Is personal recovery a transdiagnostic concept? Testing the fit of the CHIME framework using narrative experiences.

BACKGROUND: Personal recovery is operationalized in the CHIME framework (connectedness, hope, identity, meaning in life, and empowerment) of recovery processes. CHIME was initially developed through analysis of experiences of people mainly with psychosis, but it might also be valid for investigating recovery in mood-related, autism and other diagnoses. AIMS: To examine whether personal recovery is transdiagnostic by studying narrative experiences in several diagnostic groups. METHODS: Thirty recovery narratives, retrieved from "Psychiatry Story Bank" (PSB) in the Netherlands, were analyzed by three coders using CHIME as a deductive framework. New codes were assigned using an inductive approach and member checks were performed after consensus was reached. RESULTS: All five CHIME dimensions were richly reported in the narratives, independent of diagnosis. Seven new domains were identified, such as "acknowledgement by diagnosis" and "gaining self-insight". These new domains were evaluated to fit well as subdomains within the original CHIME framework. On average, 54.2% of all narrative content was classified as experienced difficulties. CONCLUSIONS: Recovery stories from different diagnostic perspectives fit well into the CHIME framework, implying that personal recovery is a transdiagnostic concept. Difficulties should not be ignored in the context of personal recovery based on its substantial presence in the recovery narratives.

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.

Job performance in healthcare: a systematic review.

BACKGROUND: Healthcare organisations face major challenges to keep healthcare accessible and affordable. This requires them to transform and improve their performance. To do so, organisations must influence employee job performance. Therefore, it is necessary to know what the key dimensions of job performance in healthcare are and how these dimensions can be improved. This study has three aims. The first aim is to determine what key dimensions of job performance are discussed in the healthcare literature. The second aim is to determine to which professionals and healthcare organisations these dimensions of job performance pertain. The third aim is to identify factors that organisations can use to affect the dimensions of job performance in healthcare. METHODS: A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The authors searched Scopus, Web of Science, PubMed, and Google Books, which resulted in the identification of 763 records. After screening 92 articles were included. RESULTS: The dimensions - task, contextual, and adaptative performance and counterproductive work behaviour - are reflected in the literature on job performance in healthcare. Adaptive performance and counterproductive work behaviour appear to be under-researched. The studies were conducted in different healthcare organisations and pertain to a variety of healthcare professionals. Organisations can affect job performance on the macro-, meso-, and micro-level to achieve transformation and improvement. CONCLUSION: Based on more than 90 studies published in over 70 journals, the authors conclude that job performance in healthcare can be conceptualised into four dimensions: task, contextual and adaptive performance, and counterproductive work behaviour. Generally, these dimensions correspond with the dimensions discussed in the job performance literature. This implies that these dimensions can be used for further research into job performance in healthcare. Many healthcare studies on job performance focus on two dimensions: task and contextual performance. However, adaptive performance, which is of great importance in constantly changing environments, is under-researched and should be examined further in future research. This also applies to counterproductive work behaviour. To improve job performance, interventions are required on the macro-, meso-, and micro-levels, which relate to governance, leadership, and individual skills and characteristics.

Defining the concept of mental dysregulation in patients requiring ambulance and/or emergency department care: protocol for a Delphi consensus study.

INTRODUCTION: From the patient and staff perspective, care delivery for patients experiencing a mental health problem in ambulance and emergency department (ED) settings is challenging. There is no uniform and internationally accepted concept to reflect people with a mental health problem who require emergency care, be it for, or as a result of, a mental health or physical health problem. On initial presentation to the emergency service provider (ambulance or ED), the cause of their healthcare condition/s (mental health and/or physical health) is often initially unknown. Due to this (1) the prevalence and range of underlying causes (mental and/or physical) of the patients presenting condition is unknown; (2) misattribution of physical symptoms to a mental health problem can occur and (3) diagnosis and treatment of the initial somatic complaint and cause(s) of the mental/physical health problem may be hindered.This study will name and define a new concept: 'mental dysregulation' in the context of ambulance and ED settings. METHODS AND ANALYSIS: A Delphi study, informed by a rapid literature review, will be undertaken. For the literature review, a steering group (ie, persons with lived experience, ED and mental health clinicians, academics) will systematically search the literature to provide a working definition of the concept: mental dysregulation. Based on this review, statements will be generated regarding (1) the definition of the concept; (2) possible causes of mental dysregulation and (3) observable behaviours associated with mental dysregulation. These statements will be rated in three Delphi rounds to achieve consensus by an international expert panel (comprising persons with lived experience, clinicians and academics). ETHICS AND DISSEMINATION: This study has been approved by the Medical Ethical Committee of the University of Applied Sciences Utrecht (reference number: 258-000-2023_Geurt van der Glind). Results will be disseminated via peer-reviewed journal publication(s), scientific conference(s) and to key stakeholders.

The importance of informal support and a listening ear: A narrative analysis of emotional conflict and support needs of siblings of children with a psychiatric disorder.

This study investigates the self-reported impact of children's psychiatric disorders on their siblings and assesses what forms of support such children most value. We used a qualitative research design with open interviews to stimulate children between 8 and 15 years old to talk about their experiences living with a brother or sister with a psychiatric disorder. Their stories were analysed within a hermeneutic phenomenological framework in order to identify narrative themes and interpret the meaning of shared experiences. From our analysis, nine shared narrative themes emerge. Overall, siblings report feeling conflicted about adapting their lives to their brother's or sister's disorder and signal a need for personalized attention from parents. They also indicate that being involved in the care for their brother or sister helps them to better understand their behaviour. Finally, siblings reveal that, in their experience, formal, protocolized forms of support foreground family problems and stress. Thus, we recommend to involve children in the care process; to acknowledge their personal needs and conflicts; and to be mindful of the style of support: help offered in an informal or playful way, instead of formal and protocolized, could be a more effective way of meeting siblings' needs.

Bayesian network analysis of antidepressant treatment trajectories.

It is currently difficult to successfully choose the correct type of antidepressant for individual patients. To discover patterns in patient characteristics, treatment choices and outcomes, we performed retrospective Bayesian network analysis combined with natural language processing (NLP). This study was conducted at two mental healthcare facilities in the Netherlands. Adult patients admitted and treated with antidepressants between 2014 and 2020 were included. Outcome measures were antidepressant continuation, prescription duration and four treatment outcome topics: core complaints, social functioning, general well-being and patient experience, extracted through NLP of clinical notes. Combined with patient and treatment characteristics, Bayesian networks were constructed at both facilities and compared. Antidepressant choices were continued in 66% and 89% of antidepressant trajectories. Score-based network analysis revealed 28 dependencies between treatment choices, patient characteristics and outcomes. Treatment outcomes and prescription duration were tightly intertwined and interacted with antipsychotics and benzodiazepine co-medication. Tricyclic antidepressant prescription and depressive disorder were important predictors for antidepressant continuation. We show a feasible way of pattern discovery in psychiatry data, through combining network analysis with NLP. Further research should explore the found patterns in patient characteristics, treatment choices and outcomes prospectively, and the possibility of translating these into a tool for clinical decision support.

Interventions to reduce interpersonal stigma towards patients with a mental dysregulation for ambulance and emergency department healthcare professionals: review protocol for an integrative review.

INTRODUCTION: Worldwide, there is an increase in the extent and severity of mental illness. Exacerbation of somatic complaints in this group of people can result in recurring ambulance and emergency department care. The care of patients with a mental dysregulation (ie, experiencing a mental health problem and disproportionate feelings like fear, anger, sadness or confusion, possibly with associated behaviours) can be complex and challenging in the emergency care context, possibly evoking a wide variety of feelings, ranging from worry or pity to annoyance and frustration in emergency care staff members. This in return may lead to stigma towards patients with a mental dysregulation seeking emergency care. Interventions have been developed impacting attitude and behaviour and minimising stigma held by healthcare professionals. However, these interventions are not explicitly aimed at the emergency care context nor do these represent perspectives of healthcare professionals working within this context. Therefore, the aim of the proposed review is to gain insight into interventions targeting healthcare professionals, which minimise stigma including beliefs, attitudes and behaviour towards patients with a mental dysregulation within the emergency care context. METHODS AND ANALYSIS: The protocol for a systematic integrative review is presented, using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols recommendations. A systematic search was performed on 13 July 2023. Study selection and data extraction will be performed by two independent reviewers. In each step, an expert with lived experience will comment on process and results. Software applications RefWorks-ProQuest, Rayyan and ATLAS.ti will be used to enhance the quality of the review and transparency of process and results. ETHICS AND DISSEMINATION: No ethical approval or safety considerations are required for this review. The proposed review will be submitted to a relevant international journal. Results will be presented at relevant medical scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42023390664 (https://www.crd.york.ac.uk/prospero/).

