NeuroBel: Spanish screening test for oral psycholinguistics disabilities in elderly people with mild cognitive impairment and early-stage Alzheimer’s disease

Journal Pre-proof NeuroBel: Spanish screening test for oral psycholinguistics disabilities in elderly people with mild cognitive impairment and early-stage Alzheimer’s disease ´ J.A. Adrian, ´ J.C. Arango-Lasprilla, F. Cuetos ´ G. Bermudez-Llus a,

PII:

S0021-9924(18)30208-9

DOI:

https://doi.org/10.1016/j.jcomdis.2019.105943

Reference:

JCD 105943

To appear in:

Journal of Communication Disorders

Received Date:

21 September 2018

Revised Date:

31 August 2019

Accepted Date:

24 September 2019

´ JA, Arango-Lasprilla JC, Cuetos F, ´ Please cite this article as: Bermudez-Llus a´ G, Adrian NeuroBel: Spanish screening test for oral psycholinguistics disabilities in elderly people with mild cognitive impairment and early-stage Alzheimer’s disease, Journal of Communication Disorders (2019), doi: https://doi.org/10.1016/j.jcomdis.2019.105943

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

NeuroBel: Spanish screening test for oral psycholinguistics disabilities in elderly people with mild cognitive impairment and early-stage Alzheimer’s disease

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G. Bermúdez-Llusáa, J.A. Adriána, J.C. Arango-Lasprillab and F. Cuetosa

Department of Psychology and Speech-Therapy, University of Málaga, Spain BioCruces Bizkaia Health Research Institute. Barakaldo, Bizkaia, Spain.

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IKERBASQUE. Basque Foundation for Science, Bilbao, Spain.

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Department of Cell Biology and Histology, University of the Basque Country UPV/EHU, Leioa, Spain.

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Running Head: NeuroBel: Spanish screening test

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Key words: oral language screening, elderly, Altheimer´s disease, mild cognitive

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impairment, cognitive neuropsychology

Highlights    

Quick battery in Spanish to detect oral psycholinguistic impairments in the elderly. Discriminate Alzheimer Disease from Mild Cognitive Impairment, and Controls. Provide cut-off points for Spanish Speaking clinicians to use. Provide completion times to decide whether supplementary psycholinguistic assessment is required. 1

1. Introduction It is evident that increasing life expectancies in developed countries and emerging economies are causing a parallel increase in the prevalence of diseases associated with aging, such as Alzheimer's disease (AD), Parkinson's disease, cerebrovascular accidents,

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and other neurodegenerative diseases. The presence of dementia has been associated with advanced age. However, it would not be appropriate to infer that aging is the cause of dementia or that aging and dementia are comparable situations (Murman, 2015).

Nevertheless, with increased age, individuals develop an increased risk for pathological

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cognitive deterioration (Bermejo & Del ser, 1993). Detecting the preclinical processes

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associated with degenerative cognition early in aging is key to both preventing the development of these types of diseases and to treating them.

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Physical and psychological decline that occurs with age can affect various cognitive functions (see Salthouse, 2010; 2012 for a more thorough review), such as

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episodic memory (e.g., Backman, Jones, Berger, Laukka, & Small, 2005; Backman, L., Small, B., & Fratiglioni, 2001), executive functions (e.g., Albert, Moss, Tanzi, & Jones,

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2001), attention (e.g., Estévez-González et al., 2003; Linn et al., 1995; Rapp, & Reischies, 2005), spatial and visual abilities (e.g., Small, Herlitz, Fratiglioni, Almkvist,

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& Backman, 1997), psychomotor speed (e.g., Masur, Sliwinski, Lipton, Blau, & Crystal, 1994), and language abilities (e.g., Obler, & Albert, 1984). Regarding linguistic capacities, it is very common to see various changes in

language over the course of a person’s lifetime. For example, normal aging does not have the same effect on language comprehension as it does on production (JuncosRabadán, 1998). Thus, in terms of lexical access and loss of vocabulary during a 2

conversation, older people make more mistakes than younger people (Bowles, Obler, & Albert, 1987). For example, there are considerable differences between middle-aged adults and those over the age of 70, for whom lexical access difficulties related to naming are usual (the so-called “tip-of-the-tongue phenomenon”) (Burke, Mackay, Whorthey, & Wade, 1991; Burke, Whorthey, & Martin, 1988). Difficulties can also appear in structured and organized speech, without losing the thread or the original idea of a talk. Age is also related to difficulty with syntactic processing. The production of

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sentences is generally less complex in adults older than 70 than in younger individuals (Obler, & Albert, 1984; Obler, & Pekkala, 2008). In contrast, semantic processing

(meaning) is usually kept intact in this advanced stage of life, and the level of passive

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vocabulary knowledge is maintained and often even increases (Wingfield, Aberdeen, & Stien, 1991).

