Are Normal Controls Still Normal?

Property of University of EdinburghProperty of University of Edinburgh

Are Normal Controls Still Normal?

B048430

9940

MSc Cognition in Science and Society

The University of Edinburgh

2014


Table of Content

Acknowledgments............................................................................................................... i

List of Tables and Figures....................................................................................................ii

1. Introduction..................................................................................................................... 1

1.1. Bias in Control Group Selection....................................................................... 1

1.2. Bias in Volunteer Panels................................................................................... 2

1.3. Possible Bias in Repeated Testing - Practice/Learning Effect......................... 3

1.4. Possible Bias in Repeated Testing - Cognitive Domains................................. 4

1.5. Aim and Scope.................................................................................................. 5

1.6. Limitations........................................................................................................ 6

2. Methods........................................................................................................................... 6

2.1. Participants....................................................................................................... 6

2.2. Test Materials................................................................................................... 7

2.3. Procedure.......................................................................................................... 12

2.4. Design................................................................................................................14

3. Results............................................................................................................................. 14

3.1. Matching Groups...............................................................................................14

3.2. Norms Distribution and 2x2 ANOVA.............................................................. 16

4. Discussion........................................................................................................................ 31

4.1. The Volunteers' Performance Compared to Published Norms......................... 31

4.2. Effects of Age, Education and Interaction....................................................... 32

4.2.1. IQ and Language................................................................................ 33

4.2.2. Attention............................................................................................ 33

4.2.3. Memory.............................................................................................. 34

4.2.4. Executive Functions........................................................................... 35

4.2.5. Processing Speed and Visuospatial Processing................................. 36

5. Conclusion....................................................................................................................... 36

References


i

Acknowledgments:

I would like to thank my supervisors Dr Thomas Bak and Dr Mario A. Parra Rodriguez for

their support, guidance and enthusiasm for this project. I would also like to thank Rini Kaplan

with whom I share the dissertation topic and the experience of many hours in the lab assessing

volunteers. Further acknowledgment to Lisa Reuter for testing 10 participants and Natalie

Rangolam for testing 6 participants.

Special thanks go to all the volunteers who participated in this study. Thank you for

answering our email, letters and calls.

Finally, I wish to thank my flatmates for their unwavering support!


ii

List of Tables and Figures

Table 1 Seven main categories for cognitive domains............................................. 4

Table 2 Total number of participants who participated in this study....................... 7

Table 3 List of nine tests with subcategories and their corresponding

cognitive domains........................................................................................ 11

Table 4 Total number of inexperienced participants and experienced participants.. 14

Table 5 Scores of outlier N18 compared to cut-off scores provided by norms.........15

Table 6 Total number of inexperienced/experienced participants divided

by age groups...............................................................................................16

Table 7 Means with standard deviations and norms for ROCFT Copy.................... 17

Table 8 Means with standard deviations and norms for ROCFT

Immediate Recall..........................................................................................17

Table 9 Means with standard deviations and norms for ROCFT

Delayed Recall............................................................................................. 18

Table 10 Means with standard deviations and norms for ADASCog

and subcategories......................................................................................... 19

Table 11 Means with standard deviations and norms for GNT.................................. 22

Table 12 Means with standard deviations and norms for NART............................... 23

Table 13 Means with standard deviations and norms for ACE-III

and subcategories......................................................................................... 23

Table 14 Means with standard deviations and norms for TEA 3 and 5...................... 26

Table 15 Means with standard deviations and norms for DSCT................................ 28

Table 16 Means with standard deviations and norms for TMT A.............................. 29

Table 17 Means with standard deviations and norms for TMT B...............................30

Fig. 1 Procedure of Test Administration................................................................ 13

Fig. 2 2x2 ANOVA results for ROCFT Immediate Recall.................................... 18

Fig. 3 2x2 ANOVA results for ROCFT Delayed Recall........................................18

Fig. 4 2x2 ANOVA results for ADAS Total.......................................................... 21

Fig. 5 2x2 ANOVA results for ADAS Memory.................................................... 21

Fig. 6 2x2 ANOVA results for GNT...................................................................... 22

Fig. 7 2x2 ANOVA results for ACE Fluency........................................................ 25

Fig. 8 2x2 ANOVA results for ACE Total.............................................................26

Fig. 9 2x2 ANOVA results for ACE Attention...................................................... 26

Fig. 10 2x2 ANOVA results for TEA 3................................................................... 27

Fig. 11 2x2 ANOVA results for DSCT.................................................................... 28

Fig. 12 2x2 ANOVA results for TMT Part B.......................................................... 30


1

1. Introduction

In many research fields and especially in cognitive neuropsychology, control groups are

indispensible. They form the backbone of any empirical study and statistical model, since

norms and cut-off lines are based on how cognitively impaired cases fare compared to the

healthy population. How else can one determine whether there is a pathological development

or deterioration in someone's cognitive abilities, without knowing first how a healthy brain

develops, works and ages? To know what is abnormal, one first has to know what constitutes

as normal. Selecting participants for such a healthy "normal" group, however, can be

problematic. There are many factors that could influence our cognition, such as age, education,

social background or even leisure activities. Where do we live? At what university did we

study? How many languages do we speak? How active are we, mentally and physically,

especially when we are older?

While many research articles go into great detail as to how, where and why exactly they have

recruited their patient groups, the same can often not be said regarding the information given

about the control groups. In many cases, only the bare numbers are provided to show that the

samples were matched on basic demographics, such as age, education and gender. Control

groups are just mentioned as an afterthought, even though they are as crucial to the study as

patient groups. Matching the participants on a few selected variables, however, does not mean

that the sample chosen for the study truly represents the normal population or, for that matter,

even truly matches the patient group. The question arises; are these so called normal control

groups really good representatives of the average population? Ignoring this question could

lead to bias and, consequently, might contort the results of a study. The following sections

will elaborate on a few possible causes of bias that have to be considered when using healthy

"normal" controls in experimental designs.

1.1. Bias in Control Group Selection

Criticizing controls and questioning whether they are truly representative samples of the

"normal" public seems to be a taboo in the science community. Although there are many

possible sources for bias, the literature so far has paid little attention to this problem

(Schechter, Strasser, Santangelo, Kim, & Endicott, 1994). One of the main issues with control

groups is how and where they are recruited. Getting volunteers from the general public is

often an arduous job and it is all too tempting for researchers to recruit friends, colleagues or

students (Patel, Doku, & Tennakoon, 2003). Especially studies carried out at universities like

to take advantage of having an abundance of students at their hands. They are easy to recruit,


2

already matched in age and education, happy with little to no payment and are often even

obligated to participate in experimental studies to receive credit points. However, university-

educated volunteers are by far not representative of the general public. Even if matched on

years of education, are Oxbridge or Ivy League graduates really comparable to their

counterparts from lower ranked universities or vocational education? Choosing elite groups,

which might even have insider knowledge on experiments and procedures, can distort the

results of studies and set the norm of what constitutes "normal performance" at a much higher

level than it actually is.

Recruiting volunteers from the general public might mitigate these biases, however, the

selection process can bring its own set of problems. A volunteer's motivation, for example, is

rarely questioned. While some are simply interested in the topic, others might choose to take

part in neuropsychological studies, because they are concerned about their own mental status.

Instead of going to a doctor, which could have a negative stigma to it, they get a free

evaluation by taking part in an experiment (Schechter, et al., 1994). Since research studies

often lack in-depth evaluation due to limited funding or time, especially when dealing with

large subject pools, the so called "normal" and healthy participants might not be truly free of

any mental disorders, known or unknown to them (Schechter, et al., 1994). A study on

recruitment and screening of normal controls by Shtasel (1991) showed that out of 1284

volunteers responding to a newspaper advert for a biomedical research, 50.9% were excluded

after a preliminary telephone screening, due to having a history of psychiatric, neurologic, or

medical problems. Of the remaining volunteers another 49.7% were excluded after an in-

person evaluation. In the end, only 157 volunteers were admitted to the study (Shtasel, et al.,

1991). Without these screening processes, however, even a handful of participants could

influence the results of the study and the healthy controls score lower than they actually

should. To avoid these issues that arise from recruiting from the general public, research

institutions now frequently use volunteer panels. They make the recruitment process easier,

the control groups are less elite than through in-house selection and it is possible to monitor

the panelists' mental health over a longer period of time.

1.2. Bias in Volunteer Panels

Schechter et al. proposed a model for such a panel, called the Central Recruitment Program,

in 1994 (Schechter, et al., 1994). The idea behind it was to get individuals who do not sign up

to participate in one specific study, but are rather part of a subject pool used for a variety of

experiments. They should be screened in-depth before they are accepted into the panel. Only


3

volunteers who meet a project's specific criteria are selected as control subjects and they

should not participate in the same type of study too often (Schechter, et al., 1994).

Furthermore, the participants on those volunteer panels should be regularly assessed, since a

mental illness could develop at any future point in time (Schechter, Singer, Kuperman, &

Endicott, 1998). This is a somewhat idealistic view of a panel and does not quite work in

reality. The suggested thorough screening process might be somewhat extreme. It is highly

time consuming and time is, more often than not, money. Furthermore, although no evaluation,

as discussed above, is certainly problematic, meticulously screening volunteers for any sort of

psychological or medical affliction might lead to an overly healthy panel, also not truly

representing the general public.

While these forms of biases have been discussed in some literature, albeit not in many

experimental studies, practically no literature exists on another form of bias that could be

found in volunteer panels; the fact that volunteers stay on these panels for years, sometimes

decades. They are repeatedly tested with assessment tools specifically designed to screen for

cognitive abilities. There is a strong possibility of practice/learning effect bias.

