Using the Barnes Language Assessment with Older Ethnic

Minority Groups

ABSTRACT (word count 227)

Objective

There are many issues concerning the assessment of older people from

ethnic minority groups, the most significant being the language barrier

experienced by those whose English is an additional language (EAL). This

study aimed to test the hypothesis that EAL participants would score less well

than those with English as a first language (EFL) on the subtests of the

Barnes Language Assessment (BLA), elucidate the reasons for any such

differences and discuss the implications

Methods

The Barnes Language Assessment (BLA) is an accurate tool providing

information about expected patterns of language in different dementia

syndromes. This study compares the performance of EAL participants with

EFL participants. The BLA was administered to 144 participants, divided into

sub-groups with respect to age, gender and educational background, none of

whom had a working diagnosis of dementia.

Results

Results suggest that EAL speakers performed less well compared to EFL

speakers when other variables were matched. Significantly better BLA

scores, at the one per cent level, were found in both EAL and EFL groups with

higher educational achievement for eight of the fifteen sub-tests.

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Conclusion

Differences were found in performance on the BLA between EAL and EFL

participants. The degree of difference between EAL and EFL speakers

decreased as educational achievement rose. The consequences of these

findings for service delivery and the problems of recruitment of older EAL

participants are discussed.

2

INTRODUCTION

The number of older people from minority ethnic communities in the United

Kingdom has risen sharply over recent decades (Odutoye and Shah, 1999)

and are predicted to continue to do so. It is recognised that social research

has not yet fully explored the issues facing black and minority ethnic elders

(Lindesay et al 1997; Richards et al 2000). The results of such research may

have implications for policy development and service provision.

Studies suggest that ethnic minority populations have a greater incidence of

dementia, the cause attributed to unidentified genes or other risk factors

(Tang et al 1998). Dementia is diagnosed later in these groups (Ayalon and

Arean 2004), so ethnic elders are less likely to access important early

interventions and support. A number of explanations are given for this delay

in diagnosis, such as a reluctance to access services (Eolas 1999), difficulty

getting appropriate information, and lack of knowledge about services,

together with a lack of appropriate test materials (Richards et al 2000). Even

when interpreters or bilingual interviewers are used, there seem to be

particular problems around the reliability of the interview process in ethnic

minority groups (Rait et al 2000) (Shah1999).

Finally, there are differences in culture and belief, with some traditional

approaches to health and well-being conflicting with western values (Butt and

O’Neil 2004). The effects of ageing may be experienced and treated in a

different way in minority cultures.

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Language, age and education

Ethnicity and bilingualism are not the same; although many people in ethnic

minority groups are bilingual. However, language barriers are often cited as

the cause of difficulties when assessing ethnic elders.

Age is significant when considering language barriers in ethnic communities.

At present ethnic individuals of over 85 years are more likely to be

monolingual than younger people. In the future, although this “older old” group

will expand, the proportion with some knowledge of English may increase.

However barriers in the use of English language assessments may continue

to exist, as may the effect of lack of formal education.

Education level is known to be a significant influence on ethnic elders’

performance on cognitive testing (Richards et al 2000; Lindesay et al 1997).

However, education level alone is an inadequate indicator of performance

when considering a group with such varied ‘education experience’. This is due

to an absence of internationally standardised educational levels.

The Barnes Language Assessment

The initial research leading to the development of the BLA was carried out by

a group of speech and language therapists, specialized in working with older

people. The test provides a valuable screen and baseline measurement of

language skills (Bryan et al 2001). Feedback from participants and clinicians

was that the project highlighted the need to distinguish between EAL and EFL

speakers, as well as to control for variables other than age and gender (Bryan

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et al 2006). These were social class, occupation and education levels. There

are indications, based on the literature, that EAL speakers will do significantly

worse on language tests when compared to EFL speakers. The second

project, carried out between 2002-2005, established robust normative data for

EFL elders, and norms for EAL elders. This study aimed to test the hypothesis

that EAL participants would score less well than EFL participants, elucidate

the reasons for any such differences and discuss the implications.

METHOD

Sampling

144 healthy community living participants over the age of 50 were recruited

from a variety of settings including day centres, community groups, work-

places and via word of mouth. The project was advertised by A4 posters,

letters and personal contact. Interviews were carried out in participants’

homes, central locations (eg. day centres) and at the University of Surrey.

Criteria for inclusion in the study included no evidence of a dementia, no

significant current depression, no significant neurological history, no reading

or writing impairment. The criteria were applied using screening tools

described below. The 144 participants were divided into EFL (89) and EAL

(55).

During the analysis stage, the EAL participants were grouped according to

ethnic background; European, Asian (including Chinese and Japanese), Other

e.g. Creole and Guyanese, and level of education (see Table one)

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The aim was to identify any patterns emerging in the data, particularly error

patterns, although it is acknowledged that such broad groupings will need to

be refined. Discussion of emerging error patterns particular to ethnic groups is

the subject of a future paper.

Table 1 here

Participants were reassured throughout the process that the project was to

collect data about ‘normal’ functioning and not in order to identify any

pathological process. However, if participants expressed concern about their

performance they were advised to contact their GP. Only one individual had a

significantly impaired performance and it was found that she was being

monitored by her GP; her data was eliminated.

Tools

Before the BLA was administered, a pre-assessment screen was carried out

to eliminate any significant conditions e.g. dyslexia or depression. The pre-

assessment contained the following screens; Mini Mental State Examination

(Folstein et al,1975) to exclude cognitive impairment; BASDEC (Brief

Assessment Schedule Depression Cards) (Adshead et al, 1992) to exclude

depression; WRAT (Wide Range Achievement Test) (Jastak and Jastak 1978)

to exclude reading and writing problems; Health Screen to establish the

presence of any neurological conditions.

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The BLA is made up of 15 subtests. The subtests are grouped into

expression (5 subtests), comprehension (3 subtests), reading and writing (3

subtests), memory (2 subtests) and executive function (1 subtest). Key areas

of language functioning are included in each modality e.g. word fluency,

naming, word and sentence comprehension, word and sentence reading and

writing.

Data Analysis

Analysis was undertaken on two levels. Using SPSS version 15, first summary

statistics were extracted and secondly bivariate analysis was conducted on

the BLA sub-tests with respect to EFL /EAL. Analysis of education levels, age

and gender were also conducted. Where necessary, the variables were tested

for normality (Shapiro-Wilk) and approrialte tests (t-tests, Mann Whitmey U,

Spearman’s rank) were performed.

RESULTS

The results confirmed the hypothesis that EAL speakers would perform less

well on the BLA compared to EFL speakers. Gender was not found to be a

significant variable at the one per cent level in relation to performance on the

BLA, and age was only significant at the one per cent level for two sub-tests

(verbal fluency animals and trail time). Both of these are timed tests. However,

significantly better BLA scores at the one per cent level were found in both

EAL and ESL groups with higher educational achievement for eight out of the

fifteen subtests (spoken word to picture matching, verbal fluency S and

animals, word definition, TROG, forward digit span, sentence writing errors,

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story re-telling) two further sub-tests were significant at the five per cent level

(spelling to dictation and following commands).

The table below presents summary statistics across langugae background

and education groups

Table 2 here

Although EAL speakers’ mean scores were usually lower than scores of the

EFL participants (see Table 2), there were some subtests where EFL/EAL

scores in the higher education sub-groups (O/A levels and diploma/degree)

were similar e.g. Following Commands and Sentence Writing, Picture

Description and Word-Picture Matching.

Generally, scores increased for both EFL and EAL when the subject’s

education levels were higher. Differences between EFL and EAL tended to

reduce as the education level rose i.e. there was a greater difference between

EFL and EAL in the no qualifications sub-group.

The no qualification EAL sub-group did poorly on verbal production sub-tests

(Picture Naming, Word Fluency, Word Definition ) when compared with their

EFL counterparts and other EAL speakers in higher education groups. On a

test of Picture Description, this sub-group’s score differed from all the other

groups (2.5, compared to 4 for other groups) and Single Word Spelling was

significantly lower than all other groups. Also, in the no qualification EAL sub-

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group, Trail Test time was much higher than other groups (a higher score

indicating less ability).

