Martina Uttinger

Sex differences in cognitive functioning in at-risk mental state for psychosis, first episode psychosis and healthy control subjects.

BACKGROUND Several sex differences in schizophrenia have been reported including differences in cognitive functioning. Studies with schizophrenia patients and healthy controls (HC) indicate that the sex advantage for women in verbal domains is also present in schizophrenia patients. However, findings have been inconsistent. No study focused on sex-related cognitive performance differences in at-risk mental state for psychosis (ARMS) individuals yet. Thus, the aim of the present study was to investigate sex differences in cognitive functioning in ARMS, first episode psychosis (FEP) and HC subjects. We expected a better verbal learning and memory performance of women in all groups. METHODS The neuropsychological data analysed in this study were collected within the prospective Früherkennung von Psychosen (FePsy) study. In total, 118 ARMS, 88 FEP individuals and 86 HC completed a cognitive test battery covering the domains of executive functions, attention, working memory, verbal learning and memory, IQ and speed of processing. RESULTS Women performed better in verbal learning and memory regardless of diagnostic group. By contrast, men as compared to women showed a shorter reaction time during the working memory task across all groups. CONCLUSION The results provide evidence that women generally perform better in verbal learning and memory, independent of diagnostic group (ARMS, FEP, HC). The finding of a shorter reaction time for men in the working memory task could indicate that men have a superior working memory performance since they responded faster during the target trials, while maintaining a comparable overall working memory performance level.

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

Abstract 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.

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

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.

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.

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.

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.

The frankfurt complaint questionnaire for self-assessment of basic symptoms in the early detection of psychosis-factor structure, reliability, and predictive validity

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.

Early Detection of Psychosis - Helpful or Stigmatizing Experience for Those Concerned?

This chapter provides an overview of the literature on early detection of psychosis concerning stigma and discrimination in individuals with an at-risk mental state (ARMS) for psychosis. Extended surveys about stigma and psychosis/schizophrenia show that these patients belong to the most stigmatized patient groups. Therefore, ARMS individuals are conceivably affected by stigma and its consequences. In response to the recent scientific debate concerning potential stigma associated with an ARMS for psychosis, a small but growing number of studies on the topic have been carried out. The following two questions are addressed in this chapter: (1) do ARMS individuals experience stigma - and if so, what kind of stigma, and (2) are early detection centers contributing to stigma in any form or is the support offered rather experienced as helpful? Special emphasis is placed on the subjective perspective of ARMS individuals. Research reviewed in this chapter suggests that ARMS individuals fear stigma rather than having experienced it. They suffer from fear of negative reactions from peers, leading to concealment of mental issues, social withdrawal and delayed help-seeking. According to the literature reviewed, early detection services help individuals coping with symptoms, social isolation and potential stigma instead of enhancing or causing the latter. More emphasis should be placed on the subjective experiences and perspectives of those concerned in future research. Potential stigma including self-stigmatization should be assessed and included into treatment recommendations for individuals with an ARMS.