1.3. Possible Bias in Repeated Testing - Practice/Learning Effect

It is quite common in neuropsychological evaluations to repeatedly use the same battery of

well established cognitive screening tests. While serial testing can be essential for monitoring

disease progression or possible recovery in patients, especially with healthy controls, it can

also lead to the so called 'practice effect' (Bartels, Wegrzyn, Wiedl, Ackermann, & Ehrenreich,

2010). This effect can be either specific to certain tests - participants might develop better

test-taking strategies or recall certain items and answers (Benedict & Zgaljardic, 1998) - or it

can be a more general effect, because participants get familiar with the testing environment

which could reduce anxiety (Bartels, et al., 2010). In both cases the participants score better

on a test they know than in a novel experimental situation with a never before seen test. A

study by Krenk et al. (2012) showed that a sample of around 150 healthy elderly controls

improved significantly on a series of cognitive tests from the first two sessions to the third

session (Krenk, Rasmussen, Siersma, & Kehlet, 2012). Bartels et al. (2010) investigated

practice effects in tests that are used to screen for impairment in specific cognitive domains

and they found significant improvement, especially during the first three months, in almost all

tests across various domains (Bartels, et al., 2010). One possible way to prevent or at least

reduce the magnitude of practice effect is to introduce alternative test forms. However, a few

studies have shown that not all cognitive domains react equally well to variations of tests and


4

especially procedural and nonverbal memory tests seem to improve more persistently

(Benedict & Zgaljardic, 1998; Beglinger, et al., 2005). This could mean that independently of

how familiar one is with one specific test, learning still occurs, simply by taking part in

cognitively demanding experiments. Not many studies have investigated whether there is an

improvement in cognitive domains due to repeated exposure to testing.

1.4. Possible Bias in Repeated Testing - Cognitive Domains

Each neuropsychological disorder can affect and disrupt our cognition differently. There

are various causes of cognitive problems, such as traumatic brain injuries, strokes, cancer or

neurodegenerative diseases, such as Alzheimer's or Parkinson's, to name a few. Although

certain diseases might show a similar pathology, each type might show different symptoms,

afflicting specific cognitive domains, depending on location. A patient with vascular dementia,

for example, might have more difficulties in sustaining attention than someone with

Alzheimer's disease, which in turn might manifests itself more in episodic memory problems

than attentional problems (Graham, Emery, & Hodges, 2004). It is therefore important that

neuropsychological assessments do not just deal with our overall cognition, but also look at

separate cognitive domains to determine what kind of impairment one is dealing with. The

degree of subtlety into which the domains are divided can vary across studies (e.g. memory,

semantic and episodic memory, anterograde and retrograde episodic memory etc.). However,

seven main domains can be derived from the literature dealing with the cognitive assessment

tests used in this study (Caselli, et al., 2007; Kipps & Hodges, 2005) and are listed in table 1.

Even normal ageing causes a slowing of our cognitive abilities, and yet, not all cognitive

domains are equally affected by age. While language, IQ or general knowledge and, to a

degree, numerical abilities do not seem to significantly decline over time, others, such

processing speed, executive functions and certain aspects of memory, are strongly associated

with age-related decline (Deary, et al., 2009). However, the degree of decline varies from

individual to individual and some people seem to age better than others. One possible

explanation for this is that by keeping yourself mentally, intellectually and physically active,

Table 1 Seven main categories for cognitive domains.

Cognitive Domains

Memory Language Visuospatial

Processing Attention

Executive

Functions

Processing

Speed IQ

The neuropsychological tests used in this study screen for impairment in one or more of these seven domains. A

detailed list of which test assesses which domain is provided in table 3.


5

cognitive decline can be reduced or slowed down (Deary, et al., 2009). This could mean that

volunteers, who choose to be on a panel and who are repeatedly tested and constantly learning,

show less of a decline in their cognitive domains than the average "normal" person from the

general public.

1.5. Aim and Scope

The University of Edinburgh uses a research volunteer panel since the early 1990s,

consisting at the moment of 833 volunteers. It is not quite clear when exactly it started, since

correspondence before 2001 has not been recorded, but some participants of this study stated

they have signed up as early as 1990. Although the panel is quite versatile and combines a

wide range of years of education, social background and age, it could be improved by keeping

more detailed records. While the in-depth evaluation process suggested by Schechter et al.

(1994) might be a bit extreme, the University of Edinburgh does not assess their recruits

thoroughly. The volunteers fill out a questionnaire when they sign up, in which they only have

to state whether they have normal hearing and sight. If participants meet any exclusion criteria,

such as mental illnesses or mild cognitive impairment (MCI) it is found out during a study

and then, hopefully, noted down. Yet more often than not, it is neither detected nor passed on

to the panel's administration and as a result, such participants might contaminate the study's

outcome. Furthermore, there are no records of how many and what kind of tests a volunteer

has done. Participants taking part in this study have done experiments ranging from 0 to over

100. This could lead to practice effect bias and bias due to improved cognitive abilities. Since

it is not possible to determine how often a participant has done one specific test,

investigations into practice effects are limited for this study. It will therefore concentrate on

the following research questions:

RQ1: Do volunteers, age 55-75, on average perform better on eight cognitive test compared to

the published norms?

RQ2: Do experienced volunteers (two or more experiments per year) score differently on the

eight tests than volunteers who have little to none experience and if so, is there an interaction

between age and experience?

RQ3: Is the effect more pronounced in certain cognitive domains than others?


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1.6. Limitations

The original idea of this research project was to compare the volunteers from the panel to

the general public, in addition to comparing the experienced panelists to the inexperienced

ones. If our hypotheses were true, the volunteers and especially the experienced ones, should

be significantly better than the general public due to the fact that they are on a panel (selection

bias) as well as being repeatedly exposed to cognitive tests (practice/learning effect bias).

However, it was remarkably difficult to recruit people from the general public. Several

attempts were made to recruit people in person as well as with flyers, yet the response rate

was little to none. This could be due to the fact that no payment was offered or because the

testing sessions were 1.5 hours to 2 hours long which is quite a time investment. Perhaps there

is simply a reluctance in the general public to take part in psychological experiments,

conducted by postgraduate students. It is also interesting to note that it was a much longer and

more difficult process to recruit the volunteers who had been on the panel for a while,

compared to the newly joined volunteers. While the latter were still eager to participate in

experiments, the "veteran" volunteers seemed to have developed a certain fatigue towards

participation.

This study, therefore, is not able to draw comparisons between volunteers and the general

public and focuses on the experienced vs. inexperienced volunteers within the panel instead.

To make the sample size more robust, the people recruited from the general public were

added to the inexperienced groups. However, if provided with more time there would be great

possibilities for future studies which could provide to the lack of experimental literature on

control group bias.

2. Methods

2.1. Participants

The participants for this study were selected from the University of Edinburgh's research

volunteer panel as well as from the general public. To maximize the chances of finding

potentially high differences in experience among the volunteers, only the contact information

of volunteers who had been on the panel for more than five years or less than nine months

were used. During the early stages of this study, the University of Edinburgh had just finished

their latest recruitment phase and in order to reach more inexperienced volunteers, their

information was subsequently added to the contact list. Preliminary excluding criteria were

abnormal hearing and vision or medical conditions, as stated on the contact information sheet


7

provided by the university. Volunteers younger than 55 or older than 75 were excluded to

facilitate finding a concise sample of a healthy, senior control group. Due to the fact that no

payment was offered, except for a maximum reimbursement of £4 for parking, bus and train

fares, only volunteers who lived in Edinburgh were contacted. This criterion was changed to

volunteers who lived no further than one hour by away from Edinburgh by car, in hopes of

finding more participants.

From the volunteers who had joined the panel in the last nine months, 48 volunteers were

contacted, 32 were scheduled, 3 withdrew and 29 were tested. From the volunteers who have

been on the panel for more than five years, 90 volunteers were contacted, 29 were scheduled,

5 withdrew and 24 were tested.

To find participants from the general public, flyers were created, stating the nature and

duration of the study, asking for healthy, English native speaking participants over 55 and

providing them with the researchers' and supervisors' contact details. The flyers were hung up

in various community centers, supermarkets, parks and medical centers. After getting little to

no responses, flyers were handed out in person to people in the city and in front of churches.

As mentioned above, the recruitment was not very fruitful and only 8 participants were

scheduled and tested. Table 2 shows an overview of the total number of participants recruited.

Table 2 Total number of participants who participated in this study.

Participants (n=61)

Male Female Age Mean Age

(SD)

Years of

Education

Mean YoE

(SD)

Left-

Hnd.

Right

-Hnd.

Total 21 40 55-75 64.93

(5.31) 8-26.5

16.60

(3.40) 7 54

> 5 Years

(n=24) 9 15 58-75

66.50

(5.25) 10-21

16.31

(3.16) 4 20

< 9 Mth.

(n=29) 7 22 55-72

63.48

(4.61) 10-26.5

17.45

(3.23) 3 26

General

Pub.(n=8) 5 3 55-73

65.50

(7.01) 8-19

14.38

(3.96) 0 8

2.2. Test Materials

It was important for this study to select well established cognitive screening tests which are

commonly used for assessing cognitive abilities and impairment, not only because they cover

a broad spectrum of cognitive domains, but also due to their popularity in neuropsychological

Demographics (gender, age, mean age with standard deviation (SD), years of education, mean years of education

(YoE) with SD, left-handedness and right-handedness) are given for the total number of participants, volunteers

who have been on the panel for more than 5 years (> 5), volunteers who have joined in the last 9 months (<9 mth.)

and the people recruited from the general public.


8

research. It is highly probable that some of the volunteers, especially the experienced ones,

would have come across one or two of the tests during their time on the panel. Nine tests were

selected to fit into a two hour testing session per participant.

