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Aphasiology
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/paph20
Language processing in glioma patients: speed or
accuracy as a sensitive measure?
Saskia Mooijman, Laura S. Bos, Elke De Witte, Arnaud Vincent, Evy Visch-
Brink & Djaina Satoer
To cite this article: Saskia Mooijman, Laura S. Bos, Elke De Witte, Arnaud Vincent, Evy Visch-
Brink & Djaina Satoer (2021): Language processing in glioma patients: speed or accuracy as a
sensitive measure?, Aphasiology, DOI: 10.1080/02687038.2021.1970099
To link to this article: https://doi.org/10.1080/02687038.2021.1970099
© 2021 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group.
Published online: 21 Sep 2021.
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Language processing in glioma patients: speed or accuracy as
a sensitive measure?
Saskia Mooijman
a,b,c
, Laura S. Bos
a,b
, Elke De Witte
a,d
, Arnaud Vincent
a
, Evy Visch-
Brink
a
and Djaina Satoer
a
a
Department of Neurosurgery, Erasmus Mc University Medical Centre Rotterdam, The Netherlands;
b
Amsterdam Centre for Language and Communication, University of Amsterdam, The Netherlands;
c
Centre
for Language Studies, Radboud University, Nijmegen, The Netherlands;
d
Centre for Linguistics, Clinical and
Experimental Neurolinguistics, Free University, Brussels, Belgium
ABSTRACT
Background: Glioma (brain tumour) patients can suer from mild
linguistic and non-linguistic cognitive problems when the glioma is
localised in an eloquent brain area. Word-nding problems are
among the most frequently reported complaints. However, mild
problems are dicult to measure with standard language tests
because they are generally designed for more severe aphasic
patients.
Aims: The aim of the present study was to investigate whether
word-nding problems reported by patients with a glioma can be
objectied with a standard object naming test, and a linguistic
processing speed test. In addition, we examined whether word-
nding problems and linguistic processing speed are related to
non-verbal cognitive abilities.
Methods & Procedures: We tested glioma patients (N=36) as part
of their standard pre-treatment clinical work-up. Word-nding pro-
blems were identied by a clinical linguist during the anamnesis.
Linguistic processing speed was assessed with a newly designed
sentence judgment test (SJT) as part of the Diagnostic Instrument
for Mild Aphasia (DIMA), lexical retrieval with the Boston Naming
Test (BNT), presence of aphasia with a Token Test (TT), and non-
verbal processing with the Trail Making Test A and B (TMT). Test
performances of glioma patients were compared to those of
healthy control participants (N=35).
Outcomes & Results: The results show that many glioma patients
(58%) report word-nding problems; these complaints were in only
half of the cases supported by deviant scores on the BNT. Moreover,
the presence of reported word-nding problems did not correlate
with the BNT scores. However, word-nding problems were signi-
cantly correlated with reaction times on the SJT and the TMT.
Although there were no signicant dierences between the patient
and control group on the SJT, a subgroup of patients with a glioma
in the frontal lobe of the language-dominant hemisphere was
ARTICLE HISTORY
Received 23 February 2021
Accepted 16 August 2021
KEYWORDS
Glioma; processing speed;
word-finding problems;
cognition
CONTACT Saskia Mooijman s.mooijman@erasmusmc.nl Department of Neurosurgery, Erasmus MC - University
Medical Center 3000 CA Rotterdam, The Netherlands.
APHASIOLOGY
https://doi.org/10.1080/02687038.2021.1970099
© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/
licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
slower on the SJT. Finally, performance on the SJT and TMT were
signicantly correlated in the patient group but not in the control
group.
Conclusions: Linguistic processing speed appears to be an impor-
tant factor in explaining reported word-nding problems.
Moreover, the overlap between speed of language processing
and non-verbal processing indicates that patients may rely on
more domain-general cognitive abilities as compared to healthy
participants. The variability observed between patients emphasises
the need for tailored neuro-linguistic assessments including an
extensive anamnesis regarding language problems in clinical work-
up.
Introduction
Gliomas
Gliomas are the most common type of primary brain tumour. The World Health
Organization categorises gliomas into four grades. High-grade gliomas (HGG, grades III–
IV) are more aggressive and more common than low-grade gliomas (LGG, grades I–II;
Sanai & Berger, 2012). Gliomas are often located in eloquent areas of the brain (Duau &
Capelle, 2004; Gerritsen et al., 2019). In these cases, surgery is aimed at resecting the
tumour whilst preserving cognitive functions (Ilmberger et al., 2008; Sanai & Berger, 2008;
De Witte & Mariën, 2013). Due to the preferential localisation of gliomas in eloquent areas
of the brain, patients may experience neurological and cognitive impairments that can
have serious consequences on their quality of life.
Sensitivity of assessments
It is of central importance for quality of life to investigate how patients subjectively
experience (loss of) abilities, such as language (Cruice, Worrall, & Hickson, 2006). Word
retrieval diculties are among the most common complaints of people with a glioma
(Racine et al., 2015). Importantly, performance on objective cognitive tests may not
necessarily reect the patients’ complaints (Gehring et al., 2015; Racine et al., 2015;
Taphoorn & Klein, 2004; Van der Linden et al., 2020). More specically, patients appear
to report language complaints that are not supported by lower scores on standard
language measures, demonstrating insucient sensitivity of those tests (Brownsett
et al., 2019; Satoer et al., 2012).
For instance, Satoer et al. (2012) compared scores on the Aphasia Severity Rating Scale
(ASRS; Goodglass et al., 2001) to the self-reported problems and found that more patients
reported issues in daily communication than were shown to have impairments based on
the ASRS (57% vs. 39%, respectively). This shows the value of combining standardised
tests with an evaluation of self-reported complaints in the assessment of cognitive
abilities of glioma patients (Taphoorn & Klein, 2004).
A potential reason for the discrepancy between subjectively experienced language
diculties and objective test performance, is that aphasia assessments are generally
designed for patients who suered a stroke. Glioma patients, with comparable lesion
2S. MOOIJMAN ET AL.
size and location, typically have milder language and/or cognitive decits (Anderson et al.,
1990). These mild impairments can be the result of neural reorganisation (i.e., compensa-
tion for loss of function) due to the slow growth rate of gliomas as compared to the
sudden onset of neurological damage caused by stroke (Duau, 2008, 2014). The subtlety
of cognitive-linguistic impairments in glioma patients poses a problem for the assessment
of their cognitive functions.