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Although minor linguistic changes are a normal process of healthy aging, a

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number of studies have shown that the simplification of grammatical structure, narrative difficulties, errors in the identification and description image themes, reading comprehension, and vocabulary loss are common problems appearing in the preclinical

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stages of AD and mild cognitive impairment (MCI) (Cuetos, Arango -Lasprilla, Uribe, Valencia, & Lopera, 2007; Forbes, Shanks, & Venneri, 2004; Forbes, Venneri, & Ellis,

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2003; Forbes, Venneri, & Shanks, 2002; Garrand, Maloney, Hodges, & Patterson, 2005;

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Tsantali, Economidis, & Tsolaki, 2013). In general, in the initial phases of cognitive impairment due to AD or MCI, the literature has shown that linguistic aspects related to semantic processing are the first to deteriorate, including denomination (object, actions, famous faces, etc.), verbal fluency, spontaneous writing, and tasks of semantic memory (Arango-Lasprilla, Cuetos, Valencia, Uribe, & Lopera, 2007; Garrand et al., 2005; Jones, Laukka, & Backman, 2006; Rodríguez-Ferreiro, & Menéndez, 2009; Small et al.,

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1997). In contrast, sublexical abilities such as reading aloud, lexical decision-making, and word repetition tend to be preserved longer (Arango-Lasprilla, Iglesias, & Lopera, 2003, Cuetos, Martínez, Martínez, Izura & Ellis, 2003). The majority of neuropsychological instruments available to assess these linguistic changes in elderly individuals and individuals with dementia are tests that were created in the US, the United Kingdom and other English-speaking countries for an Anglo-Saxon population (e.g., Bayles, K.A., & Tomoeda, 1993; Bryan, Binder,

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Dann, Funnell, Ramse, & Stevens, 2001; Ferris, Ihl, Robert, Winblad, Gatz, Tennigkeit, & Gauthier, 2009). However, it is well known that Spanish is a language spoken, as a mother tongue, by almost five hundred million people (Eberhard, Simons, & Fennig,

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2019), and many of these people are of advanced age, which suggests that there are

likely a large number of Spanish-speaking individuals with dementia around the world.

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Regarding the evaluation of language in Spanish-speaking individuals, verbal

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fluency tests are most often used for neuropsychological screening of language impairment in elderly individuals (e.g., Nutter-Upham et al., 2008, Tsantali et al., 2013; Rinehardt et al., 2014). For example, tests measuring the ability to generate the names

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of animals (Carnero-Pardo & Lendínez-González, 1999), household objects (Fernández et al., 2002), objects in a supermarket (Garcés, Santos, Pérez and Pascual, 2004), and

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public or famous people (Ferrero-Arias, Sánchez-Saudinós, & Lamet-Gil, 2001) are

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used most frequently. These tests are also used for the categorical recall of items such as fruits, colors, and cities (Pascual-Millán et al., 1990), deriving fluency data regarding semantic categories from the Spanish-speaking population of healthy elderly adults living in the US (Acevedo et al., 2000). These tasks demonstrate good discriminative capacity between patients with AD and healthy people (Goñi-Sarriés, López-Goñi, Granados-Rodríguez, & González-Jiménez, 2015), but they do not allow the

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specification of which aspects of language processing are more highly impacted and which remain relatively intact. When evaluating language in adults, the model most widely accepted internationally by experts is based on the psycholinguistic approach. This model represents a complicated neural network, which is commonly depicted using box and arrow diagrams. These boxes and arrows represent modules and pathways, respectively, involved in different components of the cognitive processing system used in the

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understanding and production of language (Ellis & Young, 1998). The psycholinguistic approach, rather than classifying patients based on the classic syndromes (Broca’s

aphasia, Wernicke’s aphasia, etc.), tries to determine which components of the linguistic

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processing system are damaged and, thus, responsible for the disorder. Since many people with aphasia do not easily fit into a particular syndrome category and since

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patients with the same syndrome do not usually form a homogeneous group, it seems

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more useful, from both a clinical and a research perspective, to try to understand the linguistic processes that are damaged in people with aphasia than to classify them into syndromes (Caramazza, 1984; Cuetos, Glez-Nosti, Martínez, Mantiñán, Olmedo, &

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Dioses, 2010; Ellis, 1987).

From this theoretical model, the majority of standardized tests available in

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Spanish-speaking countries such as the United States (US) are long batteries: for

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instance, the Evaluación del Procesamiento Lingüístico en la Afasia (EPLA) (Valle & Cuetos, 1995) and the Batería para la Evaluación de los trastornos afásicos (BETA) (Cuetos, & González, 2009). These tests are valuable for clinical descriptions of language disorders in adults and/or for research, since they evaluate all the components of the linguistic processing system, both those involved in comprehension and those involved in production. These batteries not only quantify the severity of the linguistic

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disorder but also identify the cognitive processes that are damaged. This quantification occurs both at the level of words and at the level of sentences, identifying possible cognitive and psycholinguistic dissociations (e.g., verb-object naming dissociation). The problem is that these batteries are expensive and require a long administration time for an initial screening. Recently, Wilson, Eriksson, Schneck and Lucanie (2018) developed a rapid test (Quick Aphasia Battery, QAB) that provides a multidimensional assessment of

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language function in people with aphasia. Tests that are easy to administer in daily clinical practice are needed to differentiate between cognitive impairment and normal

aging. Specifically, tests that assess language are critical, since linguistic impairment is

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one of the first disordered behaviors that appears in many neurodegenerative dementias. In addition, we need a test to help describe linguistic deficits, for example, depicting

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whether oral comprehension disorders are due to deficits in the identification of

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phonemes, the recognition of words, or the access of meaning. For this reason, a group of psycholinguistics and neuropsychology professionals has created a short screening test (the NeuroBel) that can be easily administered at home

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(Adrián, Jorquera, & Cuetos, 2015). The test only takes a few minutes and psychometrically evaluates the main processes involved in oral language using

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psycholinguistics paradigms. This test would allow speech-language pathologists,

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neuropsychologists, clinical psycholinguists, psychologists, geriatricians, and other professionals to efficiently assess elderly individuals, such as Alzheimer’s disease patients, who are not able to tolerate lengthy assessments and could contribute to the evaluation of cognitive deterioration in aging. Today, there are no short standardized tests in Spanish for the rapid evaluation of language in the elderly population from the perspective of the psycholinguistics.

