The relationship between negative symptoms and cognitive functioning in patients at clinical high risk for psychosis.

Negative symptoms and neurocognitive performance have been reported to be negatively associated in patients with emerging psychosis. However, most previous studies focused on patients with frank psychosis and did not differentiate between subdomains of negative symptoms. Hence, we aimed to elucidate the specific relationship between negative symptoms and cognitive functioning in patients at clinical high risk (CHR) for psychosis. Data from 154 CHR patients collected within the prospective Früherkennung von Psychosen (FePsy) study were analyzed. Negative symptoms were assessed with the Scale for the Assessment of Negative Symptoms (SANS) and cognitive functioning with an extensive neuropsychological test battery. Regression analyses revealed significant negative associations between negative symptoms and cognitive functioning, particularly in the domains of nonverbal intelligence and verbal fluency. When analyzing each negative symptom domain separately, alogia and asociality/anhedonia were significantly negatively associated with nonverbal intelligence and alogia additionally with verbal fluency. Overall, our results in CHR patients are similar to those reported in patients with frank psychosis. The strong negative association between verbal fluency and negative symptoms may be indicative of an overlap between these constructs. Verbal fluency might have a strong influence on the clinical impression of negative symptoms (particularly alogia) and vice versa.

Early detection of psychosis: helpful or stigmatizing experience? A qualitative study.

AIM: Despite the large scientific debate concerning potential stigmatizing effects of identifying an individual as being in an at-risk mental state (ARMS) for psychosis, studies investigating this topic from the subjective perspective of patients are rare. This study assesses whether ARMS individuals experience stigmatization and to what extent being informed about the ARMS is experienced as helpful or harmful. METHODS: Eleven ARMS individuals, currently participating in the follow-up assessments of the prospective Basel Früherkennung von Psychosen (FePsy; English: Early Detection of Psychosis) study, were interviewed in detail using a semistructured qualitative interview developed for this purpose. Data were analysed using Interpretative Phenomenological Analysis. RESULTS: Most individuals experiencing first symptoms reported sensing that there was 'something wrong with them' and felt in need of help. They were relieved that a specific term was assigned to their symptoms. The support received from the early detection centre was generally experienced as helpful. Many patients reported stigmatization and discrimination that appeared to be the result of altered behaviour and social withdrawal due to the prepsychotic symptoms they experienced prior to contact with the early detection clinic. CONCLUSIONS: The results suggest that early detection services help individuals cope with symptoms and potential stigmatization rather than enhancing or causing the latter. More emphasis should be put on the subjective experiences of those concerned when debating the advantages and disadvantages of early detection with regard to stigma. There was no evidence for increased perceived stigma and discrimination as a result of receiving information about the ARMS.

The Frankfurt Complaint Questionnaire for self-assessment of basic symptoms in the early detection of psychosis-Factor structure, reliability, and predictive validity.

OBJECTIVES: Patients with schizophrenia often experience subtle disturbances in several domains of information processing-so-called basic symptoms (BS). BS are already present before onset of frank psychosis and can be assessed by interviews but also by the self-administered Frankfurt Complaint Questionnaire (FCQ). We investigated the factor structure, reliability, and predictive validity for transition to psychosis of the FCQ, comparing previously proposed factor solutions containing 1, 2, 4, and 10 factors. METHODS: Confirmatory factor analysis was used in a sample of 117 at-risk mental state and 92 first-episode psychosis participants of the Basel FePsy (early detection of psychosis) study. RESULTS: Although all factor models fitted to the data, the 2- or 4-factor solutions performed best among the models that used at least half of the FCQ items, suggesting the covariance between FCQ items is best explained by 2 to 4 underlying factors. No FCQ-scale predicted transition to psychosis. CONCLUSION: We could confirm a 2- to 4-factor structure of the FCQ in a sample of at-risk mental state and first-episode psychosis patients using confirmatory factor analysis. Contrary to interview-assessed cognitive-perceptive BS, self-assessed BS do not seem to improve prediction of psychosis. This result reinforces reports of poor correspondence between interview- and questionnaire-assessed BS.

Correlations between self-rating and observer-rating of psychopathology in at-risk mental state and first-episode psychosis patients: influence of disease stage and gender.

AIM: Research findings on the correlations between self-rating and observer-rating of schizophrenic psychopathology are inconsistent and have rarely considered first-episode psychosis (FEP) and at-risk mental state (ARMS) for psychosis patients. This study investigates these correlations in ARMS and FEP patients and how they are moderated by disease stage and gender. METHODS: In the Basel Früherkennung von Psychosen (FePsy) study, positive and negative psychotic and affective symptoms were rated in 126 ARMS and 94 FEP patients using two observer- and three self-rating scales. The agreement between self-rating and observer-rating and the moderating influence of disease stage and gender was quantified using Pearson correlation and multiple regression models. RESULTS: Correlations between self- and observer-rated subscales covering the same symptom dimension were low and mostly non-significant except for one correlation of positive and one of negative symptoms. There was no moderating influence of disease stage and gender on the correlations between self-rating and observer-rating except for one higher association in positive symptoms in FEP compared to ARMS and in women compared to men. However, these significant interaction effects did not withstand correction for multiple testing. CONCLUSIONS: This study suggests that the agreement between self-rating and observer-rating in FEP and ARMS patients is rather low, similar across symptom dimensions, and only partially dependent on disease stage and gender. However, low correlations between self-rating and observer-rating do not necessarily indicate that these patients have difficulties reporting their symptoms. They could also have occurred because the scales did not exactly cover the same symptom dimensions.

Prediction of psychosis using neural oscillations and machine learning in neuroleptic-naïve at-risk patients.

OBJECTIVES: This study investigates whether abnormal neural oscillations, which have been shown to precede the onset of frank psychosis, could be used towards the individualised prediction of psychosis in clinical high-risk patients. METHODS: We assessed the individualised prediction of psychosis by detecting specific patterns of beta and gamma oscillations using machine-learning algorithms. Prediction models were trained and tested on 53 neuroleptic-naïve patients with a clinical high-risk for psychosis. Of these, 18 later transitioned to psychosis. All patients were followed up for at least 3 years. For an honest estimation of the generalisation capacity, the predictive performance of the models was assessed in unseen test cases using repeated nested cross-validation. RESULTS: Transition to psychosis could be predicted from current-source density (CSD; area under the curve [AUC] = 0.77), but not from lagged phase synchronicity data (LPS; AUC = 0.56). Combining both modalities did not improve the predictive accuracy (AUC = 0.78). The left superior temporal gyrus, the left inferior parietal lobule and the precuneus most strongly contributed to the prediction of psychosis. CONCLUSIONS: Our results suggest that CSD measurements extracted from clinical resting state EEG can help to improve the prediction of psychosis on a single-subject level.