DISCUSSION

The findings show that in order to effectively assess a wide population of older

people that includes ethnic elders, adapted norms on formal language tests

are needed. This finding is supported by the differences found between the

EAL and EFL groups tested on the BLA. The EAL group did less well on a

language test than their contemporaries in the EFL group. The results show

that education is a significant factor in EAL performance, and that the higher

the level of education, the less the difference between EAL and EFL

performance.

The sub-group that did consistently worse was the EAL group with no formal

qualifications. This could be explained by a number of factors. The first may

be unfamiliarity with the test format, so poor Trail Test scores (time and error)

could be due to unfamiliarity with the test concept (a type of puzzle) that may

have strong cultural bias. The fact that tests of verbal output (expression)

were more poorly performed by EAL sub-groups lends support to the view

that some ethnic older people will have limited functional use of English, poor

vocabulary and reduced use and understanding of more complicated syntax.

Those with a higher levels of education are more likely to have worked in the

UK, have required English as part of their job specification, and/or have been

exposed to some formal English teaching.

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There are therefore two types of EAL individuals, for whom different

approaches to assessment and management are required, one of whom has

some functional English, the other, very limited or no functional English.

For those with functional English, consideration of error profiles is also an

important finding from the study (to be expanded in a future paper). It is likely

that some ‘errors’ found on subtests such as reading aloud may be based on

regular patterns of pronunciation within certain language cultures.

Understanding this would reduce the possibilities of “false positive” diagnoses,

but further analysis is needed to provide a framework within which to

understand and measure such error patterns. This work could be subject of

future research.

Surprisingly age alone was not a significant variable. The ‘older old’ in our

study tended to fall into the EAL no qualifications group and therefore, as

described above, were the worst performers. However, data analysis

suggested this was due to lack of knowledge of the English language rather

than age per se. This does not negate the fact that there is a group of older

ethnic people for whom accessing services remains problematic due to lack of

English and for whom using a tool like the BLA would not be appropriate.

Another finding was the difficulty in recruiting participants from minority ethnic

groups. The problem increased with age, the 80+ group being the most

difficult to recruit. The method of recruitment varied from contacting agencies

such as local day centres, facilities for older people and exercise groups, to

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word of mouth via friends and work contacts. It was assumed at the

beginning of the research that older age recruitment would be easier than it

was. The result was that the target number of participants (5) in some EAL

sub-groups was not achieved, notably the 80+ group.

One factor that could have contributed is a suspicion amongst older ethnic

elders about participating in research and answering questions. This may be

due to different cultural attitudes to ageing, and resistance to pressure to

conform to a different culture not fully understood. Some participants may

have felt being tested meant being “checked on”, while others were unwilling

to disclose frailties. Some may have felt that because you are old there is no

value in you being tested. Elsewhere, a lack of respect or understanding of

culture has been attributed to the poor development of relationship between

researchers and minority elder participants (Brangman 1995; Bedolla 1995.)

A functional level of English is required to complete the BLA. Many older

people from an ethnic background may have limited English, relying on family

to translate where necessary, and mixing only with those from the same

ethnic, and therefore language, background. This was particularly true of the

Chinese community, and is supported by evidence (Yu 2000).

Also, as noted earlier, there may be cultural differences amongst ethnic

groups, not only with regard to attitude to research but also in terms of the

type of tasks that they were asked to do. The differences applied not only to

linguistic tasks such as reading and writing, but also to other tasks e.g. picture

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recognition or the Trail Test (Carter et al 2005). Therefore, the very act of

being involved in a formal test may be a factor that prevented people from

taking part in the study. A lack of familiarity with the test situation per se may

cause difficulties in participating in structured tests or interviews and has been

cited as one cause of misdiagnosis in minority elders (Espino et al 1998).

It is also possible that some people have no faith in mainstream services and

would prefer to gain support and advice from their own community voluntary

organisations (Butt and O’Neil 2004).

CONCLUSION

The findings of this research support the suggestion that there are differences

in performance on formal language tests between those who are EAL and

EFL speakers. As the results indicate, in order to accurately test language,

adapted norms are needed to allow for those differences. The BLA has

adapted norms. Distinct groups were found within the EAL group i.e. those

with useable English and those with very limited or no functional English. The

use of formal tests such as the BLA may not be appropriate for the second

group. The project has raised issues about the access of EAL individuals to

assessment services, together with a number of potential research questions:-

- Are there a group of people for whom alternative methods of

assessment and service provision are necessary in order to meet

their needs successfully?