Processing speed
Including a measure of response speed in the assessment of glioma patients may increase
sensitivity of standard measures and provide a way to objectively measure self-reported
word-nding problems. Language processing in patients with a glioma was investigated
by Moritz-Gasser et al. (2012), who studied the correlation between naming capacities and
the ability to return to work after surgery. They found that naming speed, rather than
accuracy, signicantly predicted return to work, an important marker for quality of life.
Importantly, none of the patients in their study was classied as “aphasic” according to
the Boston Diagnostic Aphasia Examination (BDAE; Goodglass & Kaplan, 1972), a test
battery originally designed for stroke patients. Another recent study has shown that
patients with gliomas are signicantly slower on a speeded naming test compared to
healthy participants (Ras et al., 2020). This dierence could not be explained by naming
ability measured with the Boston Naming Test (BNT; Kaplan et al., 2001).
As for non-verbal processing speed, previous studies have shown that glioma patients
performed signicantly worse than a healthy control group (Habets et al., 2014; Wefel
et al., 2016). Interestingly, it even appeared to be the most-often impaired cognitive ability
in this patient group (Ek et al., 2010). These studies typically operationalise non-verbal
processing speed with a Symbol Digit Modalities Test (Smith, 1973) or the Trail Making
Test Part A (TMT-A; Army Individual Test Battery, 1944).
Including an assessment of processing speed may not only increase the sensitivity of
measures, but may also bear a direct relationship with communicative diculties experi-
enced by patients in everyday conversations. Everyday communication requires the
conversational partners to process information quickly and respond to it in an appropriate
manner, and speedy processing of linguistic information is crucial (e.g., Carragher et al.,
2012). Subjectively experienced word-nding problems may therefore be the result of not
only a lexical retrieval problem, but may also be due to slowed processing.
Domain generality of processing speed
The nding that patients with a glioma are slower on both linguistic (Moritz-Gasser et al.,
2012; Ras et al., 2020) and non-linguistic tasks (Ek et al., 2010; Habets et al., 2014; Wefel
et al., 2016), raises the question whether slowed performance of a language test is specic
to language processing, or whether it has a more domain-general origin. This topic has
been investigated in people with aphasia due to stroke. For example, individuals with
aphasia (and individuals with left-hemispheric lesions without aphasia) were found to have
lower processing speed both within and outside the language domain (Yoo et al., 2021).
APHASIOLOGY 3
Moritz-Gasser et al. (2012) and Ras et al. (2020), on the other hand, found that naming
speed of patients with a glioma could not be explained by non-verbal processing speed
measured with the TMT-A. Their ndings suggest that there is a discrepancy between naming
accuracy, naming speed, and general processing speed. However, these two studies investi-
gated processing speed in the production of language, leaving receptive linguistic processing
speed of patients with a glioma open for investigation. It is not self-evident that the inuence
of processing speed is the same in both language modalities, as a discrepancy between
decits in language production and reception has been described (De Witte et al., 2015b).
From this discussion of the literature it has become clear that the subjectively experi-
enced communication diculties are not always supported by impaired performance on
standard language measures. Measuring processing speed may be useful in objectively
assessing subjectively experienced word-nding problems, not only because information
processing speed has often been found to be impaired in patients with a glioma, but also
because everyday communication relies on speeded integration of linguistic information.
Problems in everyday communication may therefore be the result of slower linguistic or
non-linguistic processing abilities.
Present study
We aim to investigate whether including a measure of response speed in a receptive
language test is a sensitive measure for self-reported word-nding problems in patients
with a glioma. The presence of self-reported word-nding problems was correlated with
lexical retrieval, receptive linguistic processing speed, and non-verbal cognitive abilities.
We compared a group of patients with a glioma to a group of age- and education-
matched healthy control participants. Individual patients were also described and com-
pared to norm groups. The following research questions were investigated:
RQ1: To what extent can self-reported word-nding problems of patients with gliomas be
explained by:
i. Lexical retrieval as measured with the Boston Naming Test or performance on a Token
Test?
ii. Linguistic processing speed as measured with a time-pressured sentence judgment test?
iii. Non-verbal cognitive abilities as measured with the Trail Making Test A and B?
RQ2: Is linguistic processing speed of patients with gliomas related to non-linguistic cognitive
abilities?
Based on previous ndings in the literature, we hypothesised a discrepancy between the
subjectively experienced word-nding problems and the objectively measured abilities of
patients (Brownsett et al., 2019; Satoer et al., 2012). The addition of reaction time measures to
a sentence judgment test is expected to lead to a sensitive measure that can explain
anamnestic complaints (Moritz-Gasser et al., 2012; Ras et al., 2020). Finally, if the word-
4S. MOOIJMAN ET AL.
nding problems and slower language processing are the result of a more global cognitive
impairment, we expect that patients will also exhibit longer reaction times on a non-linguistic
task.
Methods
Participants
The study group consists of glioma patients (N = 50) who have undergone awake
surgery (between March 2015 and November 2017) at the Erasmus MC University
Medical Centre. All patients diagnosed with a glioma, regardless of the hemispheric
localisation, were included in the study, as previous research has shown that patients
with a glioma in the right hemisphere may also experience language diculties
(Vilasboas et al., 2017; De Witte et al., 2015c). Fourteen patients were excluded due to
a recurrent tumour with second or third surgery (N = 10)
1
; too many missing data
(N = 2); or co-occurring developmental dyslexia (N = 1) or Noonan Syndrome (N = 1).
This resulted in 36 participants in the patient group. All patients were native speakers of
Dutch.
Healthy native speakers of Dutch (N = 35) constituted the control group of the study.
They were matched to the patient group on age and education but not on gender, as
gender has generally not been shown to inuence performance on standard language
tests (e.g., Snitz et al., 2009; De Witte et al., 2015b). They were included if they had no
(history of) cardiovascular, neurological, psychiatric, or developmental language disor-
ders; no toxic substance abuse; normal vision and hearing; no sleep medication, psycho-
tropic, or neuroleptic drugs. The demographic information of the patients and control
participants is given in Table 1. None of the participants was nancially compensated for
his/her participation. The Ethical Committee of the Erasmus MC approved of the study
and all participants gave their informed consent.