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The initial goal of this study is to preliminarily compare the concurrent validity and discriminability of a brief battery of tasks called the NeuroBel to that of the gold standard screening test for dementia (the Mini-Mental State Examination or MMSE) in detecting and describing linguistic disabilities in Spanish-speaking individuals. This manuscript aims to share information about this potentially promising measure at an early stage to foster interest and hopefully support the further

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development of the NeuroBel.

2. Method 2.1 Participants

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A total of 104 patients were considered feasible candidates for participation in

this study. Of those, 65 met the clinical criteria of early-stage Alzheimer's disease (AD)

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or mild cognitive impairment (MCI). Eventually, those with an unclear diagnosis (15

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individuals) were excluded prior to dividing the clinical participants into two groups (25 AD individuals and 25 MCI individuals).

Ultimately, 75 monolingual Spanish participants residing in the province of

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Málaga, Spain (19 men and 56 women) who were between 64 and 88 years old voluntarily participated in this pilot study. The education level of participants ranged

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from functional illiteracy (less than one year of formal schooling) to 17 years of

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schooling (mean = 7.8; SD = 4.3). Twenty-five participants in the sample had originally been diagnosed with early-stage AD. Twenty-five patients had a diagnosis of amnestic MCI. The remaining 25 participants acted as a control group based on the absence of a clinical diagnosis of cognitive impairment (healthy aging). Control participants were matched to the MCI group on age, sex, and level of schooling.

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Table 1 shows the sociodemographic characteristics and MMSE scores of the participants by group. As seen in Table 1, the groups were similar with respect to gender, age, and years of formal schooling. Conversely, significant between-group differences were observed for MMSE scores.

TABLE 1 HERE The geriatric and neuropsychological team (four blind evaluators with at least 5

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years of clinical experience) checked each participant´s clinical history to ensure that every participant had been diagnosed correctly within one of the two clinical groups being examined. Clinical reports included different batteries of Spanish

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neuropsychological tests exploring different areas of cognition (e.g., memory, fluency),

clinical diagnoses of the participants.

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geriatric reports, and, in some cases, neuroimaging data, which were used to confirm the

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The inclusion criteria for the AD group was a score of 4 on the Global Deterioration Scale (GDS4). The inclusion criteria for the MCI group was a score of 3

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on the Global Deterioration Scale (GDS3). The inclusion criteria for the control group was a score of 1 or 2 on the Global Deterioration Scale (GDS1-2) (Reisberg, Ferris, de

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León, & Crook, 1982, de Leon, & Reisberg, 1999). Participants with a GDS score > 5 were excluded, since at these stages, an individual can no longer survive without

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assistance, dementia is advanced, and the evaluation of cognitive or linguistic tasks is difficult.

To elicit clinical information and determine whether inclusion/exclusion criteria were met, the team excluded participants from the final sample who (a) had

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severe visual or auditory disorders; (b) scored 5 or higher on the Global Deterioration Scale (GDS) or on the Functional Assessment Stages; (c) had an MMSE score lower than 16, which represents the lower limit of moderate cognitive deficit or GDS4; (d) had a history or neurological or psychiatric illness; or (e) had depressive symptoms (PHQ-9 score >9). We used the Spanish version of the Patient Health Questionnaire PHQ-9 (Kroenke, Spitzer, & Williams, 2001).

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2.2 Instrumentation The NeuroBel consists of 8 tasks that evaluate all the components of linguistic processing, from the most peripheral to the most central, both in oral comprehension

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and production (Adrián, et al., 2015). The appendix shows a more detailed explanation of the test scoring and examples. The NeuroBel is conceptually based on the EPLA

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(Valle & Cuetos, 1995), which is the Spanish version of the PALPA test

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(Psycholinguistic Assessments of Language Processing in Aphasia; Kay, Lesser, & Coltheart, 1992) and the BETA (Cuetos, & González, 2009), although the NeuroBel uses different stimuli. Therefore, the NeuroBel is not a modified version or a short form

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of these assessments. Four of the NeuroBel tasks explore receptive abilities or language comprehension, and the rest explore the expressive or productive part of oral

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communication. The linguistic stimuli (words) used for some NeuroBel tasks (Auditory

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lexical decision, Spoken word to picture matching, Picture naming, and Action naming) were selected from the “Diccionario de frecuencias de las unidades lingüísticas del castellano” (Alameda, & Cuetos, 1995) (Dictionary of frequent linguistic units of Spanish) and from normative data of naming times for action pictures (Cuetos & Alija, 2003).

