Original Articles
 

By Dr. Simon B Thompson , Ms. Jenna Gander
Corresponding Author Dr. Simon B Thompson
Psychology Research Centre , Bournemouth University, - United Kingdom BH12 5BB
Submitting Author Dr. Simon B Thompson
Other Authors Ms. Jenna Gander
Psychology Research Centre , Bournemouth University, - United Kingdom BH12 5BB

GERIATRIC MEDICINE

Alzheimers Disease,Benton Visual Retention Test; Correlation, Dementia, Immediate Memory; Intelligence Quotients, Memory, Normative Values, Wechsler, Younger Age Group

Thompson SB, Gander J. Immediate Memory Functioning and Intelligence Quotients of 18-30 Years Age Group Using New Data Derived From the Benton Visual Retention Test: Applicability to Alzheimers Disease Patients. WebmedCentral GERIATRIC MEDICINE 2011;2(3):WMC001652
doi: 10.9754/journal.wmc.2011.001652
No
Submitted on: 01 Mar 2011 03:50:51 PM GMT
Published on: 02 Mar 2011 07:08:49 PM GMT

Abstract


The aim of this study was to create a normative data set of performance scores for the Benton Visual Retention Test (BVRT) for individuals aged between 18 and 30 years. Previously, no normative data existed for BVRT performance for this particular age group.The data collected examined the correlation between cognitive functioning as tested by the Weschler Adult Intelligence Scale III (WAIS III) and BVRT.The Hospital Anxiety and Depression Scale (HADS) was used as a screening process to gain a cognitive profile of the sample population.Fifty participants carried out the BVRT, WAIS III and HADS.The data collected were analysed using the Pearson’s Correlation Co-efficient and results indicated a strong relationship between BVRT performance across all three administrations and full IQ. In addition, strong relationships were identified between Total Correct responses and Total Errors score with Verbal IQ and Performance IQ. However, no significant correlations were found between Anxiety and Depression levels and BVRT performance, this may have been due to 90% of the sample being within a normal, healthy range.These findings suggest IQ levels are a strong indicator for BVRT performance. Furthermore, the development of a new set of normative data for the 18-30 year old age group, will allow the use of the BVRT as a clinical instrument to assess brain damaged and diseased individuals more accurately, particularly those diagnosed with Alzheimer’s disease. 