Experiences of Siblings of Children With Neurodevelopmental Disorders: Comparing Qualitative Analysis and Machine Learning to Study Narratives.

Introduction: Relatively few studies have focused on the wellbeing, experiences and needs of the siblings of children with a psychiatric diagnosis. However, the studies that have been conducted suggest that the impact of such circumstances on these siblings is significant. Studying narratives of diagnosed children or relatives has proven to be a successful approach to gain insights that could help improve care. Only a few attempts have been made to study narratives in psychiatry utilizing a machine learning approach. Method: In this current study, 13 narratives of the experiences of siblings of children with a neurodevelopmental disorders were collected through largely unstructured interviews. The interviews were analyzed using the traditional qualitative, hermeneutic phenomenology method as well as latent Dirichlet allocation (LDA), an unsupervised machine learning method clustering words from documents into topics. One aim of this study was to evaluate the experiences of the siblings in order to find leads to improve care and support for these siblings. Furthermore, the outcomes of both analyses were compared to evaluate the role of machine learning in analyzing narratives. Results: Qualitative analysis of the interviews led to the formulation of nine main themes: confrontation with conflicts, coping strategies siblings, need for rest and time for myself, need for support and attention from personal circle, wish for normality, influence on personal choices and possibilities for development, doing things together, recommendations and advices, ambivalence and loyalty. Using unsupervised machine learning (LDA) 24 topics were formed that mostly overlapped with the qualitative themes found. Both the qualitative analysis and the LDA analysis detected themes that were unique to the respective analysis. Conclusion: The present study found that studying narratives of siblings of children with a neurodevelopmental disorder contributes to a better understanding of the subjects' experiences. Siblings cope with ambivalent feelings toward their brother or sister and this emotional conflict often leads to adapted behavior. Several coping strategies are developed to deal with the behavior of their brother or sister like seeking support or ignoring. Devoted support, time and attention from close relatives, especially parents, is needed. The LDA analysis didn't appear useful to distract meaning and context from the narratives, but it was proposed that machine learning could be a valuable and quick addition to the traditional qualitative methods by finding overlooked topics and giving a rudimental overview of topics in narratives.

Bumetanide for Irritability in Children With Sensory Processing Problems Across Neurodevelopmental Disorders: A Pilot Randomized Controlled Trial.

BACKGROUND: Treatment development for neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) is impeded by heterogeneity in clinical manifestation and underlying etiologies. Symptom traits such as aberrant sensory reactivity are present across NDDs and might reflect common mechanistic pathways. Here, we test the effectiveness of repurposing a drug candidate, bumetanide, on irritable behavior in a cross-disorder neurodevelopmental cohort defined by the presence of sensory reactivity problems. METHODS: Participants, aged 5-15 years and IQ ≥ 55, with ASD, ADHD, and/or epilepsy and proven aberrant sensory reactivity according to deviant Sensory Profile scores were included. Participants were randomly allocated (1:1) to bumetanide (max 1 mg twice daily) or placebo tablets for 91 days followed by a 28-day wash-out period using permuted block design and minimization. Participants, parents, healthcare providers, and outcome assessors were blinded for treatment allocation. Primary outcome was the differences in ABC-irritability at day 91. Secondary outcomes were differences in SRS-2, RBS-R, SP-NL, BRIEF parent, BRIEF teacher at D91. Differences were analyzed in a modified intention-to-treat sample with linear mixed models and side effects in the intention-to-treat population. RESULTS: A total of 38 participants (10.1 [SD 3.1] years) were enrolled between June 2017 and June 2019 in the Netherlands. Nineteen children were allocated to bumetanide and nineteen to placebo. Five patients discontinued (n = 3 bumetanide). Bumetanide was superior to placebo on the ABC-irritability [mean difference (MD) -4.78, 95%CI: -8.43 to -1.13, p = 0.0125]. No effects were found on secondary endpoints. No wash-out effects were found. Side effects were as expected: hypokalemia (p = 0.046) and increased diuresis (p = 0.020). CONCLUSION: Despite the results being underpowered, this study raises important recommendations for future cross-diagnostic trial designs.

