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Cognitive profiles across the psychosis continuum
... For example, the clinical group may be diffuse and heterogeneous due to comorbidity and to a convergence of different pathophysiological pathways on the same symptoms. In line with this, there has been considerable effort invested in finding subgroups of patients based on cognition or symptoms over the last 50 years and many putative stratifications have been proposed [14][15][16][17][18][19][20] , yet none have advanced beyond proof-of-concept. We have suggested that one of the main reasons is that clustering algorithms always yield a result, regardless of whether clearly defined clusters are evident in the data, resulting in ill-defined and poorly replicated subtypes. ...
Cognitive impairments are a core feature of psychosis that are often evident before illness onset and have substantial impact on both clinical and real-world functional outcomes. Therefore, these are an excellent target for stratification and early detection in order to facilitate early intervention. While many studies have aimed to characterise the effects of cognition at the group level and others have aimed to detect individual differences by referencing subjects against existing norms, these studies have limited generalisability across clinical populations, demographic backgrounds and instruments and also do not fully account for the inter-individual heterogeneity inherent in psychosis. Here, we outline the rationale, design and analysis plan for the PRECOGNITION project which aims to address these challenges. This project is a collaboration between partners in five European countries, that aims to (i) translate normative modelling approaches that have been pioneered in brain imaging to psychosis data, to yield cognitive growth charts for longitudinal tracking and prediction at the individual level (ii) develop machine learning models for harmonising and stratifying cohorts on the basis of these models; (iii) provide comprehensive reference models that provide broad sociodemographic coverage including different languages and distinct norms for individuals with psychosis and unaffected individuals and (iv) stratification models and predictions for functional outcome measures in psychosis cohorts. Crucially, this project will be guided throughout by experts with lived experience.
Introduction
Prior research examining cognitive heterogeneity in psychotic disorders primarily focused on chronic schizophrenia, with limited data on first-episode psychosis (FEP). We aimed to identify distinct cognitive subgroups in adult FEP patients using data-driven cluster-analytic approach, and examine relationships between cognitive subgroups and a comprehensive array of illness-related variables.
Methods
Two-hundred-eighty-nine Chinese patients aged 26–55 years presenting with FEP to an early intervention program in Hong Kong were recruited. Assessments encompassing premorbid adjustment, illness-onset profile, symptom severity, psychosocial functioning, subjective quality-of-life, and a battery of cognitive tests were conducted. Hierarchical cluster-analysis was employed, optimized with k-means clustering and internally-validated by discriminant-functional analysis. Cognitive subgroup comparisons in illness-related variables, followed by multivariable multinominal-regression analyzes were performed to identify factors independently predictive of cluster membership.
Results
Three clusters were identified including patients with globally-impaired (n = 101, 34.9%), intermediately-impaired (n = 112, 38.8%) and relatively-intact (n = 76, 26.3%) cognition (GIC, IIC and RIC subgroups) compared to demographically-matched healthy-controls’ performance (n = 50). GIC-subgroup was older, had lower educational attainment, greater positive, negative and disorganization symptom severity, poorer insight and quality-of-life than IIC- and RIC-subgroups, and higher antipsychotic-dose than RIC-subgroup. IIC-subgroup had lower education levels and more severe negative symptoms than RIC-subgroup, which had better psychosocial functioning than two cognitively-impaired subgroups. Educational attainment and disorganization symptoms were found to independently predict cluster membership.
Discussion
Our results affirmed cognitive heterogeneity in FEP and identified three subgroups, which were differentially associated with demographic and illness-related variables. Further research should clarify longitudinal relationships of cognitive subgroups with clinical and functional outcomes in FEP.
Current diagnostic systems for mental disorders were established before the tools of neuroscience were available, and although they have improved the reliability of psychiatric classification, progress toward the discovery of disease etiologies and novel approaches to treatment and prevention may benefit from alternative conceptualizations of mental disorders. The Research Domain Criteria (RDoC) initiative is the centerpiece of NIMH's effort to achieve its strategic goal of developing new methods to classify mental disorders for research purposes. The RDoC matrix provides a research framework that encourages investigators to reorient their research perspective by taking a dimensional approach to the study of the genetic, neural, and behavioral features of mental disorders, RDoCs integrative approach includes cognition along with social processes, arousal/regulatory systems, and negative and positive valence systems as the major domains, because these neurobehavioral systems have all evolved to serve the motivational and adaptive needs of the organism. With its focus on neural circuits informed by the growing evidence of the neurodevelopmental nature of many disorders and its capacity to capture the patterns of co-occurrence of behaviors and symptoms, the RDoC approach holds promise to advance our understanding of the nature of mental disorders.
Background. Impairment in a wide range of cognitive abilities has been consistently reported in individuals with schizophrenia. Both neurocognitive and social cognitive deficits are thought to underlie severe functional disabilities associated with schizophrenia. Despite the key role in schizophrenia outcome, cognition is still poorly assessed in both research and clinical settings.
Methods. In this guidance paper, we provide a systematic review of the scientific literature and elaborate several recommendations for the assessment of cognitive functions in schizophrenia both in research settings and in real-world clinical practice.
Results. Expert consensus and systematic reviews provided guidance for the optimal assessment of cognitive functions in schizophrenia. Based on the reviewed evidence, we recommend a comprehensive and systematic assessment of neurocognitive and social cognitive domains in schizophrenia, in all phases of the disorder, as well as in subjects at risk to develop psychosis. This European Psychiatric Association guidance recommends not only the use of observer reports, but also self-reports and interview-based cognitive assessment tools. The guidance also provides a systematic review of the state of the art of assessment in first episode of psychosis patients and in individuals at risk for psychosis.
Conclusion. The comprehensive review of the evidence and the recommendations might contribute to advance the field, allowing a better cognitive assessment, avoiding overlaps with other psychopathological dimensions. The dissemination of this guidance paper may promote the development of shared guidelines concerning the assessment of cognitive functions in schizophrenia, with the purpose to improve the quality of care and to obtain recovery.
Keywords Assessment instruments; cognitive functioning; early psychosis; evidence-based; high-risk for psychosis; psychosocial functioning; schizophrenia; systematic review
Cognitive impairment in schizophrenia represents one of the main obstacles to clinical and functional recovery. This expert group paper brings together experts in schizophrenia treatment to discuss scientific progress in the domain of cognitive impairment to address cognitive impairments and their consequences in the most effective way. We report on the onset and course of cognitive deficits, linking them to the alterations in brain function and structure in schizophrenia and discussing their role in predicting the transition to psychosis in people at risk. We then address the assessment tools with reference to functioning and social cognition, examining the role of subjective measures and addressing new methods for measuring functional outcomes including technology based approaches. Finally, we briefly review treatment options for cognitive deficits, focusing on cognitive remediation programs, highlighting their effects on brain activity and conclude with the potential benefit of individualized integrated interventions combing cognitive remediation with other approaches.