Introduction


Individuals may suffer from impaired cognition as a result of brain injury or brain disease. This could result in the skills and abilities the individual had prior to injury or disease onset, being significantly damaged or completely lost. Brain injury or disease can affect any part of the brain and the impairment can be displayed in any cognitive skills such as attention, communication, visual perception, and memory. Over 1.4 million people per year, sustain brain injury and one of the most common age groups at risk are 15-19 year olds. Brain disease affects a considerably larger percentage of the population e.g. Alzheimer’s alone exceeding 3 million each year (Fay, 2010) and Parkinson affects 12,000 people each year in the UK alone (Parkinson’s disease Society, 2010).
Most research investigating brain damage and disease has attempted to measure the extent of impairment on the individual’s cognitive abilities. The Benton Visual Retention Test (BVRT) developed by Arthur L. Benton (Benton Sivan, 1992) is a widely used instrument, assessing individual’s visual perception, visual memory and visuo-constructive abilities, for this reason it is highly valued in clinical settings (Thompson, Ennis, Coffin & Farman, 2007; Thompson, 2011). Lezak (1983) and many other neuropsychologists through time often use figure drawings to assess people's deficits because of their sensitivity in detecting many types of cognitive impairments and diseases. This is the main strength of the BVRT. The BVRT has been used to assess brain disorders such as Attention-deficit hyperactivity disorder (ADHD), Alzheimer’s disease, stroke patients, Bipolar disorder, Schizophrenia and many others. Marsh and Hirsch (2006) looked at the effectiveness of different neuropsychological tests and showed the BVRT to be significantly more effective in detecting defective visual retention. They further recommend that it is highly valuable for evaluating brain damaged or diseased patients.
Tasks which are visual memory and visuo-spatial in nature have often been included in many intelligence scales (Binet & Simon, 1908). However, these subtests were not an adequate measure of any specific visual-memory or visuo-spatial abilities and so Arthur L. Benton designed his first edition of the BVRT (Benton, 1946). Since then revisions and improvements have been made and the BVRT is currently in its Fifth Edition (Benton Sivan, 1992).
There are many ways of detecting brain damage and disease e.g. Tomography (fMRI, PET, CAT) is a technique using gamma rays, ultrasound or x-rays to obtain detailed images of areas inside the body. Whilst these tests are effective in detecting physical damage, they cannot measure the amount of memory loss or capacity to sustain attention. Neuropsychological instruments have proven far more useful in determining an individual’s cognitive function. Neuropsychological tests, such as the BVRT, are used to analyse and interpret the individual’s responses to cognitive based tasks and compare performance to normative data. The results of these tests allow the psychologist to make inferences about what the individual is able to do within his or her environment, by assessing their performance on the specific tasks relative to how a cohort of healthy people within the same age range performed on the same set of tasks. By identifying brain-behaviour relationships, treatments can be tailored to focus on the individual’s particular strengths to compensate for their limitations in cognitive functioning.
In clinical settings the BVRT is often used as an instrument to determine cognitive function in the older population that are more susceptible to brain diseases such as Alzheimer’s and Parkinson’s disease. Whereas, in educational fields the main focus of the test has been to asses learning difficulties and attention disorders such as ADHD in young children up to early/mid teens. Currently there is a lack of research assessing cognitive function in late teens and young adults, or the data needs updating (eg Benton, Eslinger & Damasio, 1981). The existing normative data are based on children aged up to 15 and adults over the age of 30. The importance of the BVRT remains highly valued and it is important to have normative data to demonstrate the performance of individuals within this age group, thus providing a base line comparison for patients that may suffer from brain injury or disease that affects their cognitive function (Thompson, 2002). Existing normative data are based upon correlations with IQ levels as this has been identified as a key factor in BVRT performance (Arenberg, 1978; Le Carret, Rainville, Lechevallier, Lafont, Letenneur & Fabrigoule. 2003; Emdad & Sondgaard, 2006).
Cognitive decline in older populations
Significant correlations between performance and chronological age have been identified, and in early detection of brain disease such as Alzheimer’s concerning the older population. Arenberg (1978) studied males that had received a high level of education with a good economic status, and found a gradual decline in BVRT performance from 20-80 years of age, and an increased rate of number of errors when completing the tasks from 60-70 and 70-80 years of age. However as noted previously, research has indicated significant correlations between intelligence and BVRT performance, and so these findings may only be representative of individuals with advanced levels of education. The research of Seo and colleagues (2007), offered further support to these findings. They looked at the BVRT performance of an educationally diverse elderly population on the BVRT and found that both age and education play a role in non-verbal memory and reconstructive abilities. Both older age and lower educational levels related to poorer performance on the BVRT. Poitrenaud and Clement (1965) carried out a similar study on a culturally diverse population; the findings support those of Seo and colleagues (2007).
The BVRT Manual (fifth edition) provides normative data which demonstrates a significant relationship between chronological age and BVRT performance; a progressive increase from 8 to 15 years of age (Benton Sivan, 1992). Performance begins to progressively decline through the fifties; a drop of about 1 point in mean number of correct score, then a further 2 points in the sixties. Benton concluded that performance on the BVRT declines significantly after the age of 60 years and inter-individual variability correspondingly increases. Various neuropsychologists have researched into what changes occur within the brain that results in cognitive decline. It has been found that it may be as a result of a loss of synapses within circuits of the hippocampus and also a decrease in metabolic activity in the entorhinal cortex which is the major input and output of the hippocampus. Leon (2001) found that in normal individuals, the level of metabolic activity in the entorhinal cortex can predict the amount of cognitive decline over the next 3 years.
Alzheimer’s disease and other brain diseases commonly affecting the older populations have been studied in some depth to understand the contribution of the disease to further impairment of the individual’s cognitive abilities. Alzheimer’s in particular, is characterised by progressive brain deterioration and impaired memory and other mental abilities. An article by Amieva and colleagues (2005) reported a 9 year cognitive decline prior to the onset of dementia, with significantly low performances on the BVRT even in the early years, which progressively declined further with time. It is however, important to note in longitudinal studies, such as this, other factors that may be responsible for the change need to be taken into account. Thompson, MacDonald and Coates (2001) carried out a study in which they found, using a battery of neuropsychological tests including the BVRT, significant improvement on performance in both visuo-spatial and visual memory tests after 16 weeks of Aricept treatment used to improve the symptoms of Alzheimer’s.