Materials
Word-finding problems
Information on word-nding problems in patients was based on complaints reported
during the preoperative anamnesis. The information in the anamnesis is gathered in an
interview with the patient by a clinical linguist, using a standard set of questions about
encountered problems with language, memory, attention, and executive functioning. The
word-nding complaints were labelled as follows: 0: no complaints; 1: mild complaints, if
the patients only reported diculties after more targeted questions, if they indicate that
they “sometimes” experience problems, or if their partner reported word-nding dicul-
ties; 2: clear complaints, if the patient presented their word-nding complaints centrally in
the anamnesis, or with modiers such as “often”, or “severe”. The same coder re-coded the
data at a later timepoint and the intra-coder reliability was assessed using an intra-class
correlation analysis. The intra-class correlation estimate was based on a single-rating,
absolute-agreement, two-way mixed-eects model. The results show that agreement
between these two timepoints was good-excellent (intraclass correlation coecient = .89,
p < .001).
APHASIOLOGY 5
An example of a mild complaint
“Patient does not report cognitive problems. After additional questions, he reports subtle
word-nding diculties. Handwriting is also a bit messier.”
An example of a clear complaint
“Patient reports word-nding diculties that result in avoiding talking to people. Word is in
mind but cannot be pronounced. Patient also fails in writing and typing. In addition, there are
sound changes, and articles and function words that are forgotten.”
Standard language tests
The Boston Naming Test (BNT; Kaplan et al., 2001), a standard test to assess anomia in
individuals with aphasia was administered. Patients also completed the shortened Token
Test (TT; De Renzi & Faglioni, 1978), a standard test to measure aphasia severity.
Linguistic processing speed
The Sentence judgment Test (SJT), a subtest of the Diagnostic Instrument for Mild Aphasia
(DIMA; Satoer et al., 2021), was used to test comprehension and language processing on
the semantic, syntactic, and phonological level. The SJT was administered in E-Prime
Table 1. Demographic and tumour characteristics. Education level based on Verhage (1964): Dutch
classification system including 7 categories. 1: did not finish primary school, 2: finished primary school, 3:
did not finish secondary school, 4: finished secondary school, low level, 5: finished secondary school,
medium level, 6: finished secondary school, highest level, and/or college degree, 7: university degree).
Demographic characteristics for patients and control participants
Group Patients Control participants
Gender Female 12 20
Male 24 15
Mean age (range) 45.37 (18–73) 42.75 (19–61)
Mean education (range) 5.36 (3–7) 5.53 (3–7)
Handedness Right 28 N/A
Left 8 N/A
Tumour characteristics for 36 patients
Variable Count (%)
Hemispheric lateralisation Left hemisphere 24 (67)
Right hemisphere 12 (33)
Tumour localisation: lobe Frontal 19 (53)
Temporal 7 (19)
Insular 1 (3)
Parietal 3 (8)
Frontoparietal 2 (6)
Parietotemporal 1 (3)
Temporoparietal 1 (3)
Frontotemporal 2 (6)
Tumour histological type Astrocytoma 13 (36)
Oligodendroglioma 12 (33)
Glioblastoma 10 (28)
Xanthoastrocytoma 1 (3)
Tumour grade (WHO classification) Grade I 1 (3)
Grade II 20 (56)
Grade II 5 (14)
Grade IV 10 (26)
6S. MOOIJMAN ET AL.
software (Psychology Software Tools, 2012) or in Praat (Boersma & Weenink, 2018). The
SJT consists of 30 sentences, half of which contain errors in three dierent linguistic
domains. The phonological items aim to assess phonological awareness by including
pseudo-words (Example 1). The syntactic items contain errors in verb inection (tense and
agreement), word order, or pronouns (Example 2), and the semantic items include
sentences with semantic anomalies (Example 3).
Example 1 De zanper koopt een blando.
The zanper buy-AGR a blando
“The zanper buys a blando”.
Example 2 Linda zingt gisteren een lied.
Linda sing-AGR.PRES yesterday a song
“Linda sings a song yesterday”.
Example 3 De loodgieter repareert de regenboog.
The plumber repair-AGR the rainbow
“The plumber repairs the rainbow”.
The participants read the sentences on a computer screen and rated their correct-
ness by pressing the keys “F” for fout “wrong” and “J” for juist “right” on the
keyboard. Reaction times (RTs) in milliseconds and accuracy were measured. RTs
were operationalised as the time between the start of the stimulus presentation
and the manual response of the participant. Items were presented in randomised
order, and the test contained four practice items to familiarise participants with the
procedure.
Non-language tests
Nonverbal cognitive abilities of the participants were assessed using the Trail Making
Test A and B (TMT-A and -B; Army Individual Test Battery, 1944). In the TMT-A, the
participant connects numbers (1–25) in an ascending order on a paper sheet. The
TMT-B requires the participant to connect alternating numbers and letters (i.e.,
1-A-2-B-3 etc.). The score on both tasks consists of the time in seconds it takes to
nish. Visuoperceptual speed underlies performance on the TMT-A, while TMT-B
relies more heavily on updating and concept-shifting abilities (Sánchez-Cubillo
et al., 2009). The dierence score TMT-BA, operationalised as the ratio score B:A,
provides a relatively pure measure of cognitive exibility.
Procedure
The clinical sta at the Erasmus MC University Medical Centre collected the data of
the patients. An elaborate neuro-linguistic test protocol was administered as part of
the standard clinical work-up, and the tests we report on in the present study are
part of this protocol. The results of the preoperative assessment were compared to
APHASIOLOGY 7
the performance of healthy control participants, who were tested in a private setting.
The BNT, SJT, and TMT were administered in a random order. The entire procedure
lasted approximately 15 minutes.
Data analysis
All statistical analyses were carried out in R (R Core Team, 2019) and the graphics were
created using R-package ggplot2 (Wickham, 2016). The results on the SJT, TMT, TT, and BNT
constitute the dependent variables. The data were analysed using regression models in the
R package lme4 (Bates et al., 2015) and lmerTest (Kuznetsova et al., 2017) to retrieve p-values.
The accuracy scores and RTs of the SJT were analysed with a (generalised) linear mixed-
eects regression model with random slopes for participants and items. The outcomes of
the TMT, TT, and BNT were analysed using a linear regression model. The scores on the TMT
were log-transformed to meet the model criteria. We adhered to an α-level of 0.05.