The Rey-Osterrieth Complex Figure Test (ROCFT) was first developed by Swiss

psychologist André Rey in 1941 and later standardized into a 36-point scale, based on 18

elements within the figure, by Osterrieth in 1944 (Rey, 1941; Osterrieth, 1944). Copying the

ROCFT measures visuospatial perception, construction and organizational strategies, whereas

the recall is used to measure visual memory and how much of the original information could

be retained over time (Benett-Levy, 1984; Troyer & Wishart, 1997; Fastenau, Denburgh &

Hufford, 1999). The administration procedures can vary, depending on how one sets the time

intervals between copy and delayed recall and whether one allows for an immediate or short-

term recall after the copy trial. The procedure used in this study follows Meyers and Meyers

(1995) proposition of Copy, Immediate Recall and 30-min Delayed Recall. Looking at

different ways of administration they have shown that an immediate or short-term recall has a

significant effect on the 30-min Delayed Recall which has to be considered when looking at

norms that only had a copy and delayed trial (Meyers & Meyers, 1995). Norms were taken

from a study conducted by Fastenau et al. (1999) who present age-appropriate norms for Copy,

Immediate Recall and Delayed Recall, based on a sample of 211 healthy adults with an age

range from 30 - 85 years and an education range of 12 - 25 years (Fastenau, et al., 1999) The

test was administered on paper, allowing pencil and rubber.

The Alzheimer's Disease Assessment Scale - Cognitive Behavior Section (ADASCog) was

first published in 1984, specifically designed to assess patients with Alzheimer's disease (AD)

type dementia (Rosen, Mohs, & Davis, 1984). Similar to the ACE it covers cognitive domains,

such as memory, language, constructional abilities and executive functions. Although the test

is very popular in research and clinical trials, there are not many studies that reference

normative data for the ADASCog (Graham, Cully, Snow, Massman, & Doody, 2004). Unlike

the ACE, the ADASCog is not used to detect cognitive impairment, but rather to evaluate the

severity of it and the degree of decline. Graham et al. (2004) are one of the few who provide

norms for each subtest, as well as norms for total scores according to age and education,

based on a sample of 124 participants aged 55 - 89 (Graham, et al., 2004). Scores in this study,

therefore, were compared to this set of norms. The test was administered on paper. Word lists

and pictures of objects were presented on flashcards.


9

The Graded Naming Test (GNT) was designed by McKenna and Warrington in 1980 as an

instrument to detect mild word retrieval difficulties and improvement or deterioration of

naming abilities (Warrington, 1997). Noting that, if less frequent words are more vulnerable

to word-finding difficulties, an individual with an extensive vocabulary would not score

abnormally on common vocabulary tests, McKenna and Warrington (1980) presented a

naming test of graded difficulty to better assess an individual's naming abilities (McKenna &

Warrington, 1980). In 1997 Warrington looked at the performance of normal control subjects

on the NART and the GNT and suggested a restandardization due to the impression that the

test has become less difficult and the overall level of performance has shifted (Warrington,

1997). Norms were taken from this restandardization. The test was administered with the

pictures printed on 30 sheets of A4 paper.

The National Adult Reading Test (NART) was created by Nelson and McKenna in 1982 as

a way to determine pre-morbid IQ (Nelson & Willison, 1991). In dealing with cognitive

impairment and deteriorating diseases, such as dementia, it is important to know what pre-

morbid IQ the patient had to estimate the severity of decline. Due to the fact that reading

abilities seem to be quite resistant to the progression of dementia, the NART offers a better

prediction of pre-morbid IQ than current vocabulary levels (Nelson & Willison, 1991).The

test is comprised of 50 irregular words which do not follow the common rules of grapheme-

phoneme representation and pronunciation. Without knowing the word, patients would

generally not be able to guess the correct pronunciation of it. NART error scores are usually

converted into WAIS IQs . After introducing WAIS-R, calculated IQs were on average 7.5

points lower than in the original WAIS and the NART was restandardized in 1991 (Nelson &

Willison, 1991). This study used the norms presented for NART errors in the manual. The

words were printed on an A4 sheet and read out loud by the participants.

The Addenbrooke's Cognitive Examination (ACE) was introduced by Mathuranath et al. in

2000 as a quick and straight forward test that could detect early dementia and differentiate

between AD and frontotemporal dementia (FTD) (Mathuranath, Nestor, Berrios, Rakowicz, &

Hodges, 2000). It underwent several revisions since then, namely changing the design to

make the test easier to administrate, as well as making the content more cross-cultural

applicable and to increase sensitivity (Mioshi, Dawson, Mitchell, Arnold & Hodges, 2006;

Hsieh, Schubert, Hoon, Mioshi, & Hodges, 2013). It is a very popular screening test for

dementia, since it usually takes less than fifteen minutes to complete and has proven to be

highly accurate (Mathuranath, et al., 2000). This study used the current version ACE-III


10

which includes subcategories measuring orientation and attention, memory, verbal fluency,

language and visuospatial abilities. A comparison between ACE-III to ACE-R showed that

dementia patients generally scored 1-2 points lower on the ACE-III, but sensitivity and

specificity values for cut-offs at 88/100 and 82/100 still remained high (Hsieh, et al., 2013).

Norms suggested by Hsieh et al. (2013) and Mioshi et al. (2006) for overall scores, as well as

scores for the separate cognitive domains, were used in this study. The test was administered

on paper with a pen or pencil.

The Test of Everyday Attention (TEA) was developed by Robertson et al. (1994) as a

measurement of different forms of attention and how they are affected depending on the

location of the lesion (Robertson, Ward, Ridgeway, & Nimmo-Smith, 1996). This study uses

three auditory subtests of the TEA; Elevator Counting (subtest 2) requires sustained attention.

It has been shown that especially lesions to the prefrontal cortex can result in problems

sustaining attention and concentration (MacPherson, Turner, Bozzali, Cipolotti, & Shallice,

2010). Elevator Counting with Distraction (subtest 3) and Reversal (subtest 5), on the other

hand, rely heavily on attention switching and auditory-verbal working memory (Robertson, et

al., 1996; Chan, 2000). Norms were taken from Robertson et al. (1996) who presented norms

for the age range 50 to 64 and 65 to 80 (Robertson, et al.,1996) and the TEA manual

(Robertson, et al., 1994). The test was administered on either a laptop or an iPad.

The Digit Symbol-Coding Test (DSCT), also known as the Digit Symbol (DS) or Digit

Symbol Substitution Test (DSST) is one of the fourteen subtests of the Wechsler Adult

Intelligence Scale III (WAIS-III) which is used as a measurement of general adult intelligence

(Wechsler, 1997). The DSCT has proven to be one of the more sensitive subtests used in the

WAIS when screening for brain damage. It not only measures processing speed, but studies

further suggest that performance also relies on visual scanning, perceptual organization,

visual-motor coordination and, to a lesser degree, memory and the abilities to form new

verbal associations (Crowe et al., 1999; Joy, Fein & Kaplan, 2003). The performance on the

DSCT is known to drop with age, although not necessarily due to reduced motor control, as a

study by Salthouse (1992) investigated, but rather a slowing of overall cognitive processing

(Salthouse, 1992). Norms were taken from the WAIS-III manual.

The Trail Making Task (TMT) was originally part of the Army Individual Test of General

Ability in 1944 and was subsequently incorporated into the Halstead-Reitan

Neuropsychological Test Battery (Corrigan & Hinkeldey, 1987; Reitan, 1958). The test

requires visual-conceptual and visual-motor tracking skills, using cognitive abilities, such as


11

scanning, processing speed, mental flexibility and executive functions (Tombaugh, 2004).

While Part A mostly relies on visuospatial processing, Part B depends more heavily on

executive functions and attention switching, due to its more complex task of connecting

numbers and letters in ascending order (Kipps & Hodges, 2005). Even though the TMT is

widely used, there are no clear sets of norms. Some studies calculate the difference (B-A, or

sometimes A-B) and ratio (B/A) of the two parts (Corrigan & Hinkeldey, 1987; Giovagnoli, et

al., 1996). Other studies try to define norms on mean number of seconds the parts require,

stratifying it by age and education (Tombaugh, 2004). Norms for this study were taken from

Tombaugh (2004) who used a sample of 911 participants, aged 18-89 years and two education

levels (Tombaugh, 2004). The test was administrated on paper with pen or pencil.

The Boston Cookie Theft (BCT) description task is a component of the Boston Diagnostic

Aphasia Examination (Goodglass & Kaplan, 1983). It is used to assess spontaneous speech

and looks at linguistic features, such as syntax, lexicon, phonology or prosody (Giles,

Patterson, & Hodges, 1996). The picture was presented on an A4 paper and the written

sample was collected on paper as well. Due to limited time, the results of the test were not

further assessed in this study. The participants did not seem to present with any language

impairment and generally had no difficulties describing the picture. However, in a future

study it would still be very interesting to see how healthy "normal" controls differ from each

other in spontaneous speech and writing.

Table 3 shows an overview of the cognitive domains utilize by each test.

Table 3 List of 9 tests with subcategories and their corresponding cognitive domains.

Cognitive Domains

Tests Memory Language Visuospatial

Processing Attention

Executive

Functions

Processing

Speed IQ

ROCFT

Copy Imm. Recall Delayed Recall ADASCog Word Recall Word Delayed Word Recogn. Instructions Commands Naming Comprehension Word Finding Language Construction


12

Nr cancelling Orientation Ideational Pr. Maze GNT NART ACE Memory Language Visuospatial Attention Verbal Fluency TEA 2,3,5 DSCT () () TMT A TMT B

2.3. Procedure

After receiving the approval of the ethics committee, the recruitment process started in

April and ended in early July. The contact information for the volunteers was randomly

divided between the two main researchers to ensure each had an equal amount of experienced

and inexperienced participants, as well as participants from younger and older age groups.