Netherton and colleagues (1989) used the BVRT to study patients with Parkinson’s Disease, these patients showed an increase in figural reproduction errors between test periods spaced six months apart, the control group however showed no increase in errors over this time and fewer errors in general.
Poitrenaud and Barrere (1973) looked at 46 middle aged individuals who had been either referred for neuropsychological testing or who had reported having experienced mental difficulties. The study involved a battery of five tests, one of which was the BVRT. Of the 46 patients, 31 performed normally and 15 performed defectively. Five years later the sample was assessed again. Subsequent testing showed that of the 46, 30 were diagnosed as mentally intact and 16 diagnosed with dementia. Of the 16 patients diagnosed with dementia, 14 were from the original 15 that performed badly. The Rey Auditory-Verbal Learning Test, another of the other five battery tests, and the BVRT accounted for 93% of the correct prediction rate and individually showing 85% predictive accuracy.
Brain damage and disease in younger populations
Disorders of a visuo-spatial nature are particularly prevalent after damage to the posterior parietal lobe, such as unilateral neglect. Balint’s syndrome and constructional apraxia patients often have similar lesions within this region. Vilkki (1989) studied brain damaged patients with lesions to the anterior and posterior areas of the brain. He showed subjects with anterior lesions made significantly more perseveration errors (figure in previous design replicated in reconstruction of following design) than subjects with posterior lesions, with both left and right hemispheres of the brain. Petris (1981) compared performance on the BVRT of brain damaged patients to control patients. Patients with brain disease produced a higher average percentage of omission errors (28%) - single figure of a design being completely omitted or no recognisable attempt was made to reconstruct the figure - than the control group (14%), and higher frequency of size errors (2.7% vs. 0.3%) (Reconstruction wrongly sized), yet made less perseveration errors than the control group (33% vs. 42%). Benton Sivan (1992) concluded that omission errors and size errors are particularly prominent in patients with cerebral disease. Damage located toward the front of the brain tends to result in the most severe problems associated with attention and concentration, which could explain the omission and size errors found.
The BVRT has been used in adults and younger individuals that have suffered from strokes and post-traumatic stress. By using the BVRT they have found a cognitive decline due to the impact of trauma on hippocampal functioning, which affects memory. Emdad and Sondegaard (2006) studied Post Traumatic Stress Disorder (PTSD) patients by assessing intelligence levels using the Raven Standard Progression Matrices (RSPM) (see Thompson, 2000; 2001; 2006; 2010), and visual memories using the BVRT. In comparison to the control group, the PSTD patients demonstrated a strong negative correlation between the BVRT and RSPM. PSTD patients showed poor short term, non-verbal memory, and these deficits were related to individual’s intelligence. However the same results were not found in the control group, where comparable differences in RSPM score showed no significant relationship to performance on the BVRT.
In the younger population, the use of the BVRT in assessing learning difficulties in children and young adults has been extremely important in the improvement of their abilities and assessing their progress. Dige and Maarh (2008) studied patients with different levels of ADHD. Using the BVRT, they were able to show ADHD patients performed considerably poorer in such tests, and the more severe the case of ADHD the higher the amount of errors.
Park (2008) looked at Schizophrenic patients and the nature of visual recall and recognition through the use of the BVRT, she found that patient’s performance was widely variable in visual memory and there was no significant difference between recall and recognition. From looking at research into the affects of these brain diseases and the use of the BVRT as a clinical instrument, it is clear to understand its value in this field. The BVRT appears to tap into a unique combination of skills that are characterised by both short-term memory and psychomotor abilities. The BVRT not only records where errors are made in responses, but also the different types of errors being made, this allows for assessment of qualitative as well as quantitative patterns to facilitate more comprehensive interpretation. For example Robinson-Whelen (1992) reported a significant difference between controls and patients with mild to moderate levels of dementia, specifically in the number of omission errors that were made. Baum, Edwards, Yonan and Storandt (1996) also found specific associations between test errors and Alzheimer’s patients.
Affects of mood disorders on cognition
Anxiety and Depression are known disorders that can impact performance on many cognitive based tasks (Eysenck, 1997, p.8). Such that if individuals are feeling anxious or depressed this may significantly affect their performance. Anxiety suggests that individuals may be tense, restless and have trouble concentrating on the current task at hand. Similar symptoms may be found in individuals that are depressed; fatigue, difficulty concentrating and lack of motivation will affect performance and so how they perform on a given task will not be an accurate measure of how they would usually perform had they been in a calm, relaxed, healthy state. Especially in medical practice, it is very important to ensure that possible mood disorders such as depression and anxiety are not influencing a patient’s performance.
Weems and colleagues (2007) found certain cognitive errors demonstrated specific associations with anxiety symptoms. Findings from Ellis and colleagues (2008) further support this, and showed mild anxiety was associated with better cognition, where more severe anxiety was associated with worse cognition.
Several studies have indicated that sufferers of severe depression may experience impairment in motivation, attention, and concentration. This is related to poor BVRT performance, however not as significantly as such illnesses as Dementia (Crookes & McDonald, 1972; Birch & Davidson, 2007). Research into the effects of less severe levels of Depression is yet to be completed and therefore the current findings are inconclusive.
Intelligence and cognitive abilities
In a vast amount of research on cognitive abilities a major factor has been intelligence. As educational levels increase so does performance on tests such as the BVRT, and so higher IQ scores suggest better cognitive skills. In the early 19th century, the concept of intelligence was widely debated. David Wechsler viewed intelligence as a multidimensional response construct, one that manifests itself in many forms, not only as a global entity, but as a collection of specific abilities. Weschler concluded that intelligence is the ‘’capacity of the individual to act purposefully, to think rationally and deal effectively with his environment’’ (Weschler, 2002).
Le Carret and colleagues (2003) carried out research into how educational levels influence visual working memory using the BVRT on elderly individuals. They found that higher levels of intelligence resulted in better performance but as a result of better executive abilities rather than visual discrimination skills. They concluded that higher levels of education meant individuals were able to use more efficient strategies.
The Normative standard section of the BVRT states that performance on all three administrations for the three forms correlates substantially with intelligence level (Benton Sivan, 1992). Correlation coefficients for the stated age groups claim to average from 0.46 to 0.71. All published normative data collected and explained in the manual are described on the basis of the relationships between intellectual level and chronological age with BVRT performance.

