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.

Childhood abuse v. neglect and risk for major psychiatric disorders.

BACKGROUND: Childhood maltreatment (CM) is a strong risk factor for psychiatric disorders but serves in its current definitions as an umbrella for various fundamentally different childhood experiences. As first step toward a more refined analysis of the impact of CM, our objective is to revisit the relation of abuse and neglect, major subtypes of CM, with symptoms across disorders. METHODS: Three longitudinal studies of major depressive disorder (MDD, N = 1240), bipolar disorder (BD, N = 1339), and schizophrenia (SCZ, N = 577), each including controls (N = 881), were analyzed. Multivariate regression models were used to examine the relation between exposure to abuse, neglect, or their combination to the odds for MDD, BD, SCZ, and symptoms across disorders. Bidirectional Mendelian randomization (MR) was used to probe causality, using genetic instruments of abuse and neglect derived from UK Biobank data (N = 143 473). RESULTS: Abuse was the stronger risk factor for SCZ (OR 3.51, 95% CI 2.17-5.67) and neglect for BD (OR 2.69, 95% CI 2.09-3.46). Combined CM was related to increased risk exceeding additive effects of abuse and neglect for MDD (RERI = 1.4) and BD (RERI = 1.1). Across disorders, abuse was associated with hallucinations (OR 2.16, 95% CI 1.55-3.01) and suicide attempts (OR 2.16, 95% CI 1.55-3.01) whereas neglect was associated with agitation (OR 1.24, 95% CI 1.02-1.51) and reduced need for sleep (OR 1.64, 95% CI 1.08-2.48). MR analyses were consistent with a bidirectional causal effect of abuse with SCZ (IVWforward = 0.13, 95% CI 0.01-0.24). CONCLUSIONS: Childhood abuse and neglect are associated with different risks to psychiatric symptoms and disorders. Unraveling the origin of these differences may advance understanding of disease etiology and ultimately facilitate development of improved personalized treatment strategies.

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/).

Making meaning of trauma in psychosis.

Background: Finding new meaning and identity in the aftermath of trauma has been identified as a key process of mental health recovery. However, research indicates that this meaning-making process is compromised in people with psychosis. Considering the high prevalence, yet under-treatment of trauma in people with psychosis, it is urgent to gain insight into how their meaning-making process can be supported. Aim: To gain insight into how people with psychosis make meaning of trauma and identify barriers and facilitators in their meaning-making process. Methods: Qualitative inquiry of N = 21 interviews transcripts from the Dutch Psychiatry Storybank. We included interviews of people who (a) lived through multiple psychotic episodes, and (b) spontaneously addressed traumatic experiences in a low-structured interview. Storyline analysis was performed to gain insight into the meaning-making of trauma within their self-stories. Psychosocial conceptualizations of narrative identity were used to inform the analysis. A data-validation session with four experts-by-experience was organized to check and improve the quality of our analysis. Results: We identified four different story types: (1) Psychiatry as the wrong setting to find meaning; (2) The ongoing struggle to get trauma-therapy; (3) Exposure to trauma as a threat to a stable life, and (4) Disclosure as the key to resolving alienation. Each story type comprises a different plot, meaning of trauma withing the self-story, (lack of) integration and barriers and facilitators in the meaning-making process. Overall, barriers in the meaning-making process were mostly situated within mental healthcare and stigma-related. People felt particularly hindered by pessimistic ideas on their capacity to develop self-insight and cope with distress, resulting in limited treatment options. Their process of adaptive meaning-making often started with supportive, non-judgmental relationships with individuals or communities that offered them the safety to disclose trauma and motivated them to engage in a process of self-inquiry and growth. Conclusion: The outcomes illuminate the social context of the meaning-making challenges that people with psychosis face and illustrate the devastating influence of stigma. Our outcomes offer guidance to remove barriers to adaptive meaning-making in people with psychosis, and can help clinicians to attune to differences in the meaning-making of trauma.

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.

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.

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.

"It has to be better, otherwise we will get stuck." A Review of Novel Directions for Mental Health Reform and Introducing Pilot Work in the Netherlands.

