Department of Health Sciences, University of Leicester and Leicestershire Partnership NHS Trust
Leicestershire Partnership NHS Trust
School of Psychology, University of Leicester, Leicester, UK
Correspondence: Dr Mohammed Al-Uzri, Neuropsychopharmacology Unit, Department of Health Sciences, Leicester General Hospital, Leicester LE5 4PW, UK. Tel: +44(0) 116 225 7924; fax: +44(0) 116 225 7925; email: mmaul{at}le.ac.uk
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Aims To examine the extent of memory impairment in community-based patients with schizophrenia using a clinically relevant test.
Method All patients with schizophrenia (n=190) in one catchment area were identified, of whom 133 were potentially eligible for the study; 73 patients volunteered to take part. They were assessed using the Rivermead Behavioural Memory Test (RBMT), the National Adult Reading Test, the Positive and Negative Syndrome Scale, the Health of the Nation Outcome Scales and the Scales and the Office for National Statistics Classification of Occupation. Their performance on the memory test was compared withthat of matched controls (n=71).
Results Patients as a group performed significantly worse (P<0.001) than controls on the RBMT. Using the RBMT normative scores, 81% of patients were found to have impaired memory compared with 28% of controls.
Conclusions Using a clinically relevant test, the majority of community-based patients with schizophrenia may have memory impairment.
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We excluded patients with organic brain disease, head injuries or comorbidity, and those whose first language was not English. None of the participants had had electroconvulsive therapy in the year prior to taking part in the study. Patients older than 60 years were also excluded, because Kelly et al (2000) suggested that people above this age with schizophrenia have a poorer cognitive performance than younger patients. The patients' performance on the memory test was compared with that of controls (n=71). Members of the control group live in the same city and were recruited by advertisements in the local hospital, university and supermarkets. They had no history of mental illness, and were subjected to the same exclusion criteria as the patient group.
Measures
Rivermead Behavioural Memory Test
Participants were assessed with the Rivermead Behavioural Memory Test
(RBMT; Wilson et al,
1985). This test of everyday memory has good ecological validity,
and is made up of 12 measures, each aimed at testing one aspect of everyday
memory:
The RBMT has a screening score (0-12), and is not very demanding in terms of effort or time (it takes 25-30 min to administer). It has been used before in schizophrenia studies, for example by McKenna et al (1990) and Kelly et al (2000).
National Adult Reading Test
The National Adult Reading Test (NART;
Nelson, 1982) is an estimate
measure of premorbid intelligence. It has been widely used in psychiatric
research and in particular in studies of schizophrenia
(Gilvarry et al,
2001).
Positive and Negative Syndrome Scale
The Positive and Negative Syndrome Scale (PANSS;
Kay et al, 1987) was
given to patients only. It is a widely used scale for symptom ratings in
schizophrenia.
Health of the Nation Outcome Scales
The Health of the Nation Outcome Scales (HoNOS;
Wing et al, 1998)
were used for assessment of the psychiatric patients' current community
functioning.
Demographic factors
Demographic data for all participants were documented, including occupation
group using the Office for National Statistics classification (see Appendix).
In addition, duration of illness and age at onset for the patients were
documented through information provided by the patient and verified from
medical records, including first documentation by general practitioners.
Duration of illness was defined as the period between the time that first
psychotic symptoms were reported and the time of current assessment. Age at
onset was defined as the age when first psychotic symptoms were reported.
Assessment procedure
A psychologist administered the cognitive assessments independently from
the clinical assessment, which was made by a clinician (M.A.-U.) masked to the
cognitive assessment. The responsible consultants (J.B. and S.F.) assessed the
patients' level of community functioning using the HoNOS, and were also
unaware of the cognitive assessment. Illness duration and age at onset were
calculated independently by D.M.
Statistical analysis
Sample size was calculated to achieve statistical power of an 80%
possibility of obtaining significant results at 5%, when submitted for ethical
committee approval. Differences between patients and controls were examined by
t-test or
2 test, as appropriate, for demographic
variables; RBMT scores were examined by logistic regression; within-group
differences were examined using analysis of variance (ANOVA); correlations
were examined using Pearson's r or Spearman's rho as appropriate. The
Statistical Package for the Social Sciences version 12 for Windows was used to
analyse the data.
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![]() View larger version (24K): [in a new window] [as a PowerPoint slide] |
Fig. 1 Flow chart of patients' selection for the study.
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Table 1 Comparison between patients who participated or refused to take part in the
study
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The participating group comprised 31 women and 42 men, and the control group 33 women and 38 men. There was a small but statistically significant difference in age (t=2.48, d.f.=142, P=0.014) and NART score (t =-2.49, d.f.=132, P=0.014) between patients and controls (Table 2).
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Table 2 Comparison between patients and control group demographics
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RBMT scores analysis
Binary logistic regression showed that patients as a group performed
significantly worse than controls on the RBMT, even after correcting for NART
score and age (B=0.665, P<0.001).
