Measuring executive function in people with severe aphasia: Comparing neuropsychological tests and informant ratings

Abstract

BACKGROUND:

Knowledge about patients’ executive function is important in the rehabilitation of language and communication in stroke patients with aphasia. Due to linguistic demands, most neuropsychological tests are unsuitable for this population, and it might seem appealing to use informant report of executive function as a substitute.

OBJECTIVE:

To investigate the relationships between scores on a neuropsychological test and informant ratings of executive function, as well as between the informant ratings and the functional communication ability, in people with severe aphasia after stroke.

METHODS:

Thirty-eight people with severe aphasia and their significant others participated. Executive function was tested with parts of the neuropsychological screening instrument CLQT and rated by significant others (informants) using BRIEF-A. Functional communication was assessed with a standardised test and rated by significant others.

RESULTS:

Results revealed few correlations between CLQT and BRIEF-A. There was no correlation between informant ratings on BRIEF-A and scores on the measures of functional communication.

CONCLUSIONS:

Informant ratings of executive function do not measure the same construct as, and cannot be used as a substitute for, standardised neuropsychological tests. Informant ratings of executive function do not seem to provide information that is relevant to the understanding of functional communication in people with severe aphasia.

Keywords

Aphasia executive function informant rating functional communication stroke

1 Background

Aphasia is a language disorder caused by acquired brain damage that results in impairments of speech, writing, and comprehension of spoken and written language (Papathanasiou, Coppens, & Davidson, 2017). In severe aphasia, language, the main vehicle for human communication, is severely limited and does not adequately meet the communicative needs (e.g. social interaction and information transfer) of the individual (Lasker, Garrett, & Fox, 2007). To communicate successfully in spite of such constraints is a challenge and the ability to do so rests on several factors, as has been described by Light and McNaughton (2014) in their model of communicative competence. One of the factors highlighted by Light and McNaughton (2014) is the strategic competence; skills and strategies that allow a person with a communication disorder to bypass limitations and make the best of their existing abilities to achieve functional communication. Functional communication can be defined as the ability to get messages across in a variety of ways, from fully formed sentences to appropriate gestures (Holland, 1982). For example, to make herself understood a person with severe aphasia (PWSA) needs to make optimal use of the linguistic abilities available, and to bypass the limitations by using compensatory strategies, such as gestures, drawing, and indicating to the communication partner what kind of support is needed. The impact of inadequate strategic competence clearly demonstrates the importance of executive function for successful functional communication, since:

“Impairment in executive functioning disrupts a person’s ability to effectively utilise intact areas of functioning, and undermines effective self-management of other areas of dysfunction, hampering attempts to employ compensatory strategies.”(Lewis, Babbage, & Leathem, 2011, p. 146)

Executive function is a term covering a group of higher cognitive control processes that serve to initiate, plan, execute and monitor goal directed behaviour (Lezak, Howieson, Bigler, & Tranel, 2012). The executive functions are dependent on the frontal lobes and their dense interconnections with other cortical areas and subcortical structures (Constantinidou, Wertheimer, Tsanadis, Evans, & Paul, 2012; Suchy, 20 09); furthermore, they are considered to be domain general, operating mainly on other cognitive processes and behaviour(Friedman & Miyake, 2017). There is a vast literature regarding executive function, but there is currently no complete consensus as to how this elusive concept should be defined. Definitions and theoretical models differ partly as a consequence of approaching the concept from different perspectives; clinical, cognitive or developmental (Suchy, Niermeyer, & Ziemnik, 2017). When exploring the impact of specific executive functions on different aspects of everyday functioning, such as communication, a clinically oriented model may be the most enlightening option. A five-component model proposed by Suchy and co-workers (Suchy, 2015; Suchy, Ziemnik, & Niermeyer, 2017) offers a description of executive function that highlights the width of the concept and that might be informative in the endeavour to understand the relation between executive function and functional communication. Suchy’s model consists of the following components: (1) Executive cognitive functions (the ability to generate plans and solutions to problems, relying on working memory and mental flexibility), (2) Initiation/maintenance (of behaviours needed to complete the plans), (3) Response selection (the ability to choose the appropriate response behaviour, among a large amount of competing possibilities, relying on updating and inhibition), (4) Meta-tasking (effective coordination of multiple goals across extended time periods, relying on prospective memory and monitoring), (5) Social cognition (understanding of socially relevant verbal communication, paralinguistic messages and social situations) (Suchy, 2015; Suchy, Ziemnik, et al., 2017).

Impaired executive function is common in stroke patients and has been shown to have a negative impact on rehabilitation outcome (Lesniak, Bak, Czepiel, Seniow, & Czlonkowska, 2008; Lipskaya-Velikovsky, Zeilig, Weingarden, Rozental-Iluz, & Rand, 2018; Shea-Shumsky, Schoeneberger, & Grigsby, 2019). Studies conducted among people with aphasia have shown that there is often concomitant executive dysfunction (El Hachioui et al., 2014; Murray, 2012; Schumacher, Halai, & Lambon Ralph, 2019), which has a negative impact on the outcome of language therapy (Gilmore, Meier, Johnson, & Kiran, 2019; Simic, Rochon, Greco, & Martino, 2019), functional communication (Fridriksson, Nettles, Davis, Morrow, & Montgomery, 2006; Olsson, Arvidsson, & Blom Johansson, 2019), and quality of life (Nicholas, Hunsaker, & Guarino, 2017). There is some evidence that a relationship exists between severity of aphasia and impairment of executive function (Baldo, Paulraj, Curran, & Dronkers, 2015; Nicholas & Connor, 2017), which indicates that executive dysfunction is likely to be common in PWSA.

Since the executive functions operate on other cognitive processes and behaviour, they can only be studied via those other processes, which makes measurement of executive function vulnerable to confounding factors (Keil & Kaszniak, 2002; Miyake, Emerson, & Friedman, 2000; Suchy, Niermeyer, et al., 2017). The most common method of measuring executive function is by using standardised neuropsychological tests, for example Stroop test, Digit span, Trail making test and Wisconsin Card Sorting Test (Conti, Sterr, Brucki, & Conforto, 2015). The kind of instruments we refer to here by the term ‘neuropsychological tests’ are administered under controlled circumstances, with a clear structure, short time frame and with an explicit goal for each task provided by the investigator (Toplak, West, & Stanovich, 2013). Such tests can be developed mainly for clinical purposes, or for experimental purposes, both having advantages and disadvantages (Suchy, Niermeyer, et al., 2017). Many tests are designed to address a distinct aspect of executive function, such as inhibition or shifting. However, the ecological validity of such narrow neuropsychological tests has been questioned (Gioia & Isquith, 2004; Lewis et al., 2011), since executive function is thought to be primarily needed in unfamiliar, complex contexts that demand simultaneous planning, problem solving and monitoring (Keil & Kaszniak, 2002; Suchy, 2009). One response to the problem of ecological validity has been to develop instruments that attempt to measure executive function through ratings performed by the person him/herself (self-rating) or by someone with good knowledge about the everyday functioning of the person (informant rating). Such rating scales typically focus on how the person manages activities or situations in their everyday life, and the assumption is that these behaviours are dependent on more or less the same executive functions that are targeted with neuropsychological tests (Suchy, Niermeyer, et al., 2017; Toplak et al., 2013), although with the added complexity of contextual factors. The scope of rating instruments and standardised neuropsychological tests are different. Standardised neuropsychological tests are not typically well suited to assess all components of executive function, for example meta-tasking and social cognition in the model by Suchy, Ziemnik, et al. (2017), whereas rating instruments often strive to cover such components.

Decision making around assessment of executive function is thus not straightforward, and even less so for PWSA (Keil & Kaszniak, 2002). People with aphasia, and particularly those with severe aphasia, are regularly excluded from research about cognitive sequelae after stroke, since their language impairments pose special challenges when assessing cognition (Barnay et al., 2014; Wall, Cumming, & Copland, 2017). These challenges also impact the extent to which PWSA are given formal neuropsychological assessments in clinical settings. To be reasonably certain test results are not confounded by problems of language comprehension or production when using neuropsychological tests with PWSA, the tests can only be allowed to require a minimum of verbal instructions; the stimulus material should preferably have no linguistic content (written words, letters or numbers) and must not require any form of verbal response. Many standardised tests are not suitable for use with PWSA without modifications (Keil & Kaszniak, 2002). Considering the challenges inherent in using neuropsychological tests with PWSA, the use of informant ratings might seem a particularly appealing alternative in this population.

However, studies in other populations have found the correlation between neuropsychological tests and informant (as well as self-) ratings to be weak or at best moderate. In a review covering 20 studies of both adults and children and nonclinical as well as clinical samples, including several different neuropsychological tests and rating instruments, Toplak et al. (2013) found that only 24% of all correlations reported were statistically significant. For those studies that reported all r-values, median correlation coefficients were between .14 and .25. Perfect correlations should of course not be expected, since the very intention of rating instruments is to add ecological validity and thus measure the impact of executive function in daily life, but if the aim is to measure aspects of the same underlying construct one would expect at least moderate correlations. Thus, it is somewhat unclear to what degree neuropsychological tests and ratings of executive function measure the same thing. In addition, we have no knowledge about whether existing rating instruments are suitable for assessment of executive function in PWSA, since no such studies exist.

As mentioned, previous studies have shown associations between executive function and functional communication in PWSA (Nicholas & Connor, 2017). Specifically, we have in a previous study found moderate to strong bivariate correlations between neuropsychological tests of executive function (parts of Cognitive Linguistic Quick Test (Helm-Estabrooks, 2001)) and two different measures of functional communication; Scenario Test (van der Meulen, van de Sandt-Koenderman, Duivenvoorden, & Ribbers, 2010) and Communicative Effectiveness Index (Lomas et al., 1989) (Olsson et al., 2019). However, there are no studies of whether this relationship holds when the executive functions are measured with informant ratings instead of neuropsychological tests. If informant ratings could provide information about executive function relevant to functional communication, this could somewhat diminish the impact of the problems associated with using standardised neuropsychological tests in this population.

Considering the impact of executive function on language rehabilitation outcome, quality of life and functional communication, information about executive function is important in aphasia rehabilitation. We know that using neuropsychological tests in this population is challenging due to the fact that the linguistic disability is a possibly confounding factor in most standardised instruments. Simultaneously, we have no knowledge about the use of informant ratings of executive function in this population and whether such ratings can provide information relevant to the understanding of functional communication. The overall aim of this observational, cross-sectional study was to gain new knowledge about assessment of executive function in PWSA by comparing the results of neuropsychological tests and informant ratings, and examining the informant ratings’ relation to functional communication. Specific research questions were:

Is there a relationship between results of a neuropsychological test (CLQT (Helm-Estabrooks, 2001)) and informant ratings (BRIEF-A (Roth, Isquith, & Gioia, 2005)) of executive function in PWSA?

Is there a relationship between the results of informant rating on BRIEF-A and functional communication in PWSA?

2 Method

2.1 Participants

2.1.1 Participants with aphasia

This study is part of a larger project and procedures for recruitment of participants has been presented in detail elsewhere (Olsson et al., 2019). The project is being conducted in Sweden. Inclusion criteria were: Severe aphasia following stroke, defined as 0–2 on the BDAE Aphasia Severity Rating Scale (ASRS) (Goodglass, Kaplan, & Barresi, 2001), >6 months post onset, and native (or equivalent) speaker of Swedish pre-stroke. In addition, all participants were required to have a significant other who agreed to complete the BRIEF-A rating. Exclusion criteria were: cognitive, motor, visual or hearing impairments to a degree that prohibited participation in formal language testing, a previous history of cognitive impairment, and/or incomplete BRIEF-A ratings.

Demographic information of the participants with aphasia are presented in Table 1.

Table 1
Demographic data of participants with aphasia, n = 38

Age, mean (range) 64.4 (26–86)

Gender, n (%)

Female 10 (26.3)

Male 28 (73.7)

Handedness

Right 31 (81.6)

Left 6 (15.8)

Ambidextrous 1 (2.6)

Education, no of years, n (%)

<10 years 18 (47.7)

10–13 years 15 (39.5)

>13 years 5 (13.3)

Months post stroke, mean (range) 81.5 (6–270)

Type of stroke, n (%)

Ischaemic 25 (65.8)

Haemorrhagic 8 (21.1)

Both 4 (10.5)

Unknown 1 (2.6)

Number of strokes, n (%)

One 28 (73.7)

Two or more^a 10 (26.3)

Severity of aphasia, n (%)

ASRS 0 3 (7.9)

ASRS 1 19 (50.0)

ASRS 2 16 (42.1)

^aOf which 3 (8%) in addition had minor damage to the right hemisphere.

2.1.2 BRIEF-A informants

For each participant with aphasia, a significant other completed the informant rating BRIEF-A. The person with the best knowledge about the everyday functioning of the PWSA available was recruited to complete the BRIEF-A. Forty-one informants completed the instrument, however three were excluded due to elevated scores on the BRIEF-A validity scale for inconsequence (see description of BRIEF-A below), resulting in 38 informants; 14 (36.8%) spouses, 7 (18.4%) children, 5 (13.2%) parents, 2 (5.3%) siblings and 9 (23.7%) formal caregivers. Thirty-one (81.6%) informants were women, 7 (18.4%) were men.

2.2 Material

2.2.1 Cognitive linguistic quick test (CLQT)

CLQT (Helm-Estabrooks, 2001) is a screening battery that can be administered by speech and language pathologists. It is specifically developed for people with communication disorders. Being an instrument developed for clinical use it has high sensitivity for dysfunction in the target populations, whereas the specificity (in terms of specifically measuring discrete subcomponents of functions) is likely not as high (Suchy, Niermeyer, et al., 2017). Test-retest reliability has been shown to be good, especially for the tasks used in this study. Four minimally linguistic tasks designed to target a subset of executive functions were selected from the battery:

Symbol cancellation Designed to assess visuospatial skills and areas of visual field problems. It can be simultaneously used to assess attention, inhibition and the ability to shift attention (Helm-Estabrooks, 2001, 2002). The participant is presented with a page filled with star-like symbols of five different designs and asked to cross out all symbols of one special kind.

Symbol trails Designed to assess working memory, planning and mental flexibility (Helm-Estabrooks, 2001). The participant is asked to draw lines between symbols in increasing size and alternating between circles and triangles.

Mazes Designed to assess planning, anticipating problems and attention (Helm-Estabrooks, 2001). The task consists of two mazes, with the second being somewhat more difficult. Points are subtracted each time a line is drawn $\frac{1}{2}$ inch (1.27 cm) or more into a wrong path.

Design generation Designed to assess productivity and creativity, ability to vary responses, self-monitor and use effective strategies (Helm-Estabrooks, 2001). The participant is presented with a number of squares with four dots, and is instructed to draw as many different designs as possible by connecting the dots in each square with four straight lines.

In addition to the scores on the individual tasks, a composite score was calculated, giving a CLQT total score (CLQTtot).

To compare results to normal performance, the CLQT manual provides criterion cut scores, which are based on data from non-clinical and clinical samples. Performance at or above criterion cut score is considered within normal range. Criterion cut scores are based on two age intervals (18–69 and 70–89). To make comparisons on group level possible, a transformed score was calculated for each participant by subtracting the criterion cut score for the relevant age group from the participant’s score. Thus, the transformed score represents the number of points above or below criterion cut score; performance at criterion cut score generates a transformed score of 0.

2.2.2 Behaviour rating inventory of executive function –Adult version (BRIEF-A)

BRIEF-A (Roth et al., 2005) is a frequently used rating instrument, with the Swedish translation (available from the publisher Hogrefe) being widely used among neuropsychologists in Sweden (Egeland et al., 2017). Parallel self- and informant rating protocols are available. The latter was used for this study. BRIEF-A consists of 75 items within nine clinical scales that reflect different aspects of executive function: Inhibit, Shift, Emotional control, Self-monitor, Initiate, Working memory, Plan/organise, Task monitor, and Organisation of materials. In addition, the clinical scales form two broader indexes: Behavioural Regulation Index (BRI) and Metacognition Index (MI), this two-component structure has been confirmed by factor analysis. Finally, an overall summary score, Global Executive Composite (GEC), can be calculated. Each item is scored by the informant on a three-point scale, indicating whether they think the individual (in this study, the PWSA) has never, sometimes or often had problems with the behaviour described in the item, during the last month. Higher scores indicate more frequent problems. American norms are based on a large number of ratings. Normative conversion tables for seven age groups (18–90 years) are provided to convert raw scores into T scores which, according to the manual, can be used for the interpretation of the level of executive function of the individual. T scores have a mean of 50 and a standard deviation of 10. A T score at or above 65 is considered clinically significant. According to the manual, the BRIEF-A is designed for adults with ‘a variety of developmental disorders and systemic, neurological, and psychiatric illnesses’ and is appropriate for adults across a wide range of social and demographic contexts (Roth et al., 2005). The informant rating version is suggested for use when self-report is not possible because of limited reading skills or because of ‘cognitive impairments that affect the ability to understand or otherwise respond in a reliable and valid manner to written information’. The instrument has been shown to have good internal consistency and test-retest reliability (Roth et al., 2005).

BRIEF-A includes a set of questions to ensure the validity of the responses, checking negativity, infrequency and inconsistency. In the present study, no participants with elevated validity scores were included.

2.2.3 Scenario test

The Scenario Test (van der Meulen et al., 2010) was developed as an objective measure of multi-modal communication of people with moderate to severe aphasia. The test adopts a role-playing format to provide an interactive setting with a supportive communication partner. During administration, the PWSA is presented with pictures and verbal descriptions of everyday scenarios and asked to convey a specific message within that situation to the investigator (e.g. to ask the taxi driver for a receipt or book an appointment with a doctor). If needed, prompting is provided as specified in the manual, to guide the PWSA to try using other ways to convey the message. Any mode of communication is accepted. Maximum score for a task is gained when the participant independently conveys the target message, irrespective of communication mode used, score is reduced if prompting is needed. Maximum score of the Scenario Test is 54.

2.2.4 Communicative effectiveness index (CETI)

CETI is an informant rating of functional communication in daily living (Lomas et al., 1989). CETI uses visual analogue scales where the informant rates the person with aphasia’s performance in 16 every day communication situations (e.g. having a spontaneous conversation, or communicating physical problems such as aches and pains). The mean of the 16 items is calculated, which gives a maximum score of 100. A higher score indicates better communicative effectiveness.

2.3 Procedure

Both tests (CLQT and ST) were administered and scored by the first author and video recorded. If the significant others were present at the first meeting with the PWSA, they were given the BRIEF-A and CETI along with verbal instructions, which gave them the opportunity to ask for any clarifications. Significant others that could not be present were given instructions by telephone, and the questionnaires were sent by mail. They were encouraged to contact the first author if they had any questions while completing the questionnaire.

2.4 Data analysis

Non-parametric methods for statistical analyses were used because of non-normally distributed data.

Transformed CLQT scores were used for relating performance to criterion cut scores. Difference to criterion cut score was analysed using Mann-Whitney U test.

For BRIEF-A, raw scores and T-scores are presented.

For the comparison between CLQT and BRIEF-A, raw scores were used. These are the scores normally presented for CLQT. For BRIEF-A, on the other hand, the scores normally presented are the T scores. The BRIEF-A raw scores, by themselves, are hard to interpret, since all subscales include different numbers of items and thus have differing minimum and maximum scores. However, they were used in the correlation analysis because it was considered inappropriate to mix age adjusted T scores and non-age-adjusted CLQT raw scores in the analysis.

For investigating relations between functional communication and informant ratings of executive function, Scenario Test total scores and CETI mean scores were correlated against BRIEF-A raw scores.

All statistical analyses were conducted with IBM SPSS Statistics, version 25. P-values ≤.05 are presented in bold text, as an indication of the significance level commonly used in previous studies of relations between neuropsychological tests and ratings. Cohen (1988) guidelines for interpretation of correlation coefficients were used (.10–.29 = small,.30–.49 = medium,.50–1.00 = large). 95% BCa bootstrap (2000 samples) confidence intervals are presented for the correlation analyses.

The study was approved by the regional ethical review board of Uppsala, Dnr 2017/183.

3 Results

3.1 Neuropsychological test of executive function –CLQT

Based on the CLQT total score, 79% of the participants performed below criterion cut score (Table 2). Symbol trails and Design generation were the most challenging subtests, with 65.8% and 73.7%, respectively, performing below cut score. The difference to criterion cut score was significant for CLQT total and all subtests except Mazes.

Table 2
Results of the CLQT, n = 38

Task (total possible score) (Criterion Cut Score 18–69 years, 70–89 years) Median raw score (IQR) Median transformed score (IQR) Comparison to criterion cut score^a No (%) of participants scoring below criterion cut score

Symbol cancellation (12) (11, 10) 10 (3–11.25) –1 (–7–1) p = 0.002 21 (55.3)

Symbol trails (10) (9, 6) 6 (1.75–9.25) –2 (–5.25–1) p = 0.001 25 (65.8)

Mazes (8) (7, 4) 4 (4–8) 0 (–3–1) p = 0.211 13 (34.2)

Design generation (13) (6, 5) 3 (1–5) –3 (–4–0) p < 0.001 28 (73.7)

CLQT total (43) (33, 25) 24 (10.75–32) –6.5 (–18 ––1) p < 0.001 30 (79.0)

Task (total possible score) (Criterion Cut Score 18–69 years, 70–89 years)	Median raw score (IQR)	Median transformed score (IQR)	Comparison to criterion cut score^a	No (%) of participants scoring below criterion cut score
Symbol cancellation (12) (11, 10)	10 (3–11.25)	–1 (–7–1)	p = 0.002	21 (55.3)
Symbol trails (10) (9, 6)	6 (1.75–9.25)	–2 (–5.25–1)	p = 0.001	25 (65.8)
Mazes (8) (7, 4)	4 (4–8)	0 (–3–1)	p = 0.211	13 (34.2)
Design generation (13) (6, 5)	3 (1–5)	–3 (–4–0)	p < 0.001	28 (73.7)
CLQT total (43) (33, 25)	24 (10.75–32)	–6.5 (–18 ––1)	p < 0.001	30 (79.0)

^aComparison to hypothetical median of 0 with one-sample Wilcoxon signed rank test.

3.2 Informant ratings of executive function –BRIEF-A

We found no systematic differences between the ratings by family members and formal care givers (Mann-Whitney U test, p-values ranging from .053 to .380), or between ratings by men and women (Mann-Whitney U test, p-values ranging from .125 to .971) on any of the clinical scales. The results of BRIEF-A are presented in Table 3. Higher scores indicate more severe problems, and a T score at or above 65 is considered to indicate clinically relevant executive dysfunction. Median T score was below 65 for all clinical scales. Only Working memory comes close with 16 participants (42.1%), having a T score above 65. In another three scales (Initiation, Planning/organising, and Task monitoring) about a fifth of the participants have median T scores above 65. A one-sample Wilcoxon signed rank test comparing T score median to hypothetical median of 65 shows that all subscale medians are significantly (all p < 0.001) below 65, except Working memory (p = 0.433). Based on the composite score GEC, 5.2% of the participants have clinically significant executive dysfunction.

Table 3
Results on BRIEF-A, raw scores and T-scores, n = 38. A higher score indicates more severe problems. Scores above 65 are considered clinically relevant

BRIEF -A clinical scales Median raw score (IQR) Median t-score (IQR) Min-max t-score No (%) of participants with T score ≥65

Inhibition 10 (9–12) 48 (43.5–54) 40–71 1 (2.6)

Flexibility 11 (8–12) 59 (48–62) 40–81 6 (15.8)

Emotional control 16.5 (12–19) 53.5 (44.75–58.5) 40–68 2 (5.3)

Self-monitoring 7.5 (6–10) 45.5 (40–54) 39–75 2 (5.3)

Initiation 13 (11–15) 57 (49.5–62.25) 42–75 7 (18.4)

Working memory 15 (11.75–18) 64 (53.5–73) 42–85 16 (42.1)

Planning, organising 17 (13–19) 58.5 (49–64) 42–76 8 (21.1)

Task monitoring 8.5 (7–11) 51 (46–61) 41–69 7 (18.4)

Organisation of materials 10 (8–12.25) 45 (41–52.25) 39–66 1 (2.6)

BRI score 44 (37–52) 51 (46–57.25) 40–70 2 (5.2)

MI score 66 (50.75–73) 56.5 (47.75–62) 41–74 4 (10.5)

GEC score 111 (89.75–122.25) 55.5 (47–60) 41–73 2 (5.2)

BRIEF -A clinical scales	Median raw score (IQR)	Median t-score (IQR)	Min-max t-score	No (%) of participants with T score ≥65
Inhibition	10 (9–12)	48 (43.5–54)	40–71	1 (2.6)
Flexibility	11 (8–12)	59 (48–62)	40–81	6 (15.8)
Emotional control	16.5 (12–19)	53.5 (44.75–58.5)	40–68	2 (5.3)
Self-monitoring	7.5 (6–10)	45.5 (40–54)	39–75	2 (5.3)
Initiation	13 (11–15)	57 (49.5–62.25)	42–75	7 (18.4)
Working memory	15 (11.75–18)	64 (53.5–73)	42–85	16 (42.1)
Planning, organising	17 (13–19)	58.5 (49–64)	42–76	8 (21.1)
Task monitoring	8.5 (7–11)	51 (46–61)	41–69	7 (18.4)
Organisation of materials	10 (8–12.25)	45 (41–52.25)	39–66	1 (2.6)
BRI score	44 (37–52)	51 (46–57.25)	40–70	2 (5.2)
MI score	66 (50.75–73)	56.5 (47.75–62)	41–74	4 (10.5)
GEC score	111 (89.75–122.25)	55.5 (47–60)	41–73	2 (5.2)

BRI = Behavior Rating Index, MI = Metacognition Index, GEC = Global Executive Composite.

3.3 Functional communication

Median score (inter-quartile range) for Scenario Test was 36 (19.5–44) out of maximum 54 (n = 37 for ST, as one participant did not complete the test), and for CETI 47.2 (37.0–59.1) out of maximum 100.

3.4 The relationship between performance-based tests (CLQT) and informant ratings (BRIEF-A)

Spearman’s rank correlations between subtests of CLQT and clinical scales of BRIEF-A are presented in Table 4. For both measures, raw scores are used. A higher CLQT score indicates better performance, while a higher BRIEF-A score indicates more frequent problems. Thus, negative correlations would be expected.

Table 4
Spearman’s rank correlations between performance-based test of executive function (CLQT raw scores) and informant ratings of executive function (BRIEF-A raw-scores), n = 38. P-values in parentheses, correlations with p≤0.05 indicated with bold text. 95% BCa bootstrap confidence intervals in brackets

BRIEF-A clinical scales CLQTsc CLQTst CLQTm CLQTdg CLQTtot

Inhibition –0.09 (0.606) [–0.378–0.226] –0.21 (0.203) [–0.556–0.154] –0.06 (0.733) [–0.412–0.296] –0.08 (0.617) [–0.440–0.262] –0.15 (0.360) [–0.494–0.200]

Flexibility –0.10 (0.543) [–0.421–0.233] –0.03 (0.870) [–0.373–0.331] –0.04 (0.792) [–0.387–0.302] –0.21 (0.214) [–0.501–0.127] –0.08 (0.622) [–0.431–0.286]

Emotional control 0.14 (0.413) [–0.228–0.471] 0.20 (0.223) [–0.145–0.533] 0.12 (0.466) [–0.217–0.441] 0.14 (0.394) [–0.141–0.415] 0.20 (0.224) [–0.138–0.529]

Self-monitoring –0.22 (0.176) [–0.525–0.102] –0.19 (0.266) [–0.475–0.135] 0.00 (0.979) [–0.318–0.300] 0.01 (0.956) [–0.320–0.327] –0.09 (0.593) [–0.429–0.249]

Initiation –0.10 (0.547) [–0.451–0.288] –0.35 (0.034) [–0.638––0.014] –0.15 (0.375) –0.490–0.208] –0.24 (0.156) [–0.545–0.143] –0.25 (0.132) [–0.571–0.117]

Working memory –0.24 (0.146) [–0.545–0.107] –0.61 (<0.001) [–0.793––0.307] –0.29 (0.076) [–0.572–0.020] –0.26 (0.114) [–0.579–0.113] –0.42 (0.009) [–0.668––0.096]

Planning, organising –0.09 (0.598) [–0.436–0.274] –0.34 (0.035) [–0.584––0.054] –0.18 (0.285) [–0.509–0.164] –0.14 (0.401) [–0.450–0.197] –0.23 (0.172) [–0.533–0.100]

Task monitoring –0.24 (0.151) [–0.543–0.097] –0.30 (0.076) [–0.569–0.023] –0.01 (0.963) [–0.338–0.290] –0.16 (0.353) [–0.457–0.145] –0.20 (0.223) [–0.508–0.111]

Organisation of materials –0.09 (0.589) [–0.177–0.245] –0.13 (0.437) [–0.432–0.170] 0.06 (0.701) [–0.280–0.395] 0.00 (0.999) [–0.323–0.331] –0.05 (0.759) [–0.386–0.287]

BRI –0.01 (0.945) [–0.322–0.291] 0.00 (0.997) [–0.362–0.356] 0.06 (0.702) [–0.261–0.388] 0.00 (0.993) [–0.291–0.301] 0.04 (0.820) [–0.304–0.377]

MI –0.17 (0.301) [–0.524–0.201] –0.44 (0.006) [–0.679––0.136] –0.14 (0.391) [–0.473–0.199] –0.22 (0.189) [–0.538–0.174] –0.29 (0.079) [–0.619–0.075]

GEC –0.15 (0.371) [–0.488–0.228] –0.32 (0.049) [–0.597–0.005] –0.07 (0.678) [–0.408–0.273] –0.15 (0.364) [–0.465–0.200] –0.20 (0.220) [–0.549–0.148]

BRIEF-A clinical scales	CLQTsc	CLQTst	CLQTm	CLQTdg	CLQTtot
Inhibition	–0.09 (0.606) [–0.378–0.226]	–0.21 (0.203) [–0.556–0.154]	–0.06 (0.733) [–0.412–0.296]	–0.08 (0.617) [–0.440–0.262]	–0.15 (0.360) [–0.494–0.200]
Flexibility	–0.10 (0.543) [–0.421–0.233]	–0.03 (0.870) [–0.373–0.331]	–0.04 (0.792) [–0.387–0.302]	–0.21 (0.214) [–0.501–0.127]	–0.08 (0.622) [–0.431–0.286]
Emotional control	0.14 (0.413) [–0.228–0.471]	0.20 (0.223) [–0.145–0.533]	0.12 (0.466) [–0.217–0.441]	0.14 (0.394) [–0.141–0.415]	0.20 (0.224) [–0.138–0.529]
Self-monitoring	–0.22 (0.176) [–0.525–0.102]	–0.19 (0.266) [–0.475–0.135]	0.00 (0.979) [–0.318–0.300]	0.01 (0.956) [–0.320–0.327]	–0.09 (0.593) [–0.429–0.249]
Initiation	–0.10 (0.547) [–0.451–0.288]	–0.35 (0.034) [–0.638––0.014]	–0.15 (0.375) –0.490–0.208]	–0.24 (0.156) [–0.545–0.143]	–0.25 (0.132) [–0.571–0.117]
Working memory	–0.24 (0.146) [–0.545–0.107]	–0.61 (<0.001) [–0.793––0.307]	–0.29 (0.076) [–0.572–0.020]	–0.26 (0.114) [–0.579–0.113]	–0.42 (0.009) [–0.668––0.096]
Planning, organising	–0.09 (0.598) [–0.436–0.274]	–0.34 (0.035) [–0.584––0.054]	–0.18 (0.285) [–0.509–0.164]	–0.14 (0.401) [–0.450–0.197]	–0.23 (0.172) [–0.533–0.100]
Task monitoring	–0.24 (0.151) [–0.543–0.097]	–0.30 (0.076) [–0.569–0.023]	–0.01 (0.963) [–0.338–0.290]	–0.16 (0.353) [–0.457–0.145]	–0.20 (0.223) [–0.508–0.111]
Organisation of materials	–0.09 (0.589) [–0.177–0.245]	–0.13 (0.437) [–0.432–0.170]	0.06 (0.701) [–0.280–0.395]	0.00 (0.999) [–0.323–0.331]	–0.05 (0.759) [–0.386–0.287]
BRI	–0.01 (0.945) [–0.322–0.291]	0.00 (0.997) [–0.362–0.356]	0.06 (0.702) [–0.261–0.388]	0.00 (0.993) [–0.291–0.301]	0.04 (0.820) [–0.304–0.377]
MI	–0.17 (0.301) [–0.524–0.201]	–0.44 (0.006) [–0.679––0.136]	–0.14 (0.391) [–0.473–0.199]	–0.22 (0.189) [–0.538–0.174]	–0.29 (0.079) [–0.619–0.075]
GEC	–0.15 (0.371) [–0.488–0.228]	–0.32 (0.049) [–0.597–0.005]	–0.07 (0.678) [–0.408–0.273]	–0.15 (0.364) [–0.465–0.200]	–0.20 (0.220) [–0.549–0.148]

BRI = Behavior Rating Index, MI = Metacognition Index, GEC = Global Executive Composite, sc = symbol cancellation, st = symbol trails, m = mazes, dg = design generation, tot = total.

Six (10%) of the correlations were significant if adopting a significance level of p≤0.05. Five of the six significant correlations include CLQT Symbol trails, two BRIEF-A Working memory. Considering the risk of type 1 error introduced by adopting a somewhat generous significance level, the correlations between BRIEF-A Working memory and CLQT Symbol trails (r_s = –0.61, p < 0.001), BRIEF-A Working memory and CLQT total (r_s = –0.42, p = 0.009), and BRIEF-A MI and CLQT Symbol trails (r_s = –.44, p = 0.006) appear to be the most robust. With Bonferroni correction (rendering an α-level of p≤0.0008) none of the correlations are significant.

3.5 The relationship between functional communication and informant rating of executive function

Spearman’s rank correlations between clinical scales of BRIEF-A (raw scores) and the two measures of functional communication (Scenario Test and CETI) are presented in Table 5. No correlations with a p-value ≤.05 were found. The correlation between BRIEF-A Initiation and Scenario Test is the only one that approaches the significance level of p≤0.05 (r_s = –.31, p = 0.063)

Table 5
Spearman’s rank correlations between informant ratings of executive function (BRIEF-A raw-scores) and two measures of functional communication (Scenario Test n = 37 and CETI n = 38). P-values in parentheses, correlations with p≤0.05 indicated with bold text. 95% BCa bootstrap confidence intervals in brackets

BRIEF -A clinical scales Scenario Test (n = 37) CETI (n = 38)

Inhibition –0.09 (0.608) [–0.440 –0.289) 0.11 (0.506) [–0.217 –0.408]

Flexibility –0.18 (0.291) [–0.516 –0.176] –0.08 (0.635) [–0.365 –0.218]

Emotional control 0.09 (0.594) [–0.271 –0.425] 0.27 (0.100) [–0.038 –0.529]

Self-monitoring 0.08 (0.653) [–0.306 –0.476] 0.21 (0.211) [–0.097 –0.468]

Initiation –0.31 (0.063) [–0.659 –0.089] –0.17 (0.306) [–0.502 –0.188]

Working memory –0.22 (0.183) [–0.557 –0.139] –0.14 (0.415) [–0.456 –0.203]

Planning, organising 0.00 (0.981) [–0.371 –0.359] –0.03 (0.845) [–0.382 –0.295]

Task monitoring 0.08 (0.619) [–0.278 –0.456] –0.12 (0.464) [–0.452 –0.217]

Organisation of materials 0.14 (0.426) [–0.255 –0.510] 0.21 (0.214) [–0.136 –0.526]

BRI 0.02 (0.895) [–0.345 –0.390] 0.21 (0.208) [–0.099 –0.488]

MI –0.06 (0.721) [–0.437 –0.314] –0.06 (0.727) [–0.418 –0.301]

GEF –0.06 (0.712) [–0.440 –0.325] –0.05 (0.746) [–0.314 –0.411]

BRIEF -A clinical scales	Scenario Test (n = 37)	CETI (n = 38)
Inhibition	–0.09 (0.608) [–0.440 –0.289)	0.11 (0.506) [–0.217 –0.408]
Flexibility	–0.18 (0.291) [–0.516 –0.176]	–0.08 (0.635) [–0.365 –0.218]
Emotional control	0.09 (0.594) [–0.271 –0.425]	0.27 (0.100) [–0.038 –0.529]
Self-monitoring	0.08 (0.653) [–0.306 –0.476]	0.21 (0.211) [–0.097 –0.468]
Initiation	–0.31 (0.063) [–0.659 –0.089]	–0.17 (0.306) [–0.502 –0.188]
Working memory	–0.22 (0.183) [–0.557 –0.139]	–0.14 (0.415) [–0.456 –0.203]
Planning, organising	0.00 (0.981) [–0.371 –0.359]	–0.03 (0.845) [–0.382 –0.295]
Task monitoring	0.08 (0.619) [–0.278 –0.456]	–0.12 (0.464) [–0.452 –0.217]
Organisation of materials	0.14 (0.426) [–0.255 –0.510]	0.21 (0.214) [–0.136 –0.526]
BRI	0.02 (0.895) [–0.345 –0.390]	0.21 (0.208) [–0.099 –0.488]
MI	–0.06 (0.721) [–0.437 –0.314]	–0.06 (0.727) [–0.418 –0.301]
GEF	–0.06 (0.712) [–0.440 –0.325]	–0.05 (0.746) [–0.314 –0.411]

4 Discussion

This observational, cross-sectional study revealed that correlations between neuropsychological tests and informant ratings were, even when adopting a generous significance level of p≤0.05, significant in merely 10% of the cases. Results on the neuropsychological test (CLQT) indicated that a large proportion (79%) of the participantshad impairments of executive function, whereas the informant rating (BRIEF-A) of the same participants indicated clinically significant executive impairments in only a small proportion (5%). Further, no significant correlations between functional communication and informant ratings of executive function emerged. This is in contrast to previous findings where functional communication has been related to executive function scoring on neuropsychological tests (Olsson et al., 2019). The research questions will be discussed in more detail below.

4.1 The relationship between neuropsychological test results and informant ratings of executive function in PWSA

Our results confirm that previously reported findings of few correlations between neuropsychological tests and ratings of executive function in other populations are also valid regarding PWSA. In fact, our findings indicate that in PWSA the correlation between the two types of instruments may be somewhat weaker than has been reported in other populations. In the review by Toplak et al. (2013), 19% of the correlations between BRIEF-A and various neuropsychological tests were considered statistically significant, whereas this was true for 10% of the possible correlations in the present study. A pattern emerged which indicates that results on CLQT Symbol trails are most closely related to the BRIEF-A results, since five of the six correlations with p≤0.05 include this task. However, when applying a significance level of p≤0.05, half of the significant correlations found (i.e. 5%) could be disregarded as possible products of chance. In fact, with Bonferroni correction, none of the correlations are significant. These results replicate findings in a study of several clinical samples by Lovstad et al. (2016), which identified no significant correlations between neuropsychological tests and informant ratings with BRIEF-A. Our results strongly question whether neuropsychological tests and informant ratings aiming to measure executive function succeed in tapping into the same construct when used with PWSA.

Additionally, the results indicate a consistent bias towards a more positive picture of PWSA functioning as measured on BRIEF-A compared to CLQT (only 1 participant had the reverse pattern). These results should be interpreted with some caution, since the cut-off scores of CLQT and BRIEF-A are based on American samples only. However, regarding the CLQT, our participants’ results are very similar to the ones of the left-hemisphere injured group reported by Helm-Estabrooks (2001), providing support that our participants perform as could be expected on this test. Regarding BRIEF-A, matters are a bit more complicated. The ratings are based upon what the informant perceives is a problem, which opens up for cultural differences regarding what is thought of as normal functioning and what might be considered a problem (Lovstad et al., 2016). In studies from Norway (which is culturally and socioeconomically more similar to Sweden than the USA) healthy control groups have been found to have lower mean scores than in the US normative data (Finnanger et al., 2015; Lovstad et al., 2012; Lovstad et al., 2016), which would lower the cut off for clinically relevant dysfunction (since higher scores indicate more problems). Lovstad et al. (2012) suggests that a cut off somewhere between 55–60 might be appropriate for Scandinavian populations. A rather large proportion of our participants fall within this “grey zone”; 17 participants (45%) have BRIEF-A GEC T scores between 65 (the US cut off) and 55, indicating that culture appropriate norms might have a large impact on this instrument’s potential for identifying possible clinically relevant problems.

However, the precarious interpretation of norms and cut offs does not impact the fact that the neuropsychological tests and informant ratings show very little correlation, and even if the bias is considerably less pronounced when comparing to Norwegian control group data, there is still a clear tendency that the informant ratings indicate less problems with executive function than do the neuropsychological test.

4.2 The relationship between the results of informant ratings on BRIEF-A and functional communication in people with severe aphasia

The second research question regarded the relationship between functional communication and BRIEF-A informant ratings. Executive function, as measured with neuropsychological tests, and functional communication have been shown to be related. We have previously reported a strong bivariate correlation between CLQT and Scenario Test (r_s = 0.64, p < 0.001) and a moderate correlation between CLQT and CETI (r_s = 0.42, p = 0.004) in a group from which the participants of this study are drawn (Olsson et al., 2019), possibly reflecting the impact of strategic skills on communication as described by Light and McNaughton (2014). If CLQT and BRIEF-A results did represent aspects of the same underlying construct, one would expect to find similar results when investigating the relationship between BRIEF-A and the measures of functional communication. Another possible result could have been that BRIEF-A could reveal previously undetected aspects of the relations between executive function and functional communication. However, all correlations were weak and none had p-values ≤.05 (Table 5). This suggests that BRIEF-A, in contrast to standardised neuropsychological tests, does not provide useful information about strategic or other skills that are directly relevant to functional communication.

4.3 Limitations

CLQT is an instrument intended for screening, and it is not sufficient for an in-depth assessment of level of cognitive functioning. Nonetheless, it was considered appropriate for this study since the main focus was not on establishing the absolute level of executive function in PWSA in relation to other populations, but investigating the relation between two different approaches to measuring executive function within this population. In addition, few standardised tests are appropriate for PWSA due to linguistic demands, and CLQT is one of few that is specifically intended for populations with communication disorders.

The ambition was originally to relate information about the PWSAs’ brain injuries to their scores on CLQT and BRIEF-A. This could have been interesting, since previous research has indicated different patterns of executive dysfunction with different sites of injury. For example, Lovstad et al. (2012) found that participants with dorsolateral prefrontal injuries demonstrated the pattern we found in the present study, with low performance on neuropsychological tests but relatively low levels of problems reported through self- or informant ratings, while participants with orbitofrontal injuries demonstrated the opposite pattern. Unfortunately, the information available from the medical records of our participants was frequently too imprecise to be used for such analyses.

4.4 Further research

BRIEF-A is a widely used instrument with good psychometric properties. However, the items leave the informant quite a lot of room for interpretation. The BRIEF-A questionnaire focuses on clinically relevant aspects of everyday functioning, however it may be more difficult to determine what the informant ratings represent. One way to investigate this issue further would be to conduct interviews with informants to gain insight into how they interpret and respond to the items. Such a study is ongoing.

Executive function status is an important factor in the rehabilitation of individuals following stroke, not least for those with severe aphasia. However, these patients are frequently not offered a proper assessment of their cognitive abilities, due to the challenges of using existing standardised instruments. As shown in the present study, informant ratings cannot be used as a substitute. Much work is needed to establish clinically feasible, valid ways of assessing executive (and other cognitive) functions in PWSA, a work that likely demands close cooperation between neuropsychologists and speech language pathologists.

Further research focusing on the analysis and understanding of the specific impact of the executive functions on functional communication is required. We know that some aspects of executive function (that can be captured by neuropsychological tests) are related to functional communication (Fridriksson et al., 2006; Olsson et al., 2019), a connection that also seems theoretically justified considering the importance of executive function to the use of compensatory strategies (Lewis et al., 2011). However, how can results of such tests be interpreted to help us design interventions, and which aspects of executive function are the most important? Considering the poor correlation between functional communication and BRIEF-A indicated by the present study, informant ratings of executive function does not seem to be the way forward in this specific issue. Perhaps, the impact of executive function on communication and communication intervention might be best understood if studied within the actual context of communication? An interesting attempt was made by Purdy and Koch (2006), in developing a new scoring system for Communicative Abilities of Daily Living (Holland, 1980) focusing on cognitive flexibility, and this seems to be an area worthy of continued research attention.

4.5 Conclusions

This study is, to our knowledge, the first investigating the use of informant ratings of executive function in PWSA. Our findings show that results of neuropsychological tests (CLQT) and informant rating (BRIEF-A) of executive function do not correlate with one another when used with PWSA. The executive impairments revealed by neuropsychological tests are not reflected in the informant ratings. Consequently, the two types of instrument cannot be assumed to measure the same underlying construct. Further, the lack of correlations between BRIEF-A and measures of functional communication indicates that aspects of executive function relevant to functional communication are not captured by BRIEF-A. These results need to be considered in clinical settings where assessment of executive function in PWSA is desired, since it is clear that informant ratings cannot be used as a substitute for neuropsychological tests. To provide a proper assessment of executive function in this population, instruments must apparently be chosen with great care.

Conflict of interest

The authors report no conflict of interest.

Footnotes

Acknowledgments

The authors would like to thank the participants for their time, effort and patience as well as the speech-language pathologists, The Aphasia Association and Forsa folk high school, who assisted in recruitment.This work was made possible by generous donation from Solveig and Arne Morin and a grant from The Swedish Stroke Association.

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Age, mean (range)	64.4 (26–86)
Gender, n (%)
Female	10 (26.3)
Male	28 (73.7)
Handedness
Right	31 (81.6)
Left	6 (15.8)
Ambidextrous	1 (2.6)
Education, no of years, n (%)
<10 years	18 (47.7)
10–13 years	15 (39.5)
>13 years	5 (13.3)
Months post stroke, mean (range)	81.5 (6–270)
Type of stroke, n (%)
Ischaemic	25 (65.8)
Haemorrhagic	8 (21.1)
Both	4 (10.5)
Unknown	1 (2.6)
Number of strokes, n (%)
One	28 (73.7)
Two or more^a	10 (26.3)
Severity of aphasia, n (%)
ASRS 0	3 (7.9)
ASRS 1	19 (50.0)
ASRS 2	16 (42.1)