Method


Rationale
The aim of this study is to gain a set of normative data for performance on the BVRT for individuals aged between 18 and 30 years of age. Currently no normative data exists for BVRT performance for this particular age group. The BVRT is an essential instrument in clinical research when studying patients with brain disease or brain damage. However, for an accurate assessment of an individual’s BVRT performance, a set of normative data for that specific age range for comparison must exist. Furthermore, this study aims to look at the correlation between cognitive functioning (as tested by the WAIS III and IQ’s) and BVRT scores for this age group, to determine if a significant relationship exists between IQ and BVRT performance as has been observed in other age groups previously studied.
Materials
Benton Visual Retention Test
Benton designed his first edition of the BVRT in 1946 (Benton, 1946). After reviewing limitations and weaknesses, reviews have been made, a first revision was made in 1955 (Benton, 1955), and further revisions in 1963 (Benton, 1963) and 1974 (Benton, 1974). Each time, a new set of normative data have been produced for various age groups. Each revision has enhanced the use of the BVRT in clinical practice and research.
The BVRT has 3 similar forms of task C, D and E, each consisting of 10 designs containing one or more figures. There are 4 methods of administration A, B, C and D. Clinical investigators have devised novel administrations of the BVRT to answer specific research questions. For the purpose of this study, administrations A, B and D will be used to see how healthy 18 – 30 year olds perform with time constrictions and delays outlined below.
Administration A – Participant views each design for 10 seconds and then immediately reproduces the design from memory.
Administration B – (serves as a comparison for the amount of time needed to process each stimulus). Participant views each design for 5 seconds and immediately reproduces the design form memory.
Administration D – (requires examinees to retain the percept for a brief period of time). Participant views each design for 10 seconds, after a delay of 15 seconds, is then asked to reproduce design from memory.
WAIS III
David Wechsler designed the first edition of the Weschler Adult Intelligence Scale in 1939 (Weschler, 1939). Weschler observed certain attributes which can account for the overall variance of intelligence; these include basic human motivations, attitudes and personality traits, such as persistence, goal awareness and enthusiasm. The WAIS reflects an individual’s overall ability, where the subtests look at such skills as abstract reasoning, perceptual skills, verbal skills and speed processes. Since 1939, revisions have been made, to allow for changes in social and culture era, the WAIS is now in its third edition (Weschler, 2002).
The Wechsler Adult Intelligence Scale consists of 14 subtests. When restricted by time, it is possible to follow the short form WAIS III, which still remains far superior to many other intelligence scales available (Weschler, 2002). For the purpose of this study the short form of WAIS III will be used. The scoring process involves the conversion of raw scores into scaled scores which provide 3 levels of IQ; Performance IQ, Verbal IQ and Full Scale IQ.
Hospital Anxiety and Depression Scale
The HADS is a self screening questionnaire first designed in 1983 by Snaith and Zigmond, based on an item analysis of a longer list of items given to patients attending an out-patient clinic (Snaith & Zigmond, 1983). The Anxiety scale was based on ‘feelings of tension’, ‘tendency to unnecessarily worry’ and ‘apprehensive anticipation’. The Depression Scale was based on ‘enjoyment of usual activities’, ‘retention of a sense of humour’, ‘depressed mood’ and ‘optimistic attitude’.
The HADS is a Questionnaire consisting of 14 questions, 7 for anxiety and 7 for depression, each scoring 0-3 points per item. In this study the HADS is used as a screening technique in order to gain a cognitive profile of the sample population. For this reason the aim is to use participants that score at either a normal (0-7), mild (7-10) or moderate (11-14) level for both Anxiety and Depression. A score of 15 or higher suggests possible presence of a mood disorder which may interfere with the rest of the study.
Experimental hypotheses
Based on existing research the hypotheses for this study include:
H1 There will be a significant relationship between Full IQ and Total Errors score and Total Correct responses on the BVRT.
H2 There will be a significant relationship between Full IQ and Total Errors score and Total Correct responses across the three administrations A, B and D.
H3 Both Performance IQ and Verbal IQ will be significantly correlated with Total Errors score and Total Correct responses.
H4 There will be a significant relationship between Total Errors Score and Total Correct responses and Anxiety and Depression score on the HADS.
Study design
This study will look at the interactions between Performance on the BVRT and IQ Levels. A Pearson product-moment correlation coefficient was used to analyse the relationship between Total Errors score, and Total Correct responses under the 3 administrations A,B and D of the BVRT, together with:
Full IQ
Performance IQ
Verbal IQ
A Pearson product-moment correlation coefficient analysed the relationship between Total Errors score, and Total Correct responses under the 3 administrations of the BVRT (A, B and D) and Depression and Anxiety scores on the HADS.
In order to determine if age or gender had any significant influence on the data collected, a 3 x 2 unrelated ANOVA was implemented to investigate a significant difference in performance on the BVRT between genders and age groups. The first Independent variable (IV) was gender, which had two levels; Males and Females. The second independent variable was age group, and was split into 3 levels; 18-20 (mode = 19, median = 19), 21-23 (mode = 21, median = 21) and 24-27 (mode = 26, median = 26). The dependent variables were Total Errors score and Total Correct responses.
Participants
A sample of 50 undergraduate Bournemouth University students took part in the study; they were recruited on a volunteer basis. 14 male and 36 female first, second and third year students took part in the study. The age range was between 18-30 years old, with the mean age being 22. The sample was recruited via emails to students, and through the university study program SONA, this allows first and second year students to view the available studies in which they can participate with the incentive of gaining research experience which is mandatory for their university course. All participants were British Citizens living in the United Kingdom with English as their first language. All participants came from similar socio-economic and educational backgrounds. All participants were psychologically assessed using the HADS self-screening questionnaire to ensure they were within the healthy range.
Procedure
Prior to the commencement of the study, ethics approval was obtained from the Bournemouth University Research & Ethics Committee (11.11.2009) to clarify that the study adhered to all ethical guidelines. Two computer laboratories at Bournemouth University were booked for 10 sessions, participants were seen for 2 hour sessions over a period of 2 weeks; two sessions each Monday, one on each Tuesday, one on each Wednesday and one on each Thursday. Five Participants took part in each session allowing for confounding variables to be controlled and for the efficiency of the running of the experiment within the time allocated. Each participant entered the 1st Lab and sat at individual desks separated by partitions to ensure there were no interactions between participants. In front of each participant was a study information sheet, participant information sheet, consent Form, HADS questionnaire, WAIS response booklet and 3 BVRT response booklets.
On commencement of the study the experimenter explained in full what the study involved, the order in which it would be carried out and the aim of the research. Participants were asked to read the study information sheet, and given the opportunity to ask any questions or to withdraw themselves from the study. Once everything was made clear, participants were asked to fill in the Participant Information sheet and read and sign the Consent Form. When all forms were completed, they were then asked to turn to the HADS Questionnaire. The experimenter instructed participants to read each statement and report their immediate response to each item without spending too much time making long thought-out replies. All completed forms were then collected and the first test was ready to be administered.
The BVRT was displayed on the projector screen at the front of the lab. The procedure and requirements of the test were explained using the standardised explanation for each administration. The participants completed the three administrations which were timed using a stopwatch by the experimenter. Once the BVRT was completed the three response booklets were then collected in.
The WAIS III Short Form Administration was then explained to the participants using the standardised explanation in the WAIS III Administration Manual. Eight subtests were carried out en masse to participants, the two remaining subtests required one on one examination and each participant was called into the second lab one at a time to carry them out.
Once all participants had completed all tests, they were fully debriefed on every aspect of the study and again offered the opportunity to ask any questions or withdraw themselves and any information they had given from the study. They were also informed that results were available for collection from the researchers.


