Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-24T23:42:50.443Z Has data issue: false hasContentIssue false
  • English
  • Français

A Multidimensional Assessment of Metacognition Across Domains in Multiple Sclerosis

Published online by Cambridge University Press:  10 August 2020

Audrey Mazancieux Open the ORCID record for Audrey Mazancieux [Opens in a new window] ,
Chris J.A. Moulin ,
Olivier Casez  and
Céline Souchay
Audrey Mazancieux*
Affiliation:
LPNC CNRS 5105, Université Grenoble Alpes, Grenoble, France
Chris J.A. Moulin
Affiliation:
LPNC CNRS 5105, Université Grenoble Alpes, Grenoble, France Institut Universitaire de France, Paris, France
Olivier Casez
Affiliation:
Department of Neurology, Université Grenoble Alpes, Grenoble, France
Céline Souchay
Affiliation:
LPNC CNRS 5105, Université Grenoble Alpes, Grenoble, France
*
*Correspondence and reprint requests to: Audrey Mazancieux: 1251 avenue Centrale, St Martin d’Hères, 38040GrenobleFrance. Email: audrey.mazancieux@univ-grenoble-alpes.fr
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

In neurological diseases, metacognitive judgements have been widely used in order to assess the degree of disease awareness. However, as yet little research of this type has focused on multiple sclerosis (MS).

Method:

We here focused on an investigation of item-by-item metacognitive predictions (using feeling-of-knowing judgements) in episodic and semantic memory and global metacognitive predictions in standard neuropsychological tests pertinent to MS (processing speed and verbal fluency). Twenty-seven relapsing–remitting MS (RR-MS) patients and 27 comparison participants took part.

Results:

We found that RR-MS patients were as accurate as the group of comparison participants on our episodic and semantic item-by-item judgements. However, for the global predictions, we found that the MS group initially overestimated their performance (ds = .64), but only on a task on which performance was also impaired (ds = .89; processing speed). We suggest that MS patients, under certain conditions, show inaccurate metacognitive knowledge. However, postdictions and item-by-item predictions indicate that online metacognitive processes are no different from participants without MS.

Conclusion:

We conclude that there is no monitoring deficit in RR-MS and as such these patients should benefit from adaptive strategies and symptom education.

