![]() It is thus crucial to develop culturally- and linguistically-adapted norms to the reference population in order to maximize accuracy in the detection of cognitive impairments. It is also established that the psycholinguistic characteristics of a given concept vary cultures and languages. It is well established that performance on such tasks is influenced by psycholinguistic factors (e.g., word frequency or familiarity). Indeed, in addition to the influence sociodemographic variables, many subtests of the MoCA require language and semantic treatment of information, such as denomination, verbal episodic memory, repetition, and abstraction. Local norms can also be more rigorous than non-cultural specific norms to identify cognitive difficulties in older adults ( Arsenault-Lapierre et al., 2011). Therefore, normative data adjusted for individuals’ sociodemographic characteristics are important to support the clinical use of the MoCA. Only one population-based study in Chinese elders found that sex was associated with MoCA test performance, but only in individuals with less than 5 years of education ( Lu et al., 2011). Some studies have also indicated that sex may affect performance on cognitive screening tests, but it has rarely been the case with the MoCA ( Conti et al., 2015 Freitas et al., 2011 Kenny et al., 2013 Malek-Ahmadi et al., 2015 Narazaki et al., 2013 Ng et al., 2015 Rossetti et al., 2011 Santangelo et al., 2015). According to previous normative studies, two factors-age and education -contribute to explaining up to 49% of the variance in MoCA scores ( Freitas et al., 2011). This also applies to the MoCA, as seen in several normative studies in various countries, including Portugal ( Freitas, Simoes, Alves & Santana, 2011), Ireland ( Kenny et al., 2013), Italy ( Conti, Bonazzi, Laiacona, Masina & Coralli, 2015 Santangelo et al., 2015), Japan ( Narazaki et al., 2013), China ( Lu et al., 2011), Singapore ( Ng et al., 2015), and the United States ( Malek-Ahmadi et al., 2015 Rossetti, Lacritz, Cullum & Weiner, 2011). ![]() Several studies across countries and languages have shown that cognitive performance is influenced by sociodemographic variables such as age, education, and sex. This test has proved to be sensitive to mild cognitive deficits and to predict future cognitive decline in several cognitively impaired states, including Alzheimer's disease and dementias (see Davis et al., 2015 for complete review), Parkinson's disease ( Gill, Freshman, Blender & Ravina, 2008), chronic obstructive pulmonary disease ( Villeneuve et al., 2012), rapid eye movement sleep behavior disorder ( Gagnon, Postuma, Joncas, Desjardins & Latreille, 2010), Huntington's disease ( Mickes et al., 2010 Videnovic et al., 2010), cerebrovascular diseases ( Cameron, Ski & Thompson, 2012 Cumming, Bernhardt & Linden, 2011 Pendlebury, Cuthbertson, Welch, Mehta & Rothwell, 2010 Popovic, Seric & Demarin, 2007 Schweizer, Al-Khindi & Macdonald, 2012), human immunodeficiency virus ( Overton et al., 2013), traumatic brain injury ( de Guise et al., 2013), and cancer ( Olson et al., 2011). The Montreal Cognitive Assessment (MoCA Nasreddine et al., 2005) is a widely used cognitive screening tool that was originally designed for detection of mild cognitive impairment (MCI), a clinical state generally defined as the prodromal stage of several dementias depending on the cognitive impairment observed ( Petersen, 2004), and more specifically a prodromal stage of Alzheimer's Disease when mild amnesia is observed ( Albert et al., 2011). Moreover, early identification of prodromal dementia is essential in order to detect individuals in which further cognitive decline can be prevented or postponed using early interventions or treatments ( Alzheimer's Disease International, 2009). Given that aging is the most important risk factor for cognitive decline, detection of cognitive impairment in at-risk middle-aged and elderly individuals has become a research and clinical priority. ![]() In particular, the number of individuals with dementia worldwide is estimated to double every 20 years, from 35.6 million in 2010, to 65.7 million in 2030, to 115.4 million in 2,050 ( Prince et al., 2013). This demographic trend has important economic, political, and societal implications. The number of individuals aged 60 years or over is expected to at least double by 2,050, reaching approximately 2 billion older individuals worldwide ( United Nations, 2013). Used by permission of the publisher.Cognitive screening, Cognition, Neuropsychology, Montreal Cognitive Assessment, Aging, Norms Introduction MDE Professional Development Series for Literacy Leaders All rights reserved.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |