Sample

We identified every patient with a possible diagnosis of schizophrenia, from psychiatric records, in one catchment area of approximately 100 000 people in south Leicestershire. This included examining old records of all psychiatric patients in the catchment area to make sure no potential patient was missed. The diagnoses were confirmed using ICD-10 criteria (World Health Organization, 1992). The area can be described as a suburban British residential area with a predominantly middle-class working population. The two consultants responsible for the area have a policy of not discharging patients with schizophrenia from their care even if the patients need minimal psychiatric input. The only exceptions were cases of severe and incapacitating schizophrenia that necessitated a referral to rehabilitation psychiatry. Such patients usually move out of the area into long-term care units or sheltered accommodation.

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 (Reference Kelly, Sharkey and Morrison2000) 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

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 χ² 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.

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 × 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).

Table 3 Rivermead Behavioural Memory Test screening score

	Severely impaired (0–2)	Moderately impaired (3–6)	Poor (7–9)	Normal (10–12)
Patients (n=73)	2	25	32	14
Controls (n=71)	0	1	19	51

Table 4 Rivermead Behavioural Memory Test screening scores reduced to ‘impaired’ or ‘normal’

	Impaired memory (0–9)	Normal memory (10–12)	Total
	n (%)
Patients	59 (81)	14 (19)	73 (100)
Controls	20 (28)	51 (72)	71 (100)

χ²=39.569, d.f.=1, P<0.001 (two-tailed)

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).

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).

Using ANOVA, we found a significant difference in RBMT scores between diagnostic groups (patients v. controls) (F=72.4, d.f.=1, P<0.0001) and the three age-groups (F=6.5, d.f.=2, P=0.002), but no significant interaction between diagnosis and age (F=1.7, d.f.=2, P=0.18). The reason for the lack of significant interaction is that the age effect was not linear, but was particularly pronounced in the oldest age-group (46-60 years). There was no drop in the RBMT score with age in the control group, but there was a drop in the oldest age-group in participants with schizophrenia.

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).

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 (Reference McKenna, Tamlyn and LundMcKenna et al, 1990; Reference Kelly, Sharkey and MorrisonKelly 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 (Reference Palmer, Heaton and PaulsonPalmer 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 (Reference Berman, Veigner and MersonBerman 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 (Reference Rossi, Mancini and StrattaRossi 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 (Reference GreenGreen, 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 (Reference Kelly, Sharkey and Morrison2000), 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. Reference Kelly, Sharkey and MorrisonKelly 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 (Reference WoodsWoods, 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 (Reference Thompson, Gallagher and HughesThompson et al, 2005). However, a review by Reference Martinez-Aran, Vieta and ColomMartinez-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 (Reference Keri, Kelemen and BenedekKeri 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.

Standard Occupational Classification 2000 (from the Office for National Statistics)

1. 1 Managers and senior officials

2. 2 Professional occupations

3. 3 Associate professional and technical occupations

4. 4 Administrative and secretarial occupations

5. 5 Skilled trades occupations

6. 6 Personal service occupations

7. 7 Sales and customer service occupations

8. 8 Process, plant and machine operatives

9. 9 Elementary occupations

10. 10 Unemployed