Results


Statistics
50 participants took part in the study; their full IQ’s ranged from 90 to 155 with an average of 118 and standard deviation of 16.1. The average of Total Correct responses (on all 3 administrations) were 20.34 with a standard deviation of 4.36, the average total number of errors made was 16.80, with a standard deviation of 9.98. The average score of the HADS was 3.94 for Depression with a standard deviation of 3.59 and 3.88 for Anxiety with a standard deviation of 3.22. SPSS 18 was used for statistical analysis of the data (Illustrations 1 - 4).
Hypothesis 1
A Pearson product-moment correlation coefficient was computed to assess the relationship between Full IQ and Total Errors score and Total Correct responses on the BVRT (Illustration 4). There was a significant correlation between Full IQ and Total Correct responses, r = 0.001, n = 50, p = 0.440. There was a significant correlation between Full IQ and Total of Errors Score, r = 0.000, n = 50, p = - 0.484. Both Variables; Total Correct responses and Total Errors Score demonstrate a strong relationship which is significant at a level of p
The scatter plot demonstrates a steep decline in the Total Errors score as individual’s Full IQ increases, illustrating a strong negative correlation. Also, a few anomalies can be seen within the error scores, 7 participants error scores appear to be significantly larger compared to the rest of the data group. The Total Correct responses incline at a milder rate as Full IQ increases and remain more consistent; a strong positive correlation is clearly demonstrated.
Hypothesis 2
A Pearson product-moment correlation coefficient was computed to assess the relationship between Full IQ and Total Errors score and Total Correct responses across the three administrations A, B and D:
There was a significant correlation between Full IQ and Error score Administration A (mean = 5.06), r = 0.006, n = 50, p = -.384
Error score Administration B (mean = 7.00), r = 0.003, n = 50, p = -.411
Error score Administration D (mean = 4.74), r = 0.009, n = 50, p = -.364
Correct responses Administration D (mean = 7.36), r = 0.005, n = 50, p = .391
These relationships are significant at a level of p
Correct responses Administration A (mean = 7.14), r = 0.032, n = 50, p = .303
Correct responses Administration B (mean = 5.84), r = 0.026, n = 50, p = .315
These correlations are significant at a p
A scatter plot summarises these results (Illustration 5). Illustration 6 demonstrates the spread of correct responses across the 3 administrations. It is clear that for administrations A, B and D, correct responses are significantly positively correlated with Full IQ scores. Similarly, Illustration 7 demonstrates how administrations A, B and D error scores are significantly negatively correlated with Full IQ.
Hypothesis 3
A Pearson product-moment correlation coefficient was computed to assess the relationship between both Performance IQ and Verbal IQ and Total Errors score and Total Correct responses. Performance IQ was significantly correlated with Total Correct responses, r = 0.001, n = 50, p = .457. Performance IQ was also significantly correlated with Total Errors score, r = 0.001, n = 50, p = -.464. Verbal IQ was also significantly correlated with Totals r of Errors score, r = 0.003, n = 50, p = -.417. These relationships are significant at a level of p
In Illustration 8, the relationships are demonstrated further through the gradient of the regression lines. Again the spread of Total Correct responses is more evenly spread in comparison to Total Error scores for both VIQ and PIQ. For PIQ the regression lines appear more closely related (Illustration 8).
Hypothesis 4
A Pearson product-moment correlation coefficient was computed to assess the relationship between Anxiety and Depression scores on the HADS and Total Correct responses, and Total Errors score on the BVRT. No significant correlations were found between Anxiety and Correct response score, r = 0.434, n = 50, p = -0.113, or between Anxiety and Errors score, r = 0.435, n = 50, p = .113. No significant correlations were found between Depression and Total Correct responses, r = 0.112, n = 50, p = 0.228, or between Depression and Total Errors score, r = 0.116, n = 50, p = -.255.
3 x 2 unrelated ANOVA for gender and age
A 3 x 2 unrelated ANOVA was carried out to identify any significant effects age and gender had on correct responses. The first IV was Age, there were 3 levels; 18-20 (mean correct responses = 19.32), 21-23 (21.33) and 24-27 (21.4). The second IV was Gender which had 2 levels; male (22.21) and female (19.61). The main affects for Gender and Age were not significant.
A 3 x 2 unrelated ANOVA was carried out to identify any significant effects age and gender had on number of errors made. The first IV was Age, there were 3 levels; 18-20 (mean error score = 18.84), 21-23 (15.06) and 24-27 (14.30). The second IV was Gender which had 2 levels; male (11.78) and female (18.75). The main effects for Age were not significant. However the main effects for Gender were significant; F(1,50) = 4.178, P< 0.05 (P=0.047).
Although a significant difference has been found, the sample collected only represented 14 males compared to 36 females. This questions the validity of these findings, as the sample may not represent a fair number of each gender.
Summary BVRT results
Illustrations 10 - 12, demonstrate the expected BVRT performance scores for 18-30 year old individuals depending on IQ score grouping, for each administration A, B and D). The way in which they are tabularised are based upon how existing Normative data are recorded in the BVRT Manual (Benton Sivan, 1992). Illustration 13 summarises FIQ, Correct and Error scores of the BVRT for each participant.