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2.3 Procedure This study was approved by the Ethics Committee of the University of Málaga, Spain. AD and MCI participants were recruited from the Healthy Aging Center of the City Council of Malaga, Spain (Centro de Envejecimiento Saludable del Ayuntamiento de

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Málaga), the Nursing Home Virgen del Carmen de Estepona, Málaga, Spain (Residencia de Ancianos Virgen del Carmen), and the Associations of Relatives of People with Alzheimer's Disease in Málaga and Estepona, Spain (Asociaciones de

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familiares de Enfermos de Alzheimer de Málaga y Estepona). Control participants were recruited from participants’ friends and relatives or were the healthy attendees of the

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Centers.

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We explained the purpose of the study to each participant and asked them to provide signed informed consent. Finally, all participants that met the inclusion criteria were evaluated using the NeuroBel test.

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The NeuroBel considers both the direct scores (correct answers) and the time spent in the execution of each task. After providing the instructions for each task, a

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psychologist demonstrated 1 to 2 examples for the participant, ensuring the participant

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had correctly understood the task. Time control: Evaluators were trained in a group setting on how to correctly

use the stopwatch during the assessment. Once the examples had been demonstrated, the instructions were memorized, the timer was started, and the task began. When the participant had answered the last item of the task, the stopwatch was stopped between tasks, and the score and the time were written down.

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2.4 Statistics Data analysis was performed using the Statistical Package for the Social Sciences (SPSS-22). The means, standard deviations, and execution times of the NeuroBel tasks were calculated separately for each group, including the total score of the complete test (execution time).

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Two one-way between-groups ANOVAs and a post hoc Tukey's honestly significant difference (HSD) analysis were carried out to examine possible group

differences in NeuroBel total scores and execution times. Two MANOVA (Pillai's trace

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multivariate analysis) tests and a post hoc Tukey's honestly significant difference (HSD) analysis were carried out to examine the NeuroBel task scores and execution times.

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A discriminant analysis was also calculated to construct a canonical linear

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predictive model of group membership using the NeuroBel tasks as independent variables.

The sensitivity and specificity of the NeuroBel test, including true positives

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(with cognitive impairment), false positives (healthy), area under the curve (AUC) as a measure of accuracy, efficacy, and optimal cut points (C.P.) by a ROC (receiver

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operating characteristic) analysis, were calculated.

3. Results

The NeuroBel obtained good reliability in terms of internal consistency

(Cronbach's alpha = .84) and had a high bivariate Pearson’s correlation with the MMSE (r = .89, p < .01).

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3.1. Group comparisons: One-way ANOVA & MANOVA The results obtained in the 2 one-way ANOVAs comparing NeuroBel total scores and execution times across the three groups are represented in Figure 1.

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FIGURE 1 HERE

There were significant differences between the three groups both in total score

(F(2,72) = 132.99, p <.001; partial η2 = .787, 90% confidence interval (CI) [.707, .828]) and

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execution time (F(2,72) = 33.67, p <.001; partial η2 = .483, 90% confidence interval (CI)

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[.303, .577]; see Table 2).

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TABLE 2 HERE

A post hoc analysis using Tukey's honestly significant difference (HSD) test to

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explore possible differences in NeuroBel scores between groups, showed significant differences (at p <.05) between the AD group and the other 2 groups (MCI group and

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Controls) across all NeuroBel tasks (p <.001).

MANOVA showed significant differences between the three groups for both

NeuroBel task scores (F(2,72) = 7.729, p <.001; partial η2 = .177, 90% confidence interval (CI) [.051, .291]). Significant differences (at p <.05) were also shown between the scores of the MCI group and Controls in the Phoneme discrimination task (p =.047), Auditory sentence comprehension task (p =.001), Picture naming task (p <.001), and Sentence

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completion task (p <.001). However, there were no significant differences (n.s.) between the scores of the MCI group and Controls in the other 4 tasks of the NeuroBel: Auditory lexical decision, Spoken word to picture matching, Repetition, and Action naming. MANOVA showed significant differences in execution times between the three groups (F(2,72) = 7.013, p <.001; partial η2 = .163, 90% confidence interval (CI) [.042, .276]). A post hoc analysis using Tukey's honestly significant difference (HSD) test examined possible differences in execution times for the full NeuroBel battery between

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groups and showed that the control group exhibited a significantly (p <.001) shorter execution time than participants with AD or MCI. The comparison between execution

times of AD and MCI individuals only trended toward statistical significance (p = .052).

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Participants in the AD and MCI groups showed similar execution times (n.s.) in 4 of the 8 NeuroBel tasks: Phoneme discrimination, Auditory sentence

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comprehension, Repetition, and Sentence completion. Controls were significantly (p

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<.05) faster than the other two groups in 4 of the 8 tasks: Phoneme discrimination (p <.001), Auditory lexical decision (p <.001), Repetition (p <.001 Controls vs AD; p = .049 Controls vs MCI), and Picture naming (p <.001). In contrast, execution times

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between Controls and AD participants were not different in 2 of the 8 tasks: Auditory sentence comprehension and Sentence completion; execution times were not different

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between Controls and MCI participants in 1 of the 8 tasks: Action naming. The effect

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size, calculated through partial eta-squared analysis, showed that the variance explained by the group variable was 45.9% (partial η2 = .459).

3.2 Discriminant analysis In Table 3 (upper panels), standardized canonical discriminant function coefficients and the matrix structure of the canonical discriminant functions are shown.

