTEQ scores.
Journal of Pain and Symptom Management  , DOI: ( /j.jpainsymman )
Copyright © 2009 U.S. Cancer Pain Relief Committee Terms and Conditions

6. Fig. 5
Model tested using covariance modeling for understanding the associations among symptom cluster, self-efficacy, functional limitation, and physical activity behavior in a sample of 292 individuals with multiple sclerosis. All coefficients are standardized estimates. Solid lines represent statistically significant paths, and dashed lines represent nonsignificant paths. Accel = accelerometer counts.
Journal of Pain and Symptom Management  , DOI: ( /j.jpainsymman )
Copyright © 2009 U.S. Cancer Pain Relief Committee Terms and Conditions