Table 3 shows the distribution
of both patients and controls across different scores categories of the RBMT
scores. Reducing this into a 2 x 2 table
(Table 4) showed that 81% of
patients had impaired memory compared with 28% of controls. Thus, using RBMT
scores of impaired v. normal gives a 76% chance of correctly
predicting group membership (patients or controls respectively).
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View this table: [in a new window] |
Table 3 Rivermead Behavioural Memory Test screening score
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Table 4 Rivermead Behavioural Memory Test screening scores reduced to `impaired' or
`normal'
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Age
There was a significant inverse correlation between age and RBMT score for
the whole sample (patients and controls): r=-0.375, two-tailed,
P<0.001. That was also the case when correlations for both groups
were examined separately, although the correlation was stronger between age
and RBMT score in patients (r=-0.369, P=0.001) than in
controls (r=-0.277, P=0.020). To further examine the age
effect on both groups separately, we divided the two samples (patients and
controls) into three age-groups: 18-30 years, 31-45 years and 46-60 years (see
Fig. 2).
![]() View larger version (28K): [in a new window] [as a PowerPoint slide] |
Fig. 2 Performance of different age-groups on the Rivermead Behavioural Memory
Test (P<0.001 for patients v. controls in all
age-groups). , patients (n=73); , controls
(n=71).
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Using one-way ANOVA, there was no significant difference in RBMT scores among the different age-groups of controls. However, there were significant differences among different age-groups in patients (F=4.686, d.f.=2, P=0.007). The post hoc Tukey honestly significant difference test showed significant differences between the youngest (18-30 years) and oldest (46-60 years) groups (P=0.012) and between the middle (31-45 years) and oldest age-groups (P=0.018), but no significant difference between the youngest and middle age-groups.
Illness duration and age at onset
For 67 patients we were able to obtain accurate information on the illness
duration (mean 669 weeks, median 504, s.d.=546), length of stay (mean 186
days, median 75, s.d.=323) and age at onset (mean 27.2 years, median 26,
s.d.=7.9). Using Pearson correlation, we found a significant inverse
correlation between illness duration and RBMT screening score
(r=-0.335, P=0.006). In contrast, there was no significant
correlation between length of stay or age at onset and RBMT screening
score.
Medication
Patients were on different antipsychotic medication regimens: 29 were
taking atypical antipsychotic agents, 33 typical agents, 7 were taking both,
and 4 were taking no antipsychotic at the time of the study. Twenty-seven were
taking anticholinergic medication. Analysis of variance showed no significant
effect for type of antipsychotic on the RBMT score; it also showed no
significant difference on RBMT score between patients taking or not taking
anticholinergic medication.
Symptom ratings
The total PANSS rating showed mild psychopathological disorder in 73
patients (mean 50.77, mode 42, range 30-84). Using Pearson correlation there
was a significant inverse correlation between RBMT score and the negative
sub-scale of the PANSS (r=-0.262, two-tailed, P=0.027).
However, the correlation was not significant with the total score, general or
positive sub-scales.
Occupation and HoNOS score
There was a significant inverse correlation between RBMT score and
occupational groups (Spearman's rho=-0.332, two-tailed, P<0.001),
i.e. the lower the score on the RBMT the higher the category of occupational
group (1, managers and senior officials; 10, unemployed). This is to say that
the lower a person scores on RBMT, the more likely that person would be to be
unemployed.
We were able to obtain HoNOS scores for 58 patients. There was no significant correlation between RBMT score and the total HoNOS score. However, there was a significant correlation between the RBMT score and the functional impairment subscale (items 4 and 5) of the HoNOS (Pearson's r=-0.297, P=0.02).
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The patients who took part in our study were relatively young and free from psychotic symptoms, living in the community and with no documented comorbidity. The exclusion criteria were also designed to avoid the participation of any patients disadvantaged in terms of age and language. Except for years in education, there was no significant demographic or clinical difference between the patients who took part in the study and those who declined. This suggests that participants might have better memory functioning than those who declined to take part in the study. Therefore, the prevalence of memory impairment reported would be a conservative estimate of its overall prevalence in schizophrenia when taking other confounding factors (clinical or demographic) into consideration. This is supported by the findings of Tamlyn et al (1992) who used the same test (RBMT) to examine their cohort; they reported a much higher prevalence of memory impairment in their subgroup of chronically ill and hospitalised patients, 27 out of 28 of whom scored in the impaired range.
The prevalence of schizophrenia in our study population (1.9 per 1000) is at the lower end of that expected (1.4-4.6 per 1000 population; Jablensky, 2000). This could be explained by the demographic characteristics of the catchment area. As a suburban district, it is more likely to have a lower prevalence of psychotic disorders compared with city centres, which are associated with higher morbidity in general (Mortensen et al, 1999). In addition, patients who develop schizophrenia might well migrate towards the city centre, especially when they need supported or hostel accommodation, which is most likely to be available in urban areas. This was particularly true for our study because patients who needed rehabilitation services and supported accommodation were moved outside the catchment area.