Background: The current state of mental health care in the Netherlands faces challenges such as fragmentation, inequality, inaccessibility, and a narrow specialist focus on individual diagnosis and symptom reduction. Methods: A review suggests that in order to address these challenges, an integrated public health approach to mental health care that encompasses the broader social, cultural, and existential context of mental distress is required. Results: A Mental Health Ecosystem social trial seeks to pilot such an approach in the Netherlands, focusing on empowering patients and promoting collaboration among various healthcare providers, social care organizations, and peer-support community organizations, working together in a regional ecosystem of care and committed to a set of shared values. In the ecosystem, mental health problems are examined through the prism of mental variation in context whilst scaling up the capacity of group-based treatment and introducing a flexible and modular approach of (2nd order) treatment by specialists across the ecosystem. The approach is to empower naturally available resources in the community beyond professionally run care facilities. Digital platforms such as psychosenet.nl and proud2bme.nl, which complement traditional mental health care services and enhance public mental health, will be expanded. The capacity of recovery colleges will be increased, forming a national network covering the entire country. GEM will be evaluated using a population-based approach, encompassing a broad range of small-area indicators related to mental health care consumption, social predictors, and clinical outcomes. The success of GEM relies heavily on bottom-up development backed by stakeholder involvement, including insurers and policy-making institutions, and cocreation. Conclusion: By embracing a social trial and leveraging digital platforms, the Dutch mental health care system can overcome challenges and provide more equitable, accessible, and high-quality care to individuals.

Muva physical activity intervention to improve social functioning in people with a severe mental illness: study protocol of a pragmatic stepped wedge cluster randomized trial.

BACKGROUND: People with severe mental illness (SMI) often suffer from long-lasting symptoms that negatively influence their social functioning, their ability to live a meaningful life, and participation in society. Interventions aimed at increasing physical activity can improve social functioning, but people with SMI experience multiple barriers to becoming physically active. Besides, the implementation of physical activity interventions in day-to-day practice is difficult. In this study, we aim to evaluate the effectiveness and implementation of a physical activity intervention to improve social functioning, mental and physical health. METHODS: In this pragmatic stepped wedge cluster randomized controlled trial we aim to include 100 people with SMI and their mental health workers from a supported housing organization. The intervention focuses on increasing physical activity by implementing group sports activities, active guidance meetings, and a serious game to set physical activity goals. We aim to decrease barriers to physical activity through active involvement of the mental health workers, lifestyle courses, and a medication review. Participating locations will be divided into four clusters and randomization will decide the start of the intervention. The primary outcome is social functioning. Secondary outcomes are quality of life, symptom severity, physical activity, cardiometabolic risk factors, cardiorespiratory fitness, and movement disturbances with specific attention to postural adjustment and movement sequencing in gait. In addition, we will assess the implementation by conducting semi-structured interviews with location managers and mental health workers and analyze them by direct content analysis. DISCUSSION: This trial is innovative since it aims to improve social functioning in people with SMI through a physical activity intervention which aims to lower barriers to becoming physically active in a real-life setting. The strength of this trial is that we will also evaluate the implementation of the intervention. Limitations of this study are the risk of poor implementation of the intervention, and bias due to the inclusion of a medication review in the intervention that might impact outcomes. TRIAL REGISTRATION: This trial was registered prospectively in The Netherlands Trial Register (NTR) as NTR NL9163 on December 20, 2020. As the The Netherlands Trial Register is no longer available, the trial can now be found in the International Clinical Trial Registry Platform via: https://trialsearch.who.int/Trial2.aspx?TrialID=NL9163 .

Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers.

Physiological signals (e.g., heart rate, skin conductance) that were traditionally studied in neuroscientific laboratory research are currently being used in numerous real-life studies using wearable technology. Physiological signals obtained with wearables seem to offer great potential for continuous monitoring and providing biofeedback in clinical practice and healthcare research. The physiological data obtained from these signals has utility for both clinicians and researchers. Clinicians are typically interested in the day-to-day and moment-to-moment physiological reactivity of patients to real-life stressors, events, and situations or interested in the physiological reactivity to stimuli in therapy. Researchers typically apply signal analysis methods to the data by pre-processing the physiological signals, detecting artifacts, and extracting features, which can be a challenge considering the amount of data that needs to be processed. This paper describes the creation of a "Wearables" R package and a Shiny "E4 dashboard" application for an often-studied wearable, the Empatica E4. The package and Shiny application can be used to visualize the relationship between physiological signals and real-life stressors or stimuli, but can also be used to pre-process physiological data, detect artifacts, and extract relevant features for further analysis. In addition, the application has a batch process option to analyze large amounts of physiological data into ready-to-use data files. The software accommodates users with a downloadable report that provides opportunities for a careful investigation of physiological reactions in daily life. The application is freely available, thought to be easy to use, and thought to be easily extendible to other wearable devices. Future research should focus on the usability of the application and the validation of the algorithms.

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.

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.

Topic Modeling for Interpretable Text Classification From EHRs.

The clinical notes in electronic health records have many possibilities for predictive tasks in text classification. The interpretability of these classification models for the clinical domain is critical for decision making. Using topic models for text classification of electronic health records for a predictive task allows for the use of topics as features, thus making the text classification more interpretable. However, selecting the most effective topic model is not trivial. In this work, we propose considerations for selecting a suitable topic model based on the predictive performance and interpretability measure for text classification. We compare 17 different topic models in terms of both interpretability and predictive performance in an inpatient violence prediction task using clinical notes. We find no correlation between interpretability and predictive performance. In addition, our results show that although no model outperforms the other models on both variables, our proposed fuzzy topic modeling algorithm (FLSA-W) performs best in most settings for interpretability, whereas two state-of-the-art methods (ProdLDA and LSI) achieve the best predictive performance.