Keywords

Multiple sclerosisMetacognitionSelf-awarenessMetamemoryAnosognosia
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 27 , Issue 2 , February 2021 , pp. 124 - 135
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Basso, M.R., Shields, I.S., Lowery, N., Ghormley, C., Combs, D., Arnett, P.A., & Johnson, J. (2008). Self-reported executive dysfunction, neuropsychological impairment, and functional outcomes in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 30(8), 920–930.CrossRefGoogle ScholarPubMed
Beatty, W.W., & Monson, N. (1991). Metamemory in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 13(2), 309–327.CrossRefGoogle ScholarPubMed
Beck, A.T., Steer, R.A., & Brown, G.K. (1996). Beck depression inventory-II. San Antonio, 78(2), 490–498.Google Scholar
Calabrese, P. (2006). Neuropsychology of multiple sclerosis. Journal of Neurology, 253, 10–15.CrossRefGoogle ScholarPubMed
Carone, D.A., Benedict, R.H.B., Munschauer, F.E. III, Fishman, I., & Weinstock-Guttman, B. (2005). Interpreting patient/informant discrepancies of reported cognitive symptoms in MS. Journal of the International Neuropsychological Society, 11(5), 574–583.CrossRefGoogle ScholarPubMed
Chiaravalloti, N.D., & DeLuca, J. (2008). Cognitive impairment in multiple sclerosis. The Lancet Neurology, 7(12), 1139–1151.CrossRefGoogle ScholarPubMed
Connor, L.T., Dunlosky, J., & Hertzog, C. (1997). Age-related differences in absolute but not relative metamemory accuracy. Psychology and Aging, 12(1), 50–71.CrossRefGoogle Scholar
Drew, M., Tippett, L.J., Starkey, N.J., & Isler, R.B. (2008). Executive dysfunction and cognitive impairment in a large community-based sample with Multiple Sclerosis from New Zealand: a descriptive study. Archives of Clinical Neuropsychology, 23(1), 1–19.CrossRefGoogle Scholar
Ernst, A., Blanc, F., Voltzenlogel, V., De Seze, J., Chauvin, B., & Manning, L. (2013). Autobiographical memory in multiple sclerosis patients: assessment and cognitive facilitation. Neuropsychological Rehabilitation, 23(2), 161–181.CrossRefGoogle ScholarPubMed
Fisk, J.D., Ritvo, P.G., Ross, L., Haase, D.A., Marrie, T.J., & Schlech, W.F. (1994). Measuring the functional impact of fatigue: initial validation of the fatigue impact scale. Clinical Infectious Diseases, 18, 79–83.CrossRefGoogle ScholarPubMed
Flavell, J.H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906–911.CrossRefGoogle Scholar
Fleming, S.M., & Lau, H.C. (2014). How to measure metacognition. Frontiers in Human Neuroscience, 8, 443.CrossRefGoogle ScholarPubMed
Green, D.M., & Swets, J.A. (1966). Signal Detection Theory and Psychophysics (Vol. 1). New York: Wiley.Google Scholar
Hertzog, C. (1992). Improving memory: the possible roles of metamemory. In Memory Improvement (pp. 61–78). Springer, New York.CrossRefGoogle Scholar
Higham, P.A. (2011). Accuracy discrimination and type-2 signal detection theory: clarifications, extensions, and an analysis of bias. In Constructions of Remembering and Metacognition (pp. 109–127). Palgrave Macmillan, London.CrossRefGoogle Scholar
Kesselring, J., & Klement, U. (2001). Cognitive and affective disturbances in multiple sclerosis. Journal of Neurology, 248(3), 180–183.CrossRefGoogle ScholarPubMed
Kinsinger, S.W., Lattie, E., & Mohr, D.C. (2010). Relationship between depression, fatigue, subjective cognitive impairment, and objective neuropsychological functioning in patients with multiple sclerosis. Neuropsychology, 24(5), 573–580.CrossRefGoogle ScholarPubMed
Kuznetsova, A., Brockhoff, P.B., & Christensen, R.H.B. (2017). lmerTest package: tests in linear mixed effects models. Journal of Statistical Software, 82(13).CrossRefGoogle Scholar
Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863.CrossRefGoogle ScholarPubMed
Maor, Y., Olmer, L., & Mozes, B. (2001). The relation between objective and subjective impairment in cognitive function among multiple sclerosis patients-the role of depression. Multiple Sclerosis Journal, 7(2), 131–135.Google ScholarPubMed
Mazancieux, A., Souchay, C., Casez, O., Moulin, C.J.A. (2019). Metacognition and self-awareness in multiple sclerosis. Cortex, 111, 238–255.CrossRefGoogle ScholarPubMed
McGlynn, S.M., & Schacter, D.L. (1989). Unawareness of deficits in neuropsychological syndromes. Journal of Clinical and Experimental Neuropsychology, 11(2), 143–205.CrossRefGoogle ScholarPubMed
Mograbi, D.C., & Morris, R.G. (2014). On the relation among mood, apathy, and anosognosia in Alzheimer’s disease. Journal of the International Neuropsychological Society, 20(1), 2–7.CrossRefGoogle ScholarPubMed
Moulin, C.J., Perfect, T.J., & Jones, R.W. (2000). Global predictions of memory in Alzheimer’s disease: evidence for preserved metamemory monitoring. Aging, Neuropsychology, and Cognition, 7(4), 230–244.CrossRefGoogle Scholar
Nelson, T. (1984). A comparison of current measures of the accuracy of feeling-of-knowing predictions. Psychological Bulletin, 95(1), 109–133.CrossRefGoogle ScholarPubMed
Nelson, T.O., & Narens, L. (1990). The psychology of learning and motivation. In Metamemory: A Theoretical Framework and New Findings.Google Scholar