The main predictor in each model was group (patients vs. control participants), and
covariates age and education level were included in all models. Within the patient group,
the eects of tumour grade (LGG vs. HGG) and hemisphere (left vs. right) and the interac-
tion eect between these factors were estimated. The output of the statistical models is
included in the Appendix.
The analysis of the SJT results was carried out with the anomalous sentences.
2
Linguistic levels (semantics, syntax, phonology) and trial-by-trial sequence (i.e., the position
of each item in the test) were included as additional within-participant predictors. We
removed outliers before the group analysis of the RTs of the SJT. Items with an RT below
500 milliseconds were removed as it is assumed that participants need at least 500
milliseconds to properly assess an item, so shorter RTs are likely due to slips of attention.
In addition, items with an RT above 10 seconds were removed, as the E-Prime experiment
included a time limit and any responses longer than 10 seconds were classied as null
responses. This led to the exclusion of 13 trials (0.7%). Thereafter, outliers per participant
were calculated and removed from the dataset using the trimr package (Grange, 2015). An
outlier was dened as an RT value of 2 SD above or below the mean for each participant.
This led to the exclusion of 87 trials (5%). The remainder of the RTs were log transformed
to normalise the data and meet the model criteria. The log-transformed RTs provided
a good t for the raw data (ρ = .96, p < .001).
To estimate the relationship between the anamnestic complaints and the scores on the
objective measures, the correlation between these measures was calculated using
Pearson’s correlation coecient.
Results
Lexical retrieval
The results at the individual patient level are presented in Table 2. Preoperatively, 15 out
of 36 patients (42%) did not report any word-nding diculties. Twenty-one patients
(58%) reported word-nding problems of which twelve patients (33%) reported mild
word-nding problems, and nine patients (25%) reported serious word-nding problems.
Tumour grade did not signicantly inuence the experienced word-nding problems
8S. MOOIJMAN ET AL.
Table 2. Individual patient scores. Table legend: PP; participant number, Age; age in years at time of assessment, Edu; education level based on Verhage (1964),
Sex; male (M) or female (F), Hand; handedness left (L) or right (R), Grade; tumour grade from I–IV based on WHO classification, Location; location of the tumour: left
(L) or right (R) hemisphere followed by lobe, WFP; word-finding problems, BNT; score on Boston Naming Test, TT; score on shortened Token Test, TMT-A; score
(sec) on Trail Making Test-A, TMT-B; score (sec) on Trial Making Test-B, TMT-BA; ratio of difference score TMT part A and B, SJT; reaction times (ms) and accuracy
scores on the Sentence Judgment Test. Deviant scores marked in bold.
PP Age Edu Sex Hand Grade Location WFP BNT TT TMT-A TMT-B TMT-BA SJT
Semantics Syntax Phonology Accuracy
118 6 M L I L Frontal No 58 36 21 38 1.8 1759 2459 1824 15
221 5 M R III L Fronto-parietal Mild 45 34 41 100 2.4 3313 4473 2842 12
323 5 F R II L Frontal Clear 56 36 28 64 2.3
423 6 M R IV L Frontal No 48 36 17 33 1.9 1723 2088 1333 15
532 5 F L III L Fronto-temporal Clear 49 31 55 174 3.2
632 5 M R III R Parietal No 51 28 29 80 2.8
733 4 M R II R Frontal Mild 44 34 37 108 2.9 2696 4035 2827 14
834 5 M L II L Frontal No 48 33 29 58 2.0
936 7 M R II R Frontal Mild 58 34 24 34 1.4 1479 1576 1327 15
10 36 5 M R II L Frontal Clear 54 33 34 84 2.5 6695 5977 4228 11
11 36 6 M R IV L Temporo-parietal Clear 54 35 19 46 2.4 3647 3012 1491 15
12 42 5 F L IV L Temporal Clear 34 25 46 127 2.8 3163 4300 2991 15
13 42 5 F R IV L Frontal No 38 34 23 84 3.7 3648 2660 2707 13
14 42 7 M R III R Parieto-temporal Mild 57 35 22 48 2.2 2404 2421 1441 11
15 43 5 F R II R Frontal No 52 34 17 56 3.3 1578 2180 1142 15
16 45 5 M R II R Fronto-parietal Clear 56 36 24 87 3.6
17 46 6 M L III L Frontal Mild 50 36 18 40 2.2 2468 4789 2271 14
18 47 3 F R II L Frontal No 48 35 30 103 3.4
19 47 5 M R II R Temporal Mild 2898 2597 2211 12
20 48 5 M R II R Frontal No 49 33 41 52 1.3 2309 3157 1405 14
21 49 6 F L IV L Frontal No 56 30 27 62 2.3
22 49 5 F R II R Temporal No 54 35 31 60 1.9 2506 3582 1599 14
23 50 7 M R II R Frontal No 59 35 14 38 2.7 1596 2408 1404 15
24 51 5 F R II L Parietal Mild 35 35 21 34 1.6
25 51 6 M R II L Insular Clear 48 35 33 52 1.6
26 51 7 M R II L Frontal No 58 36 19 34 1.8
27 52 5 M R II L Temporal Mild 54 29 80 2.8
28 53 4 M L II L Parietal No 34 33 35 79 2.3
29 54 5 F R IV L Temporal Mild 44
30 57 5 M R II R Frontal Mild 36 36 42 56 1.3 2210 2683 1853 13
31 59 6 M R II R Fronto-temporal No 53 36 15 49 3.3 2586 2152 2774 13
(Continued)
APHASIOLOGY 9
Table 2. (Continued).
PP Age Edu Sex Hand Grade Location WFP BNT TT TMT-A TMT-B TMT-BA SJT
Semantics Syntax Phonology Accuracy
32 62 5 F R II L Temporal Mild 55 17 37 2.2 1414 2097 1103 12
33 63 5 M R IV L Frontal Mild 53 35 3329 3614 3225 13
34 66 5 M R IV L Frontal No 32 53 106 2.0
35 69 6 F L IV L Temporal Clear 20 32.5 38 199 5.2
36 73 6 M R IV L Frontal Clear 54 35 48 318 6.6 5595 6030 4928 14
10 S. MOOIJMAN ET AL.
(ß = −0.26, SE = 0.34, p = .45), neither did the hemispheric localisation (ß = 0.58, SE = 0.62,
p = .36). There was no signicant interaction between grade and hemispheric localisation
(ß = 0.36, SE = 0.72, p = .62).
