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In South Africa, most of the cognitive tests employed for neuropsychological evaluation are those developed in educationally advantaged settings such as the US, but the normative data accompanying the tests are unsuitable for use with South African examinees who have a disadvantaged quality of education, and/or whose primary language is other than English. A recently completed collation of Africa-based normative data (Shuttleworth-Edwards & Truter, 2022) includes a chapter on Performance Validity Tests (PVTs) with proposed cut-off points to assist in the identification of noncredible performance. The aim of this study was to compare the cut-off points established using educationally disadvantaged South African nonclinical normative samples for which only specificity percentages are available, with those established using clinical samples with designated valid and invalid performers for which both specificity and sensitivity data are available. A further aim was to compare the Africa-based cut-off points with age-equivalent cut-off points where available for US-based data on the targeted tests.
Participants and Methods:
The collation of Africa-based studies delineates cut-off scores for invalid test performance based on both nonclinical as well as clinical populations for three stand-alone PVTs especially developed to identify invalid performance including the Dot Counting Test (DCT), the Rey Fifteen Item Test (FIT), and the Test of Memory Malingering (TOMM); and three commonly employed cognitive tests for which there are embedded validity indicators including the Digit Span Age-Corrected Scaled Score (ACSS) and Reliable Digit Span (RDS), the Rey Auditory Verbal Learning Test (RAVLT), and the Trail Making Test A and B (TMT A and B). For studies using nonclinical norming data alone, specificity percentages to derive the cut-off points were set at a minimum of 90%. For studies using clinical samples specificity was set at a minimum of 90%, and the associated sensitivity percentages were reported indicating each test’s ability to correctly identify those with an invalid performance. The studies included participants stratified for both child and adult age groups (age 8 to 79 years) from South African educationally disadvantaged backgrounds. The data were tabled together for descriptive comparison purposes, including a column for the US-base cut-off points for equivalent age stages where available.
Results:
There was a high level of compatibility between the proposed cut-off points established for the South African nonclinical normative samples compared with those using clinical samples of designated valid and invalid performers. There was a trend for more lenient cut-offs for younger children and older adults compared to older children and younger adults. Compared with US-based data where available, adjustments towards leniency were called-for on all indicators.
Conclusions:
Cut-off scores for invalid cognitive test performance can be verified by perusing data derived from nonclinical norming samples as well as those from clinical samples, although the latter have the advantage of providing the sensitivity data to demonstrate the efficacy of a proposed cut-off score for identifying noncredible test performance. Adjustments towards leniency need to be made for cut-off scores for young children and older adults within an educationally disadvantaged population, and for disadvantaged adult populations compared with US-based educationally advantaged populations.
South Africa has a multi-lingual population where fewer than 10% of the population speak English as a first language. This poses a challenge regarding language usage for a verbal fluency task. This study investigated the difference in number of words produced by independent groups of non-English examinees required to produce words in English, or in their first language, on a category verbal fluency task.
Participants and Methods:
A study on South African non-English first language participants was conducted using the Category Verbal Fluency test (animals) for a sample of nonclinical adults (N = 264) aged 18-60 years with 8-12 years of disadvantaged (poorly resourced) quality of education. Participants either had an African indigenous first language, or Afrikaans (a Dutch derivative) as a first language. The data were derived from one group of either African indigenous or Afrikaans first language participants who were required to use English for word production (Group A English) (n = 159; African indigenous n = 135; Afrikaans n = 24) and another group of participants who were required to use their first language (Group B First Language) (n = 105; African indigenous n = 83; Afrikaans n = 22). The comparative data were stratified for age ranges 18-20, 21-30, 31-40, 41-50 and 51-60 years. Level of education was broadly equivalent across the comparative groups. T-test analyses compared the number of words produced between the English versus indigenous African groups, and English versus Afrikaans first language groups for each age category.
Results:
The comparison for the indigenous African first language participants, revealed no significant differences in word production for words produced in English or first language regardless of age. In the comparison for the Afrikaans first language participants there was a highly consistent tendency for better word production in Afrikaans than in English. These results indicate that socio-cultural factors may be influential for English language proficiency on a verbal fluency task, rather than the effect of first language usage “per se”.
Conclusions:
Since the dismantling of the Apartheid system in South Africa thirty years ago, English has become the main language used in government and business and is the preferred language of tuition in schools for those speaking English or an African indigenous language, whereas during the Apartheid era, two official languages were used for government, business, and schooling (Afrikaans and English). Currently, many Afrikaans speaking individuals continue to have Afrikaans as the preferred primary language of tuition in the schools and it persists as the preferred language for use in many Afrikaans dominated business arenas. This study attests to a high level of English fluency amongst those South Africans with an indigenous African first language, who clearly are as fluent in word production using English as they are when using their first language, in contrast to the indications for Afrikaans speaking individuals. Practitioners need to be alert to sociocultural factors that can impact on the optimal use of language in test situations, which may not necessarily be the first language.
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