Bumetanide Effects on Resting-State EEG in Tuberous Sclerosis Complex in Relation to Clinical Outcome: An Open-Label Study.

Neuronal excitation-inhibition (E/I) imbalances are considered an important pathophysiological mechanism in neurodevelopmental disorders. Preclinical studies on tuberous sclerosis complex (TSC), suggest that altered chloride homeostasis may impair GABAergic inhibition and thereby E/I-balance regulation. Correction of chloride homeostasis may thus constitute a treatment target to alleviate behavioral symptoms. Recently, we showed that bumetanide-a chloride-regulating agent-improved behavioral symptoms in the open-label study Bumetanide to Ameliorate Tuberous Sclerosis Complex Hyperexcitable Behaviors trial (BATSCH trial; Eudra-CT: 2016-002408-13). Here, we present resting-state EEG as secondary analysis of BATSCH to investigate associations between EEG measures sensitive to network-level changes in E/I balance and clinical response to bumetanide. EEGs of 10 participants with TSC (aged 8-21 years) were available. Spectral power, long-range temporal correlations (LRTC), and functional E/I ratio (fE/I) in the alpha-frequency band were compared before and after 91 days of treatment. Pre-treatment measures were compared against 29 typically developing children (TDC). EEG measures were correlated with the Aberrant Behavioral Checklist-Irritability subscale (ABC-I), the Social Responsiveness Scale-2 (SRS-2), and the Repetitive Behavior Scale-Revised (RBS-R). At baseline, TSC showed lower alpha-band absolute power and fE/I than TDC. Absolute power increased through bumetanide treatment, which showed a moderate, albeit non-significant, correlation with improvement in RBS-R. Interestingly, correlations between baseline EEG measures and clinical outcomes suggest that most responsiveness might be expected in children with network characteristics around the E/I balance point. In sum, E/I imbalances pointing toward an inhibition-dominated network are present in TSC. We established neurophysiological effects of bumetanide although with an inconclusive relationship with clinical improvement. Nonetheless, our results further indicate that baseline network characteristics might influence treatment response. These findings highlight the possible utility of E/I-sensitive EEG measures to accompany new treatment interventions for TSC. Clinical Trial Registration: EU Clinical Trial Register, EudraCT 2016-002408-13 (www.clinicaltrialsregister.eu/ctr-search/trial/2016-002408-13/NL). Registered 25 July 2016.

The sensory-reactivity PROM set: identification of a parent reported outcome measure set for autism spectrum disorder.

BACKGROUND: Most children with autism spectrum disorder (ASD) suffer from aberrant responses to sensory stimuli that significantly impact the quality of life. To develop sensory interventions, individually tailored outcome measures are crucially needed for the domain of sensory reactivity problems. Here, we describe the identification of relevant sensory themes according to caregivers of children with ASD according to the guidelines for developing a (parent proxy) patient-reported outcome measure set. Subsequently, we identify parallels between these themes and a well-validated and supported PROMIS® portal to facilitate implementation. Interviews with clinicians and focus groups and interviews with parents of children with ASD were used in the initial phase for concept elicitation. Codes and themes were generated by qualitative thematic data analysis on the transcripts and cognitive interviews with different parents were used for revisions. The resulting themes were compared to existing generic PROMIS-item banks and other existing questionnaires. RESULTS: A total of 11 parent-reported outcomes were identified that could be either classified as directly or indirectly related to sensory reactivity. Directly related themes comprised of: (1) sensory stimulation tolerance and (2) sensitivity to sensory stimuli. Indirectly related themes were: (3) irritable behavior (4) anxiety problems (5) mood problems (6) sleep problems (7) fatigue (8) physical complaints (9) daily functioning and participation (10) routines, structure and dealing with change and (11) problems in social interaction and communication. Seven out of 11 themes could be measured with generic PROMIS item banks. The four remaining outcomes (sensory stimulation tolerance; irritable behaviour; routines, structure and dealing with change; and sensitivity to sensory stimuli) were found suitable to be inventoried by existing PROMs. CONCLUSION: The majority of parent-reported problems seemed related to indirect consequences of sensory reactivity, which are suitable to be measured with generic item banks. In sum, we identified a sensory-reactivity PROM (parent-proxy) set consisting of PROMIS® item banks and additional domains that together form a comprehensive and readily available outcome set for sensory reactivity problems in children with ASD.