At the group level, patients (M = 48.9, 82%) deviated from the control participants
(M = 52.9, 88%) on the BNT (ß = 3.54, SE = 1.62, p = .03). The patients’ BNT scores were not
signicantly inuenced by tumour grade (ß = 4.41, SE = 3.71, p = .24), hemispheric
localisation (ß = 8.57, SE = 6.78, p = .22), or an interaction between these factors
(ß = −7.23, SE = 7.87, p = .37). The experienced word-nding problems were not always
accompanied by deviant scores on the BNT and these outcomes were not correlated
(ρ = −.15, p = .40). Of the patients who reported word-nding diculties, one did not
perform the BNT. Ten out of the remaining twenty patients with reported word-nding
problems (50%) also showed deviant scores on the BNT.
The scores on the shortened Token Test did not correlate with the reported word-
nding diculties (ρ = −.07, p = .71). The mean score of the patient group was 33.8 out of
36 points. Adhering to the cut-o score of 29 (De Renzi & Faglioni, 1978), only one patient
showed a deviant score on the Token Test. The Token Test scores were not signicantly
inuenced by tumour grade (ß = 1.79, SE = 1.08, p = .11), or hemispheric localisation
(ß = −1.38, SE = 1.86, p = .47). And there was no signicant interaction eect between
these variables (ß = 1.43, SE = 2.19, p = .52).
Linguistic processing speed
At the group level, there were no signicant dierences for RTs between patients and
control participants (ß = −0.02, SE = 0.08, p = .84), but the dierence between the two
groups on accuracy scores in all linguistic domains combined was signicant (ß = 1.16,
SE = 0.41, p = .01). The dierences between the groups are presented in Figure 1. Tumour
grade, hemispheric localisation, or the interaction between these factors, did not signi-
cantly aect RTs nor accuracy scores. The reported word-nding problems were strongly
correlated with the RTs on the SJT averaged over all linguistic domains (ρ = .64, p < .01),
and with each linguistic level separately (syntax: ρ = .61, p = .003; semantics: ρ = .64,
p = .002; phonology: ρ = .55, p = .01). However, the word-nding complaints did not
correlate signicantly with the accuracy scores on the SJT over all linguistic domains
(ρ = −.23, p = .31).
At the individual patient level, it appears that there is a subgroup of patients with
deviant RTs in the SJT compared to normative data (Satoer et al., 2021). Six out of twenty-
one (29%) patients had slightly deviant RTs (≥1.5 SD from population mean) in at least one
of the three linguistic domains (phonology, semantics, syntax). All six patients with
deviant RTs on the SJT had a glioma in the left hemisphere, and all but one (83%) in
the frontal lobe. One patient (17%) had a grade-II glioma, two patients (33%) a grade-III
glioma, and three patients (50%) had a grade-IV glioma. Eight out of twenty-one (38%)
patients showed deviant accuracy scores on the SJT. Nine out of 35 control participants
(26%) had deviant RTs on one of the language domains of the SJT, and two control
participants (6%) showed deviant accuracy scores.
APHASIOLOGY 11
Non-verbal cognitive measures
At the group level, there was no statistically signicant dierence between the patient
group and the control group on the TMT-A and B (ß = 0.08, SE = 0.08, p = .30 for TMT-A
and ß = 0.13, SE = 0.09, p = .16 for TMT-B). However, patients had a larger dierence score
on the TMT-BA compared to healthy participants (ß = 0.56, SE = 0.19, p = .004). The
dierences between the groups are presented in Figure 2. Within the patient group,
patients with an HGG were slower to nish the TMT-B (ß = −0.51, SE = 0.22, p = .03) and
had a larger ratio score on TMT-BA (ß = −0.96, SE = 0.45, p = .04) compared to patients
with an LGG. This was not the case for the TMT-A (ß = −0.22, SE = 0.16, p = .17). There were
no signicant main eects of hemispheric localisation or interaction eects between
these factors on any of the TMTs.
Figure 1. Reaction times (in milliseconds) and accuracy (percentage correct) on the SJT for healthy
control participants (HC) and patients (PT) and per linguistic domain. Error bars represent the standard
error.
12 S. MOOIJMAN ET AL.
In the patient group, performance speed on the TMT-A and -B strongly correlated with
the RTs on the SJT (ρ = .61, p = .01 for TMT-A and ρ = .74, p < .001 for TMT-B), indicating
that longer RTs on the SJT were accompanied by longer completion time on the TMT-A
and -B. The ratio of the dierence score TMT-BA also correlated moderately with the RTs
on the SJT (ρ = .59, p = .01), indicating a shifting component in the SJT independent of
speed. Interestingly, in the control group signicant correlations between the RTs on the
SJT and the TMT-A and -B were absent (ρ = .20, p = .256 and ρ = .10, p = .58, respectively).
In the control participants, the ratio score of the dierence TMT-BA also did not correlate
signicantly with the RTs on the SJT (ρ = −.07, p = .682). These correlations are presented
in Figure 3.
There was a weak but signicant correlation between the reported word-nding pro-
blems and the TMT-B (ρ = .44, p = .01) and a marginally signicant correlation between the
word-nding problems and the TMT-A (ρ = .34, p = .052). The correlation between word-
Figure 2. Scores (in seconds) on the TMT-A and TMT-B and ratio scores on TMT-BA per participant
group. Error bars represent the standard error.
APHASIOLOGY 13
nding problems and the TMT-BA was not signicant (ρ = .32, p = .07). Model comparison
showed that the linear regression model with only the RTs in the SJT as a predictor (and no
TMT measure) yielded the best t for the word-nding problems (Figure 4).
Eleven out of 33 patients (33%) had an impaired score on at least one of the
subcomponents of the TMT (Tombaugh, 2004). Three patients (9%) scored >1.5 SD
from the normal score on both the TMT-A and B. Three patients (9%) had problems
with the TMT-B and a deviant dierence score TMT-BA (cut-o ratio score >3,
Arbuthnott and Frank, 2000). Five out of 33 patients (15%) had a selective problem
with concept shifting (cognitive exibility), exemplied by a deviant dierence score
TMT-BA.
Figure 3. Correlations between the reaction times (milliseconds) on the SJT and the TMT-A (A), TMT-B
(B), and TMT-BA (C).
