Psychosis as an Evolutionary Adaptive Mechanism to Changing Environments

Background: From an evolutionary perspective it is remarkable that psychotic disorders, mostly occurring during fertile age and decreasing fecundity, maintain in the human population. Aim: To argue the hypothesis that psychotic symptoms may not be viewed as an illness but as an adaptation phenomenon, which can become out of control due to different underlying brain vulnerabilities and external stressors, leading to social exclusion. Methods: A literature study and analysis. Results: Until now, biomedical research has not unravelld the definitive etiology of psychotic disorders. Findings are inconsistent and show non-specific brain anomalies and genetic variation with small effect sizes. However, compelling evidence was found for a relation between psychosis and stressful environmental factors, particularly those influencing social interaction. Psychotic symptoms may be explained as a natural defense mechanism or protective response to stressful environments. This is in line with the fact that psychotic symptoms most often develop during adolescence. In this phase of life, leaving the familiar, and safe home environment and building new social networks is one of the main tasks. This could cause symptoms of “hyperconsciousness” and calls on the capacity for social adaptation. Conclusions: Psychotic symptoms may be considered as an evolutionary maintained phenomenon.Research investigating psychotic disorders may benefit from a focus on underlying general brain vulnerabilities or prevention of social exclusion, instead of psychotic symptoms

Psychosis as an evolutionary adaptive mechanism to changing environments

__Background:__ From an evolutionary perspective it is remarkable that psychotic disorders, mostly occurring during fertile age and decreasing fecundity, maintain in the human population. __Aim:__ To argue the hypothesis that psychotic symptoms may not be viewed as an illness but as an adaptation phenomenon, which can become out of control due to different underlying brain vulnerabilities and external stressors, leading to social exclusion. __Methods:__ A literature study and analysis. __Results:__ Until now, biomedical research has not unravelld the definitive etiology of psychotic disorders. Findings are inconsistent and show non-specific brain anomalies and genetic variation with small effect sizes. However, compelling evidence was found for a relation between psychosis and stressful environmental factors, particularly those influencing social interaction. Psychotic symptoms may be explained as a natural defense mechanism or protective response to stressful environments. This is in line with the fact that psychotic symptoms most often develop during adolescence. In this phase of life, leaving the familiar, and safe home environment and building new social networks is one of the main tasks. This could cause symptoms of "hyperconsciousness" and calls on the capacity for social adaptation. __Conclusions:__ Psychotic symptoms may be considered as an evolutionary maintained phenomenon. Research investigating psychotic disorders may benefit from a focus on underlying general brain vulnerabilities or prevention of social exclusion, instead of psychotic symptoms

Information extraction from free text for aiding transdiagnostic psychiatry: constructing NLP pipelines tailored to clinicians’ needs

Background: Developing predictive models for precision psychiatry is challenging because of unavailability of the necessary data: extracting useful information from existing electronic health record (EHR) data is not straightforward, and available clinical trial datasets are often not representative for heterogeneous patient groups. The aim of this study was constructing a natural language processing (NLP) pipeline that extracts variables for building predictive models from EHRs. We specifically tailor the pipeline for extracting information on outcomes of psychiatry treatment trajectories, applicable throughout the entire spectrum of mental health disorders (“transdiagnostic”). Methods: A qualitative study into beliefs of clinical staff on measuring treatment outcomes was conducted to construct a candidate list of variables to extract from the EHR. To investigate if the proposed variables are suitable for measuring treatment effects, resulting themes were compared to transdiagnostic outcome measures currently used in psychiatry research and compared to the HDRS (as a gold standard) through systematic review, resulting in an ideal set of variables. To extract these from EHR data, a semi-rule based NLP pipeline was constructed and tailored to the candidate variables using Prodigy. Classification accuracy and F1-scores were calculated and pipeline output was compared to HDRS scores using clinical notes from patients admitted in 2019 and 2020. Results: Analysis of 34 questionnaires answered by clinical staff resulted in four themes defining treatment outcomes: symptom reduction, general well-being, social functioning and personalization. Systematic review revealed 242 different transdiagnostic outcome measures, with the 36-item Short-Form Survey for quality of life (SF36) being used most consistently, showing substantial overlap with the themes from the qualitative study. Comparing SF36 to HDRS scores in 26 studies revealed moderate to good correlations (0.62—0.79) and good positive predictive values (0.75—0.88). The NLP pipeline developed with notes from 22,170 patients reached an accuracy of 95 to 99 percent (F1 scores: 0.38 – 0.86) on detecting these themes, evaluated on data from 361 patients. Conclusions: The NLP pipeline developed in this study extracts outcome measures from the EHR that cater specifically to the needs of clinical staff and align with outcome measures used to detect treatment effects in clinical trials