Bumetanide for Core Symptoms of Autism Spectrum Disorder (BAMBI): A Single Center, Double-Blinded, Participant-Randomized, Placebo-Controlled, Phase-2 Superiority Trial.

OBJECTIVE: Recent trials have indicated positive effects of bumetanide in autism spectrum disorder (ASD). We tested efficacy of bumetanide on core symptom domains using a single center, parallel-group, participant-randomized, double-blind, placebo-controlled phase-2 superiority trial in a tertiary hospital in the Netherlands. METHOD: Unmedicated children aged 7 to 15 years with ASD and IQ ≥55 were block-randomized 1:1 to oral-solution bumetanide versus placebo, titrated to a maximum of 1.0 mg twice daily for 91 days (D91), followed by a 28-day wash-out period. The primary outcome was difference in Social Responsiveness Scale-2 (SRS-2) total score at D91, analyzed by modified intention-to-treat with linear mixed models. RESULTS: A total of 92 participants (mean age 10.5 [SD 2.4] years) enrolled between June 2016 and December 2018. In all, 47 children were allocated to bumetanide and 45 to placebo. Two participants dropped out per treatment arm. After 91 days, bumetanide was not superior to placebo on the primary outcome, the SRS-2 (mean difference -3.16, 95% CI = -9.68 to 3.37, p = .338). A superior effect was found on one of the secondary outcomes, the Repetitive Behavior Scale-Revised (mean difference -4.16, 95% CI = -8.06 to -0.25, p = .0375), but not on the Sensory Profile (mean difference 5.64, 95% CI = -11.30 to 22.57, p = .508) or the Aberrant Behavior Checklist Irritability Subscale (mean difference -0.65, 95% CI = -2.83 to 1.52, p = .552). No significant wash-out effect was observed. Significant adverse effects were predominantly diuretic effects (orthostatic hypotension (17 [36%] versus 5 [11%], p = .007); hypokalemia (24 [51%] versus 0 [0%], p < .0001), the occurrence of which did not statistically influence treatment outcome. CONCLUSION: The trial outcome was negative in terms of no superior effect on the primary outcome. The secondary outcomes suggest efficacy on repetitive behavior symptoms for a subset of patients. CLINICAL TRIAL REGISTRATION INFORMATION: Bumetanide in Autism Medication and Biomarker Study (BAMBI); https://www.clinicaltrialsregister.eu/; 2014-001560-35.

The Predictive Validity of Machine Learning Models in the Classification and Treatment of Major Depressive Disorder: State of the Art and Future Directions.

Major depressive disorder imposes a substantial disease burden worldwide, ranking as the third leading contributor to global disability. In spite of its ubiquity, classifying and treating depression has proven troublesome. One argument put forward to explain this predicament is the heterogeneity of patients diagnosed with the disorder. Recently, many areas of daily life have witnessed the surge of machine learning techniques, computational approaches to elucidate complex patterns in large datasets, which can be employed to make predictions and detect relevant clusters. Due to the multidimensionality at play in the pathogenesis of depression, it is suggested that machine learning could contribute to improving classification and treatment. In this paper, we investigated literature focusing on the use of machine learning models on datasets with clinical variables of patients diagnosed with depression to predict treatment outcomes or find more homogeneous subgroups. Identified studies based on best practices in the field are evaluated. We found 16 studies predicting outcomes (such as remission) and identifying clusters in patients with depression. The identified studies are mostly still in proof-of-concept phase, with small datasets, lack of external validation, and providing single performance metrics. Larger datasets, and models with similar variables present across these datasets, are needed to develop accurate and generalizable models. We hypothesize that harnessing natural language processing to obtain data 'hidden' in clinical texts might prove useful in improving prediction models. Besides, researchers will need to focus on the conditions to feasibly implement these models to support psychiatrists and patients in their decision-making in practice. Only then we can enter the realm of precision psychiatry.