Volunteers were contacted via e-mail, in which the pre-questionnaire was attached as a PDF

file, as well as inline. If there was no e-mail address available or turned out invalid, volunteers

were contacted via letters, which included the pre-questionnaire and a stamped return

envelope. Volunteers were subsequently contacted by phone to schedule the testing session.

Participants from the general public were scheduled via phone or email. Each participant was

given a number to secure anonymity of their data. Testing started at the end of May and lasted

until end of July. Each session started with a short conversation, not just to welcome the

participants, but also to observe their language abilities as part of the ADASCog. After

signing the consent form, the testing would begin. Upon completing the last test, the

participants were asked to fill out a questionnaire, asking them about leisure activities, as well

as whether they felt like their memory, concentration, and language abilities have changed in

the last years and if so whether they felt like it impaired their everyday life. The participants

were further given a language questionnaire if they stated that they spoke any other languages

next to English. When necessary, participants were reimbursed with £4. During the session

they were provided with water and snacks. Figure 1 gives an overview of the test procedure.

Main cognitive domains assessed by each test and subtest are signaled with ticks. The DSCT mainly relies on

visuospatial processing and processing speed, however, it might also tap into memory and executive functions. This

is signaled with ticks in brackets.


13

Fig. 1 Procedure of test administration. Sessions would usually take 1.5 to 2 hours.

ROCFT

Copy

ROCFT

Immediate

Recall

ADASCog

GNT

NART

ACE-III

TEA 2, 3, 5

BCT Oral

DSCT

TMT A, B

BCT

Written

5 Min

Break

All ROCFT tests are timed. Participants are told not to hurry, and

are allowed to use the rubber, if they feel it is necessary. After

the Immediate Recall the time is noted; 30 minutes until the

ROCFT Delayed Recall start.

Five questions from the ACE-III are added to the ADASCog

subsection Orientation (No./Floor, Street/Hospital, Town,

County, Country), so the participants would not have to be

repeatedly tested on these. The scores are subsequently added

to the ACE. For the words and objects, it is ensured the

participants can properly see the flashcards. The maze is timed

in full seconds and 45 seconds are given for the nr. cancelling.

Participants are allowed to go through the GNT and NART at

their own speed. If they make a mistake on the GNT they are

asked whether they know another name for the object,

otherwise they could continue.

Depending on how quickly the tests

proceeded, participants are either asked to

draw the ROCFT Delayed Recall, or, if there is

enough time, continue on to the ACE-III.

Otherwise a quick break is taken to get to the

30 minute mark for the Delayed Recall.

they could continue.

It is ensured that tones are clearly audible. Examples are

played for all the tasks, if needed repeatedly. Task 5 proved to

be rather complicated to understand and sometimes drawings

are used to illustrate how it works. A few participants could

not perform the task 5 and are given 0 points for it.

Both TMT A and B are timed. Short samples are given for all

three tests to ensure participants know what to do

Participants are given 120 seconds to transcribe as many

symbols as possible.

Questions on the ACE-III that were already

asked in the ADASCog Orientation subsection

(Day, Date, Month, Year, Season) and the

copying of the cube are not asked again and

the scores were taken from the ADASCog.

ROCFT

Delayed

Recall


14

2.4. Design

The two groups, experienced and inexperienced, were further divided into age categories of

{55-65} years and {66-75} years, to compare how the age groups performed in relation to

their level of experience. The cut-off 65 was chosen, since it is often the age of retirement.

Furthermore, geriatric health care centers start offering assistance to those who are 65 or older,

while early-onset Alzheimer's is usually diagnosed in people below 65 (Alzheimer's Society).

SPSS was used to run the analysis. To see how the experienced group fares compared to the

inexperienced one, and whether there is a main effect of age or experience, a 2x2 ANOVA

was conducted for each test and subtest. Kolmogorov-Smirnov (K-S) or Shapiro-Wild (S-W)

were used to test for normal distribution. Since this study is dealing with healthy participants,

tests which evaluate cognitive impairment, such as the ADASCog or ACE, often show ceiling

effects. If the distribution was not normal, attempts were made to log transform the data,

however, this usually did not normalize the distribution. As it is, the 2x2 ANOVA might

therefore not be robust enough for groups in which the assumption of a normal distribution is

violated. This has to be considered when looking at the results.

3. Results

3.1. Matching Groups

To determine whether experience has an effect on scores, the 61 volunteers are split into

two groups according to their frequency of participation on the panel. Participating in two or

more experiments per year counts as experienced, less than two times per year as

inexperienced. Cut-off line is determined by total number of experiments (range: 0-125

experiments, mean=12.32 (SD=21.39)) divided by total years since starting participation on

the panel (range: 0-23 years, mean=3.80 (SD=5.397)). Table 4 shows gender, age and

education range, as well as experience on the panel for the two groups.

Table 4 Total number of inexperienced participants and experienced participants.

Participants

Inexperienced (n=27) Experienced (n=34)

Female 18 22

Male 9 12

Age 55 - 75 55 - 74

Mean Age (SD) 64.56 (6.25) 65.24 (4.52)

Years of Education 8 - 20 10 - 26.5

Mean YoE (SD) 16.06 (3.00) 17.03 (3.67)

No. of Years on Panel 0-23 0-14


15

Mean NoY (SD) 4.26 (6.34) 3.44 (4.58)

No. of Experiments 0-25 1-125

Mean NoE (SD) 5.24 (7.99) 17.94 (26.60)

Experience(SD) 0.62 (0.80) 4.86 (3.13)

An independent sample t-test is conducted to see whether the groups match. The Levene's

Test for Equality of Variances for age is significant with F(59)=6.981, p=0.011. In all

probability, equality of variance can therefore not be assumed. Even though the two groups

might not be homogenous in age, they are matched on all three variables. Age difference for

inexperienced (M=64.56, SE=1.20) and experienced (M=65.24, SE=0.78) is not significant

t(45.86)= -0.475, p= 0.637. Difference in education for inexperienced (M=16.06, SE=0.58)

and experienced (M=17.03, SE=0.63) is not significant t(59)= -1.113, p= 0.270. Gender for

inexperienced and experienced is also not significant t(59)= -0.157, p= 0.875.

In a next step, the inexperienced and experienced groups are further divided into age {55-

65} and {66-75}. Controlling for outliers shows that one participant in particular scored

below average on all tests, with exception of the NART. The fact that most scores are also

below what published norms consider as "normal", even when applying double or triple

standard deviation (SD), gives reason to suspect presence of MCI. Table 5 lists the

participant's scores and cut-off norms:

Table 5 Scores of outlier N18 compared to cut-off scores provided by norms

N18

Age:57 ROCFT ACE ADAS GNT NART TEA DSCT TMT

Scores 28/6/9.5 80 20 20 2 4/1/0 34 116/172

Cut-off 28.5/9.5/10 82/88 5.24 16 30 7/6/2 46 41.86/89.76

Since this study is trying to detect very subtle changes in cognitive domains between the two

older and younger groups, scores like these could influence the outcome. Due to the

participant's 80 on ACE, the scores are excluded from the inexperienced group. Another

participant scored 80 on ACE and is not included in the experienced group. To match for age

between the experienced and inexperienced {66-75} year-olds, one 73 year-old participant,

Scores are provided for participant N18, 57 years old (18 years of education). Cut-off scores are calculated

according to published norms. Highlighted in red shows all the scores that are below the norms and are considered

abnormal.


(YoE) with standard deviation, number of years participants have been on the panel, mean number of years on the

panel (NoY) with standard deviation, number of experiments they have participated in, mean number of

experiments (NoE) with standard deviation) for both groups.

Experience: Number of total experiments divided by number of years on the panel. Mean and standard deviation

are given for both groups. 2.0 experiments or more per year counts as experienced.


16

who scored abnormally on TMT B (180.5 seconds), is excluded from the inexperienced group.

The final groups are presented in table 6.

Table 6 Total number of inexperienced/experienced participants divided by age groups.

Participants

Inexperienced Experienced

55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Female 10 6 11 11

Male 4 5 4 7

Mean Age (SD) 59.79 (2.81) 70.55 (2.66) 61.07 (2.66) 68.78 (2.26)

Years of Educ. 13 - 20 8 - 20 10 - 21 10 - 26.5

Mean YoE (SD) 17.21 (2.01) 14.50 (3.63) 17.33 (2.69) 16.61 (4.41)

Years on Panel 0 - 15 0 - 23 0 - 8 0 - 14

Mean YoP (SD) 4.21 (5.48) 4.55 (8.02) 1.53 (2.62) 5.22 (5.28)

No.Experiments 0 - 25 0 - 25 1 - 70 1 - 125

Mean NoE (SD) 2.28 (8.53) 4.82 (8.39) 9.20 (17.78) 26.06 (31.03)

Experience(SD) 0.55 (0.69) 0.44 (0.65) 4.44 (3.79) 5.16 (2.62)

Equality of variances can be assumed for all variables in both groups. Group {55-65}: Age

difference between inexperienced (M=59.79, SE=.75) and experienced (M=61.07, SE=0.69)

is not significant t(27)= -1.262, p= 0.218. Difference in education between inexperienced

(M=17.21, SE=0.54) and experienced (M=17.33, SE=0.69) is not significant t(27)= -0.134, p=

0.894. Gender between inexperienced and experienced is also not significant t(27)= 0.111, p=

0.913. Group {66-75}: Age difference between inexperienced (M=70.55, SE=.80) and

experienced (M=68.78, SE=0.53) is not significant t(27)= 1.919, p= 0.067. Difference in

education between inexperienced (M=14.50, SE=1.09) and experienced (M=16.61, SE=1.04)

is not significant t(27)= -1.333, p= 0.194. Gender between inexperienced and experienced is

also not significant t(27)= 0.337, p= 0.739. It can be concluded that the groups are matched.