RBMTand schizophrenia
Our study suggests that the RBMT is a good clinical marker for memory
impairment in schizophrenia. This is supported by previous use of the RBMT in
studies of schizophrenia, which consistently showed that people with this
disorder underperform on this test
(McKenna et al, 1990;
Kelly et al, 2000).
Our study had the advantage, compared with previous studies, of the inclusion
of a control group. This made it possible to examine the ability of the RBMT
in discriminating between patients and controls. It is not common in
psychiatric research to have an instrument with such a good ability (76%) to
predict patient or control status. A similar ability (76%) was reported in
previous work (Palmer et al,
1997); however, this involved a more demanding neuropsychological
battery which is difficult to incorporate into everyday clinical practice, and
furthermore lacked the specificity of everyday memory. Therefore, the RBMT has
the potential to become an important tool in our clinical practice for the
identification of memory impairment in schizophrenia, which may help predict
functional outcome.
Specificity of memory impairment
The premorbid IQ reported for the patients in this study was much higher
than that reported in previous studies. This is another indication that our
sample can be considered among the less ill of patients with schizophrenia,
making the memory impairment reported even more significant. The difference in
premorbid IQ between patients and controls was small in clinical terms, but
statistically significant. However, even after correcting for this difference
in premorbid IQ, patients' performance on the RBMT was worse than that of
controls. Therefore, the underperformance of patients on the RBMT, as a
measure of working memory, cannot be explained as a symptom of generalised
reduction of intellectual ability, but is rather a specific cognitive deficit.
Furthermore, this deficit was not related to symptom rating, except for
negative symptoms, or medication in clinically stable patients. This supports
the view that memory impairment is a core element of the clinical presentation
of schizophrenia.
The association between memory impairment and the negative symptoms sub-scale of the PANSS is an important replication of previous findings (Berman et al, 1997). Conceptually, both denote the lack of a normally existing function. More importantly, this is further evidence that they may have a common underlying substrate (Rossi et al, 1997). This is an important contribution of neuropsychology towards better understanding of the underlying pathophysiology of schizophrenia.
Memory impairment and level of functioning
The association of memory impairment with occupational group provides
further evidence for the importance of such impairment in schizophrenia. This
echoes previous findings (Green,
1996), which suggested an association between memory impairment
and functional outcome. This would have important implications for the
development of any intervention that involves the use of memory. First, it
suggests that patients with such impairment might not benefit from
interventions that require intact memory. Second, it might be necessary to
include memory remediation programmes in rehabilitation services to improve
level of functioning. Further validity for the RBMT comes from the significant
correlation with the functional impairment sub-scale of the HoNOS. This
finding echoes that previously reported by Kelly et al
(2000), which reinforces the
importance of memory impairment in influencing level of functioning in
patients with mental illness.
Age and memory impairment
An interesting finding emerged when we divided the patient and control
groups, separately, into three different age categories. The average RBMT
scores for the controls were not significantly different across age-groups and
remained within the normal memory category. In contrast, the patients' average
RBMT scores remained within the impaired memory range across age-groups. In
addition, there was a significant reduction in the average score for the
oldest group of patients, which suggests that memory impairment as a subset of
cognitive performance is compromised before the age of 60 years (cf.
Kelly et al, 2000). We
can conclude that memory decline might have a different course in
schizophrenia compared with that in the general population and that older
people with schizophrenia (aged 46-60 years) are significantly disadvantaged
compared with younger people with this disorder.
The significance of the association between illness duration and memory impairment reported in this study raises important issues. Ostensibly, one can conclude that memory function in schizophrenia has a deteriorating course. However, it is important to examine the impact of potential mediating factors, such as the course of the illness, before such a conclusion can be drawn definitively. This is particularly important in the absence of clear neuropathological evidence to support a degenerative nature of the illness (Woods, 1998). Therefore, what can be concluded from the result of this study is that longer illness duration might carry a higher risk of worsening memory impairment.
Finally, it is not known whether memory impairment which was identified by the RBMT is exclusive to schizophrenia or extends to other psychotic disorders. Bipolar affective disorders have also been associated with cognitive impairment, including memory impairment, during the acute phase of the illness as well as during euthymic periods (Thompson et al, 2005). However, a review by Martinez-Aran et al, 2000 suggested that during symptom remission cognitive dysfunction in patients with bipolar disorder is more likely to improve. In addition, relatives of patients with schizophrenia show cognitive deficits such as memory impairment, whereas relatives of patients with affective bipolar disorders do not show such impairment (Keri et al, 2001). These findings suggest that cognitive dysfunction in general, and memory impairment in particular, may be a possible trait marker for schizophrenia to a greater degree than for bipolar affective disorders. Further research is needed to clarify this issue.
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