Discussion


Firstly, the results obtained from the study provide support for Hypothesis 1. There was a significant positive correlation between IQ Score and Total Correct Responses on the BVRT. There was also a significant negative correlation between IQ Score and Total Errors score on the BVRT. By correlating the results of the two tests in a scatter plot (Illustration 6), the strength of relationships of these significant correlations can be further understood. The Linear Regression line for errors shows a steeper decline in comparison to the incline in correct responses, suggesting that there may be a slightly stronger relationship between IQ and errors made than IQ and correct responses. These results strongly suggest that IQ level is in some way related to our visual perception, visual memory and visuo-constructive abilities. A lower IQ suggests that the individual’s ability to perform well in such tests is weaker. Based on this study, Hypothesis 1 was accepted.
Hypothesis 2 predicted that IQ would be significantly correlated with Total Correct responses and Total Errors made across all administrations of the BVRT. The data collected supported this Hypothesis, and positive correlations were found between IQ and Total Correct responses for A, B and D, and negative correlations between IQ and Total Errors score made on A, B and D. Illustrations 6 and 7 help to further understand the relationships identified. From the linear regression lines it is clear that all administrations have strong relationships with IQ Level. For both Errors and Correct Scores the line shows a steeper decline (in errors), and more gentle incline (in correct responses) for administration B. This would suggest that the participants had more difficulty in reconstructing images when they were only able to view the image for 5 seconds prior to drawing it. Statistical analysis revealed that although they were still significant at a level of p
It was expected that both Verbal IQ (VIQ) and Performance IQ (PIQ) would be significantly correlated with the Total Correct responses and Total Errors score on the BVRT. Again, significant correlations were found, both PIQ and VIQ was positively correlated with Total Correct responses, and negatively correlated with the Total Errors made. Illustrations 8 and 9 demonstrate the strength of the relationships through the gradient of the regression lines. Another observation which was very interesting was the mean average of participants VIQ’s (110.2) was much lower than the mean average of participants PIQ’s (127.4).
VIQ is assessed by 7 of the 14 subsections of the WAIS, it is indicative of an individual’s ability to work with abstract symbols, verbal memory skills, and fluency abilities. PIQ is assessed by the other 7 subsections, and is indicative of an individual’s ability to work with concrete situations, to integrate perceptual stimuli with motor responses and visuo-spatial ability. As visuo-spatial ability is also part of what is being assessed in the BVRT, this could explain the strong relationship identified. In clinical settings if PIQ is significantly higher than VIQ, it may be suggestive of a learning disability, autism or mental retardation, they may also have difficulty understanding auditory directions and putting them into practice. In the case of the current study it may be a reflection of their educational backgrounds or degree type. On the basis of these results Hypothesis 3 was accepted.
Finally, the strength of relationship between Anxiety and Depression Scores on the HADS and Total Correct responses and Total Error scores on the BVRT was tested. There were no significant correlations between Anxiety and Depression Scores with performance on the BVRT. Of the 50 participants only 7 were classified as above normal levels of Depression and only 2 above Mild levels. Even less scored above Normal levels of Anxiety, 2 were classified as Mild and 3 Moderate. However, as the HADS was being used to gain a Cognitive Profile of the sample, it was the initial aim to only have participants scoring in low levels of Anxiety and Depression to ensure that this did not interfere with their performance. Of the few that did score slightly above healthy levels, there was no significant effect on their performance on the BVRT. Based on this evidence the Null Hypothesis was retained and the Alternative Hypothesis 4 was rejected.
Although a significant difference was found between males and females performance, the sample collected only represented 14 males compared to 36 females. This may question the validity of these findings, as the sample may not be representative of each gender and so it is not possible to further generalise this to the population.
When looking at the BVRT results it is clear that the most common errors that were made were Distortion Errors, these are inaccurate reproductions of a single figure of a design. On average participants made between 2 to 3 Distortion errors on administrations A and D, for administration B the average was 3-4 errors. The second most common errors were Omission and Addition Errors, an omission error can be classified by a single figure of a Design being completely omitted or no recognisable attempt was made to reconstruct the figure. An Addition Error in contrast would be when an additional figure present in the reconstructed design which could not be scored as a Perseveration or Distortion Error.
On average participants made between 1 and 2 Omission errors for administration A, B and D. Misplacements and Rotations were the next most commonly made errors, Size and Perseverations errors were far less common. Administration B resulted in the least amount of correct responses and the most amounts of errors made. Almost 100 more errors in total for the 50 participants were made in administration B as compared to administration A, and over 100 in comparison to administration D. Of the 50 participants, irrespective of IQ, an average of 7-8 correct scores for both administrations A and D was found as compared to 5-6 for administration B. These findings further indicate that the sample population of 18 to 30 year old individuals struggled most when only viewing the image for a brief period of time, suggesting that to fully absorb an image 5 seconds is not adequate.
By looking at the standard deviation (SD) we can see how the data was distributed across the sample population. The data appears to be equally distributed across Administrations for correct responses, with the largest being 2.02 for administration D. Total Correct responses has a standard deviation of 4.36. For Error scores however the distribution seems more widely spread, for administration A the SD = 3.55, for B = 4.23 and D = 4.73, overall error scores had an SD of 9.98. This suggests that there may be certain factors which influence individual’s susceptibility to errors rather than just the administration of the test. For Total Errors score, participants ranged from 1 (with an IQ of 125) and 41(with an IQ of 95).
During the study significant correlations were identified between Full Scale IQ’s and performance on the BVRT for administrations A, B and D. This adds further support for a vast amount of existing literature on this relationship. Carret and colleagues (2003) carried out a study to investigate how educational levels influence visual working memory using the BVRT on elderly individuals. They found that higher levels of intelligence did result in better performance; these findings coincide with the data collected in the current study, which demonstrates the same findings for a younger age group of 18 to 30 year olds.
Emdad and Sondegaard (2006) looked at intelligence levels and BVRT performance on Post Traumatic Stress Disorder (PTSD) patients. They found that despite comparable differences in levels of intelligence, this had no significant relationship with performance on the BVRT on the control group. However with the PSTD group, they found deficits in short term memory and non-verbal memory, these were directly related to intelligence. Emdad and Sondegaard’s study suggest that intelligence only influences performance if it is related to the specific deficits identified by BVRT performance. Whereas the current study provides convincing evidence to suggest that in healthy 18-30 year olds, significant correlations could be found between IQ and BVRT performance. The participants used in Emdad and Sondegaard’s study were of an older age group and only 20 control participants took part, this might explain the difference in findings.
Ellis and colleagues (2008) found that mild anxiety was associated with better cognition, when severity increased, performance went down. This study found no correlation between anxiety score on the Hospital Anxiety and Depression Scale (HADS) and performance on the BVRT. However, 45 of the 50 participants in the study all scored at a normal healthy level and no participants scored above a moderate level. Therefore it cannot be concluded from this study that Anxiety levels do not influence BVRT performance.
The Normative standards for clinical use of administration A, was based on Benton (1963) looking at over 600 individuals mainly in and out patients of a hospital in Iowa. According to this existing data, an individual aged between 15 and 49 with an IQ of 95-109 should obtain a correct score of 8 on administration A and with an IQ of 110 or higher should obtain a correct score of 9. According to the data collected in the current study, an individual with an IQ score of 110 or above should obtain a correct score of 7 or 8.
Furthermore, the existing data suggests an individual whose IQ is between 90 and 94 will have an error score of 4, from 95 – 104 an error score of 3, 105 – 109 an error score of 2 and 110 and above an error score of 1. The data in the current study has found slightly different margins, an individual whose IQ is 95 or below may have an error score of 10, between 96-110 an error score of 5 or 6, and 111 or higher an error score of between 3 and 5. The slight difference in data could be due to the existing data being quite dated, in current times people may be educated to a higher level which might affect the correct or error scores.
The Normative standards for individuals aged 60 and younger for administration B, according to the manual, are based on performance in administration A, minus 1 point for correct scores. These data were based on the research of Von Kerekjarto (1961). The relation for error scores between the two administrations has not yet been reported. A similar pattern was found in this study, correct scores were on average one point less for each IQ range. What is interesting to observe in the present study is that the number of errors made increases by a larger amount. For individuals whose IQ’s are between 96 and 110, error score is estimated to be 7 or 8 compared to 5 or 6 for A, and 95 and below, is 13 or 14 compared to 10.
Data collected lead to the conclusion that normal adults aged 60 years and younger perform as well in administration D as they do on administration A. Administration D involves a short delay of 15 seconds after viewing an image for 10 seconds, before constructing the design on paper; this meant retaining an image for a brief period of time. This was developed in order to identify participants with brain disease who would perform even normally or mildly defective on other administrations.
Vakil and colleagues (1989) found correlations of 0.54 for correct scores and 0.65 for error scores and so differences in performance, in either direction, may be encountered. Severe impairments in the delay conditions suggest a defect in memory storage capacity; however superior performance has not yet been examined. It may be that the delay condition allows individuals time to fully construct the design in their mind, which would be beneficial for someone who has slowed information processing abilities. As of yet, data collected for administration D has not been adequate for routine clinical use. The present study produced findings that represent a similar pattern to that found in the existing literature, what is interesting to note is a total of 128 Distortion errors for the 50 participants were made in administration A, compared to 107 in administration D. This is a significantly lower sum suggesting the delay resulted in fewer distortion errors, still no other significant differences were found for any other types of errors.
Methodological issues
According to the Handbook of normative data for neuropsychological assessment, (Mitrushina & Boone 2005, p.400) 7 key criteria were deemed to be adequate for evaluating the studies on the BVRT. These include Composition Description and Age Intervals, Educational Levels, IQ levels, Specification of Test Version and Data Reporting, all of which have been clarified and controlled for. The 7th criterion is number of participants. The results of the present study may be restricted by the number of participants that were used in the sample. Although 50 participants is considered a desirable sample size, the smaller the sample the more influenced by individual differences it may be, therefore 50 may not be a representative depiction of the entire population of 18 to 30 year old individuals.
The results obtained were significant; it may be beneficial to repeat the study on a larger sample which may have more validity when generalising to the larger population. Also only 14 of the participants were males and 36 were females, in addition 25 of the participants were between 18 and 20 and the other 25 ranged from 21-27. A more varied sample of ages and equally divided sample of males and females may offer further validity. The results of the present study offer further support for a large amount of existing literature, and so in future research the same findings would be expected.
Another possible limitation may be that the study was carried out on groups of 5 participants at a time. Although they were separated by partitions the presence of others may have interfered with their performance on the tasks. For example, when filling out the Hospital Anxiety and Depression Scale Questionnaire they may have been worried that others may see how they were filling it in and not have been honest. Also as the HADS is a self-screening questionnaire, this may have also meant that their answers were dishonest possibly due to a fellow student carrying out the study despite full confidentiality of the data.
However, research has indicated that the HADS is valid as a screening technique for cognitive profiles. When completing the WAIS III, they may not have paid their full attention to the task at hand, and possibly been discouraged if others were answering questions more promptly and easily. In future research where time constraints are not an issue, the study could be carried out on an individual basis, therefore eliminating the distraction of the presence of others.
The study was particularly time consuming, thus may have lead to participants experiencing boredom and fatigue, this may have contributed to the variation in some levels of the data. This could be the cause of larger standard deviations in some parts of the data, such as the vast range in IQ scores or Error scores on the BVRT. Timing was an issue for both the researcher and participants, who were all also students under pressure from deadlines and vast workloads. To spread the study over a number of days when the participants are not in a time of increased stress and workload, with distractions on their mind, this may add further validity to the study.
Implications for future research
The development of this set of normative data for this new age group, 18 to 30 year olds, will greatly aid in the advance of the use of the BVRT as an instrument in clinical fields. The BVRT can now be used on brain damaged patients or patients suffering from brain diseases within this younger age group to accurately measure the extent of damage to their visual perception, visual memory and visuo-constructive abilities.
Future research can now accurately assess performance of neuro-psychologically impaired individuals within this new age group, suffering from such disorders as Post Traumatic Stress and Schizophrenia, on the BVRT, by comparing to this new set of normative data. This can then be used for comparison against that of existing literature on other age groups to see how age may affect the extent of impairment of these cognitive skills. In addition, individuals with learning disabilities and ADHD can now be assessed to investigate the possibilities of progress or decline with age into early adulthood, now that a set of normative data exists for this age range.