O’Brien, A., Gaudino-Goering, E., Shawaryn, M., Komaroff, E., Moore, N.B., & DeLuca, J. (2007). Relationship of the Multiple Sclerosis Neuropsychological Questionnaire (MSNQ) to functional, emotional, and neuropsychological outcomes. Archives of Clinical Neuropsychology, 22(8), 933–948.CrossRefGoogle ScholarPubMed
Pannu, J.K., & Kaszniak, A.W. (2005). Metamemory experiments in neurological populations: a review. Neuropsychology Review, 15(3), 105–130.CrossRefGoogle ScholarPubMed
Phillips, L.J., & Stuifbergen, A.K. (2006). Predicting continued employment in persons with multiple sclerosis. Journal of Rehabilitation, 72(1), 35–43.Google Scholar
Planche, V., Gibelin, M., Cregut, D., Pereira, B., & Clavelou, P. (2016). Cognitive impairment in a population-based study of patients with multiple sclerosis: differences between late relapsing−remitting, secondary progressive and primary progressive multiple sclerosis. European Journal of Neurology, 23(2), 282–289.CrossRefGoogle Scholar
Prakash, R.S., Snook, E.M., Lewis, J.M., Motl, R.W., & Kramer, A.F. (2008). Cognitive impairments in relapsing-remitting multiple sclerosis: a meta-analysis. Multiple Sclerosis Journal, 14(9), 1250–1261.CrossRefGoogle ScholarPubMed
Prigatano, G.P. (1999). Principles of neuropsychological rehabilitation. New York: Oxford University Press.Google Scholar
Rabbitt, P. (Ed.). (2004). Methodology of frontal and executive function. London: Psychology Press.CrossRefGoogle Scholar
Randolph, J.J., Arnett, P.A., & Freske, P. (2004). Metamemory in multiple sclerosis: exploring affective and executive contributors. Archives of Clinical Neuropsychology, 19(2), 259–279.CrossRefGoogle ScholarPubMed
Rao, S.M., Leo, G.J., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology, 41(5), 685–691.CrossRefGoogle ScholarPubMed
Roberg, B.L., Bruce, J.M., Lovelace, C.T., & Lynch, S. (2012). How patients with multiple sclerosis perceive cognitive slowing. The Clinical Neuropsychologist, 26(8), 1278–1295.CrossRefGoogle ScholarPubMed
Rosti-Otajärvi, E., Ruutiainen, J., Huhtala, H., & Hämäläinen, P. (2014). Relationship between subjective and objective cognitive performance in multiple sclerosis. Acta Neurologica Scandinavica, 130(5), 319–327.CrossRefGoogle ScholarPubMed
Ruet, A. (2015). Cognitive Impairment in Multiple Sclerosis. In Neuropsychiatric Symptoms of Inflammatory Demyelinating Diseases (pp. 227–247). Cham: Springer.CrossRefGoogle Scholar
Santiago, O., Guardia, J., Casado, V., Carmona, O., & Arbizu, T. (2007). Specificity of frontal dysfunctions in relapsing–remitting multiple sclerosis. Archives of Clinical Neuropsychology, 22(5), 623–629.CrossRefGoogle ScholarPubMed
Schnyer, D.M., Verfaellie, M., Alexander, M.P., LaFleche, G., Nicholls, L., & Kaszniak, A.W. (2004). A role for right medial prefrontal cortex in accurate feeling-of-knowing judgments: Evidence from patients with lesions to frontal cortex. Neuropsychologia, 42(7), 957–966.CrossRefGoogle ScholarPubMed
Sherman, T.E., Rapport, L.J., & Ryan, K.A. (2008). Awareness of deficit in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 30(3), 301–311.CrossRefGoogle ScholarPubMed
Shimamura, A.P., & Squire, L.R. (1986). Memory and metamemory: a study of the feeling-of-knowing phenomenon in amnesic patients. Journal of Experimental Psychology: Learning, Memory, and Cognition, 12(3), 452–460.Google ScholarPubMed
Smith, M.M., & Arnett, P.A. (2010). Awareness of executive functioning deficits in multiple sclerosis: self versus informant ratings of impairment. Journal of Clinical and Experimental Neuropsychology, 32(7), 780–787.CrossRefGoogle Scholar
Souchay, C. (2007). Metamemory in Alzheimer’s disease. Cortex, 43(7), 987–1003.CrossRefGoogle ScholarPubMed
Souchay, C., & Isingrini, M. (2004). Age related differences in metacognitive control: role of executive functioning. Brain and Cognition, 56(1), 89–99.CrossRefGoogle ScholarPubMed
Souchay, C., Isingrini, M., Clarys, D., Taconnat, L., & Eustache, F. (2004). Executive functioning and judgment-of-learning versus feeling-of-knowing in older adults. Experimental Aging Research, 30(1), 47–62.CrossRefGoogle ScholarPubMed
Souchay, C., Moulin, C.J., Clarys, D., Taconnat, L., & Isingrini, M. (2007). Diminished episodic memory awareness in older adults: evidence from feeling-of-knowing and recollection. Consciousness and Cognition, 16(4), 769–784.CrossRefGoogle ScholarPubMed
Trapp, B.D., & Nave, K.A. (2008). Multiple sclerosis: an immune or neurodegenerative disorder? Annual Review of Neuroscience, 31, 247–269.CrossRefGoogle ScholarPubMed
Walker, L.A., Osman, L., Berard, J.A., Rees, L.M., Freedman, M.S., MacLean, H., & Cousineau, D. (2016). Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS): Canadian contribution to the international validation project. Journal of the Neurological Sciences, 362, 147–152.CrossRefGoogle ScholarPubMed
Westfall, J., Kenny, D.A., & Judd, C.M. (2014). Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli. Journal of Experimental Psychology: General, 143(5), 2020–2045.CrossRefGoogle ScholarPubMed
Wojcik, D.Z., Moulin, C.J., & Souchay, C. (2013). Metamemory in children with autism: exploring “feeling-of-knowing” in episodic and semantic memory. Neuropsychology, 27(1), 19–27.CrossRefGoogle Scholar