3.2. Norms, Distribution and 2x2 ANOVA

ROCFT

On the Copy task, all groups score similarly, varying between 32/33 and 36 points out of a

maximum of 36. Both the inexperienced and experienced groups score around 1 point better

on the ROCFT Copy than the norms given by Fastenau et al. (1999) suggest.


(YoE) with standard deviation, number of years participants have been on the panel, mean number of years on the

panel (NoY) with standard deviation, number of experiments they have participated in, mean number of

experiments (NoE) with standard deviation) for age groups 55 - 65 and 66 - 75 for both inexperienced and

experienced participants.

Experience: Number of total experiments divided by number of years on the panel. Mean and standard deviation are

given for all four groups. 2.0 experiments or more per year counts as experienced.


17

Table 7 Means with standard deviations and norms for ROCFT Copy

ROCFT Copy


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Min 33 33.5 33 32

Max 36 36 36 36

Mean (SD) 35.43 (0.94) 35.14 (1.05) 35.33 (1.11) 35.17 (1.34)

TOTAL 35.30 (0.98) 35.24 (1.23)

Norm (Fastenau, et al., 1999)

Mean Age 63 Mean Age 68

31.94 (3.37) 31.76 (3.63)

Due to ceiling effects in the scores of all four groups, no further inferential analyses are

conducted.

On the Immediate Recall, scores differ more distinctly from each other. Although the

experienced group scores only marginally better than the inexperienced group, experienced

{66-75} and inexperienced {66-75} are at opposite ends, with the older experienced

volunteers scoring the highest and the older inexperienced volunteers scoring the lowest out

of the four groups. Compared to the norms and including SD, all groups score 4 to 7 points

better.

Table 8 Means with standard deviations and norms for ROCFT Immediate Recall

ROCFT Immediate Recall


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Min 8 3 6.5 14

Max 29.5 28 27 34

Mean (SD) 21.43 (5.26) 16.41 (9.34) 19.00 (6.09) 22.67 (5.80)

TOTAL 19.22 (7.60) 21.00 (6.13)

Norms (Fastenau, et al., 1999)


15.52 (5.82) 15.18 (5.58)

For the Immediate Recall, the scores in all groups are normally distributed: Inexperienced

{55-65}, D(14)=0.152, p=0.200 and inexperienced {66-75}, D(11)=0.140, p=0.200.

Descriptive statistic and norms are provided of the test for all four groups. Total lists the mean scores and standard

deviation for inexperienced and experienced participants, irrespective of their age.

Published norms are provided for comparison.





18

Experienced {55-65}, D(15)=0.165, p=0.200 and experienced {66-75}, D(18)=0.113,

p=0.200.

The Delayed Recall shows a similar result to the Immediate Recall. Experienced volunteers

are only marginally better than inexperienced, but the older age groups differ more

prominently from each other than the younger groups. All score 4 to 7 points better than the

norms suggest.

Table 9 Means with standard deviations and norms for ROCFT Delayed Recall

ROCFT Delayed Recall


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Min 7 3 8 13.5

Max 30 30 28 33

Mean (SD) 19.93 (5.60) 16.50 (8.26) 18.23 (5.56) 22.69 (5.75)

TOTAL 18.42 (6.96) 20.67 (6.01)

Norms (Fastenau, et al., 1999)


15.91 (5.91) 15.29 (5.57)

The scores for Delayed Recall are also normally distributed: Inexperienced {55-65},

D(14)=0.189, p=0.186 and inexperienced {66-75}, D(11)=0.109, p=0.200. Experienced {55-

65}, D(15)=0.151, p=0.200 and experienced {66-75}, D(18)=0.101, p=0.200.

Scores for both recalls are further analyzed to see whether there are significant effects:




Fig. 2 2x2 ANOVA results for ROCFT Immediate Recall Fig. 3 2x2 ANOVA results for ROCFT Delayed Recall


19

For both ROCFT Immediate Recall (Fig.2) and Delayed Recall (Fig.3), more experience

significantly improves the performance of the older groups. On the Immediate Recall, no

significant main effect of experience F(1,54)=1.192, p=0.280 or age F(1,54)=0.147, p=0.702

can be seen. However, the amount of experience significantly interacts with age between the

groups, F(1,54)=6.150, p=0.016. Results for the Delayed Recall are almost identical. There is

no significant main effect of experience F(1,54)=1.842, p=0.180 or age F(1,54)=0.097,

p=0.757, but experience significantly interacts with age between the two age groups,

F(1,54)=5.666, p=0.021.

ADASCog:

The norms provided for ADAS Total do not include scores for maze time or number

cancelling. Furthermore, while Graham et al. (2004) provide norms for the components of

memory and language domains, they do not offer the same for visuospatial, processing speed

or executive functions, mainly because they do not look at maze and number cancelling scores.

Only the total scores are therefore compared to the norms. Due to miscommunication in test

instruction, maze time is not considered in this study, only maze errors.

The ADASCog measures number of errors, lower scores are therefore better than higher

scores. Both inexperienced and experienced groups seem to score marginally worse than what

the norms suggest. Especially when looking at the maximum scores of the older groups there

is a discrepancy between the published norms and the data here. Even with double or triple

SD, some participants would have to be excluded due to abnormal scores. However, since

there are only few published papers on ADASCog norms for healthy adults, and the

participants with high scores did not perform significantly worse than others on any of the

other tests, they are not excluded from the data set. Executive functions show strong ceiling

effects with everyone scoring between 0 and 1 point and are not further analyzed. Processing

speed, language and visuospatial domain are analyzed, but do not show any significant results.

Table 10 Means with standard deviations and norms for ADASCog and subcategories

ADASCog


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Total Score

Min 0.33 1.67 0.67 0.33

Max 6.70 14.67 9.50 13.33

Mean (SD) 3.08 (2.14) 7.79 (3.40) 4.92 (2.30) 5.57 (3.09)

TOTAL 5.15 (3.85) 5.28 (3.02)

Memory


20

Min 0.33 0.67 0.67 0.33

Max 6.70 12.67 9.50 12.33

Mean (SD) 2.80 (2.04) 6.33 (3.40) 4.32 (2.77) 5.07 (2.86)

TOTAL 4.35 (3.20) 4.73 (2.80)

Language

Min 0.00 0.00 0.0 0.00

Max 2.00 3.00 2.0 2.00

Mean (SD) 0.43 (0.65) 1.09 (1.22) 0.53 (0.74) 0.56 (0.70)

TOTAL 0.72 (0.98) 0.55 (0.71)

Visuospatial

Min 1.00 0.00 0.00 1.00

Max 29.00 26.00 27.00 22.00

Mean (SD) 11.36(7.59) 11.45(8.63) 10.20(7.20) 10.56(5.83)

TOTAL 11.40 (7.89) 10.39 (6.39)

Attention

Min 0.00 0.00 0.00 1.00

Max 400 2.00 1.00 1.00

Mean (SD) 0.36 (1.08) 0.64 (0.67) 0.33 (0.49) 0.33 (0.49)

TOTAL 0.48 (0.92) 0.33 (0.48)

Exec.Function

Min 0.00 0.00 0.00 0.00

Max 1.00 1.00 1.00 1.00

Mean (SD) 0.14 (0.36) 0.18(0.40) 0.13 (0.35) 0.17 (0.38)

TOTAL 0.16 (0.37) 0.15 (0.36)

Processing Speed

Min 1.00 0.00 0.00 1.00

Max 29.00 26.00 27.00 21.00

Mean (SD) 11.29(7.63) 11.36(8.55) 10.13(7.22) 10.50(5.72)

TOTAL 11.32 (7.87) 10.33 (6.34)

Norms (Graham, et al., 2004)

Age 55 - 64 Age 65 - 69 Age 70 - 74

3.60 (1.64) 4.51 (2.18) 5.13 (2.06)

The ADASCog Total scores follow normal distribution; Inexperienced {55-65}, D(14)=0.220,

p=0.065 and inexperienced {66-75}, D(11)=0.171, p=0.200. Experienced {55-65},

D(15)=0.116, p=0.200 and experienced {66-75}, D(18)=0.163, p=0.200.

Descriptive statistic and norms are provided of the test and all the subcategories for all four groups. Total lists the

mean scores and standard deviation for inexperienced and experienced participants, irrespective of their age.

ADASCog subtests word recall, delayed recall, word recognition and instructions are combined into Memory

subcategory.

ADASCog subtests commands, naming, comprehension, word finding difficulties and language are combined into

Language subcategory.

ADASCog subtests construction and number cancelling with errors are combined into Visuospatial subtests.

ADASCog subtests number cancelling errors and orientation are combined into Attention subcategory.

ADASCog subtests ideational praxis and maze errors are combined into Executive Functions subcategory.

ADASCog subtests number cancelling and errors and maze errors are combined into Processing Speed

subcategory.



21

According to the Shapiro-Wilk Test of Normality, the ADASCog Memory scores follow

normal distribution; Inexperienced {55-65}, D(14)=0.912, p=0.170, inexperienced {66-75},

D(11)=0.971, p=0.892 and experienced {55-65}, D(15)=0.944, p=0.432, experienced {66-75},

D(18)=0.943, p=0.332. The K-S Test of Normality, however, shows a slightly positively

skewed distribution for the experienced {66-75} group, D(18)=0.209, p=0.037.

Both ADASCog Total and Memory are further analyzed to see whether there are significant

effects:

The ADASCog Total (Fig.4) shows a significant main effect of age F(1,54)=10.732, p=0.002,

independently of experience. There is no significant main effect of experience F(1,54)=0.053,

p=0.819. However, experience significantly interacts with the two age groups,

F(1,54)=6.149, p=0.016.