Conclusion


In conclusion to this study a new set of Normative Data has been collected for the new age group of 18 – 30 year olds. With this development in BVRT research, clinical applications can benefit from these findings when looking at patient’s with brain damage or those suffering from a brain disease within this age group. The findings are consistent with the normative standards stated in the BVRT fifth edition manual for older age groups in that a significant relationship was found between BVRT performance and IQ levels. Higher IQ levels are associated with better performance on the BVRT, suggesting that the more intellectually advanced an individual, the more enhanced their visual perception, visual memory and visuo-constructive abilities. These new findings provide reliable data which can be used to assess the cognitive abilities of the younger age group (18-30 year olds), they also suggest that performance on the BVRT may be slightly different to that suggested in previous research. This may be because the existing data is slightly outdated, changes may have occurred, which have influenced cognitive processing, also in the current study only a small cohort of people took part with a low male to female ratio.
In addition to existing research, the findings of this study can now be applied in new settings. This younger age group (18-30 year olds) are one of the most likely to sustain brain injury. Also, Post traumatic stress disorder (PTSD), and symptoms of many mental psychiatric disorders often begin to appear within this age range. By using the BVRT as an instrument to measure their performance on cognitive tasks, new research can discover the impact of such traumas on this younger age group. Finally this new set of normative data provides support to current research that IQ level is a strong indicator of BVRT performance; this aids the interpretation of results for neuro-psychologically impaired individuals.