The formation of large-scale brain networks, and their continual refinement, represent crucial developmental processes that can drive individual differences in cognition and which are associated with multiple neurodevelopmental conditions. But how does this organization arise, and what mechanisms drive diversity in organization? We use generative network modeling to provide a computational framework for understanding neurodevelopmental diversity. Within this framework macroscopic brain organization, complete with spatial embedding of its organization, is an emergent property of a generative wiring equation that optimizes its connectivity by renegotiating its biological costs and topological values continuously over time. The rules that govern these iterative wiring properties are controlled by a set of tightly framed parameters, with subtle differences in these parameters steering network growth towards different neurodiverse outcomes. Regional expression of genes associated with the simulations converge on biological processes and cellular components predominantly involved in synaptic signaling, neuronal projection, catabolic intracellular processes and protein transport. Together, this provides a unifying computational framework for conceptualizing the mechanisms and diversity in neurodevelopment, capable of integrating different levels of analysis—from genes to cognition. The formation of large-scale brain networks represents crucial developmental processes that can drive individual differences in cognition and which are associated with multiple neurodevelopmental conditions. Here, the authors use generative network modelling to provide a computational framework for understanding neurodevelopmental diversity.
In schizophrenia, neurocognitive subtypes can be distinguished based on cognitive performance and they are associated with neuroanatomical alterations. We investigated the existence of cognitive subtypes in shortly medicated recent onset psychosis patients, their underlying gray matter volume patterns and clinical characteristics. We used a K-means algorithm to cluster 108 psychosis patients from the multi-site EU PRONIA (Prognostic tools for early psychosis management) study based on cognitive performance and validated the solution independently (N = 53). Cognitive subgroups and healthy controls (HC; n = 195) were classified based on gray matter volume (GMV) using Support Vector Machine classification. A cognitively spared (N = 67) and impaired (N = 41) subgroup were revealed and partially independently validated (Nspared = 40, Nimpaired = 13). Impaired patients showed significantly increased negative symptomatology (pfdr = 0.003), reduced cognitive performance (pfdr < 0.001) and general functioning (pfdr < 0.035) in comparison to spared patients. Neurocognitive deficits of the impaired subgroup persist in both discovery and validation sample across several domains, including verbal memory and processing speed. A GMV pattern (balanced accuracy = 60.1%, p = 0.01) separating impaired patients from HC revealed increases and decreases across several fronto-temporal-parietal brain areas, including basal ganglia and cerebellum. Cognitive and functional disturbances alongside brain morphological changes in the impaired subgroup are consistent with a neurodevelopmental origin of psychosis. Our findings emphasize the relevance of tailored intervention early in the course of psychosis for patients suffering from the likely stronger neurodevelopmental character of the disease.
Scientific evidence in the field of psychiatry is mainly derived from group-based (“nomothetic”) studies that yield group-aggregated results, while often the need is to answer questions that apply to individuals. Particularly in the presence of great inter-individual differences and temporal complexities, information at the individual-person level may be valuable for personalized treatment decisions, individual predictions and diagnostics. The single-subject study design can be used to make inferences about individual persons. Yet, the single-subject study is not often used in the field of psychiatry. We believe that this is because of a lack of awareness of its value rather than a lack of usefulness or feasibility. In the present paper, we aimed to resolve some common misconceptions and beliefs about single-subject studies by discussing some commonly heard “facts and fictions.” We also discuss some situations in which the single-subject study is more or less appropriate, and the potential of combining single-subject and group-based study designs into one study. While not intending to plea for single-subject studies at the expense of group-based studies, we hope to increase awareness of the value of single-subject research by informing the reader about several aspects of this design, resolving misunderstanding, and providing references for further reading.
The reproducibility of machine-learning analyses in computational psychiatry is a growing concern. In a multimodal neuropsychiatric dataset of antipsychotic-naïve, first-episode schizophrenia patients, we discuss a workflow aimed at reducing bias and overfitting by invoking simulated data in the design process and analysis in two independent machine-learning approaches, one based on a single algorithm and the other incorporating an ensemble of algorithms. We aimed to (1) classify patients from controls to establish the framework, (2) predict short- and long-term treatment response, and (3) validate the methodological framework. We included 138 antipsychotic-naïve, first-episode schizophrenia patients with data on psychopathology, cognition, electrophysiology, and structural magnetic resonance imaging (MRI). Perinatal data and long-term outcome measures were obtained from Danish registers. Short-term treatment response was defined as change in Positive And Negative Syndrome Score (PANSS) after the initial antipsychotic treatment period. Baseline diagnostic classification algorithms also included data from 151 matched controls. Both approaches significantly classified patients from healthy controls with a balanced accuracy of 63.8% and 64.2%, respectively. Post-hoc analyses showed that the classification primarily was driven by the cognitive data. Neither approach predicted short- nor long-term treatment response. Validation of the framework showed that choice of algorithm and parameter settings in the real data was successfully guided by results from the simulated data. In conclusion, this novel approach holds promise as an important step to minimize bias and obtain reliable results with modest sample sizes when independent replication samples are not available.
Background
Abnormal glutamate and gamma-aminobutyric acid (GABA) levels have been found in the early phase of schizophrenia and may underlie cognitive deficits. However, the association between cognitive function and levels of glutamatergic metabolites and GABA has not been investigated in a large group of antipsychotic-naïve patients.
Methods
Fifty-six antipsychotic-naïve patients with schizophrenia or psychotic disorder and 51 healthy controls underwent magnetic resonance spectroscopy to measure glutamate, glutamate+glutamine (glx), and GABA levels in dorsal anterior cingulate cortex (ACC) and glutamate and glx levels in left thalamus. The cognitive domains attention, working memory, and IQ were assessed.
Results
The whole group of antipsychotic-naïve patients had lower levels of GABA in dorsal ACC (p=0.03) and the subgroup of patients with a schizophrenia diagnosis had higher glutamate levels in thalamus (p=0.01), but glx levels in dorsal ACC and thalamus did not differ between groups. Glx levels in dorsal ACC were positively associated with working memory (logarithmically transformed: b=-0.016 (higher score indicates worse performance), p=0.005) and attention (b=0.056, p=0.035) in both patients and healthy controls, although the association with attention did not survive adjustment for multiple comparisons.
Conclusions
The findings suggest a positive association between glutamatergic metabolites and cognitive function that do not differ between patients and healthy controls. Moreover, our data indicate that decreased GABAergic levels in dorsal ACC are involved in schizophrenia and psychotic disorder, whereas increased glutamate levels in thalamus seem implicated in the schizophrenia pathophysiology. The findings imply that first-episode patients with cognitive deficits may gain from glutamate modulating compounds.
Childhood learning difficulties and developmental disorders are common, but progress toward under- standing their underlying brain mechanisms has been slow. Structural neuroimaging, cognitive, and learning data were collected from 479 children (299 boys, ranging in age from 62 to 223 months), 337 of whom had been referred to the study on the basis of learning-related cognitive problems. Machine learning identified different cognitive profiles within the sample, and hold-out cross- validation showed that these profiles were significantly associated with children’s learning ability. The same machine learning approach was applied to cortical morphology data to identify different brain profiles. Hold-out cross-validation demonstrated that these were significantly associ- ated with children’s cognitive profiles. Crucially, these mappings were not one-to-one. The same neural profile could be associated with different cognitive impairments across different children. One possibility is that the organization of some children’s brains is less susceptible to local defi- cits. This was tested by using diffusion-weighted imaging (DWI) to construct whole-brain white- matter connectomes. A simulated attack on each child’s connectome revealed that some brain net- works were strongly organized around highly con- nected hubs. Children with these networks had only selective cognitive impairments or no cogni- tive impairments at all. By contrast, the same at- tacks had a significantly different impact on some children’s networks, because their brain efficiency was less critically dependent on hubs. These children had the most widespread and severe cognitive impairments. On this basis, we propose a new framework in which the nature and mecha- nisms of brain-to-cognition relationships are moderated by the organizational context of the overall network.
The delineation of cognitive subtypes of schizophrenia and bipolar disorder may offer a means of determining shared genetic markers and neuropathology among individuals with these conditions. We systematically reviewed the evidence from published studies reporting the use of data-driven (i.e., unsupervised) clustering methods to delineate cognitive subtypes among adults diagnosed with schizophrenia, schizoaffective disorder, or bipolar disorder. We reviewed 24 studies in total, contributing data to 13 analyses of schizophrenia spectrum patients, 8 analyses of bipolar disorder, and 5 analyses of mixed samples of schizophrenia and bipolar disorder participants. Studies of bipolar disorder most consistently revealed a 3-cluster solution, comprising a subgroup with ‘near-normal’ (cognitively spared) cognition and two other subgroups demonstrating graded deficits across cognitive domains. In contrast, there was no clear consensus regarding the number of cognitive subtypes among studies of cognitive subtypes in schizophrenia, while four of the five studies of mixed diagnostic groups reported a 4-cluster solution. Common to all cluster solutions was a severe cognitive deficit subtype with cognitive impairments of moderate to large effect size relative to healthy controls. Our review highlights several key factors (e.g., symptom profile, sample size, statistical procedures, and cognitive domains examined) that may influence the results of data-driven clustering methods, and which were largely inconsistent across the studies reviewed. This synthesis of findings suggests caution should be exercised when interpreting the utility of particular cognitive subtypes for biological investigation, and demonstrates much heterogeneity among studies using unsupervised clustering approaches to cognitive subtyping within and across the psychosis spectrum.
Deficits in information processing and cognition are among the most robust findings in schizophrenia patients. Previous efforts to translate group-level deficits into clinically relevant and individualized information have, however, been non-successful, which is possibly explained by biologically different disease subgroups. We applied machine learning algorithms on measures of electrophysiology and cognition to identify potential subgroups of schizophrenia. Next, we explored subgroup differences regarding treatment response. Sixty-six antipsychotic-naive first-episode schizophrenia patients and sixty-five healthy controls underwent extensive electrophysiological and neurocognitive test batteries. Patients were assessed on the Positive and Negative Syndrome Scale (PANSS) before and after 6 weeks of monotherapy with the relatively selective D2 receptor antagonist, amisulpride (280.3±159 mg per day). A reduced principal component space based on 19 electrophysiological variables and 26 cognitive variables was used as input for a Gaussian mixture model to identify subgroups of patients. With support vector machines, we explored the relation between PANSS subscores and the identified subgroups. We identified two statistically distinct subgroups of patients. We found no significant baseline psychopathological differences between these subgroups, but the effect of treatment in the groups was predicted with an accuracy of 74.3% (P=0.003). In conclusion, electrophysiology and cognition data may be used to classify subgroups of schizophrenia patients. The two distinct subgroups, which we identified, were psychopathologically inseparable before treatment, yet their response to dopaminergic blockade was predicted with significant accuracy. This proof of principle encourages further endeavors to apply data-driven, multivariate and multimodal models to facilitate progress from symptom-based psychiatry toward individualized treatment regimens.
There is some evidence that cognitive flexibility negatively impacts cognitive restructuring skill acquisition with brief training; however, there is little understanding of how this relates to learning cognitive restructuring over the course of a therapy program, and how it relates to overall treatment outcome. This study assessed the impact of cognitive flexibility on cognitive restructuring skill acquisition following group CBT, and on treatment outcome, along with changes in cognitive flexibility over treatment. 44 older participants with anxiety and depression completed self-report and neuropsychological tests of cognitive flexibility and a clinical interview at pre and post-treatment. Qualitative and quantitative measures of cognitive restructuring were completed at post-treatment. Pre-treatment cognitive flexibility was not related to the quality of cognitive restructuring at post-treatment or overall treatment outcome. However, it did predict reduction in subjective units of distress from using cognitive restructuring and therapist ratings of cognitive restructuring ability at post-treatment. Few participants showed changes in cognitive flexibility over treatment. Those with poorer cognitive flexibility may not find cognitive restructuring as useful to alleviate emotional distress as those with better cognitive flexibility. However, those with poorer cognitive flexibility can still benefit from standardised CBT, even if their use of cognitive restructuring is less effective.
Bipolar and schizophrenia network for intermediate phenotypes is a network of investigator-driven laboratories focused on
developing phenotypes, genotypes, and biomarkers for psychosis. Over the last 5 years, the consortium has accomplished a dense
phenotyping protocol using probands with a lifetime history of psychosis, their relatives, and healthy controls. This has
established a library of biomarker information on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder
with psychosis. The founding goal of establishing disease biomarkers for current psychotic diagnoses has been poorly met,
because the cognitive, electrophysiologic, eye movement, and brain imaging biomarkers did not regularly discriminate individuals
with different DSM psychosis diagnoses. In future, we will use this biomarker information to establish a pathway to biomarker-based
classification in psychoses.
Cognitive dysfunction is a well-established feature of schizophrenia, and there is evidence suggesting that cognitive deficits are secondary to abnormal neurodevelopment leading to problems in acquiring such abilities. However, it is not clear whether there is also a decline in cognitive performance over, or after, the onset of psychosis. Our objective was to quantitatively examine the longitudinal changes in cognitive function in patients who presented with first-episode psychosis (FEP), ultra-high risk (UHR) for psychosis, and controls. Electronic databases were searched for the studies published between January 1987 and February 2013. All studies reporting longitudinal cognitive data in FEP and UHR subjects were retrieved. We conducted meta-analyses of 25 studies including 905 patients with FEP, 560 patients at UHR, and 405 healthy controls. The cognitive performances of FEP, UHR, and healthy controls all significantly improved over time. There was no publication bias, and distributions of effect sizes were very homogenous. In FEP, the degree of improvement in verbal working memory and executive functions was significantly associated with reduction in negative symptoms. There was no evidence of cognitive decline in patients with UHR and FEP. In contrast, the cognitive performances of both groups improved at follow-up. These findings suggest that cognitive deficits are already established before the prodromal phases of psychosis. These data support the neurodevelopmental model rather than neurodegenerative and related staging models of schizophrenia.
Background
Current diagnostic systems for mental disorders rely upon presenting signs and symptoms, with the result that current definitions do not adequately reflect relevant neurobiological and behavioral systems - impeding not only research on etiology and pathophysiology but also the development of new treatments.
Discussion
The National Institute of Mental Health began the Research Domain Criteria (RDoC) project in 2009 to develop a research classification system for mental disorders based upon dimensions of neurobiology and observable behavior. RDoC supports research to explicate fundamental biobehavioral dimensions that cut across current heterogeneous disorder categories. We summarize the rationale, status and long-term goals of RDoC, outline challenges in developing a research classification system (such as construct validity and a suitable process for updating the framework) and discuss seven distinct differences in conception and emphasis from current psychiatric nosologies.
Summary
Future diagnostic systems cannot reflect ongoing advances in genetics, neuroscience and cognitive science until a literature organized around these disciplines is available to inform the revision efforts. The goal of the RDoC project is to provide a framework for research to transform the approach to the nosology of mental disorders.
A recent meta-analysis identified processing speed inefficiency as the largest single cognitive impairment in schizophrenia. However, the effect of potential moderator variables, such as medication status and severity of illness, remained unclear. The authors present an extended meta-analysis of processing speed and other specific cognitive functions in schizophrenia and examine the role of potential moderator variables.
In addition to the studies identified in the original analysis, subsequently published articles were identified via systematic searches of MEDLINE and PsycINFO for the period from May 2006 to January 2009. The authors extracted data for potential moderator variables, including publication year; severity of illness; chlorpromazine equivalent daily dose; and mean IQ, mean age, and sample size for each study. Effect sizes were calculated for all measures, and meta-influence and homogeneity analyses were conducted.
Eleven studies were added to the original analysis, increasing the schizophrenia sample size from 1,915 to 4,135. The largest effect size was for coding tasks (g=-1.50), followed by category fluency (g=-1.31). However, for coding tasks, variation in effect size magnitude attributable to heterogeneity was substantial. Metaregression analyses indicated that three moderator variables were related to coding task effect size: publication year, IQ difference from comparison subjects, and chlorpromazine equivalent daily dose. There was a difference of 0.8 effect size units between studies with low compared with high chlorpromazine equivalent daily dose. No significant relationships were found between any moderators and the other cognitive tasks included in the meta-analysis.
The processing speed impairment in schizophrenia is substantially affected by several moderating factors, in particular antipsychotic medication dosage.
After more than 12 years of development, the ninth edition of the Present State Examination (PSE-9) was published, together with associated instruments and computer algorithm, in 1974. The system has now been expanded, in the framework of the World Health Organization/Alcohol, Drug Abuse, and Mental Health Administration Joint Project on Standardization of Diagnosis and Classification, and is being tested with the aim of developing a comprehensive procedure for clinical examination that is also capable of generating many of the categories of the International Classification of Diseases, 10th edition, and the Diagnostic and Statistical Manual of Mental Disorders, revised third edition. The new system is known as SCAN (Schedules for Clinical Assessment in Neuropsychiatry). It includes the 10th edition of the PSE as one of its core schedules, preliminary tests of which have suggested that reliability is similar to that of PSE-9. SCAN is being field tested in 20 centers in 11 countries. A final version is expected to be available in January 1990.
The authors investigated the reliability and convergent and discriminant validity of the DSM-IV Global Assessment of Functioning Scale and two experimental DSM-IV axis V global rating scales, the Global Assessment of Relational Functioning Scale and the Social and Occupational Functioning Assessment Scale.
Forty-four patients admitted to a university-based outpatient community clinic were rated by trained clinicians on the three DSM-IV axis V scales. Patients also completed self-report measures of DSM-IV symptoms as well as measures of relational, social, and occupational functioning.
The Global Assessment of Functioning Scale, Global Assessment of Relational Functioning Scale, and Social and Occupational Functioning Assessment Scale all exhibited very high levels of interrater reliability. Factor analysis revealed that the Global Assessment of Relational Functioning Scale and the Social and Occupational Functioning Assessment Scale are each more related to the Global Assessment of Functioning Scale individually than they are to each other. The Global Assessment of Functioning Scale was significantly related to concurrent patient responses on the SCL-90-R global severity index. The Social and Occupational Functioning Assessment Scale was significantly related to concurrent patient responses on the SCL-90-R global severity index and to a greater degree with both the Social Adjustment Scale global score and the Inventory of Interpersonal Problems total score. Although the Global Assessment of Relational Functioning Scale was not significantly related to any of the three self-report measures, it was related to the presence of clinician-rated axis II pathology.
The three axis V scales can be scored reliably. The Global Assessment of Relational Functioning Scale and the Social and Occupational Functioning Assessment Scale evaluate different constructs. These findings support the validity of the Global Assessment of Functioning Scale as a scale of global psychopathology; the Social and Occupational Functioning Assessment Scale as a measure of problems in social, occupational, and interpersonal functioning; and the Global Assessment of Relational Functioning Scale as an index of personality pathology. The authors discuss further refinement and use of the three axis V measures in treatment research.
Performance on the Wechsler Adult Intelligence Scale-III (WAIS-III) was compared to performance on the Wechsler Abbreviated Scale of Intelligence (WASI), as well as short form estimations of intellectual functioning derived from WAIS-III performance, in a mixed clinical sample of 72 participants. The WASI verbal IQ (VIQ) score was significantly higher than the WAIS-III VIQ, whereas performance IQ (PIQ) estimates all differed from actual WAIS-III PIQ and full scale IQ (FSIQ). Correlations of WAIS-III scores with WASI scores were consistently lower than were correlations between the WASI-III and all other short forms. Although maintaining administration times of 15 minutesfor a two-subtest FSIQ and 30 minutes for a four-subtest FSIQ, the WASI did not consistently demonstrate desirable accuracy in predicting scores obtained from the WAIS-III. The results suggest that clinicians should use the WASI cautiously if at all, especially when accurate estimates of individuals' WAIS-III results are needed.
Importance:
Few studies have estimated the lifetime incidence of mental health disorders and the association with socioeconomic functioning.
Objective:
To investigate whether the lifetime incidence of treated mental health disorders is substantially higher than previously reported and estimate associations with long-term socioeconomic difficulties.
Design, setting, and participants:
This nationwide population-based register linkage study includes a randomly selected sample of 1.5 million individuals from the population of Denmark from 1995 to 2018. Data were analyzed from May 2022 to March 2023.
Main outcomes and measures:
Lifetime incidence of any treated mental health disorder in the general population was estimated from birth to age 100 years taking into account the competing risk of all-cause death and associations with socioeconomic functioning. Register measures were (1) from hospitals, a diagnosis of any mental health disorder at an inpatient/outpatient hospital contact; (2) from hospitals and prescription statistics, any mental health disorder/psychotropic prescription, including a hospital-contact diagnosis, or any psychotropic medication prescribed by physicians, including general practitioners or private psychiatrists; and (3) socioeconomic functioning as indicated by highest educational achievement, employment, income, residential status, and marital status.
Results:
Among a sample of 462 864 individuals with any mental health disorder, the median (IQR) age was 36.6 years (21.0-53.6 years), 233 747 (50.5%) were male, and 229 117 (49.5%) were female. Of these, 112 641 were registered with a hospital-contact mental health disorder diagnosis and 422 080 with a prescription of psychotropic medication. The cumulative incidence of a hospital-contact mental health disorder diagnosis was 29.0% (95% CI, 28.8-29.1), 31.8% (95% CI, 31.6-32.0) for females, and 26.1% (95% CI, 25.9-26.3) for males. When also considering psychotropic prescriptions, the cumulative incidence of any mental health disorder/psychotropic prescription was 82.6% (95% CI, 82.4-82.6), 87.5% (95% CI, 87.4-87.7) for females, and 76.7% (95% CI, 76.5-76.8) for males. Socioeconomic difficulties were associated with mental health disorder/psychotropic prescriptions, including lower income (hazard ratio [HR], 1.55; 95% CI, 1.53-1.56), increased unemployment or disability benefit (HR, 2.50; 95% CI, 2.47-2.53), and a greater likelihood of living alone (HR, 1.78; 95% CI, 1.76-1.80) and being unmarried (HR, 2.02; 95% CI, 2.01-2.04) during long-term follow-up. These rates were confirmed in 4 sensitivity analyses with the lowest being 74.8% (95% CI, 74.7-75.0) (1) by using varying exclusion periods, (2) by excluding prescriptions of anxiolytics and quetiapine that may be used for off-label indications, (3) by defining any mental health disorder/psychotropic prescription as any hospital-contact mental health disorder diagnosis or any psychotropic medication prescribed at least 2 times, and (4) by excluding individuals with somatic diagnoses for which psychotropics may be prescribed off-label.
Conclusions and relevance:
This registry study of data from a large representative sample of the Danish population showed that the majority of individuals either received a diagnosis of a mental health disorder or were prescribed psychotropic medication during their lifetime, which was associated with subsequent socioeconomic difficulties. These findings may help change our understanding of normalcy and mental illness, reduce stigmatization, and further prompt rethinking the primary prevention of mental illness and future mental health clinical resources.
Studies across schizophrenia (SZ) and bipolar disorder (BD) indicate common transdiagnostic neurocognitive subgroups. However, existing studies of patients with long-term illness precludes insight into whether impairments result from effects of chronic illness, medication or other factors. This study aimed to investigate whether neurocognitive subgroups across SZ and BD can be demonstrated during early illness stages. Data from overlapping neuropsychological tests were pooled from cohort studies of antipsychotic-naïve patients with first-episode SZ spectrum disorders (n = 150), recently diagnosed BD (n = 189) or healthy controls (HC) (n = 280). Hierarchical cluster analysis was conducted to examine if transdiagnostic subgroups could be identified based on the neurocognitive profile. Patterns of cognitive impairments and patient characteristics across subgroups were examined. Patients could be clustered into two, three and four subgroups, of which the three-cluster solution (with 83% accuracy) was selected for posthoc analyses. This solution revealed a subgroup covering 39% of patients (predominantly BD) who were cognitively relatively intact, a subgroup of 33% of patients (more equal distributions of SZ and BD) displaying selective deficits, particularly in working memory and processing speed, and a subgroup of 28% (mainly SZ) with global impairments. The globally impaired group exhibited lower estimated premorbid intelligence than the other subgroups. Globally impaired BD patients also showed more functional disability than cognitively relatively intact patients. No differences were observed across subgroups in symptoms or medications. Neurocognitive results can be understood by clustering analysis with similar clustering solutions occurring across diagnoses. The subgroups were not explained by clinical symptoms or medication, suggesting neurodevelopmental origins.
Introduction
Cognitive deficits are present in some, but not all patients with schizophrenia-spectrum disorders (SSD). We and others have demonstrated three cognitive clusters: cognitively intact patients, patients with deficits in a few domains and those with global cognitive deficits. This study aimed to identify cognitive subtypes of early-phase SSD with matched controls as a reference group, and evaluated cognitive subgroups regarding clinical and brain volumetric measures.
Methods
Eighty-six early-phase SSD patients were included. Hierarchical cluster analysis was conducted using global performance on the Brief Assessment of Cognition in Schizophrenia (BACS). Cognitive subgroups were subsequently related to clinical and brain volumetric measures (cortical, subcortical and cortical thickness) using ANCOVA.
Results
Three distinct cognitive clusters emerged: relative to controls we found one cluster of patients with preserved cognition (n = 25), one moderately impaired cluster (n = 38) and one severely impaired cluster (n = 23). Cognitive subgroups were characterized by differences in volume of the left postcentral gyrus, left middle caudal frontal gyrus and left insula, while differences in cortical thickness were predominantly found in fronto-parietal regions. No differences were demonstrated in subcortical brain volume.
Discussion
Current results replicate the existence of three distinct cognitive subgroups including one relatively large group with preserved cognitive function. Cognitive subgroups were characterized by differences in cortical regional brain volume and cortical thickness, suggesting associations with cortical, but not subcortical development and cognitive functioning such as attention, executive functions and speed of processing.
Objective:
Poor cognitive flexibility has been highlighted in patients with anorexia nervosa (AN), contributing to the development and maintenance of symptoms. The aim of the present study is to investigate how enhanced cognitive flexibility is involved in treatment outcomes in patients with AN.
Method:
One hundred thirty female out-patients treated for AN have been assessed at baseline and after 4 months of treatment. Path analyses were used to investigate the mediating role of cognitive flexibility, measured through the Brixton test, on a wide range of outcomes: body mass index, eating disorder symptoms, daily life functioning, anxiety, depression, emotions, self-rated silhouette.
Results:
Cognitive flexibility was improved during treatment, and enhanced cognitive flexibility explains a significant part of level of the improvement in daily life functioning (26%), reduction of eating disorder symptoms (18%) and reduction of depressive symptoms (17%). Others outcomes were also improved, but these improvements were not mediated by cognitive flexibility.
Conclusions:
Results suggest that enhancing cognitive flexibility could help reduce rigid cognitive and behavioural patterns involved in AN, thus improving everyday functioning and clinical severity. Further studies combining different types of cognitive flexibility evaluation as well as neuroimaging may be necessary to better establish which of its aspects are involved in patients' improvement.
Cognitive dysfunction is a core feature of schizophrenia. The subtyping of cognitive performance in schizophrenia may aid the refinement of disease heterogeneity. The literature on cognitive subtyping in schizophrenia, however, is limited by variable methodologies and neuropsychological tasks, lack of validation, and paucity of studies examining longitudinal stability of profiles. It is also unclear if cognitive profiles represent a single linear severity continuum or unique cognitive subtypes. Cognitive performance measured with the Brief Assessment of Cognition in Schizophrenia was analyzed in schizophrenia patients (n = 767). Healthy controls (n = 1012) were included as reference group. Latent profile analysis was performed in a schizophrenia discovery cohort (n = 659) and replicated in an independent cohort (n = 108). Longitudinal stability of cognitive profiles was evaluated with latent transition analysis in a 10-week follow-up cohort. Confirmatory factor analysis (CFA) was carried out to investigate if cognitive profiles represent a unidimensional structure. A 4-profile solution was obtained from the discovery cohort and replicated in an independent cohort. It comprised of a “less-impaired” cognitive subtype, 2 subtypes with “intermediate cognitive impairment” differentiated by executive function performance, and a “globally impaired” cognitive subtype. This solution showed relative stability across time. CFA revealed that cognitive profiles are better explained by distinct meaningful profiles than a severity linear continuum. Associations between profiles and negative symptoms were observed. The subtyping of schizophrenia patients based on cognitive performance and its associations with symptomatology may aid phenotype refinement, mapping of specific biological mechanisms, and tailored clinical treatments.
Individuals at ultra-high risk (UHR) for psychosis suffer significant
cognitive deficits that can hamper functional recovery1.
The beneficial effect of cognitive remediation on cognition and
functioning is documented in individuals with established psychosis2,3,
but little is known about the effect of this intervention
in those at UHR for psychosis.
Cognitive remediation may potentially be more beneficial in
the psychosis UHR state than in more advanced illness stages,
owing to the potential of greater brain plasticity4,5. For the same
reason, reduced doses may be sufficient to produce change.
The randomized, assessor-blinded, parallel-group, superiority
clinical trial called FOCUS is the hitherto largest trial to report
on the feasibility and efficacy of intensive neurocognitive and social
cognitive remediation in the UHR state.
Participants aged 18-40 years who fulfilled the Comprehensive
Assessment of At Risk Mental States (CAARMS) UHR criteria
were recruited to the FOCUS trial from the psychiatric in- and
outpatient facilities in the greater catchment area of Copenhagen,
Denmark from April 2014 to December 20176.
On completion of baseline assessments, participants were
randomly assigned to either 20 weeks of cognitive remediation
as an add-on to treatment as usual (TAU+CR) or to treatment as
usual alone (TAU). Randomization was stratified by current use
of antipsychotic medication (yes/no) and IQ score (≤100/>100).
The CR intervention comprised two hours of group training
(one hour of neurocognitive training, with subsequent 15 min
of bridging session, and one hour of social cognitive training)
once a week for a total of 20 weeks. For this group training, we
used the Neuropsychological Educational Approach to Cognitive
Remediation (NEAR)7 and the Social Cognition and Interaction
Training (SCIT)8 manuals. Additionally, the participants
received 12 individual sessions with a cognitive-behavioral format
designed to maximize the transfer of the effect of the CR to
their daily lives. The study report the main findings along with baseline predictors of cognitive improvements.
Objective:
Cognitive compensatory interventions aim to alleviate psychosocial disability by targeting functioning directly using aids and strategies, thereby minimizing the impact of cognitive impairment. The aim was to conduct a systematic review and meta-analysis of cognitive compensatory interventions for psychosis by examining the effects on functioning and symptoms, and exploring whether intervention factors, study design, and age influenced effect sizes.
Methods:
Electronic databases (Ovid Medline, PsychINFO) were searched up to October 2018. Records obtained through electronic and manual searches were screened independently by two reviewers according to selection criteria. Data were extracted to calculate estimated effects (Hedge's g) of treatment on functioning and symptoms at post-intervention and follow-up. Study quality was assessed using Cochrane Collaboration's risk of bias tool.
Results:
Twenty-six studies, from 25 independent randomized controlled trials (RCTs) were included in the meta-analysis (1654 participants, mean age = 38.9 years, 64% male). Meta-analysis revealed a medium effect of compensatory interventions on functioning compared to control conditions (Hedge's g = 0.46, 95% CI = 0.33, 0.60, P < .001), with evidence of relative durability at follow-up (Hedge's g = 0.36, 95% CI = 0.19, 0.54, P < .001). Analysis also revealed small significant effects of cognitive compensatory treatment on negative, positive, and general psychiatric symptoms, but not depressive symptoms. Estimated effects did not significantly vary according to treatment factors (ie, compensatory approach, dosage), delivery method (ie, individual/group), age, or risk of bias. Longer treatment length was associated with larger effect sizes for functioning outcomes. No evidence of publication bias was identified.
Conclusion:
Cognitive compensatory interventions are associated with robust, durable improvements in functioning in people with psychotic illnesses.
The current study examined the contribution of baseline neuropsychological functioning to the prediction of antidepressant outcome with cognitive behavioral therapy (CBT) for Major Depressive Disorder (MDD). We hypothesized that depressed participants who were more neurocognitively intact and had less rigid, negative thinking would respond better to CBT. Thirty-one MDD patients completed a comprehensive neuropsychological battery before initiation of CBT. A subgroup also completed a probabilistic reversal learning task. Depression severity was assessed with the Beck Depression Inventory (BDI); rigid, negative thinking was assessed with the Dysfunctional Attitudes Scale (DAS) and the Automatic Thoughts Questionnaire (ATQ) throughout treatment. Remitters were compared to non-remitters. Paradoxically, eventual remitters performed generally worse across the neuropsychological battery considered as a whole. Univariate testing showed a significant difference on only a single measure, the Continuous Performance Test d', when corrected for multiple comparisons. Baseline rigid, negative thinking did not predict treatment outcome. Results suggest that the structure of CBT may particularly benefit individuals with mild depression-related neurocognitive difficulties during a depressive episode. Further research is needed to examine these patient characteristics and their potential contribution to the mechanisms of CBT efficacy.
Aim:
To make a thorough characterization of the co-morbidity, psychopathology and demographics in the first Danish ultra high-risk (UHR) sample.
Method:
Forty-two UHR subjects went through comprehensive interviews assessing their psychopathology, psychiatric disorders, substance use and family history of psychiatric disorders.
Results:
All UHR subjects met the criteria of at least 1 axis I diagnosis in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) and met on average four diagnoses (both axis I and II), mostly within the areas of depression, anxiety and substance abuse. A total of 48% had schizotypal personality disorder and 19% had borderline personality disorder. Level of functioning was low with a mean score on the Social and Occupational Functioning Assessment Scale corresponding to "major impairment in several areas," and mean scores in the Global Functioning: Social and Role scales between "moderate impairment in social functioning" and "very serious impairment independently." Forty-seven percent were unemployed and 29% on sick leave. Fifty-five percent relied financially on public support.
Conclusion:
As seen in previous UHR populations, Danish UHR subjects had low function socio-economically and met criteria of several psychiatric diagnoses, suggesting that they require pharmacological and non-pharmacological psychiatric treatment as well as vocational and educational guidance and support.
Objective:
Neurocognition is known to impact functioning in individuals at ultrahigh risk (UHR) for psychosis, but studies investigating potential mediators of this relationship are scarce. Building on evidence from schizophrenia spectrum disorders, the study tested whether negative symptoms and social skills act as mediators between neurocognition and functional outcome in UHR individuals.
Methods:
Ultrahigh risk participants (N = 84) underwent neurocognitive testing using the Brief Assessment of Cognition in Schizophrenia. Social skills and negative symptoms were assessed using the High-Risk Social Challenge task and the Scale for the Assessment of Negative Symptoms respectively. Four instruments were used to assess overall functioning, and one instrument assessed quality of life encompassing social functioning.
Results:
The cross-sectional analyses revealed that neurocognition was related to the measures of functioning. Negative symptoms mediated the relationship between neurocognition and four of the five measures of functioning. We did not find social skills to mediate between neurocognition and functioning.
Conclusion:
Negative symptoms appear to mediate the relationship between neurocognition and functional outcome in UHR individuals, but the finding needs to be confirmed and extended to longitudinal studies. This underscores the importance of focusing on both neurocognition and negative symptoms when aiming at improving the functional outcome of UHR individuals.
Psychosis is a debilitating mental health condition affecting approximately 4 persons per 1000. Cognitive behavioural therapy for psychosis (CBTp) has been shown to be an effective treatment for psychosis and is recommended by several national guidelines. CBTp does not work equally well with everyone, however, with some 50% of clients receiving little benefit. This review sets out to systematically assess the literature and methodological quality of a number of studies, which examine factors predicting successful outcome in CBTp. The databases CINAHL, Cochrane, EBSCO, EMBASE, ISI Web of Science, MEDLINE (Ovid), PsycARTICLES, PsycINFO, PubMed, and Scopus were electronically searched. English language articles in peer reviewed journals were reviewed. Search terms “psychosis”, “psychotic disorder”, “cognitive behavioural therapy”, “cognitive therapy”, “randomised controlled trial”, “predictor”, and “treatment outcome” in various combinations were used as needed. Only randomised controlled trials (RCTs) were included. Results suggest that female gender, older age, and higher clinical insight at baseline, each predicted better outcome in CBT interventions with psychotic patients, as did a shorter duration of the illness, and higher educational attainment. Several other factors, such as higher symptom severity at baseline, were suggestive of predictive capacity but further research to clarify was indicated. Providers of mental healthcare should consider these findings when offering CBTp. The onus is also on healthcare providers to better equip non-responders to CBTp. Further investigation into a limited number of predictive factors, with an agreed set of outcome measures, would allow future researchers more direct comparisons between studies.
This article describes the National Institute of Mental Health's Research Domain Criteria (RDoC) initiative. The description includes background, rationale, goals, and the way the initiative has been developed and organized. The central RDoC concepts are summarized and the current matrix of constructs that have been vetted by workshops of extramural scientists is depicted. A number of theoretical and methodological issues that can arise in connection with the nature of RDoC constructs are highlighted: subjectivism and heterophenomenology, desynchrony and theoretical neutrality among units of analysis, theoretical reductionism, endophenotypes, biomarkers, neural circuits, construct “grain size,” and analytic challenges. The importance of linking RDoC constructs to psychiatric clinical problems is discussed. Some pragmatics of incorporating RDoC concepts into applications for NIMH research funding are considered, including sampling design.
As highlighted by articles in the current special issue, the RDoC initiative holds promise for advancing understanding of mental health problems. However, the initiative is at its early stages and it remains unclear what level of progress can be achieved and how quickly. In this closing article, we identify major challenges facing RDoC and propose concrete approaches to addressing these challenges, including (a) clearer specification of clinical problems for study, with use of symptom dimensions from integrative dimensional models of psychopathology as provisional, modifiable referents; (b) encouragement of research on a distinct set of traits corresponding to process constructs from the RDoC matrix—those represented across animal, child temperament, and adult personality literatures—to serve as interfaces between matrix constructs and clinical problems; (c) an emphasis in the near term on use of proximal units of analysis in RDoC studies—in particular, on physiological, behavioral, and self-report measures of matrix constructs (examined as states or traits, or both); (d) inclusion of a clear ontogenetic-developmental component in RDoC research projects; (e) routine analysis of the psychometric properties of nonreport (e.g., physiological, task-behavioral) variables, including systematic evaluation of their reliability and convergent-discriminant validity; (f) modification of existing grant review criteria to prioritize replication and synergy in RDoC investigative work; and (g) creation of a cumulative data network system (RDoC–DataWeb) to encourage and facilitate coordination of research efforts across RDoC research groups.
The Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS), and the Positive and Negative Syndrome Scale for Schizophrenia (PANSS) are the most widely used schizophrenia symptom rating scales, but despite their co-existence for 25years no easily usable between-scale conversion mechanism exists. The aim of this study was to provide equations for between-scale symptom rating conversions. Two-hundred-and-five schizophrenia patients [mean age±SD=39.5±11.6, 156 males] were assessed with the SANS, SAPS, and PANSS. Pearson's correlations between symptom scores from each of the scales were computed. Linear regression analyses, on data from 176 randomly selected patients, were performed to derive equations for converting ratings between the scales. Intraclass correlations, on data from the remaining 29 patients, not part of the regression analyses, were performed to determine rating conversion accuracy. Between-scale positive and negative symptom ratings were highly correlated. Intraclass correlations between the original positive and negative symptom ratings and those obtained via conversion of alternative ratings using the conversion equations were moderate to high (ICCs=0.65 to 0.91). Regression-based equations may be useful for conversion between schizophrenia symptom severity as measured by the SANS/SAPS and PANSS, though additional validation is warranted. This study's conversion equations, implemented at http:/converteasy.org, may aid in the comparison of medication efficacy studies, in meta- and mega-analyses examining symptoms as moderator variables, and in retrospective combination of symptom data in multi-center data sharing projects that need to pool symptom rating data when such data are obtained using different scales.
The self-organizing map (SOM) is an automatic data-analysis method. It is widely applied to clustering problems and data exploration in industry, finance, natural sciences, and linguistics. The most extensive applications, exemplified in this paper, can be found in the management of massive textual databases and in bioinformatics. The SOM is related to the classical vector quantization (VQ), which is used extensively in digital signal processing and transmission. Like in VQ, the SOM represents a distribution of input data items using a finite set of models. In the SOM, however, these models are automatically associated with the nodes of a regular (usually two-dimensional) grid in an orderly fashion such that more similar models become automatically associated with nodes that are adjacent in the grid, whereas less similar models are situated farther away from each other in the grid. This organization, a kind of similarity diagram of the models, makes it possible to obtain an insight into the topographic relationships of data, especially of high-dimensional data items. If the data items belong to certain predetermined classes, the models (and the nodes) can be calibrated according to these classes. An unknown input item is then classified according to that node, the model of which is most similar with it in some metric used in the construction of the SOM. A new finding introduced in this paper is that an input item can even more accurately be represented by a linear mixture of a few best-matching models. This becomes possible by a least-squares fitting procedure where the coefficients in the linear mixture of models are constrained to nonnegative values.
Morosini P-L, Magliano L, Brambilla L, Ugolini S, Pioli R. Development, reliability and acceptability of a new version of the DSM-IV Social and Occupational Functioning Assessment Scale (SOFAS) to assess routine social funtioning.
Acta Psychiatr Scand 2000: 101:323–329. © Munksgaard 2000.
Objective: Development of a scale to assess patients' social functioning, the Personal and Social Performance scale (PSP).
