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2016 FI

© Thomson Reuters, Journal Citation Reports, 2016

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  • Impact Factor: 2,103 (2016)
  • SCImago Journal Rank (SJR):0,36
  • Source Normalized Impact per Paper (SNIP):0,648

© Thomson Reuters, Journal Citation Reports, 2016

Neurologia 2018;33:138-9 - DOI: 10.1016/j.nrleng.2016.02.013
Letter to the Editor
A report on reliable differences in the profile of the ACE-III
Reporte de las diferencias confiables en el perfil del ACE-III
S.A. Dominguez-Lara,
Universidad de San Martín de Porres, Lima, Peru
Dear Editor:

In a recent study, Matías-Guiu et al.1 analysed the psychometric properties of Addenbrooke's Cognitive Examination III (ACE-III) for the diagnosis of dementia. These authors reported high reliability and inter-rater agreement (>0.90), good sensitivity and specificity, and a strong correlation with the Mini–Mental State Examination (MMSE). However, they focus on total ACE-III scores, disregarding subtest scores for attention, memory, fluency, language, and visuospatial abilities. These subtests provide valuable information on the patient's cognitive profile, which is essential for preparing a personalised treatment plan.

In clinical practice, ACE-III subscores vary from patient to patient; the reliability of such differences should therefore be assessed. Matías-Guiu et al. do not evaluate this factor; as a result, the extent to which an ACE-III profile is influenced by measurement error cannot be determined. A mathematical formula has been proposed to address this issue, and can be used to analyse the difference between 2 scores2:

In this expression, SD1, SD2, ρ1, and ρ2 are the standard deviations (SD) and reliability coefficients (normally the α coefficient3) of subtests 1 and 2, respectively, and ρ12 is the correlation between the 2 subtests. The result (0ρd1) indicates the percentage of variability corresponding to true variance; when the latter is high, it can be concluded that the error of measurement has had no decisive impact on differences.

Matías-Guiu et al. only report SDs for each subtest in one of the tables of the study, and provide no data on their α coefficients or the correlation between subtests. Using fictitious data, below is an example of how complementary analyses may fill this gap. Firstly, to estimate the α coefficient of each subtest, the mean inter-item correlation for the total scale (rij) was calculated using the following formula α (k is the number of items)4:

The α coefficient of each subtest was subsequently calculated, with the assumption that the value of rij is similar for all subscales. The result shows a low inter-item correlation (mean of 0.128).5 Based on these data, the α coefficients for attention, memory, fluency, language, and visuospatial abilities were 0.685, 0.762, 0.625, 0.762, and 0.658, respectively. If the data used for calculating the reliability of scores were real, subtest scores could not be used in clinical decision-making due to the magnitude of the reliability coefficients (α<0.90).6 A correlation of ρxy=0.50 was assumed, given that correlation coefficients were not reported. Finally, this example used the SDs of the control group of patients aged 65 or older. The potential differences between subtest scores were then calculated using all the data available.

The results shown in Table 1 demonstrate a low reliability in the differences between subscales, discouraging clinical diagnosis based on the analysis of ACE-III profiles. As most of the data used were fictitious, this example only illustrates the method to be followed. Nonetheless, if Matías-Guiu et al. were to perform this analysis using their own data, it would undoubtedly be enlightening with regards to the use of the ACE-III for clinical assessment.

Table 1.

Reliability of the differences between ACE-III subtests.

Subtest  Reliability of differences 
Attention-memory  0.442 
Attention-fluency  0.459 
Attention-language  0.463 
Attention-visuospatial  0.535 
Memory-fluency  0.519 
Memory-language  0.541 
Memory-visuospatial  0.606 
Fluency-language  0.443 
Fluency-visuospatial  0.307 
Language-visuospatial  0.580 

The author has received no funding of any kind.

Conflicts of interest

The author has no conflicts of interest to declare.

J.A. Matias-Guiu,R. Fernández de Bobadilla,G. Escuderoa,J. Pérez-Pérez,A. Cortés,E. Morenas-Rodríguez
Validación de la versión española del test Addenbrooke's Cognitive Examination III para el diagnóstico de demencia
Neurología, 30 (2015), pp. 545-551 http://dx.doi.org/10.1016/j.nrl.2014.05.004
J. Muñiz
Teoría clásica de los test
Pirámide, (2003)
L.J. Cronbach
Coefficient alpha and the internal structure of tests
Psychometrika, 16 (1951), pp. 297-334
P. Pascual-Ferrá,M.J. Beatty
Correcting internal consistency estimates inflated by correlated item errors
Commun Res Rep, 32 (2015), pp. 347-352
L.A. Clark,D. Watson
Constructing validity: basic issues in objective scale development
Psychol Assess, 7 (1995), pp. 309-319
C. Merino,J. Navarro,W. García
Revisión de la consistencia interna del Inventario de Inteligencia Emcional de Bar-On, EQ-I: YV
Rev Per Psico Trab Soc, 3 (2014), pp. 141-154

Please cite this article as: Dominguez-Lara S. Reporte de las diferencias confiables en el perfil del ACE-III. Neurología. 2018;33:138–139.

☆☆ This article has not been presented at any meeting or congress.

Copyright © 2016. Sociedad Española de Neurología