14 S. MOOIJMAN ET AL.
Discussion
Linguistic processing speed and word-nding complaints
We aimed to examine whether assessment of processing speed in a receptive language
test would provide a sensitive measure to objectively determine reported language
problems, and whether it is related to non-verbal processing speed. First, we showed
that 58% of glioma patients experience word-nding diculties in daily life, but that their
reported problems were supported by deviant BNT scores in only 50% of the cases. The
reported word-nding problems also did not correlate with the accuracy scores on the
SJT. The Token Test proved to be insensitive to detect language problems in this patient
group; only one patient scored below the cut-o level and the scores were not correlated
with the reported word-nding problems. At the group level, however, glioma patients
scored signicantly worse on the BNT and had worse accuracy scores on the SJT com-
pared to the control group.
The discrepancy between reported language complaints and scores on objective
language measures has been described in previous research (Satoer et al., 2012). In
addition, there is evidence that impaired linguistic variables found in spontaneous speech
Figure 4. Visualisation of linear regression model of the reported severity of word-finding problems
predicted by the reaction times (milliseconds) on the SJT.
APHASIOLOGY 15
of glioma patients do not correlate with performance on standardised language tests
(Satoer et al., 2018, 2013). At the same time, Brownsett et al. (2019) found that after
surgery, 58% of glioma patients reported communication diculties, which did not
correspond with the Aphasia Quotient of the Western Aphasia Battery-Revised (Kertesz,
2006, 27% of patients scoring below normal cut-o), but could be explained with the
scores on the Comprehensive Aphasia Test (Swinburn et al., 2004, 77% of patients scoring
below normal cut-o). The inconsistency between the BNT scores and the language
complaints we found in the current study could indicate that the word-nding problems
originate from an issue other than a pure lexical retrieval decit.
We investigated the relationship between the reported complaints and linguistic
processing speed. Previously, productive language tasks with a time constraint have
been reported to be dicult for glioma patients, illustrated by longer response times
on naming tasks (Moritz-Gasser et al., 2012; Ras et al., 2020). In contrast to our expecta-
tions, the results of the current study did not show deviant group-level performance on
the RT measure of the SJT, which assesses speed of receptive language processing.
However, glioma patients had signicantly lower accuracy scores compared to the control
group. This could be due to a deviant speed/accuracy trade-o, in which higher response
speed is favoured over accurate responding.
In a subsequent analysis, we looked at the individual RT scores in the SJT and found
that all patients with long RTs had a glioma in the language-dominant hemisphere, mostly
in the frontal lobe. This seems to suggest that assessing speed of language processing in
patients with left frontal damage may be particularly useful, although data from more
patients is necessary to further investigate this observation.
In contrast to the absence of a signicant correlation between the word-nding
problems and BNT and accuracy scores, more severe word-nding complaints were
accompanied by longer RTs on the SJT. We found that the presence of word-nding
problems was signicantly correlated with the overall RTs in the SJT, but also with each
linguistic level separately. The commonalities between the dierent linguistic levels may
point to a shared underlying attentional component required to perform this task. This is
in accordance with the nding that the reported complaints also correlated with perfor-
mance of the TMT. Although the TMT is not a perfectly matched non-verbal equivalent of
the linguistic processing speed task, it provides a measure of visuoperceptual speed and
relies on attention. Therefore, our ndings could imply that domain-general attentional
mechanisms underlie experienced word-nding problems. This aligns with previous
research in which attentional decits were observed in persons with self-reported mild
anomia, who performed within normal limits on standard language assessments
(Hunting-Pompon et al., 2011).
At the same time, it must be noted that the observed correlations between reported
word-nding problems and the TMT were weaker than the correlations with the SJT.
A model with linguistic processing speed as a sole predictor best t the word-nding
complaints of the patients, compared to models also including scores on the TMT as
predictors. This indicates that, despite an important role for more domain-general proces-
sing abilities in lexical retrieval, there appears to be an indispensable linguistic factor to
word-retrieval diculties.
16 S. MOOIJMAN ET AL.
The word-nding problems may be the most salient issue that glioma patients experi-
ence in everyday communication. Dialogues require conversational partners to process
verbal information quickly and respond to it promptly in an appropriate manner. This
entails the integration of a range of dierent abilities, which may be challenging for
individuals with aphasia. For example, they have been shown to experience more di-
culties with language production on a story retelling task, when they have to perform
another task simultaneously (Harmon et al., 2019). Apart from linguistically meaningful
and grammatically correct output, other cognitive functions, attention and executive
functioning in particular, have been shown to play a crucial role in the successful everyday
communication of aphasic speakers (Fridriksson et al., 2006; Olsson et al., 2019). This may
be an explanation for the relationship between word-nding complaints and slower
processing of both linguistic and non-linguistic tasks. Given the characteristics of func-
tional communication, their experienced word-nding problems could be the result of
slowed processing rather than lost function.
Underlying mechanism of linguistic processing speed
The signicant correlation between performance of the TMT and the presence of reported
word-nding diculties could imply that there is a domain-general attentional basis for the
experienced language diculties. This is corroborated by the signicant correlation
between RTs on the language task (SJT) and performance on the non-verbal tasks (TMT-
A and B), indicating that longer completion time on the TMT co-occurred with longer
reaction times on the SJT. The cognitive abilities known to underlie performance speed on
the TMT are visuoperceptual speed (TMT-A and -B) and concept shifting (TMT-B and -BA).
Remarkably, a signicant correlation only existed in the patient group and was absent
in the control group. This suggests that linguistic and non-linguistic functions are more
heavily interconnected in glioma patients as compared to healthy participants. In addi-
tion, the contribution of domain-general abilities in performing language tasks could
explain why the outcomes on the BNT and SJT were not inuenced by hemispheric
tumour localisation. If patients recruit domain-general cognitive abilities to perform
language tasks, lesions in the left or right hemisphere may lead to impairments.
These results show that the receptive linguistic processing speed partially constitutes
a more general cognitive speed. This is in accordance with the literature on persons with
aphasia due to stroke. For example, Yoo et al. (2021) found that persons with aphasia
show domain-general cognitive slowing, as indicated by slower processing speed on
linguistic and non-linguistic tasks. However, our nding is in contrast with Ras et al.’s
(2020) and Moritz-Gasser et al.’s (2012) results for patients with a glioma, who did not nd
a signicant correlation between the RTs on a rapid naming test and overall processing
speed measured with the TMT-A.