Method: PSP has been developed through focus groups and reliability studies on the basis of the social functioning component of the DSM-TV Social and Occupational Functioning Assessment Scale (SOFAS). The last reliability study was carried out by 39 workers with different professional roles on a sample of 61 psychiatric patients admitted to the rehabilitation unit. Each patient was rated independently on the scale by the two workers who knew them best.
Results: The PSP is a 100–point single-item rating scale, subdivided into 10 equal intervals. The ratings are based mainly on the assessment of patient's functioning in four main areas: 1) socially useful activities; 2) personal and social relationships; 3) self-care; and 4) disturbing and aggressive behaviours. Operational criteria to rate the levels of disabilities have been defined for the above-mentioned areas. Excellent inter-rater reliability was also obtained in less educated workers.
Conclusion: Compared to SOFAS, PSP has better face validity and psychometric properties. It was found to be an acceptable, quick and valid measure of patients' personal and social functioning.
Various schizophrenic symptoms are suggested to be linked to a dysfunction of the brain reward system. Several studies have found alterations in the reward processing in patients with schizophrenia; however, most previous findings might be confounded by medication effects.
Thirty-one antipsychotic-naïve schizophrenia patients and 31 age- and gender-matched healthy control subjects were examined with functional magnetic resonance imaging while playing a variant of the monetary incentive delay task. The task variant made it possible to separate overall salience (defined as arousing events) into behavioral salience (events where a predicted reward requires performance) and valence anticipation (the anticipation of a monetarily significant outcome). Furthermore, the evaluation of monetary gain and loss was assessed.
During reward anticipation, patients had a significant attenuation of the activation in ventral tegmentum, ventral striatum, and anterior cingulate cortex during presentation of salient cues. This signal attenuation in ventral striatum was correlated with the degree of positive symptoms. Signal attenuation was most pronounced for behavioral salience and nonsignificant for value anticipation. Furthermore, patients showed a changed activation pattern during outcome evaluation in right prefrontal cortex.
Our results suggest that changes during reward anticipation in schizophrenia are present from the beginning of the disease. This supports a possible involvement of reward disturbances in the pathophysiology of schizophrenia. The most pronounced changes were seen in relation to overall salience. In ventral striatum these changes were associated with the degree of positive symptoms.
The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized
measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale
(PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS
was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative
symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring
positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the
four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely
correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually
exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with
antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both
typological and dimensional assessment.
Despite growing evidence of the effectiveness of cognitive-behavioural therapy (CBT) for psychosis, typically only about 50% of patients show a positive response to treatment. This paper reports the first comprehensive investigation of factors which predict treatment outcome.
In a randomised controlled trial of CBT for medication-resistant psychosis (see Part I) measures were taken at baseline of demographic, clinical and cognitive variables. Changes over time were assessed on the Brief Psychiatric Rating Scale and the relationship between potential predictor variables and outcome was investigated using analysis of variance and covariance.
A number of baseline variables were identified as predictors of good outcome in the CBT group. Key predictors were a response indicating cognitive flexibility concerning delusions (P = 0.005) and the number of recent admissions (P = 0.002). Outcome was less predictable in the control group and was not predicted by any cognitive variable.
Good outcome is strongly predicted in patients with persistent delusions by a cognitive measure, while this was not the case in controls. Thus we argue that positive outcome in CBT is due in part to specific effects on delusional thinking.
Development of a scale to assess patients' social functioning, the Personal and Social Performance scale (PSP).
PSP has been developed through focus groups and reliability studies on the basis of the social functioning component of the DSM-IV Social and Occupational Functioning Assessment Scale (SOFAS). The last reliability study was carried out by 39 workers with different professional roles on a sample of 61 psychiatric patients admitted to the rehabilitation unit. Each patient was rated independently on the scale by the two workers who knew them best.
The PSP is a 100-point single-item rating scale, subdivided into 10 equal intervals. The ratings are based mainly on the assessment of patient's functioning in four main areas: 1) socially useful activities; 2) personal and social relationships; 3) self-care; and 4) disturbing and aggressive behaviours. Operational criteria to rate the levels of disabilities have been defined for the above-mentioned areas. Excellent inter-rater reliability was also obtained in less educated workers.
Compared to SOFAS, PSP has better face validity and psychometric properties. It was found to be an acceptable, quick and valid measure of patients' personal and social functioning.
Studies of neurocognitive function in patients with schizophrenia use widely variable assessment techniques. Clinical trials assessing the cognitive enhancing effect of new medications have used neurocognitive assessment batteries that differed in content, length and administration procedures. The Brief Assessment of Cognition in Schizophrenia (BACS) is a newly developed instrument that assesses the aspects of cognition found to be most impaired and most strongly correlated with outcome in patients with schizophrenia. The BACS requires less than 35 min to complete in patients with schizophrenia, yields a high completion rate in these patients, and has high reliability. The BACS was found to be as sensitive to cognitive impairment in patients with schizophrenia as a standard battery of tests that required over 2 h to administer. Compared to healthy controls matched for age and parental education, patients with schizophrenia performed 1.49 standard deviations lower on a composite score calculated from the BACS and 1.61 standard deviations lower on a composite score calculated from the standard battery. The BACS composite scores were highly correlated with the standard battery composite scores in patients (r=0.76) and healthy controls (r=0.90). These psychometric properties make the BACS a promising tool for assessing cognition repeatedly in patients with schizophrenia, especially in clinical trials of cognitive enhancement.
The concurrent, construct and discriminative validity of the World Health Organization's Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) were examined in a multi-site international study.
One thousand and 47 participants, recruited from drug treatment (n = 350) and primary health care (PHC) settings (n = 697), were administered a battery of instruments.
Measures included the ASSIST; the Addiction Severity Index-Lite (ASI-Lite); the Severity of Dependence Scale (SDS); the MINI International Neuropsychiatric Interview (MINI-Plus); the Rating of Injection Site Condition (RISC); the Drug Abuse Screening Test (DAST); the Alcohol Use Disorders Identification Test (AUDIT); the Revised Fagerstrom Tolerance Questionnaire (RTQ); and the Maudsley Addiction Profile (MAP).
Concurrent validity was demonstrated by significant correlations between ASSIST scores and scores from the ASI-Lite (r = 0.76-0.88), SDS (r = 0.59), AUDIT (r = 0.82) and RTQ (r = 0.78); and significantly greater ASSIST scores for those with MINI-Plus diagnoses of abuse or dependence (P < 0.001). Construct validity was established by significant correlations between ASSIST scores and measures of risk factors for the development of drug and alcohol problems (r = 0.48-0.76). Discriminative validity was established by the capacity of the ASSIST to discriminate between substance use, abuse and dependence. Receiver operating characteristic (ROC) analysis was used to establish cut-off scores with suitable specificities (50-96%) and sensitivities (54-97%) for most substances.
The findings demonstrated that the ASSIST is a valid screening test for identifying psychoactive substance use in individuals who use a number of substances and have varying degrees of substance use.
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