References


1. Amieva, H., Jacqmin-Gadda, H., Orgogozo, J., Le Carret, N., Helmer, C., Letennuer, L., Berberger-Gateau, P., Fabrigoule, C. & Dartiques, J., 2005. The 9 year cognitive decline before dementia of the Alzheimer’s type: A prospective population-based study. Brain A journal of Neurology, 133(2), 1-9.
2. Arenberg, D., 1978. Differences and changes with age in the Benton Visual Retention Test. Journal of Gerontology, 33, 534-540. Available from: http://geronj.oxfordjournals.org/content/33/4/534.full.pdf+html [Accessed on November 1st 2009]
3. Baum, C., Edwards, D., Yonan, C., & Storandt, M., 1996. The relation of neuropsychological test performance to performance of functional tasks in dementia of the Alzheimer type. Archives of Clinical Neuropsychology, 11(1),69-75.
4. Benton, A. L., 1946. A visual retention test for clinical use. New York: The Psychological Corporation.
5. Benton, A. L., 1955. Revised Visual Retention Test: Clinical and experimental applications. Iowa City: State University of Iowa.
6. Benton, A. L., 1963. Revised Visual Retention Test: Clinical and experimental applications (3rd ed.). New York:  The Psychological Corporation.
7. Benton, A.L., 1974. Revised Visual Retention Test: Clinical and experimental applications (4th ed.). San Antonio, TX: The Psychological Corporation.
8. Benton, A.L., Eslinger, P. J., & Damasio, A. R., 1981. Normative observations on neuropsychological test performances in old age. Journal of clinical Neuropsychology, 3, 33-42.
9. Benton Sivan, A., 1992. Benton Visual Retention Test. 5th ed. San Antonio: The Psychological Corporation.
10. Binet, A., & Simon, TH., 1908. Le development de l’intelligence chez les enfants [The development of intelligence in children]. L’Annee Psychologique, 14, 1-94.
11. Birch, L. S., & Davidson, K. M., 2007. Specificity of autobiographical memory in depressed older adults and its relationship with working memory and IQ. British Journal of Clinical Psychology, 46(2), 175-186.
12. Crookes, T. G., & McDonald, K. G., 1972. Benton’s Visual Retention Test in differentiation of depression and early dementia. American Journal of Mental Deficiency, 72, 96-99.
13. Dige, N., & Maarh, E., 2008. Memory tests in subgroups of adult attention  deficit hyperactivity reveals simultaneous capacity deficit. Intern. J. Neuroscience 118: 569-591. Informa Healthcare USA, Inc.
14. Ellis, J. M., Comijs, H., Rijmen, F., Jonker, C., & Beekman, A. F., 2008. Anxiety symptoms and cognitive performance in later life: Results from the longitudinal aging study Amsterdam. Aging and Mental Healt, 12(4), 517-523
15. Emdad, R., & Sondergaard, H.P. 2006. General Intelligence and short-term memory impairments in Post Traumatic Stress Disorder patients. Journal of Mental Health, 15(2), 205-216.
16. Eysenck, M. W., 1997. Anxiety and Cognition: A Unified Theory. East Sussex : Psycholgy Press Ltd.
17. Fay, L., 2010. Alzheimer’s Disease Facts and Figures 2010. Brain Fitness for Life. Available from: http://www.brainfitnessforlife.com/alzheimers/alzheimers-disease-2010-facts-figures/ Accessed: 30.01.2010.
18. Le Carret, N., Rainville, C., Lechevallier, N., Lafont, S., Letenneur, L., & Fabrigoule, C., 2003. Influence of education on the Benton Visual Retention Test performance as mediated by a strategic search component. Brain and Cognition, 53(2), 408-411.
19. Leon, M. J., 2001. Prediction of cognitive decline in normal elderly subjects. The National Academy of Sciences, 98(19), 10966–10971.
20. Lezak, M. D., 1983. Neuropsychological assessment (2nd ed.) New York: Oxford University Press.
21. Marsh, G. G., & Hirsch, S. H., 2006. Effectiveness of two tests of visual retention. Journal of Clinical Psychology, 38, 115-118.
22. 1989. Changes in the performance of parkinsonian patients and normal aged on the Benton Visual Retention Test. Exp Aging, Res, 15(1-2),13-8
23. Park, J. J., 2008. Pattern of Performance on the Benton Visual Retention Test in Schizophrenic patients diagnosed with research diagnostic criteria. Dissertation Abstracts International: Section B: The Sciences and Engineering, 68(10-B), 6976.
24. Parkinson’s Disease Society, 2010. London: Parkinson's Disease Society of the United Kingdom. Available from: http://www.parkinsons.org.uk/default.aspx Accessed: 30.01.2010.
25. Petris, L., 1981. Il Visual Retention Test nell’Esame della Conoscenza Visiva. Firenze: Organizzazioni Speciali.
26. Poitrenaud, J., & Clement, F., 1965. La deterioration physiologique dans le Test de Retention Visuelle de Benton: Resultats obtenus par 500 sujets normaux. Psychologie Francaise, 10, 359-368.
27. Robinson-Wheelen, S., 1992. Benton Visual Retention Test performance among normal and demented older adults. Neuropsychology, 6(3), 1992, 261-269.
28. Seo, E. H., Lee, D. Y., Choo, I. H., Youn J. C., Kim K. W., Jhoo, J. H., Suh, K. W., Paek, Y. S., Jun, Y. H. & Woo, J. I., 2007. Performance on the Benton Visual retention Test in an Educationally Diverse Elderly Population. The Journals of Gerontology Series B: Psychological sciences and Social Sciences, 62, 191-193.
29. Snaith, R.P., & Zigmond, A.S. 1983. 1992. 1994. Hospital Anxiety and Depression Scale (HADS). ACTA Psychiatrica Scandanavica, 67, 361 – 370. Nelson Publishing Company Ltd. London.
30. Thompson, S.B.N., 2000. The Central Executive System in people with Down’s syndrome and dementia. Clinical Gerontologist, 21(3), 3-32.
31. Thompson, S.B.N., 2001. Assessing dementia in Down’s syndrome: a comparison of
five tests. Clinical Gerontologist, 23(3/4), 3-19.
32. Thompson, S.B.N. MacDonald. J., & Coates, T.D. 2001. Improving Visual Memory with Aricept (Donepezil Hydrochloride, E2020) in Mild-to-Moderate Alzheimer’s disease. Clinical Gerontologist, 24(1/2), 55-73.
33. Thompson, S.B.N., 2002. Memory decline, Alzheimer’s disease and vascular dementia: the clinical picture. The Journal of Cognitive Rehabilitation, 20(2), 12-18.
34. Thompson, S.B.N., 2006. Dementia and memory: a handbook for students and professionals. Aldershot: Ashgate.
35. Thompson, S.B.N., Ennis, E., Coffin, T., & Farman, S., 2007. Design and evaluation of a computerised version of the Benton Visual Retention Test. Computers in Human Behavior, 23, 2383-2393.
36. Thompson, S.B.N., 2010. Advancing knowledge into the clinical assessment of dementia. PhD, School of Design, Engineering & Computing, Department of Psychology, Bournemouth University.
37. Thompson, S.B.N., 2011 Psychology of trauma: clinical reviews, case histories, research. Portsmouth: Blackwell-Harvard-Academic.
38. Vilkki, J., 1989. Perseveration in memory for figures after frontal lobe lesion. Neuropsychologia, 27, 1101-1104.
39. Wechsler, D., 1939. Weschler-Bellevue Intelligence Scale. New York: The Psychological Corporation.
40. Wechsler, D., 2002. WAIS-III. WMS-III. Technical Manual. New York: The Psychological Corporation.
41. Weems., C.F., Costa, N.M., Watts, S.E., Taylor, L.K., & Cannon, M.F., 2007. Cognitive errors, anxiety sensitivity, and anxiety control beliefs: their unique and specific associations with childhood anxiety symptoms. Behaviour Modification, 31(2), 174-201.

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