One potential explanation for this discrepancy lies in the dierence between modalities of
the used language tests. In the present study, we measured receptive reading abilities,
whereas Ras et al. and Moritz-Gasser et al. administered a speeded naming test, assessing
language production in a more isolated manner. As Sánchez-Cubillo et al. (2009) noted, the
TMT-A mainly relies on visual search and perceptual speed. Therefore, a comparison between
a reading task such as the SJT (both perceptual and visual) and the TMT-A may result in
stronger relationships than with a naming task. Importantly, Moritz-Gasser et al. did nd
APHASIOLOGY 17
naming speed to be highly correlated with executive tasks that require lexical access (uency
and the Stroop test), and argue that the decreased naming speed, in absence of impaired
naming accuracy, is due to the cognitive functions involved in language processing.
We found that linguistic processing speed was correlated with the ratio score of the
TMT-BA, a measure of concept shifting. This could be because multiple linguistic levels are
combined in the SJT. The participants assessed correct sentences and sentences that
contain a semantic, syntactic, or phonological error. The correct and incorrect items are
presented in a randomised order. It could thus be argued that there is constant task
switching within the SJT, placing a higher demand on cognitive exibility (Rubinstein
et al., 2001) and explaining the signicant correlation with the ratio score of the TMT-BA.
Combining various tests and presenting them in a rapidly alternating way has previously
been shown to be a good way to assess brain tumour patients (De Witte et al., 2015b). The
SJT requires the participant to simultaneously integrate various processes, such as sen-
tence processing, sentence evaluation, and task switching.
Limitations of the present study
A rst limitation is that there was missing information on the language lateralisation via
fMRI for the left-handed patients (N = 8). All left-handed patients had a glioma in the left
hemisphere. Previous research has shown that while language lateralisation is more mixed,
the majority of non-right-handed people nevertheless show typical language lateralisation
in the left hemisphere (Szaarski et al., 2002). Secondly, we could not perform analysis on
the specic tumour location and its eects on linguistic and non-linguistic functions due to
small group sizes. This is an important direction for future work. Thirdly, although the
reported word-nding problems were coded twice at dierent timepoints, allowing for an
intra-coder reliability analysis, having multiple independent coders assess the complaints
would have further increased the reliability of the scoring. A fourth limitation is the task
choice of the present study. Considering that data collection took place in a clinical context,
we were bound by the tasks that are part of the standard clinical work-up. While the TMT
and SJT are good measures of visuoperceptual processing speed and linguistic processing
speed, respectively, and both tasks rely on attentional processes, the two tasks are not
perfectly matched verbal and non-verbal variants. A nal limitation of the study is that
a pure reading task was not part of the test protocol. Consequently, we could not verify
whether reading issues interfered with performance on the SJT. While this should be
addressed in future studies, previous research has shown that reading performance is
generally unaected in glioma patients (Satoer et al., 2014, 2012).
Clinical implications and future directions
In clinical practice, demands for brevity generally compete with needs for sensitivity (e.g.,
Ek et al., 2010). Therefore, critical evaluation of the sensitivity of tests can guide the
selection of materials for a patient group. The SJT is part of the DIMA (Satoer et al., 2021),
which is designed to be both short and sensitive enough to detect mild language
diculties in patients with neurological diseases. The nding that deviant RTs in the SJT
were most often observed in glioma patients with a lesion in the frontal lobes of the
dominant hemisphere suggests that the task may be particularly suitable for this patient
18 S. MOOIJMAN ET AL.
group. This is in accordance with De Witte et al. (2015b) who also suggest the adminis-
tration of sentence judgment tests in patients with gliomas in the frontal and temporal
(sub)cortical areas. Including measures of RTs, as was done for the SJT in the DIMA, could
further increase the value of such judgment tests.
The nding that, despite a signicant correlation between the TMT and the RTs on the
SJT, not all patients with deviant scores on the SJT show impaired performance on the TMT
(or vice versa) is an indication that both tests are necessary for a reliable interpretation of
cognitive functioning. Additionally, considering that at the group level, patients do not
show signicantly lower processing speed than healthy control participants, demonstrates
the need for elaborate anamnesis and assessment tailored to the individual patient.
Our results imply that administering the SJT could be benecial for patients who report
word-nding problems, but do not show deviant scores on Token tests or standard naming
tests. Assessing linguistic processing speed provides a way to objectively assess these
complaints. The nding that word-nding problems were signicantly, but weakly correlated
with the TMT-A and – B, shows that lexical retrieval has a general processing speed
component but cannot be fully explained by this. This is an important observation that
deserves attention in the clinical setting. Clinicians could try to gain additional information
on the distinction between delayed and failed lexical access by administering a naming test
under time pressure. The anamnesis is another valuable source of information; clinicians
could ask patients more targeted questions about word retrieval. Patients dier in how they
present their complaints during the anamnesis, which emphasises the importance of asking
more thorough questions. Examples of such questions are whether dicult words surface
eventually or not at all, or whether there are specic circumstances (noisy environments,
time pressured conversations, etc.) under which word-nding problems are more prominent.
Finally, investigating the relationship between the performance of the SJT and non-
linguistic functions in populations with dierent neurological diseases, such as stroke or
traumatic brain injury, is a potential direction for future work. The result that response
speed of the SJT only correlates with visual search speed and concept shifting in the patient
group, and not in healthy participants, suggests that patients may recruit a wider network
to perform language tasks. It is interesting to see if similar relationships can be observed in
patients with other neurological impairments. Moreover, this nding can serve as a starting
point for therapy. Previous work on cognitive rehabilitation of glioma patients has found
that in-person training (Locke et al., 2008), and telerehabilitation (Van der Linden et al.,
2018) of cognitive functions is feasible and evaluated positively. Cognitive rehabilitation has
short-term positive eects on subjective cognitive functioning and longer-term objective
benets for attention and verbal memory (Gehring et al., 2009). However, detailed indivi-
dual assessment of the patient’s impairments should guide the choice of therapy.
Conclusions
This research studied the linguistic processing speed in glioma patients and investigated
whether these abilities could be a more sensitive measure to capture word-nding com-
plaints. We found that patients’ reported word-nding problems were not correlated with the
BNT, a well-known test to assess lexical retrieval diculties, nor with accuracy scores on the
SJT. However, the word-nding problems were correlated with linguistic processing speed,
operationalised as response speed in the SJT. At group-level, apart from patients with a glioma
APHASIOLOGY 19
in the frontal lobe of the dominant hemisphere, response speed of the SJT was not deviant in
glioma patients compared to the healthy control group. Furthermore, a relationship between
linguistic processing speed and non-verbal functioning was found in the glioma patients but
not in the healthy control group, suggesting that patients rely on more domain-general
abilities to perform the task. These results indicate that the SJT, a time-constrained task
assessing receptive language abilities, appears to be inuenced by non-verbal processing
speed, and that processing speed may contribute to subjectively experienced problems. This
demonstrates the importance of administering tasks that assess language as well as non-
verbal cognitive processing speed for the interpretation and dissociation of impairments.
