Normative Data for Older New Zealanders on the Addenbrooke's Cognitive Examination-Revised

To best understand data derived from assessments, a reference point to what constitutes 'normal' performance is required. This frame of reference is provided by normative data which gives the empirical context and represents the range of performances on a particular test. Normative reference groups are considered the 'gold standard' against which an individual's test performance is compared and contrasted (Feigin & Barker-Collo, 2007). Unfortunately, many tests which are used have a limited range of norms, often excluding those age groups where cognitive decline may begin to occur (Siegert & Cavana, 1997). Lezak (1987) reviewed the ten most commonly used American tests and found that adequate age norms for older people were virtually non-existent. More recently, there has been a concerted effort to collect population-based test norms for older people. For example, the Mayo clinic (Mayo's Older American Normative Studies, MOANS) has developed normative data for Americans aged 55-97 for fifteen different neuropsychological tests measuring many different cognitive functions (Roberts et al., 2009). There have been attempts to develop age appropriate norms suitable for older New Zealanders on neuropsychological tests with norms developed for: the Rivermead Behavioural Memory Test (Fraser, Glass, & Leathem, 1999), Trail Making Test (Siegert & Cavana, 1997), Rey Auditory Verbal Learning Test (Newlove, 1992), Controlled Oral Word Association Test, Graded Naming Test and the Recognition Memory Test (Harvey & Siegert, 1999). These norms are appropriate for a wide range of older age groups and specific to the New Zealand population. Results become even more meaningful and accurate when compared to others with as many similar characteristics as possible, (e.g., cultural background, education, age, sex etc). For example, more variance in cognitive assessment scores is found within older age groups; i.e., the older people get, the more heterogeneous their scores become (Hanninen et al., 1996). Education level also impacts on cognitive ability in tests. For example, higher education levels have been associated with reduced variability in cognitive scores over time and a decreased risk in developing cognitive impairments (Christensen et al., 1999). Some cognitive tests take this into consideration by offering a conversion score that takes years of education into account, (e.g., the Montreal Cognitive Assessment, Nasreddine et al., 2005). There are a number of mechanisms that may explain lower rates of cognitive decline in older people with higher levels of education. First, people with lower education may be at more risk of central nervous system damage (e.g., through illness, poor living conditions or dietary deficiency), (Leibovici, Ritchie, Ledesert, & Touchon, 1996); second, people with higher education may have greater neuronal reserve capacity or integrity and/or reduced risk of neuronal damage (Christensen, 2001; Valenzuela & Sachdev, 2006); thirdly, people with higher levels of education may be better able to generate compensatory strategies (Leibovici et al., 1996) and finally, it is possible that people with higher levels of education may be better at doing paper and pen tests which affords them a higher chance of performing well. Research amongst these hypotheses is limited. However, one study found that people with higher levels of education appear to show greater resistance to change on tests with a high learned component (e.g., tests of language and secondary memory) and that "cognitive functions such as attention, implicit memory and visual-spatial analysis, (which might be postulated to have a higher ' nature ' rather than 'nurture' component), are relatively unaffected by level of education" (Leibovici et al., 1996, p. 396). However the more recent Maastricht Aging Study suggests that higher education in general is not a protective factor against normal ageing (Van Dijk et al. …