CG16
The Effects of Learning on Cognitive Fatigue in MS

Thursday, June 2, 2016
Exhibit Hall
Gabriel Hoffnung, MA , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Nicholas A Vissicchio, B.A. , Yeshiva University Ferkauf Graduate School of Psychology, Bronx, NY
Jeffrey G Portnoy, B.A. , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Eliana Pasternak, B.A. , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Lisa Glukhovsky, M.A. , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Mary Ann Picone, M.D. , Holy Name Medical Center, Teaneck, NJ
Frederick W Foley, Ph.D. , School of Psychology, Yeshiva University, New York, NY
PDF


Background: Both cognitive and fatigue symptoms are highly common in multiple sclerosis (MS) and complaints of cognitive fatigue are also common. Learning is known to enhance performance, though not necessarily to overcome fatigue.

Objectives: To measure learning effects on a measure of cognitive fatigue in MS.

Methods: This research is being conducted as part of a large, ongoing, study at the MS Center of Holy Name Medical Center in Teaneck, NJ. N= 38 patients with definite MS have been recruited so far (current to the date of submission of this abstract). The study is being carried out using the Symbol Digit Modalities test (SDMT), a well validated cognitive measure in MS. Each patient is being administered the SDMT twice with approximately 3 to 5 minutes between each administration. Fatigue in this study is being operationalized as the difference in performance on the SDMT between the first 30 seconds (30”) and the final 30 seconds (90”) of a 90 second administration. Learning is operationalized as performance on administration two as compared to administration one. A mixed between-within (group x time) analysis of variance, was performed to compare fatigue between the two administrations.

Results: Mean (and standard deviation) for total scores on all SDMT trials (N=74) was 54.6(12.4). Mean total score for trial 1 (n=37) and trial 2 (n=37) of the SDMT were 52.6(11.8) and 56.5(12.8) respectively. Mean score for the 30” interval was 20.25(4.39) for the total sample and 19.54(4.05) and 20.97(4.65) for trials 1 and 2. Mean score for the 90” interval was 17.20(4.01) for the total sample and 16.72(4.56) and 17.67(4.05) on trials 1 and 2. A significant fatigue effect (30” vs. 90”) was noted in both the total sample (t= 10.956, p<.001) as well as on trials 1 and 2 (t= 6.799, p< .001; t= 8.783, p< .001). Learning effects were significant between trials 1 and 2 on total score (t= -5.408, p< .001), as well as at 30” and 90” (t= -4.498, p< .001; t= -2.697, p= .011).  However, there was no significant group x time effect, (Wilks’s Lambda = .987, F= .475, p= .624).

Conclusions: While learning has a significant effect on performance, and the learning effect on performance is present throughout task duration, learning does not significantly affect fatigue.