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- If that is the case, then in what form would language assessment

take?

- How can information be provided to those whose pre-morbid

English language use is limited?

- Are there error patterns that can be predicted and attributed to

specific ethnic groups?

- Are there cultural factors that give rise to difficulties on particular

test formats e.g. Animal Fluency or Trail Test?

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Conflict of InterestsThe authors confirm that no conflict of interest exists that may bias the research on which this article is based.

Ethical permissionThe work was approved by the University of Surrey Ethics Committee and the Hammersmith Hospital Research Ethics Committee.

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Table 1: Breakdown of Education level vs. Language groups

Education

groups

English European Asian Other Totals

No qualifications 13 1 2 1 17

O/A level 46 8 6 2 62

Degree/diploma 30 19 12 4 65

Totals language 89 28 20 7 144

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Table 2: Summary statistics across education groups and language

background

Sub test No qualifications O or A levels Diploma or degreeEFL EAL EFL EAL EFL EAL

Spoken-word pic Matching NR*Mean (s.d)

13-1514.75(.866)

11-1412.25(1.708)

14-1514.84(.367)

11-1513.80(1.612)

1515.00(.000)

14-1514.71(.667)

Fluency ‘s’ NR*Mean (s.d)

9+13.33(3.257)

4+6.50(2.887)

9+15.73(5.370)

7+12.93(4.026)

11+18.55(5.422)

8+16.34(5.573)

Picture naming NR*Mean (s.d)

13+14.42(.793)

7+9.00(2.160)

13+14.60(.688)

9+12.87(2.326)

14+14.62(.622)

11+13.97(1.175)

Spelling NR*Mean (s.d)

15+17.00(1.128)

5+5.50(3.873)

16+17.49(.895)

5+12.27(4.862)

16+17.38(1.293)

12+16.49(2.077)

Trail test time NR*Mean (s.d)

Up to 3817.47(15.799)

Up to 2723.98(6.667)

Up to 2610.54(6.254)

Up to 2716.14(14.018)

Up to 189.95(6.620)

Up to 2011.44(6.010)

Trail test errors NR*Mean (s.d)

Up to 91.92(3.895)

Up to 81.75(2.062)

Up to 5.44(1.560)

Up to 82.80(4.814)

Up to 5.55(1.478)

Up to 81.77(3.126)

Fluency animals NR*Mean (s.d)

10+19.58(6.515)

8+10.75(4.272)

16+23.91(5.977)

13+19.47(7.100)

16+26.52(5.462)

14+21.63(6.567)

Word definition NR*Mean (s.d)

14+17.42(3.288)

9+8.75(2.062)

15+20.16(3.960)

9+15.87(4.565)

15+21.55(3.915)

14+19.06(3.757)

Trog NR*Mean (s.d)

4+6.83(1.193)

3+3.50(1.291)

6+7.76(1.048)

4+6.07(1.710)

7+8.34(.769)

5+7.17(1.317)

Forward digit span NR*Mean (s.d)

5+5.58(.996)

5+5.25(.500)

5+6.91(1.164)

5+5.47(.834)

5+7.17(1.227)

5+6.34(1.349)

Following commands NR*Mean(s.d)

54.92(.289)

2+3.00(1.155)

55.00(.000)

2+4.53(.834)

54.97(.186)

4+4.89(.404)

Sentence writing NR*Mean (s.d)

1.17(.389)

22.25(2.630)

1.11(.383)

Up to 1.20(.561)

0.03(.186)

0.03(.169)

Story retell NR*Mean (s.d)

9+11.42(1.379)

7+10.25(3.304)

9+13.00(2.646)

8+11.93(3.011)

12+14.17(1.794)

8+12.80(2.495)

Reading NR*Mean (s.d)

38+39.17(1.030)

21+23.50(4.933)

39+39.84(.367)

27+33.27(5.800)

39+39.79(.559)

31+36.26(2.559)

Pic description NR*Mean (s.d)

4+4.25(.622)

2+2.50(1.000)

4+4.38(.490)

2+4.13(1.060)

4+4.45(.572)

2+4.14(1.004)

NR*: Normal range

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