The ADASCog Memory (Fig.5) looks similar to the ADAS Total. Age has a significant effect

F(1,54)=8.382, p=0.05 independently of experience. There is no significant main effect of

experience F(1,54)=0.032, p=0.859 or interaction between the two age groups, F(1,54)=3.537,

p=0.065. However, there is a strong trend that being more experienced reduces the effect age

has on the participant's performance significantly.

GNT:

Both inexperienced and experienced groups score similarly on the GNT. However, there

seems to be a slight difference between the younger{55-65} and the older {66-75} groups,

with the older generally scoring lower. Overall, the groups score 2 to 4 points better than the

norms suggested by Warrington (1997).

Fig. 4 2x2 ANOVA results for ADAS Total Fig. 5 2x2 ANOVA results for ADAS Memory


22

Table 11 Means with standard deviations and norms for GNT

GNT


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Min 24 22 24 21

Max 30 29 30 30

Mean (SD) 27.57 (3.34) 25.73 (2.33) 27.13 (1.64) 26.61 (2.40)

TOTAL 26.76 (2.22) 26.85 (2.08)

Norms (Warrington, 1997)

20.4 (4.1)

The scores for the GNT are normally distributed for the inexperienced {55-65}group,

D(14)=0.211, p=0.090, and the experienced {66-75}group, D(18)=0.175, p=0.148. The

distributions for the inexperienced {66-75}group, D(11)=0.259, p=0.038 and the experienced

{55-65} group, D(15)=0.266, p=0.005 can be seen as slightly bi- or multimodal. However, the

S-W test shows normal distribution for both groups with D(11)=0.866, p=0.068 and

D(15)=0.912, p=0.146. The data is further analyzed to see whether there are significant

effects:

The GNT (Fig.6) shows a significant main effect of age F(1,54)=4.549, p=0.038. There is no

significant main effect of experience F(1,54)=0.161, p=0.689 and experience does not

significantly interact with age between the two age groups, F(1,54)=1.419, p=0.239.




Fig. 6 2x2 ANOVA results for GNT


23

NART:

The NART is scored in errors. All the groups score better than the what the norms by

Nelson and Willison (1991) suggest. The lowest score is 0 and highest score is 17, whereas

the norms, including SD, are between 7.1 and 30.5. There is one outlier in the inexperienced

{66-75} group who scored 17 errors. Although this is not abnormal according to published

norms, in this sample, it skews the distribution D(11)=0.255, p=0.045. The descriptive data is

shown with the outlier included, since the scores are "normal". For any further analysis of the

NART, however, the participant's data is excluded. Results do not reach significance with or

without the outlier.

Table 12 Means with standard deviations and norms for NART

NART


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Min 2 1 0 0

Max 11 17 13 11

Mean (SD) 4.79 (2.78) 7.27 (4.54) 4.73 (3.49) 5.11 (3.05)

TOTAL 5.88 (3.79) 4.94 (3.21)

Norms (Nelson & Willison, 1991)

18.8 (11.7)

ACE-III:

The two age and experience groups do not to differ much from each other, except for the

subcategory fluency, in which the experienced seeme to be at an advantage. The volunteers

are only marginally better on the total ACE score than the norms, mainly due to small

variances in the fluency subcategory. Attention, memory, language and visuospatial

subcategories are almost identical to the norms provided by Hsieh (2013) and Mioshi (2006).

Most of the scores show ceiling effects. Language, visuospatial and memory subcategories

show no significant results and are not further analyzed.

Table 13 Means with standard deviations and norms for ACE-III and subcategories

ACE-III


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)





24

Total Score

Min 90 86 93 85

Max 100 100 100 100

Mean (SD) 97.14 (2.96) 95.91 (4.66) 98.40 (2.06) 96.28 (4.11)

TOTAL 96.60 (3.76) 97.24 (3.46)

Memory

Min 23 19 22 19

Max 26 26 26 26

Mean (SD) 25.21 (1.25) 24.82 (2.44) 25.20 (1.27) 24.83 (2.04)

TOTAL 25.04 (1.84) 25.00 (1.71)

Language

Min 25 24 25 23

Max 26 26 26 26

Mean (SD) 25.64 (0.50) 25.18 (0.67) 25.93 (0.26) 25.33 (0.91)

TOTAL 25.64 (0.57) 25.61 (0.75)

Visuospatial

Min 14 13 12 13

Max 16 16 16 16

Mean (SD) 15.64 (0.63) 15.36 (1.03) 15.67 (1.05) 15.56 (0.86)

TOTAL 15.52 (0.82) 15.61 (0.93)

Attention

Min 17 16 17 14

Max 18 18 18 18

Mean (SD) 17.79 (0.43) 17.45 (0.69) 17.80 (0.41) 17.17 (1.51)

TOTAL 17.64 (0.57) 17.45 (1.18)

Fluency (Executive Functions)

Min 9 9 13 12

Max 14 14 14 14

Mean (SD) 12.86 (1.56) 12.64 (1.57) 13.80 (0.41) 13.39 (0.85)

TOTAL 12.76 (1.54) 13.58 (0.71)

ACE-III Norms (Hsieh, et al., 2013)

ACE Total 95.4 (3.3)

Language 25.6 (0.6)

Visuospatial 15.6 (0.6)

Attention 17.4 (1.2)

ACE-R Norms (Mioshi, et al., 2006)

Memory 23.4 (2.7)

Fluency 11.9 (1.7)

The ACE Total scores are not normally distributed for the inexperienced {55-65}group,

D(14)=0.328, p=0.000, the experienced {55-65} group, D(15)=0.281, p=0.002.The

distributions following normal distribution for the inexperienced {66-75}group, D(11)=0.219,

Descriptive statistic and norms are provided of the test and subcategories for all four groups. Total lists the mean

scores and standard deviation for inexperienced and experienced participants, irrespective of their age.



25

p=0.147 and the experienced {66-75}group, D(18)=0.195, p=0.068.

ACE Fluency scores show a normal distribution for the inexperienced {66-75} group

D(11)=0.228, p=0.114. All the other groups show a negatively skewed distribution towards

the maximum score of 14: Inexperienced {55-65}, D(14)=0.268, p=0.007, experienced {55-

65}, D(15)=0.485, p=0.000 and experienced {66-75}, D(18)=0.375, p=0.000.

ACE Attention scores are all negatively skewed; Inexperienced {55-65} group D(14)=0.478,

p=0.000 and experienced {55-65}, D(15)=0.485, p=0.000. Inexperienced {66-75},

D(11)=0.332, p=0.001, and experienced {66-75}, D(18)=0.377, p=0.000.

ACE Total, Fluency and Attention are further analyzed to see whether there are significant

effects:

The ACE Fluency (Fig.7) is the only test that shows a main effect of experience

F(1,54)=7.689, p=0.008. No effect can be seen for age F(1,54)=1.068, p=0.306 or interaction

F(1,54)=0.097, p=0.757. It has to be noted that the Levene's Test of Equality of Error

Variances is significant F(3, 54)=5.681, p=002 and the distribution is not normal for all

groups. However, this result suggest that experience significantly improves performance for

both age groups.

ACE Total (Fig.8) shows no main effect of experience F(1,54)=0.740, p=0.393 or age

F(1,54)=3.153, p=0.081 on the participants' scores, however, age seems to show a trend

towards significance. The amount of experience did not significantly interact with age

between the two age groups, F(1,54)=0.221, p=0.640.

Similarly, the ACE Attention (Fig.9) shows no main effect of experience F(1,54)=0.296,

p=0.589 or age F(1,54)=3.679, p=0.060 on the participants' scores, however, age seems to

Fig. 7 2x2 ANOVA results for ACE Fluency


26

show a trend towards significance. The amount of experience did not significantly interact

with age between the two age groups, F(1,54)=0.361, p=0.550. However, the Levene's Test is

significant with F(3,54)=6.551, p=0.001.

TEA:

On the TEA 2, all participants scored 7 points out of a maximum of 7. The test is therefore

not included in any further analysis. The overall scores for the TEA 3 lie well within the

suggested range of norms. No norms are provided by Robertson et al. (1996) for the TEA 5

scores for the older groups. According to the TEA manual, scoring 0 points is acceptable

(Robertson, et al., 1994). The {55-65} groups score slightly better compared to the norms

provided for a mean age of 61 (Robertson et al, 1996).

Table 14 Means with standard deviations and norms for TEA 3 and 5

TEA


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

TEA 3

Min 1 1 5 3

Max 10 10 10 10

Mean (SD) 8.50 (2.62) 6.27 (3.35) 9.07 (1.53) 7.83 (2.41)

TOTAL 7.52 (3.11) 8.39 (2.12)

TEA 5

Min 0 0 0 0

Max 10 10 10 10

Mean (SD) 6.21 (3.89) 4.91 (3.56) 5.67 (3.31) 5.44 (3.07)

TOTAL 5.64 (3.73) 5.55 (3.13)

Fig. 8 2x2 ANOVA results for ACE Total Fig. 9 2x2 ANOVA results for ACE Attention


27

Norms for TEA 3 (Robertson, et al., 1996)

Age 50-64 Age 65-80

TEA 3 8.18 (2.8) 7.75 (2.9)

TEA 5 4.7 (3.1) -

Norms from the TEA manual (Robertson, et al., 1994)

TEA 3 6 or more 5 or more

TEA 5 2 or more 0 or more

The TEA 3 scores are not normally distributed for the inexperienced {55-65}group,

D(14)=0.290, p=0.002, the experienced {55-65} group, D(15)=0.349, p=0.000 and the

experienced {66-75}group, D(18)=0.297, p=0.000. The scores are following normal

distribution for the inexperienced {66-75}group, D(11)=0.231, p=0.105..