Effects of bumetanide on neurodevelopmental impairments in patients with tuberous sclerosis complex: an open-label pilot study.

BACKGROUND: Tuberous sclerosis complex (TSC) is an autosomal dominant disease that affects multiple organs including the brain. TSC is strongly associated with broad neurodevelopmental disorders, including autism spectrum disorder symptomatology. Preclinical TSC studies have indicated altered neuronal chloride homeostasis affecting the polarity of γ-aminobutyric acid (GABA) ergic transmission as a potential treatment target. Bumetanide, a selective NKCC1 chloride importer antagonist, may attenuate depolarizing GABA action, and in that way reduce disease burden. In this open-label pilot study, we tested the effect of bumetanide on a variety of neurophysiological, cognitive, and behavioral measures in children with TSC. METHODS: Participants were treated with bumetanide (2dd 0.5-1.0 mg) for 13 weeks in an open-label trial. The Aberrant Behavior Checklist-Irritability (ABC-I) subscale was chosen as the primary endpoint. Secondary endpoints included other behavioral questionnaires in addition to event-related potentials (ERP) and neuropsychological tests if tolerated. Additionally, the treatment effect on seizure frequency and quality of life was assessed. Endpoint data were collected at baseline, after 91 days of treatment and after a 28-day wash-out period. RESULTS: Fifteen patients (8-21-years old) with TSC were included of which 13 patients completed the study. Treatment was well-tolerated with only expected adverse events due to the diuretic effects of bumetanide. Irritable behavior (ABC-I) showed significant improvement after treatment in 11 out of 13 patients (t(12) = 4.41, p = .001, d = .773). A favorable effect was also found for social behavior (Social Responsiveness Scale) (t(11) = 4.01, p = .002, d = .549) and hyperactive behavior (ABC-hyperactivity subscale) (t(12) = 3.65, p = .003, d = .686). Moreover, patients rated their own health-related quality of life higher after treatment. At baseline, TSC patients showed several atypical ERPs versus typically developing peers of which prepulse inhibition was significantly decreased in the TSC group. Neuropsychological measurements showed no change and bumetanide had no effect on seizure frequency. LIMITATIONS: The sample size and open-label design of this pilot study warrant caution when interpreting outcome measures. CONCLUSIONS: Bumetanide treatment is a potential treatment to alleviate the behavioral burden and quality of life associated with TSC. More elaborate trials are needed to determine the application and effect size of bumetanide for the TSC population. Trial registration EU Clinical Trial Register, EudraCT 2016-002408-13 (www.clinicaltrialsregister.eu/ctr-search/trial/2016-002408-13/NL). Registered 25 July 2016.

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 ß-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 ß-amplitude in the concentration condition. Our analyses showed that neither α nor ß 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.

Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence.

Despite the high level of interest in the use of machine learning (ML) and neuroimaging to detect psychosis at the individual level, the reliability of the findings is unclear due to potential methodological issues that may have inflated the existing literature. This study aimed to elucidate the extent to which the application of ML to neuroanatomical data allows detection of first episode psychosis (FEP), while putting in place methodological precautions to avoid overoptimistic results. We tested both traditional ML and an emerging approach known as deep learning (DL) using 3 feature sets of interest: (1) surface-based regional volumes and cortical thickness, (2) voxel-based gray matter volume (GMV) and (3) voxel-based cortical thickness (VBCT). To assess the reliability of the findings, we repeated all analyses in 5 independent datasets, totaling 956 participants (514 FEP and 444 within-site matched controls). The performance was assessed via nested cross-validation (CV) and cross-site CV. Accuracies ranged from 50% to 70% for surfaced-based features; from 50% to 63% for GMV; and from 51% to 68% for VBCT. The best accuracies (70%) were achieved when DL was applied to surface-based features; however, these models generalized poorly to other sites. Findings from this study suggest that, when methodological precautions are adopted to avoid overoptimistic results, detection of individuals in the early stages of psychosis is more challenging than originally thought. In light of this, we argue that the current evidence for the diagnostic value of ML and structural neuroimaging should be reconsidered toward a more cautious interpretation.

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.