Psychiatry - Research Publications
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ItemDo schizotypy dimensions reflect the symptoms of schizophrenia?(SAGE PUBLICATIONS LTD, 2019-03)OBJECTIVE: The personality characteristics and symptoms observed in schizophrenia are postulated to lie on a continuum, with non-clinical manifestations referred to as schizotypy. High schizotypy behaviours are argued to correspond with the three main clusters of symptoms in schizophrenia: positive, negative and cognitive/disorganised symptoms, yet there is limited empirical evidence to support this. This study aimed to investigate whether schizotypy dimensions significantly correlate with their respective schizophrenia symptomatology in the largest sample to date. METHODS: A total of 361 adults (103 patients with schizophrenia/schizoaffective disorder and 258 healthy controls) were assessed for schizotypy using the Oxford-Liverpool Inventory of Feelings and Experiences. The MATRICS Consensus Cognitive Battery supplemented by the Stroop task and Wisconsin Card Sorting Test was administered to all participants to obtain objective measurements of cognition. Schizophrenia symptomatology was assessed using the Positive and Negative Syndrome Scale in patients only. RESULTS: The results demonstrated significant correlations between the Oxford-Liverpool Inventory of Feelings and Experiences positive and negative subscales and their respective Positive and Negative Syndrome Scale subscales only, indicating that positive and negative schizotypy dimensions across patients and controls accurately reflect the respective schizophrenia symptomatology observed in patients. Cognitive performance did not correlate with cognitive/disorganised symptom dimensions of the Oxford-Liverpool Inventory of Feelings and Experiences or the Positive and Negative Syndrome Scale, indicating that cognitive impairment is an independent symptom dimension that requires objective cognitive testing. CONCLUSION: Collectively, the findings provide empirical evidence for the continuum theory and support the use of schizotypy as a model for investigating schizophrenia.
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ItemSchizotypal traits are associated with poorer executive functioning in healthy adults(FRONTIERS MEDIA SA, 2015-06-01)Previous research has shown mild forms of the neurocognitive impairments seen in schizophrenia among healthy individuals exhibiting high schizotypal traits. This study aimed to explore associations between schizotypy and cognitive performance in an adult community sample. Ninety-five females and 79 males completed the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE), which measures four separable aspects of schizotypy: cognitive disorganization, unusual experiences, introvertive anhedonia, and impulsive non-conformity. Subsequently, participants were administered a neurocognitive battery incorporating measures of executive skills including inhibition, cognitive flexibility, reasoning, and problem solving along with measures of attention and processing speed and both verbal and spatial working memory. In line with predictions, the current study found that higher scores on the subscales of unusual experiences, cognitive disorganization, and impulsive non-conformity related to worse performance on a measure of inhibition. Additionally, as introvertive anhedonia increased, both attention and processing speed and reasoning and problem-solving performance became more impaired. In conclusion, this study extends schizotypy literature by examining the subscales of the O-LIFE, and enables inferences to be drawn in relation to cognitive impairment in schizophrenia.
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ItemThe dopamine D1 receptor gene is associated with negative schizotypy in a non-clinical sample(ELSEVIER IRELAND LTD, 2016-01-30)
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ItemDoes cognitive performance map to categorical diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder? A discriminant functions analysis(ELSEVIER, 2016-03-01)OBJECTIVES: Despite known overlaps in the pattern of cognitive impairments in individuals with bipolar disorder (BD), schizophrenia (SZ) and schizoaffective disorder (SZA), few studies have examined the extent to which cognitive performance validates traditional diagnostic boundaries in these groups. METHOD: Individuals with SZ (n=49), schizoaffective disorder (n=33) and BD (n=35) completed a battery of cognitive tests measuring the domains of processing speed, immediate memory, semantic memory, learning, working memory, executive function and sustained attention. RESULTS: A discriminant functions analysis revealed a significant function comprising semantic memory, immediate memory and processing speed that maximally separated patients with SZ from those with BD. Initial classification scores on the basis of this function showed modest diagnostic accuracy, owing in part to the misclassification of SZA patients as having SZ. When SZA patients were removed from the model, a second cross-validated classifier yielded slightly improved diagnostic accuracy and a single function solution, of which semantic memory loaded most heavily. CONCLUSIONS: A cluster of non-executive cognitive processes appears to have some validity in mapping onto traditional nosological boundaries. However, since semantic memory performance was the primary driver of the discrimination between BD and SZ, it is possible that performance differences between the disorders in this cognitive domain in particular, index separate underlying aetiologies.
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ItemCharacterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrum(CAMBRIDGE UNIV PRESS, 2017-07)BACKGROUND: Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. METHOD: Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). RESULTS: Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. CONCLUSIONS: Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.