TEA 5 scores are normally distributed for the inexperienced {66-75}group, D(11)=0.171,

p=0.002, the experienced {55-65} group, D(15)=0.190, p=0.151 and the experienced {66-

75}group, D(18)=0.186, p=0.100. The scores show a bi- or multimodal distribution for the

inexperienced {55-65}group, D(11)=0.248, p=0.019. Further analysis on TEA 5 does not

show any significant results. TEA 3 has the following significant effect:

It has to be noted that the Levene's Test of Equality of Error Variances for the TEA 3 is

significant with F(3,54)=3.662, p=0.018. However, with the data at hand, the results (Fig.10)

suggest that age has a significant main effect F(1,54)=6.822, p=0.012.There is no significant

Descriptive statistic and norms are provided of TEA 3 and 5 for all four groups. TEA 2 is not given, because every

participant scored 7 out of 7 points. Total lists the mean scores and standard deviation for inexperienced and

experienced participants, irrespective of their age.

Published norms are provided for comparison. Cut-off for TEA 2 is 6 or less. Norms taken from the manual provide

cut-offs for TEA 3: below 6, respectively 5 and for TEA 5: below 2 for the 50-64 year olds. A score of 0 is acceptable

for 65+.

Fig. 10 2x2 ANOVA results for TEA 3


28

main effect of experience F(1,54)=2,578, p=0.114 and experience does not significantly

interact with age between the two age groups, with F(1,54)=0.563, p=0.456.

DSCT:

The DSCT scores are transferred into a scaled score as part of the WAIS-III. The manual

offers a conversion table. The volunteers are overall score better than the norms. Within the

experienced and inexperienced groups, the younger volunteers also seem to perform better

than the older.

Table 15 Means with standard deviations and norms for DSCT

DSCT


55-65 (n=14) 66-75 (n=11) 55-65 (n=14) 66-75 (n=18)

Min 52 49 57 51

Max 97 96 100 93

Mean (SD) 75.29 (12.23) 67.73 (12.81) 75.86 (13.75) 69.89 (12.87)

TOTAL 71.96 (12.80) 72.50 (13.39)

Norms (Wechsler, 1997)

Age 55 - 64 Age 65 - 69 Age 70 - 74

46 - 71 39 - 64 36 - 61

Scaled score of 9.88 (2.87)

On the DSCT all scores follow normal distribution; Inexperienced {55-65}, D(14)=0.137,


D(14)=0.165, p=0.075 and experienced {66-75}, D(18)=0.099, p=0.200. One participant's

score from experienced {55-65} group was excluded due to errors during administration of

the test. The data is further analyzed to see whether there are significant effects:




Fig. 11 2x2 ANOVA results for DSCT


29

DSCT (Fig.10) shows no main effect of experience F(1,53)=0.154, p=0.696 or age

F(1,53)=3.784, p=0.057 and experience does not significantly interact with age between the

two age groups, F(1,53)=0.052, p=0.820. Even though there are no significant main effects,

results suggest a strong trend that age effects the scores independently of experience.

TMT A and B:

In both Part A and B, all groups perform similar to the norms suggested by Tombaugh

(2003). He provides norms for both lower education (0-12 years) and higher education (+12

years). Comparison is made to +12 years. The inexperienced and experienced groups are

almost identical, with the experienced {55-65} performing slightly better.

Table 16 Means with standard deviations and norms for TMT A

TMT A


55-65 (n=14) 66-75 (n=11) 55-65 (n=15) 66-75 (n=18)

Min 27.0 21.1 19.7 16.0

Max 55.7 56.0 62.0 68.2

Mean (SD) 37.94 (10.44) 37.59 (9.83) 34.29 (10.66) 37.50 (13.11)

TOTAL 37.78 (9.97) 36.04 (11.99)

Norms TMT A (Tombaugh, 2003)

Age 55-59 Age 60-64 Age 65-69 Age70-74

31.72 (10.14) 31.32 (6.96) 33.84 (6.69) 40.13 (14.48)

All scores for Part A follow normal distribution; Inexperienced {55-65}, D(14)=0.182,


D(15)=0.201, p=0.105 and experienced {66-75}, D(18)=0.171, p=0.172. Further analysis

shows no significant effects.

Part B has outliers, both in the experienced {55-65} and {66-75} group, scoring 150,

respectively 181.5 seconds. Even when considering triple SD from the norms given for each

age category, the scores are abnormal. Descriptive data is given without the of the two

participants. An analysis with and without the outliers show no significant results. In a next

step, three more participants, who scored above 110, are excluded to see whether there is a

significant main effect of age or experience on the performance.

Descriptive statistic and norms are provided of the Part A of the TMT for all four groups. Total lists the mean scores

and standard deviation for inexperienced and experienced participants, irrespective of their age.


Fig. 10 2x2 ANOVA results for DSCT


30

Table 17 Means with standard deviations and norms for TMT B

TMT B


55-65 (n=14) 66-75 (n=11) 55-65 (n=14) 66-75 (n=17)

Min 43.1 35.2 30.3 40

Max 114.2 113.0 111.0 93.0

Mean (SD) 66.66 (19.72) 65.91 (20.31) 56.68 (21.84) 66.67 (13.68)

TOTAL 66.32 (19.55) 62.16 (18.22)

Norms TMT B (Tombaugh, 2003)

Age 50-59 Age 60-64 Age 65-69 Age 70-74

68.74 (21.02) 64.59 (18.59) 67.12 (9.31) 86.27 (24.07)

Without the outliers, all groups are normally distributed: Inexperienced {55-65}, D(13)=0.163,


D(12)=0.150, p=0.200 and experienced {66-75}, D(17)=0.163, p=0.200. Further analysis

shows the following effects:

Part B of the TMT (Fig.11) shows a significant interaction, but in this case, it is the younger

volunteers who benefit from the level of experience. There is no significant main effect of

experience F(1,49)=0.958, p=0.333 or age F(1,49)=0.963, p=0.331. However, the amount of

experience significantly interacts with age between the two age groups, F(1,49)=6.150,

p=0.032.

Descriptive statistic and norms are provided of the Part B of the TMT for all four groups. Total lists the mean

scores and standard deviation for inexperienced and experienced participants, irrespective of their age.


Fig. 12 2x2 ANOVA results for TMT Part B


31

4. Discussion

4.1. The Volunteers' Performance Compared to Published Norms

When Nelson and Willison (1991) restandardized their NART norms, they used a sample

of 182 participants from various social classes. Their mean score of errors was 18.8 (11.7)

which set the norm at 7-30 incorrectly read words. Converting the NART error score to

WAIS-R IQs predicts a Full Scale IQ of 107.4 (17.1) (Nelson & Willison, 1991). The

inexperienced and experienced volunteers of this study scored 5.88 (3.79), respectively 4.94

(3.21). This converts into Full Scale IQs ranging between 118 and 129, with the experienced

groups starting at a slightly higher IQ of 121. One of the shortcomings of NART is that it has

difficulties predicting higher IQs than 131, which is the maximum IQ that can be calculated

from a 0 error score (Nelson & Willison, 1991). Three of the participants in this study had

perfect scores and could very well have higher IQs than 131. Two conclusions can be drawn

from these results:

One is that the NART might be in need of another restandardization. IQ test scores, while

relatively stable within one generation, have been rising over time. This is often attributed to

the "Flynn effect". In the late 1980s, James R. Flynn collected various IQ tests from all over

the world to see how IQ scores changed during the 20th century. He published his study in

1987 and although it is still not quite clear what exactly causes IQs to change, the article led

to restandardizations of many tests, such as the NART in 1991 (Flynn, 1987; Deary & Batty,

2007). However, this has been almost 25 years ago and while WAIS is currently in its IV

edition, no new norms are provided for NART.

The second conclusion is that the volunteers from the University of Edinburgh's research

panel indeed have higher IQs than the average general public. Deviations from the norms on

the following tests further support this conclusion.

The norm for the GNT is 20.41 (4.1), ranging between 16.41 and 24.51 (Warrington, 1997).

The minimum scores of the volunteers, however, already start on 22 and reach maximum

scores of 30. Almost the same can be said about the DSCT scores. Throughout the groups

there is a tendency to start in the mid to higher ranges of the norms and go beyond them,

transcribing up to 30 more symbols within 120 seconds than norm and SD provided by

Wechsler (1997) suggest.

The ROCFT Immediate and Delayed Recall depict an even clearer picture. While the norms

for both parts are set around 15 (5), averaging between 10 and 20 points, the experienced

group has a mean of approximately 21 (6) and the inexperienced of 19 (7), scoring up to 7


32

points more than what the normative data predicts (Fastenau et al., 1999).

Although the volunteers seem to perform better than the published norms, indicating that

they are not truly representing the "normal" population, not all the tests reflect this as clearly.

Little difference can be seen between the volunteers' scores and the norms for ACE (Hsieh et

al., 2013, Mioshi et al., 2006), TMT Part A and B (Tombaugh, 2003) or TEA (Robertson et al.,

1996). On the ADASCog, the inexperienced and experienced volunteers scored similar to the

norms, but individuals, especially in the {66-75}groups made almost twice as many errors

than what constitutes as normal according to Graham et al. (2004).