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.

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.

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.

A network perspective on suicidal behavior: Understanding suicidality as a complex system.

BACKGROUND: Suicidal behavior is the result of complex interactions between many different factors that change over time. A network perspective may improve our understanding of these complex dynamics. Within the network perspective, psychopathology is considered to be a consequence of symptoms that directly interact with one another in a network structure. To view suicidal behavior as the result of such a complex system is a good starting point to facilitate moving away from traditional linear thinking. OBJECTIVE: To review the existing paradigms and theories and their application to suicidal behavior. METHODS: In the first part of this paper, we introduce the relevant concepts within network analysis such as network density and centrality. Where possible, we refer to studies that have applied these concepts within the field of suicide prevention. In the second part, we move one step further, by understanding the network perspective as an initial step toward complex system theory. The latter is a branch of science that models interacting variables in order to understand the dynamics of complex systems, such as tipping points and hysteresis. RESULTS: Few studies have applied network analysis to study suicidal behavior. The studies that do highlight the complexity of suicidality. Complexity science offers potential useful concepts such as alternative stable states and resilience to study psychopathology and suicidal behavior, as demonstrated within the field of depression. To date, one innovative study has applied concepts from complexity science to better understand suicidal behavior. Complexity science and its application to human behavior are in its infancy, and it requires more collaboration between complexity scientists and behavioral scientists. CONCLUSIONS: Clinicians and scientists are increasingly conceptualizing suicidal behavior as the result of the complex interaction between many different biological, social, and psychological risk and protective factors. Novel statistical techniques such as network analysis can help the field to better understand this complexity. The application of concepts from complexity science to the field of psychopathology and suicide research offers exciting and promising possibilities for our understanding and prevention of suicide.

Efficacy of psychological interventions in young individuals at ultra-high risk for psychosis: A naturalistic study.

AIM: Early detection and intervention in individuals at risk for developing psychosis have become a priority for many clinical services around the world. Limited naturalistic evidence is available on whether detection and intervention for ultra-high risk (UHR) is effective by means of reducing psychosis risk and improving functioning. METHODS: We compared functioning scores over 5.9 (±7.7) months of time between UHR individuals (n = 61) and help-seeking adolescents without a specific UHR profile (general adolescent help-seeking population [HSP]; n = 82) aged 12 to 25 years receiving psychological interventions at a specialized UHR service in the Netherlands. Attenuated psychotic symptoms (APS) were evaluated over time within the UHR group. In addition, the impact of duration of treatment, <7 sessions, 8 to 21 sessions and >20 sessions, as well as treatment type, that is, cognitive behavioural therapy (CBT) and CBT + add on treatment, were evaluated. RESULTS: Both UHR and HSP showed an increase in functioning over time (P < .001), with no difference between these groups. The UHR group showed a reduction of APS over time (P < .001). More than 20 treatment sessions was more effective than 1 to 6 treatment sessions (P < .01, partial eta squared = .08) and CBT was equally effective as CBT-add on in improving functioning. CONCLUSIONS: The findings of this study suggest that psychological treatment is just as effective in improving functioning in UHR as in HSP. Moreover, it decreases APS in UHR. Improvement in functioning is not affected by treatment type, but positively affected by the duration of treatment.

Recovering Context in Psychiatry: What Contextual Analysis of Service Users' Narratives Can Teach About Recovery Support.

Aim: Enhancement of recovery-oriented care in psychiatry requires insight into the personal meaning and context of recovery. The Psychiatry Story Bank is a narrative project, designed to meet this need, by collecting, sharing and studying the narratives of service-users in psychiatry. Our study was aimed at expanding insight into personal recovery through contextual analysis of these first-person narratives. Methods: We analyzed 25 narratives, as collected through research interviews. To capture the storied context on both a personal, interpersonal and ideological level we combined several forms of qualitative analysis. A total of 15 narrative characteristics were mapped and compared. Results: Through comparative analysis we identified four narratives genres in our sample: Lamentation (narratives about social loss), Reconstruction (narratives about the impact of psychosis), Accusation (narratives about injustice in care), and Travelogue (narratives about identity transformation). Each genre provides insight into context-bound difficulties and openings for recovery and recovery-support. Conclusion: A contextual approach to studying personal recovery offers insights that can help attune recovery support in psychiatry. Important clues for recovery support can be found in people's narrated core struggle and the associated desire to be recognized in a particular way. Our results also indicate that familiarity with different ways of understanding mental distress, can help people to express and reframe their struggles and desires in a helpful way, thereby facilitating recognition.