Outcome prediction of electroconvulsive therapy for depression

Introduction: We developed and tested a Bayesian network(BN) model to predict ECT remission for depression, with non-response as a secondary outcome. Methods: We performed a systematic literature search on clinically available predictors. We combined these predictors with variables from a dataset of clinical ECT trajectories (performed in the University Medical Center Utrecht) to create priors and train the BN. Temporal validation was performed in an independent sample. Results: The systematic literature search yielded three meta-analyses, which provided prior knowledge on outcome predictors. The clinical dataset consisted of 248 treatment trajectories in the training set and 44 trajectories in the test set at the same medical center. The AUC for the primary outcome remission estimated on an independent validation set was 0.686 (95%CI 0.513–0.859) (AUC values of 0.505 – 0.763 observed in 5-fold cross validation of the model within the train set). Accuracy 0.73 (balanced accuracy 0.67), sensitivity 0.55, specificity 0.79, after temporal validation in the independent sample. Prior literature information marginally reduced CI width. Discussion: A BN model comprised of prior knowledge and clinical data can predict remission of depression after ECT with reasonable performance. This approach can be used to make outcome predictions in psychiatry, and offers a methodological framework to weigh additional information, such as patient characteristics, symptoms and biomarkers. In time, it may be used to improve shared decision-making in clinical practice

Kennisontwikkeling in de klinische psychiatrie: leren van elektronische patiëntendossiers

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Serious Games as Potential Therapies: A Validation Study of a Neurofeedback Game

Serious (biofeedback) games offer promising ways to supplement or replace more expensive face-to-face interventions in health care. However, studies on the validity and effectiveness of EEG-based serious games remain scarce. In the current study, we investigated whether the conditions of the neurofeedback game “Daydream” indeed trained the brain activity as mentioned in the game manual. EEG activity was assessed in 14 healthy male volunteers while playing the 2 conditions of the game. The participants completed a training of 5 sessions. EEG frequency analyses were performed to verify the claims of the manual. We found significant differences in α- to β-ratio between the 2 conditions although only in the amplitude data, not in the power data. Within the conditions, mean α-amplitude only differed significantly from the β-amplitude in the concentration condition. Our analyses showed that neither α nor β brain activity differed significantly between game levels (higher level requiring increased brain activity) in either of the two conditions. In conclusion, we found only marginal evidence for the proposed claims stated in the manual of the game. Our research emphasizes that it is crucial to validate the claims that serious games make, especially before implementing them in the clinic or as therapeutic devices.Education and Child Studie

DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text

In order to use medical text for research purposes, it is necessary to de-identify the text for legal and privacy reasons. We report on a pattern matching method to automatically de-identify medical text written in Dutch, which requires a low amount of effort to be hand tailored. First, a selection of Protected Health Information (PHI) categories is determined in cooperation with medical staff. Then, we devise a method for de-identifying all information in one of these PHI categories, that relies on lookup tables, decision rules and fuzzy string matching. Our de-identification method DEDUCE is validated on a test corpus of 200 nursing notes and 200 treatment plans obtained from the University Medical Center Utrecht (UMCU) in the Netherlands, achieving a total micro-averaged precision of 0.814, a recall of 0.916 and a F1-score of 0.862. For person names, a recall of 0.964 was achieved, while no names of patients were missed

DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text

In order to use medical text for research purposes, it is necessary to de-identify the text for legal and privacy reasons. We report on a pattern matching method to automatically de-identify medical text written in Dutch, which requires a low amount of effort to be hand tailored. First, a selection of Protected Health Information (PHI) categories is determined in cooperation with medical staff. Then, we devise a method for de-identifying all information in one of these PHI categories, that relies on lookup tables, decision rules and fuzzy string matching. Our de-identification method DEDUCE is validated on a test corpus of 200 nursing notes and 200 treatment plans obtained from the University Medical Center Utrecht (UMCU) in the Netherlands, achieving a total micro-averaged precision of 0.814, a recall of 0.916 and a F1-score of 0.862. For person names, a recall of 0.964 was achieved, while no names of patients were missed

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It is unclear whether the concepts and findings of the underlying neurobiology of adult psychopathy apply to youths as well. If so, a life span approach to treatment should be taken. Because youths' brains are still developing, interventions at an early age may be far more effective in the long run. The aim of this systematic review is to examine whether the neurocognitive and neurobiological factors that underlie juvenile psychopathy, and specifically callous-unemotional (CU) traits, are similar to those underlying adult psychopathy. The results show that youths with CU traits show lower levels of prosocial reasoning, lower emotional responsivity, and decreased harm avoidance. Brain imaging studies in youths with CU traits are still rare. Available studies suggest specific neural correlates, such as a reduced response of the amygdala and a weaker functional connectivity between the amygdala and the ventromedial prefrontal cortex. These findings are largely in line with existing theories of adult psychopathy, such as the dual-hormone serotonergic hypothesis and the integrated emotions systems theory. We recommend that future studies investigate the role of oxytocin, invest in the study of neural mechanisms, and study the precursors, risk factors, and correlates of CU traits in early infancy and in longitudinal designs