One possible explanation for the discrepancy could be that the published norms of these

studies are also based on volunteer panels and might be biased for similar reasons investigated

in this study. Graham et al. (2004) recruited their participants from a registry of normal senior

volunteers (Graham et al., 2004). Hsieh et al. (2013) do not clarify how they recruited their

controls. Mioshi et al. (2006) recruited theirs from the volunteer panel at the Medical

Research Council where the study was conducted and they were all family members of the

patient group (Misohi et al., 2006). For his normative study on the TMT, Tombaugh (2003)

reused individuals who participated in a series of experiments investigating age effects on

visual and verbal memory, as well as processing speed (Tombaugh, 2003). These volunteers

were repeatedly tested on exactly what the TMT A and B assesses. Robertson et al. (1996)

state that it was difficult to find volunteers whose IQ was below 100. Furthermore, practice

effect was discovered when the participants were repeatedly presented with the same version

of TEA and they suggest one should use alternative forms of the test (Robertson, et al., 1996).

In these four tests, all the normative data is based on control groups that were highly

experienced, either due to repeated testing or familiarity with the procedures. If the hypothesis

that experience has a positive effect on cognitive abilities holds true, there could have been

bias in all of these studies. The results of the analyses conducted on the eight tests shed light

onto what affects performance within the panel and how experience can improve cognitive

abilities.

4.2. Effects of Age, Experience and Interaction

Age is one of the key factors of cognitive decline across an adult's lifespan. For some

domains, decline already starts in the mid to late twenties. This especially holds true for

processing speed, executive functions and memory, namely the ability to encode information

into episodic memory, (Heden & Gabrieli, 2004; Deary, et al., 2009, Schaie, 1996). Other

domains, such as language and verbal abilities, remain relatively stable and only start to


33

decline at later stages in life, (Schaie, 1996; Heden & Gabrieli, 2004). One would therefore

expect significant age effects on tests assessing the domains processing speed, executive

functions, attention, memory and possibly visuospatial processing, whereas IQ and language

domains should not show much of a difference between the two age groups. While the results

support this to a degree, not all domains react to age the way it is expected and the impact of

experience on performance should not be underestimated.

4.2.1. IQ and Language

The NART, which is used to determine pre-morbid IQ and is supposed to be resistant to

age-associated decline and impairment, proves to be reliable and shows no significant

difference between the four groups. Neither do the language subcategories of the ADASCog

and ACE-III. There are no significant main effects for age or experience, supporting the idea

that language abilities remain relatively stable at an older age. However, ADASCog and ACE

are designed to assess cognitive impairment and the tasks normally do not pose much of a

challenge for healthy adults. Therefore, results often show ceiling effects.

When investigating language, the GNT is the most meaningful test in this study, since it is

used to detect word finding difficulties and includes objects that are not quite as commonly

known as the ones in ACE. Somewhat surprisingly, the results show a main effect for age

F(1,54)=4.549, p=0.038. It only accounts for about 7.8% of the differences in scores, but a

clear decline with age can be seen in both inexperienced and experienced older groups. While

the level of experience does not influence performance, age has an impact on naming abilities

and increases word finding difficulties.

4.2.2. Attention

Further expected decline due to age can be seen in attention. Sustaining attention, tested

with the TEA 2, is no problem for the healthy volunteers used in this study and they all scored

maximum points on this task. TEA 3 is used to assess the ability to switch attention, focusing

on one tone and ignoring another. Here, age has a significant main effect on the two groups

with F(1,54)=6.822, p=0.012. The performance of the {66-75} groups declines by

approximately 2 points. Although both the experienced {55-65} and {66-75} groups score

slightly better than the inexperienced ones, this does not reach significance. The results of

TEA 5, which is also testing attention, are not significant. A reason for this could be that the

task is more complex than TEA 3, and the level of performance also depends on a number of

other factors, such as knowing more than one language or mathematical skills.


34

An age-associated regression can also be noticed in the ACE subcategory Attention. It does

not quite reach significance, with F(1,54)=3.679, p=0.060, but this could be due to the fact

that the subcategories of ACE-III, similar to ADASCog, primarily assess simple tasks, such as

counting 7 away from 100 or stating dates and weekdays. The variance in scores of healthy

adults is therefore only minimal. This is also reflected in the ACE Total score which shows

that age has some effect, both inexperienced and experienced {66-75} groups scoring slightly

lower than the {55-65} groups, but it is not significant, with F(1,54)=3.153, p=0.081. There is

no main effect of experience or interaction in any of the tests assessing attention. Repeatedly

taking part in neuropsychological experiments does not seem to improve attention abilities.

4.2.2. Memory

Memory is a domain which should show clear age-associated decline. While most of the

tests indeed have significant effects of age, the level of experience plays a crucial role in the

{66-75} groups. On the ADASCog Total score, age has a significant main effect of

F(1,54)=10.732, p=0.002. Both inexperienced and experienced volunteers make more errors

in the {66-75} group than in the {55-65} group. However, the increase of errors is more

substantial in the inexperienced group, rising from 3.08 (2.14) to 7.79 (3.40), than in the

experienced group, which starts with a slightly higher error score of 4.92 (2.30), but only rises

up to 5.57 (3.09). Although experience by itself has no meaningful main effect, the interaction

between experience and age is significant with F(1,54)=6.149, p=0.016. The age-associated

decline is greater in the inexperienced group which score increases by 6 points on average.

The experienced group, on the other hand, almost remains the same, increasing by about 1

error. It is therefore possible to say that even though there is little difference between the two

younger groups, a higher level of experience can cause the age decline to stagnate.

The results of the ADASCog Total are mostly due to the ADASCog Memory subcategory,

since language, attention and executive function subcategories all show ceiling effects, with

only little variances. The ADAS Memory category, on the other hand, comprising of word

recall, delayed recall, recognition and instructions, shows an almost identical pattern to the

ADAS Total score. Although interaction does not quite reach significance, with

F(1,54)=3.537, p=0.065, a clear trend can be seen that the level of experience decreases the

magnitude of impact age has on memory.

A similar result can be seen on the ROCFT Immediate and Delayed Recall. Both tests are

used to assess visual memory and the analysis shows that experience significantly interacts

with age on the immediate recall task, with F(1,54)=6.150, p=0.016 and the delayed recall


35

task, with F(1,54)=5.666, p=0.021. Although neither age nor experience by itself has a

significant effect, together, they show a most interesting picture. On both tests, the

inexperienced {55-65} group scores on average only 2 points better than the experienced {55-

65} group. The groups do not differ much at this stage. However, the inexperienced group

declines with age and the {66-75} year-olds' mean score is down from approximately 20.68

(5.43) to 16.45 (8.8). Contrary to this, the experienced {66-75} group increases their scores

from an average of 18.61 (5.83) to 22.68 (5.78). Instead of declining with age, like the

inexperienced group does, the experienced group is actually getting better. A higher level of

experience, therefore, significantly increases the visual memory abilities of the {66-75} group.

It can be concluded that frequently taking part in neuropsychological studies and experiments

has a positive effect on memory abilities.

4.2.4. Executive Functions

Experience does have a main effect, independently of age, on the cognitive domain of

executive functions which is utilized in problem solving, planning and task flexibility (Kipps

& Hodges, 2005). The ACE Fluency subcategory is the only one of the ACE-III subtests that

reaches a significant result for experience, with F(1,54)=7.689, p=0.008. It tests verbal

fluency and participants have to list words starting with one particular letter, and name as

many animals as possible, while being under time pressure. Both younger and older

experienced groups perform significantly better on this task than the inexperienced groups.

Furthermore, the test uses a cut-off and gives maximum scores to subjects listing more than

18 words and 22 animals. Many participants, however, were able to go beyond these limits

and it is possible that the difference between the experienced and inexperienced groups would

be even more significant.

Part B of the TMT is also used to assess executive functions. Participants have to switch

between letters and numbers, trying to connect them in an ascending order as quickly as

possible. Results show that there is a significant interaction between experience and age, with

F(1,49)=6.150, p=0.032. The scores are almost identical between the inexperienced and

experienced {66-75} groups. The {55-65} groups, however, differ by more than 10 seconds

from each other, with the experienced being faster than the inexperienced. It can be concluded

that a high level of experience has a positive effect on the performance of the {55-65} group,

but the advantage disappears in the {66-75} group.

Executive functions are known to decline with age, yet there is no main effect for age on

TMT Part B. The inexperienced groups remain on approximately 66 seconds with a SD of ca.


36

20. It is only the experienced groups that decline slightly with age. It is possible that

frequently participating in experiments only has a positive impact on executive functions up

to a certain age, after which the age-associated decline sets in more prominently.

4.2.5. Processing Speed and Visuospatial Processing

Processing speed should also be affected by age. The tests used to assess this domain, such

as the TMT A and B or the DSCT, however, show no significant results in this study. The

DSCT does indicate a strong trend that age has an impact on performance, with age

F(1,53)=3.784, p=0.057, but one would have suspected a more prominent result. Reasons for

this could be that both tests also rely on visuospatial abilities and neither the ROCFT nor any

of the ADAS and ACE subcategories showed significant results for this domain. This could

mean that visuospatial abilities are not as much affected by age. Another possibility is that the

sample sizes are not extensive enough to reach significance.

5. Conclusion

Overall, volunteers from the University of Edinburgh's research panel seem to perform

better than what normative data suggest, indicating that panels are not always good

representatives of the general public. Within the panel, the experienced volunteers performed

better than the inexperienced. Not all the results reached significance, however, further

research with larger samples could rectify this. The level of experience does have a

meaningful impact on memory and executive functions. Frequently taking part in

neuropsychological experiments improves memory abilities, especially at the later age of 66

to 75. Executive functions are clearly better at a younger age, and in case of verbal fluency,

remain significantly improved even at an older age. This leads to the conclusion that the

experienced volunteers are better, not only due to practice effect and familiarity with the tests,

but also because the repeated exposure to neuropsychological assessments improves their

cognitive abilities. The fact that experienced volunteers perform significantly better on a

number of cognitive assessments has to be considered when using volunteer panels in future.


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Are Normal Controls Still Normal?

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