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The tasks (“variables”) are ordered by correlation size within each function, which provides the best possible discrimination between groups. Discriminant Function 1 indicates tasks that best differentiate between the three groups in the study (AD, MCI and Control participants), while Function 2 shows the differences between the groups after controlling for Function 1. In this case, Function 2 highlights the tasks that were less successful in differentiating participants in the MCI group from those in the control group. These results coincide with the data obtained using one-way ANOVA.

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The lower panel in Table 3 also shows the classification results of the discriminant function to determine the coherence of the data obtained from the

originally predicted membership group (AD, MCI, or Control). The results show that

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86.7% of the participants in the original groups had been correctly classified.

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TABLE 3 HERE

3. Receiver operating characteristic (ROC) analysis The ROC curve (see Figure 2) shows the true positive rate, or cognitive-

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psycholinguistic impairment (sensitivity), versus the false positive rate, or the probability of false alarm (specificity). The upper panel in Figure 2 shows the ROC

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curve accuracy score and the area under the curve (AUC) for the NeuroBel, indicating

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discrimination between the AD group and MCI+Controls (left) and between AD+MCI groups and Controls (right). The data show a sensitivity of .96 and a 1-specificity of .80 for the determination of Alzheimer’s disease (AD vs MCI + Controls) and a sensitivity of .98 and a 1-specificity of .76 for the determination of cognitive deterioration (AD + MCI vs Controls). The AUC was .97 for AD vs MCI + Controls and .98 for AD + MCI vs Controls.

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The clinical cut-offs for different groups from the ROC accuracy analyses denote that a performance score of 90 or greater indicates typical-range performance, a score between 83.75 and 90 indicates the MCI range, and a performance score below 83.75 suggests early-stage AD. In contrast, the lower panel in Figure 2 shows a composite accuracy score/time execution ROC curve, which provides valuable information about efficacy in NeuroBel performance, indicating discrimination between AD and MCI+Controls (left) and

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between AD and MCI (right). The data show a sensitivity of .96 and a 1-specificity of .68 for the determination of Alzheimer’s disease (AD vs MCI + Controls) and a sensitivity of .96 and a 1-specificity of .64 for the determination of cognitive

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deterioration (AD + MCI vs Controls). The AUC was .88 for AD vs MCI + Controls

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and .98 for AD + MCI vs Controls.

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4. Discussion

This study presents a short battery of tasks (called the NeuroBel) that was created to assess the most important psycholinguistic mechanisms in oral language processing and

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their possible decline during the cognitive aging process in older adults. The results obtained in this study, conducted in Spain, indicate that the NeuroBel is a novel and

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reliable screening measure of oral language decline in patients diagnosed with AD and

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MCI. The results provide initial reference values and cut-off points to distinguish between participants with cognitive impairment and healthy individuals. The results from one-way ANOVA suggested that the NeuroBel is a screening tool

capable of finding significant differences among the evaluated subject groups. The participants in the AD group received a significantly lower total score on the NeuroBel (77.24 out of 100) than the other two groups that were evaluated: MCI (85.02 out of

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100) and control groups (92.40 out of 100). The control group received a significantly higher total score on the NeuroBel than participants with cognitive deterioration (AD and MCI). These results highlight the soundness of the test in differentiating clinical samples from healthy, typically aging older adults. Considering the NeuroBel results at the task level, AD group participants performed significantly worse than participants from the other two groups on all tasks. In contrast, MCI group participants tended to have similar scores (no significant differences) to

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those of the control group on 50% of the tasks: quick classification of spoken words and pseudowords (Auditory lexical decision), listening to a spoken word and accurately matching it to one of four possible semantically connected images (Spoken word to

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picture), repeating words and pseudowords (Repetition), and naming verbs related to actions (Action naming).

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Of particular relevance is the discriminant analysis (DA) data reported in Table 3. DA was used to assess which variables discriminated between groups (AD, MCI, and

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Controls). The psycholinguistic tasks most highly associated with semantic processing and sentence processing (Sentence completion and Sentence comprehension) are found

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in the discriminant matrix in Table 3. In fact, the Sentence completion task was the task that was best discriminated between groups. This result reflects the decisive role that the

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frontal lobe has in morphosyntactic planning and sentence construction using a prefixed

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word given in the test (Cai, Lavidor, Brysbaert, Paulignan, & Nazir, 2008; Voets, Adcock, Flitney, Behrens, Hart, Stacey, & Matthews, 2005). The matrix includes those tasks that best differentiated the groups from each other (Function 1), such as the ability to name pictures of objects (Picture naming), the ability to complete a sentence based on a given word (Sentence completion), or the oral comprehension of instructions (Auditory sentence comprehension). In contrast, most of the tasks assessing

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nonsemantic abilities, such as distinguishing a word from a pseudoword (Lexical decision) or the repetition of words and pseudowords (Repetition), appear to be less important for distinguishing the initial phases of cognitive decline from healthy aging. The results of this study are consistent with those reported in previous scientific studies in this regard (Arango-Lasprilla et al., 2003; Arango-Lasprilla et al. 2007; Cuetos et al., 2003; Cuetos et al., 2009; Garrand et al., 2005; Jones et al., 2006; Small et al., 1997). Nevertheless, some NeuroBel tasks showed surprising results. For example, it

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appears paradoxical that a semantic task such as naming verbs (Action naming) does not appear to be among the tasks that best differentiated between the groups. This result

could be due to the number of items (only 12) used in the Action naming task, which

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may be adequate for discriminating AD patients but resulted in no significant effect

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(likely by a ceiling effect) when discriminating the MCI group from Controls. However, another possibility is that all of the items used in this NeuroBel task were either

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intransitive verbs (7 out of 12) or 1-place transitive verbs (5 out of 12), both of which have high imageability; thus, the simplicity of these verbs may also be a possible reason

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for MCI participants performing similarly to the Controls. Including more complex verbs with less imageability (e.g., buy, give) in future versions of the NeuroBel may

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better differentiate MCI individuals from Controls. Therefore, Function 2 is utilized here to highlight the tasks (50%) that were less successful in differentiating MCI group

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participants from the Controls. Identical results were obtained with one-way ANOVA. The same result was found for listening to a spoken word and accurately

matching it to one of four possible semantically connected images (Spoken word to picture task). Although not exclusively verbal, this task involved action gnosicperceptual components to select the target item. Accordingly, this task could also be

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used to differentiate between participants in the initial stages of AD (and probably those in the initial stages of semantic dementia, as well) from the other groups in this study (MCI and Controls). The results of the ROC curve, shown in Figure 2, indicate an adequate discriminative capacity (sensitivity) for detecting language decline during aging. Consequently, this screening battery can be considered acceptable for clinical use as a screening measure of language deficits in cognitive decline. The AUC shows that the

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probability of a participant in the AD group obtaining a lower score than participants in the MCI and control groups is 97%. Similarly, the probability of a participant with

cognitive decline (AD and MCI) obtaining a score lower than participants in the healthy

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control group is 98%. The cut-off points (CP) provide valuable information for

clinicians to determine whether older adults who are being evaluated fall inside or

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outside a probable linguistic involution with respect to the normal aging process. Although valuable, the NeuroBel is currently meant to be used as a screening battery,

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and comprehensive neuropsychological and medical tests should be administered to make diagnostic conclusions. Nevertheless, from a clinical perspective, the NeuroBel

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offers useful initial information, especially regarding the older adult population, which is typically evaluated in various public institutions and would benefit from identification

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for more immediate specialized support.

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In our opinion, the execution time of each task and the total test execution time per group are valuable contributions by the NeuroBel. As expected, the participants in the control group took a significantly less time (mean = 8.37 min) than the AD (mean = 14.26 min) and MCI (mean = 12.13 min) groups to complete the NeuroBel. However, differences were only found in the total execution time, and no significant differences were found in 50% of the tasks comprising the test. This result might suggest that the

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beginning of cognitive-linguistic decline during the aging process is directly correlated to longer decision-making times. Nonetheless, the observed increase in execution times may also be due to task-specific processing delays or failures, a hypothesis that should be tested in future studies. Less frequently addressed in the existing literature, the inclusion of execution times may be useful for deciding whether a more comprehensive supplementary psycholinguistic evaluation is required. Nonetheless, the replication of these findings is

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needed in the future to confirm these results, which could be particularly valuable for individuals exhibiting a ceiling effect in the execution of some tasks included in the

battery. Typically, individuals with a higher education level but whose test execution

-p

time is longer than the mean – thus perhaps indicating a subclinical presentation of the beginning stage of cognitive-linguistic decline – require extensive testing evaluations

re

(see Olabarrieta-Landa, Rivera, Galarza-del-Angel Garza, Saracho, Rodríguez, &

lP

Martínez, 2015; Rivera, Olabarrieta-Landa, Van der Elst, Gonzalez, RodríguezAgudelo, Aguayo, & Arango-Lasprilla, 2019). For example, the AUC (.88) in the ROC results shows that the efficacy (accuracy score / time execution) of the AD vs

na

MCI+Controls comparison was less important than the AUC (.98) in the ROC results of just the accuracy score, which may indicate that several participants (from the MCI or

ur

Control groups) spent longer than the average NeuroBel execution time compared to

Jo

their group partners.

In conclusion, the results obtained in this study point to the NeuroBel as a valid

and reliable test (Cronbach’s alpha = .84) in the evaluation and screening of possible psycholinguistic deficits in during aging. Its high correlation with the MMSE and its short administration time (approximately 15 min) make the NeuroBel a sound testing measure to be utilized in clinical settings as a supplementary screening method for

19

patients thought to be experiencing cognitive-linguistic decline. Moreover, the NeuroBel, given its sensitivity obtained from simple verbal fluency measures, is a potentially promising early-stage measure that could be developed beyond being a simple screening test. The NeuroBel is a potentially promising measure for fostering interest in the further development of the identification of linguistic deficit profiles in aging populations.

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4.1 Caveats and future prospects Although the NeuroBel has an adequate theoretical background, the

presentation and norms of the tasks (which could lead to their standardization) and its

-p

yield of relevant data in the screening of psycholinguistic deficits in older Spanish-

speaking adults experiencing cognitive aging should be interpreted with caution, as it is

re

preliminary. Several important limitations and observations should be considered to

lP

encourage the correct utilization and administration of the test. As such, the NeuroBel must demonstrate reliability in the future by expanding the data with larger samples that include different age ranges and education levels to strengthen the design and results. In

na

addition, future research should include Spanish-speaking participants from different geographical areas and countries. It has been noted that very few visual confrontational

ur

naming measures have been developed in Spanish, and most of the existing measures

Jo

are from English versions that have been translated to Spanish by Marquez de la Plata et al. (2009). This detail is problematic because some words are more frequently utilized in English than in Spanish and vice versa. In the case of the NeuroBel, great care was taken to select stimuli based on frequency dictionaries available in Spanish, especially for tasks that require naming or the oral recognition of vocabulary (i.e., Picture naming, Action naming, and Spoken word picture matching). Nevertheless, and due to the

20

polysemy and diversity of Spanish vocabulary, naming can vary dialectically between geographical regions, as the Spanish language is widely spoken around the world. For instance, Spanish is the second most spoken language in the US, after English, with a total prevalence of 12% among the general population and approximately one third of the older population (de Felipe, Benson, Luo, Sewell, & Sano, 2013). The Spanish speaking population in the US comes from countries in Central and South America that each have their own means of naming objects and actions. For this reason, it is

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imperative to conduct supplementary studies that consider population samples from other countries that use Spanish as a working language to evaluate possible meaning

and dialectic variations that would be acceptable in the interpretation of the NeuroBel.

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This offers a future direction: to obtain relevant transcultural data with this new psycholinguistic screening test using the oral Spanish language.

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As has been described, only a semantic-non semantic dissociation was found for the

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NeuroBel. This test provides cut-off scores for overall test performance, but there are also subtests assessing different subcomponents of the language system from a psycholinguistic perspective. However, at present, the NeuroBel cannot outline

na

impairment in a specific subdomain. In the future, these questions should be answered.

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5. Acknowledgements

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We would like to thank Marta Fresnadillo-Delgado and Elena Tomé-Rodríguez for their help in the design and drawing of some of the graphic material used in the NeuroBel.

6. References Adrián, J.A., Jorquera, J., & Cuetos, F. (2015). NEUROBEL: Breve batería neuropsicológica de evaluación del lenguaje oral en adultos-mayores. Datos 21

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26

100,00

NEUROBEL Score

90,00

80,00

70,00

AD

ro of

60,00 MCI

Controls

Group

20,00

-p re

15,00

12,50

10,00

na

7,50

lP

NEUROBEL Time

17,50

AD

MCI

Controls

Group

Jo

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Figure 1. Boxplots representing the distribution and dispersion of the results in the NeuroBel (scores and time) according to clinical membership group. The median, the quartiles (1 and 3) and the extreme values (distance or range of 95% of the cases) are also represented.

27

Accuracy scores in

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re

-p

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Accuracy scores in AD vs MCI+Controls AD+MCI vs Controls

Accuracy/Execution time in

Jo

ur

na

Accuracy/Execution time in AD vs MCI+Controls AD+MCI vs Controls

28

ro of -p re lP

Jo

ur

na

Figure 2. Upper panel: ROC curve accuracy score and the area under the curve (AUC) for NeuroBel showing discrimination between AD and MCI+Controls (left) and between AD+MCI and Controls (right). Lower panel: ROC curve accuracy/time execution (efficacy in NeuroBel performance) and the area under the curve (AUC) for NeuroBel showing discrimination between AD and MCI+Controls (left) and between AD+MCI and Controls (right).

29

f oo

pr

Table 1. Demographic data and MMSE scores of the participants, and inter-groups F and p-values by group membership.

e-

Group

Gender Agea

16 ♀

MCI

9♂

Educationa

5♂

Controls

20 ♀

5♂

F

P

1.17

.333

76.9(5.73)

76.5(5.10)

0.84

.436

7.1(2.80)

7.9(5.12)

8.6(4.60)

0.75

.477

19.56(1.58)

23.40(2.61)

28.40(1.44)

129.00

<.001

Jo ur

MMSEb

20 ♀

na l

78.5(6.10)

Pr

AD

Note. Mean values, with standard deviations in round brackets. a In years. b Spanish 30 items version.

Table 2. Means, standard deviation (in brackets) for NeuroBel total score and for each task by group membership. Mean Score (SD)

Mean Execution Time in min (SD)

30

Control

Phoneme discrimination

10.84(.7)

11.46(.6)

11.84(.3)

Lexical decision

10.96(.7))

11.56(.6)

11.72(.3)

Spoken word pict. matching

14.72(1.2)

15.36(.7)

15.64(.5)

Auditory sentence compreh.

7.68(1.5)

8.64(1.3)

9.96(.7)

F

p value

AD

MCI

Controls

2.50(.46)

2.49(.52)

1.56(.18)

2.25(.31)

1.87(.37)

1.38(.09)

1.23(.16)

1.0(.15)

.46(.17)

1.59(.30)

2.03(.40)

1.38(.29)

<.001

e-

7.729

11.02(.8)

11.40(.4)

1.32(.18)

1.22(.07)

1.08(.11)

Picture naming

9.12(1)

9.94(1.1)

11.06(.6)

2.22(.38)

1.45(.21)

.55(.18)

Action naming

8.80(1.3)

10.40(.6)

11.04(.8)

1.39(.44)

.53(.23)

.35(.18)

Sentence completion

4.96(1.4)

6.64(1.7)

9.76(1.6)

1.36(.14)

1.54(.25)

1.21(.07)

NeuroBel Total

77.24(3.7)

85.02(3.1)

92.40(2.9)

14.26(2.37)

12.13(2.20)

8.37(1.27)

Pr

10.18(.9)

na l

Repetition

f

MCI

oo

AD

pr

Tasks

132.998

<.001

F

p value

7.013

<.001

33.671

<.001

Jo ur

Table 3: Standardized Canonical Discriminant Function Coefficients, Discriminant Matrix Structure and predicted membership classification according to count of n and percentage

Predictor variables

Function 1

Function

2

Predictor variables

Phoneme discrimination

.028

.164

Lexical Decision Spoken word picture matching

.181

.344

-.113

.257

Sentence completion Picture naming

1 .591(*) .415(*)

-.423 -.120

Auditory sentence comprehension Phoneme discrimination

.361(*) .350(*)

-.108 .308

2

31

.234

.360 .362

-.201 .507

.739

-.555

f

.235

oo

-.246

Action naming Lexical Decision Repetition of words-nonwords Spoken word picture matching

.443 .262 .325 .201

.641(*) .497(*) .419(*) .268(*)

pr

Repetition Picture naming Action naming Sentence completion

.396

(*) absolute correlation between each variable and any discriminant function.

e-

Auditory sentence comprehension

Largest

Classification Results*

AD MCI Controls AD MCI .0

n

Original

na l

*Correctly 86.7% of the groups selected

%

Controls

Predicted Group Memembership

Pr

Group

AD

MCI

Controls

22 2 0 88.0 8.0 16.0

3 22 4 12.0 88.0 84.0

0 1 21 .0 4.0 100.0

Total

25 25 25 100.0 100.0

classified the cases from the originally

Jo ur

7. Appendix: Contents and structure of the NeuroBel screening test

TASK

SAMPLE ITEM

SCORE out of 100 points

-Judge whether a pair of syllables are the same or different. - TOTAL ÍTEMS: 24; 12 words were same and 12 were different

fla-fla mar-bar gas-gas fras-fros

1/2 point by correct answer (max: 12 points)

A.

C O M P R E H E N S I O N

FUNCTION ASSESSED

NEUROBEL

Phoneme discrimation

Auditory discrimination.

32

Auditory word recognition.

f

nieve (snow) rieje tornado (tornado) lorgado

-Judge whether pairs of words are the same or different with respect to the initial phoneme. -TOTAL ÍTEMS: 24; 12 were words and 12 were non-words

oo

Auditory lexical decision

1/2 point by correct answer (max: 12 points)

e-

Syntax comprehension and meaning access

-Participants must follow simple orders that the neuropsychologist asks to do or answer. -TOTAL ÍTEMS: 6

1 point by correct answer (max: 16 points)

- Señale la ventana y después la -Failure: 0 points puerta/ Point to the window and -Only one order is correct: 1 point then the door -The 2two orders are correct: 2 points (max: 12 points) - Dibuje un redondel dentro de un cuadrado/ Draw a circle inside a square

Jo ur

na l

Auditory sentence comprehension

-Testing whether there are Semantic system and auditory difficulties in word comprehension meaning access. and visual identification -TOTAL ÍTEMS: 16

Pr

Spoken word to picture matching

pr

mano; pie, pierna, oreja hand; foot, leg, ear

33

f oo pr ePr

NEUROBEL

FUNCTION ASSESSED Acoustic to Phonological conversion

na l

Object naming

phonological output lexicon access (nouns)

Jo ur

B. PRODUCTIONN

Repetition

Action naming

phonological output lexicon access (verbs)

TASK

- Repetition of words and nonwords - TOTAL ÍTEMS: 24; 12 were words and 12 were non-words -Judge naming abilities and anomia. -TOTAL ÍTEMS: 24; 12 were high frequency (mean=55,5 per million) and 12 were low frequency (mean 3,8 per million)

SAMPLE ITEM

SCORE out of 100 points

barco (ship) fanto 1/2 point by correct answer (max: 12 revolución (revolution) points) retionático tijeras (scissors)–escoba (broom) 1/2 point by correct answer (max: 12 points)

-Judge whether there are possible correr (running)-peinarse (comb) dissociation of action and object naming. -TOTAL ÍTEMS: 12. 6 were high 1 point by correct answer (max: 12 points) frequency more than 50 per million (mean=230,3 per million) and 6 were low frequency (mean 22 per million)

34

f

(max: 12 points)

Jo ur

na l

Pr

e-

pr

oo

2 points: sentence correctly completed syntactically and semantically (the participant expresses exactly what - El cocinero (the cook) …hace o happens in the picture) prepara la comida (makes or prepares the food). 1 point: sentence correctly completed syntactically, but with semantic errors, either for lack of the most correct word, for not specifying well the scene that appears in the picture or for referring to secondary things on it (i.e. “El -Participants must complete cocinero… tiene una zanahoria en la correctly both semantic (according mano/ The cook has a carrot in his hand). morphosyntactic and semantic to the context of a picture) and Sentence completion construction syntactically (from a first word 0 points: when the participant fails and provided by the clinician there is no answer. If the sentence is -TOTAL ÍTEMS: 6 incomplete and with grammatical deficits and/or semantically inappropriate, because it is not the sense of the picture. When the subject stubbornly begins the sentence with a word that is not the proposal word to begin the sentence (i.e. “El cocinero…y la olla eran llenos”/ untranslatable into English).

35