Notes
1. Patients with a recurrent tumour are excluded because it is impossible to attribute their
preoperative impairments to the presence of the tumour alone, as their impairments may
also be the result of the previous surgery.
2. An analysis including both correct and incorrect target items showed that there was
a signicant main eect of correctness of the item on the reaction times across both groups
(ß = 0.25, SE = 0.05, p < .001). Participants responded signicantly faster to anomalous
sentences than to correct target sentences.
Acknowledgments
We would like to thank two anonymous reviewers and Josje Verhagen for their invaluable input and
feedback on earlier versions of this manuscript. We are very grateful to all participants who took part in
this study.
Disclosure statement
No potential conict of interest was reported by the author(s).
ORCID
Saskia Mooijman http://orcid.org/0000-0001-5084-3362
Laura S. Bos http://orcid.org/0000-0002-5160-888X
Evy Visch-Brink http://orcid.org/0000-0001-7833-0112
Djaina Satoer http://orcid.org/0000-0002-5751-8113
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APHASIOLOGY 23
Appendices
Outcomes of the statistical models.
Inuence of participant characteristics
The demographic factors age and education level were included in the statistical models as
covariates. These factors contributed signicantly to the outcomes of the BNT, TMT, and the RT
measures of the SJT. The eect of age and education level on these tests has been corroborated in
earlier studies (Snitz et al., 2009; Tombaugh, 2004; De Witte et al., 2015b). In addition, signicant
interaction eects between age, education, and group on the SJT RTs, TMT-B, and TMT-BA, seem to
suggest that older patients with lower education are more aected by their glioma than younger
patients with a higher education when it comes to linguistic processing speed, visuoperceptual
speed, and concept shifting.
Table A. BNT Score by group, age, and education level.
Estimate Std.Error t-value p-value
(Intercept) 51.082 0.812 62.908 0.000
Group 3.543 1.624 2.182 0.033*
Age −0.022 0.061 −0.352 0.726
Education level 3.422 0.945 3.621 0.001*
Group x Age 0.275 0.122 2.249 0.028*
Group x Education level −0.963 1.890 −0.510 0.612
Age x Education level −0.049 0.086 −0.574 0.568
Group x Age x Education level 0.093 0.172 0.542 0.590
Table B. Reaction times on the sentence judgment test.
Estimate Std.Error df t-value p-value
(Intercept) 7.612 0.054 40.535 141.781 0.000
Group 0.016 0.081 47.968 0.201 0.841
Education level −0.131 0.050 48.042 −2.623 0.012*
Age 0.000 0.003 47.937 0.157 0.876
Order −0.010 0.002 722.384 −5.320 0.000*
Semantics-Phonology 0.165 0.051 11.803 3.206 0.008*
Syntax-Phonology 0.357 0.052 11.957 6.920 0.000*
Group x Education level 0.008 0.100 48.023 0.081 0.936
Group x Age −0.003 0.006 47.951 −0.438 0.663
Education level x Age 0.015 0.005 47.996 3.222 0.002*
Order x Condition Sem-Phon 0.007 0.003 722.336 2.450 0.015*
Order x Condition Syn-Phon 0.009 0.003 724.654 3.109 0.002*
Group x Education x Age −0.018 0.009 48.001 −1.947 0.057
Table C. Summary accuracy scores Sentence Judgment Test.
Estimate Std.Error z-value p-value
(Intercept) 6.850 2.154 3.180 0.001
Group 1.156 0.414 2.790 0.005*
Education level 0.431 0.248 1.740 0.082
Age 0.010 0.014 0.706 0.480
Order 0.201 0.200 1.009 0.313
Semantics-Phonology −3.351 2.169 −1.545 0.122
Syntax-Phonology −4.485 2.155 −2.081 0.037*
Group x Education level −0.136 0.497 −0.273 0.785
Group x Age 0.023 0.029 0.810 0.418
Education level x Age −0.008 0.020 −0.413 0.680
Order x Condition Sem-Phon −0.233 0.204 −1.143 0.253
Order x Condition Syn-Phon −0.128 0.202 −0.637 0.524
Group x Education x Age −0.011 0.039 −0.285 0.775
24 S. MOOIJMAN ET AL.
Table D. TMT-A Score by group, age, and education level.
Estimate Std.Error t-value p-value
(Intercept) 3.351 0.039 86.054 0.000
Group 0.082 0.078 1.048 0.299
Age 0.002 0.003 0.541 0.591
Education level −0.131 0.045 −2.886 0.005*
Group x Age −0.006 0.006 −1.090 0.280
Group x Education level 0.132 0.091 1.454 0.151
Age x Education level 0.006 0.004 1.373 0.175
Group x Age x Education level −0.004 0.008 −0.479 0.633
Table E. TMT-B Score by group, age, and education level.
Estimate Std.Error t-value p-value
(Intercept) 4.100 0.044 93.613 0.000
Group −0.125 0.088 −1.431 0.158
Age 0.004 0.003 1.175 0.245
Education level −0.181 0.051 −3.562 0.001*
Group x Age −0.011 0.007 −1.683 0.098
Group x Education level 0.188 0.101 1.851 0.069
Age x Education level 0.018 0.005 3.831 0.000*
Group x Age x Education level −0.028 0.009 −2.988 0.004*
Table F. Ratio score TMT-BA score by group, age, and education level.
Estimate Std.Error t-value p-value
(Intercept) 2.249 0.094 23.900 0.000
Group −0.558 0.188 −2.966 0.004*
Age 0.013 0.007 1.790 0.079
Education level −0.101 0.109 −0.926 0.358
Group x Age −0.027 0.014 −1.891 0.063
Group x Education level 0.129 0.218 0.593 0.555
Age x Education level 0.033 0.010 3.307 0.002*
Group x Age x Education level −0.067 0.020 −3.345 0.001*
APHASIOLOGY 25
