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      Association between cognition and color discrimination among Lebanese patients with schizophrenia

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          Abstract

          Background

          Patients with schizophrenia (SCZ) exhibit poorer color discrimination than normal individuals. Although retinal abnormalities, as well as cortical and subcortical alterations, found in patients with SCZ have been suggested to cause this poor color discrimination, the impact of cognitive impairment remains to be determined. Dopamine (DA) and glutamate (Glu), known to be disrupted in SCZ, are also suggested to play a role in color discrimination. Our objective was to investigate the contribution of cognitive impairment to color discrimination deficits in SCZ and to examine if these deficits are correlated to SCZ symptoms.

          Methods

          This study includes 127 patients with SCZ between July and September 2021. The participants completed several questionnaires, specifically the Positive and Negative Syndrome Scale (PANSS), the Montreal Cognitive Assessment (MoCA) test, and the Farnsworth D-15 test, to assess the extent of SCZ symptoms, cognition, and color discrimination respectively.

          Results

          Higher cognition (Beta = − 0.279) was significantly associated with a lower total error score (TES). Moreover, a higher positive PANSS score (Beta = 0.217) was significantly associated with a higher TES. A multinomial regression analysis taking the type of color blindness as the dependent variable showed that female sex (ORa = 5.46) was significantly associated with a certain type of color blindness.

          Conclusion

          Color discrimination deficits in patients with SCZ may be due to the effect of cognitive impairment and/or SCZ itself.

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          Most cited references31

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          The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment.

          Ziad S Nasreddine, Natalie Phillips, Valérie Bédirian … (2005)
          To develop a 10-minute cognitive screening tool (Montreal Cognitive Assessment, MoCA) to assist first-line physicians in detection of mild cognitive impairment (MCI), a clinical state that often progresses to dementia. Validation study. A community clinic and an academic center. Ninety-four patients meeting MCI clinical criteria supported by psychometric measures, 93 patients with mild Alzheimer's disease (AD) (Mini-Mental State Examination (MMSE) score > or =17), and 90 healthy elderly controls (NC). The MoCA and MMSE were administered to all participants, and sensitivity and specificity of both measures were assessed for detection of MCI and mild AD. Using a cutoff score 26, the MMSE had a sensitivity of 18% to detect MCI, whereas the MoCA detected 90% of MCI subjects. In the mild AD group, the MMSE had a sensitivity of 78%, whereas the MoCA detected 100%. Specificity was excellent for both MMSE and MoCA (100% and 87%, respectively). MCI as an entity is evolving and somewhat controversial. The MoCA is a brief cognitive screening tool with high sensitivity and specificity for detecting MCI as currently conceptualized in patients performing in the normal range on the MMSE.
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            The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia

            S R Kay, A Fiszbein, L A Opler (1987)
            The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
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              Purposeful selection of variables in logistic regression

              Zoran Bursac, C Gauss, David Williams … (2008)
              Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS) data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.
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                Author and article information

                Contributors
                Oussama Dahdouh: oussamadahdouh@hotmail.com
                Tala Solh: tasolh_1999@hotmail.com
                Corinne Lahoud: corinne.lahoud@gmail.com
                Chadia Haddad: chadia_9@hotmail.com
                Souheil Hallit: souheilhallit@hotmail.com
                Journal
                Journal ID (nlm-ta): BMC Psychiatry
                Journal ID (iso-abbrev): BMC Psychiatry
                Title: BMC Psychiatry
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1471-244X
                Publication date (Electronic): 12 September 2022
                Publication date PMC-release: 12 September 2022
                Publication date Collection: 2022
                Volume: 22
                Electronic Location Identifier: 606
                Affiliations
                [1 ]GRID grid.512933.f, ISNI 0000 0004 0451 7867, Research Department, , Psychiatric Hospital of the Cross, ; Jal Eddib, Lebanon
                [2 ]GRID grid.411324.1, ISNI 0000 0001 2324 3572, Faculty of Sciences, , Lebanese University, ; Fanar, Lebanon
                [3 ]GRID grid.444434.7, ISNI 0000 0001 2106 3658, School of Medicine and Medical Sciences, , Holy Spirit University of Kaslik, ; P.O. Box 446, Jounieh, Lebanon
                [4 ]INSPECT-LB (Institut National de Santé Publique, d’Épidémiologie Clinique et de Toxicologie-Liban), Beirut, Lebanon
                [5 ]GRID grid.444428.a, ISNI 0000 0004 0508 3124, School of Health Sciences, , Modern University for Business and Science, ; Beirut, Lebanon
                [6 ]GRID grid.443337.4, ISNI 0000 0004 0608 1585, Psychology Department, College of Humanities, , Effat University, ; Jeddah, 21478 Saudi Arabia
                Article
                Publisher ID: 4245
                DOI: 10.1186/s12888-022-04245-y
                PMC ID: 9465930
                PubMed ID: 36096757
                SO-VID: fac2ad56-8061-4223-935a-b5286884b889
                Copyright © © The Author(s) 2022
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 2 May 2022
                Date accepted : 6 September 2022
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Clinical Psychology & Psychiatry
                Keywords: color discrimination,cognitive function,psychotic symptoms,schizophrenia
                Data availability:
                ScienceOpen disciplines: Clinical Psychology & Psychiatry
                Keywords: color discrimination, cognitive function, psychotic symptoms, schizophrenia

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