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.

"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.

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.

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.

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.

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.

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.

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.

Saliva oxytocin, cortisol, and testosterone levels in adolescent boys with autism spectrum disorder, oppositional defiant disorder/conduct disorder and typically developing individuals

The aim of the current study was to compare levels of oxytocin, cortisol, and testosterone in adolescents with either autism spectrum disorder (ASD), or oppositional defiant disorder (ODD)/conduct disorder (CD), and in typically developing individuals (TDI), and relate hormone levels to severity and subtype of aggression and callous-unemotional (CU) traits. Saliva concentrations of oxytocin, cortisol, and testosterone were assessed in 114 male participants (N = 49 ASD, N = 37 ODD/CD, N = 28 TDI,) aged 12-19 years (M = 15.4 years, SD = 1.9). The ASD and the ODD/CD groups had significantly lower levels of oxytocin than the TDI group, and the ODD/CD group had significantly higher levels of testosterone than the ASD group. There were no group effects on cortisol levels. Group differences remained for oxytocin after correcting for the influence of CU traits, but were not significant after controlling for aggression. Results for testosterone became non-significant after correction for either CU traits or aggression. Across groups, higher levels of CU traits were related to higher levels of cortisol and testosterone, however, proactive and reactive aggression were unrelated to all three hormonal levels. The current findings show that, regardless of cognitive ability or comorbid disorders, the diagnostic groups (ASD, ODD/CD) differ from each other by their hormonal levels, with the ASD group characterized by relative low level of oxytocin, and the ODD/CD group by a relative low level of oxytocin and high level of testosterone. These group effects were partly driven by differences in CU traits between the groups.

Does Residential Green and Blue Space Promote Recovery in Psychotic Disorders? A Cross-Sectional Study in the Province of Utrecht, The Netherlands

Mental health is reportedly influenced by the presence of green and blue space in residential areas, but scientific evidence of a relation to psychotic disorders is scant. We put two hypotheses to the test: first, compared to the general population, psychiatric patients live in neighborhoods with less green and blue space; second, the amount of green and blue space is negatively associated with the duration of hospital admission. The study population consisted of 623 patients with psychotic disorders who had been admitted to the psychiatric ward of an academic hospital in Utrecht, The Netherlands from 2008 to 2016. Recovery was measured by length of stay. Structured patient data was linked to socio-economic status and the amount of green and blue space in the residential area. Associations were assessed by means of regression models controlling for confounding factors. Compared to the general population, psychiatric patients had a significantly lower amount of green space in their neighborhood. This result was not confirmed for blue space. Furthermore, no significant associations were found between green and blue space and the duration of hospital stay. In conclusion, previous studies focusing on other mental disorders, like anxiety or depression, found positive mental health effects of green and blue space in the neighborhood. We were not able to confirm significant effects among our study population on duration of admission, however. Future research focusing on psychotic patients could investigate the influence of exposure to green and blue space on other influences and outcomes on mental health.

Emotional face recognition in male adolescents with autism spectrum disorder or disruptive behavior disorder: an eye-tracking study

Autism Spectrum Disorder (ASD), Oppositional Defiant Disorder (ODD), and Conduct Disorder (CD) are often associated with emotion recognition difficulties. This is the first eye-tracking study to examine emotional face recognition (i.e., gazing behavior) in a direct comparison of male adolescents with Autism Spectrum Disorder or Oppositional Defiant Disorder/Conduct Disorder, and typically developing (TD) individuals. We also investigate the role of psychopathic traits, callous-unemotional (CU) traits, and subtypes of aggressive behavior in emotional face recognition. A total of 122 male adolescents (N = 50 ASD, N = 44 ODD/CD, and N = 28 TD) aged 12-19 years (M = 15.4 years, SD= 1.9) were included in the current study for the eye-tracking experiment. Participants were presented with neutral and emotional faces using a Tobii 1750 eye-tracking monitor to record gaze behavior. Our main dependent eye-tracking variables were: (1) fixation duration to the eyes of a face and (2) time to the first fixation to the eyes. Since distributions of eye-tracking variables were not completely Gaussian, non-parametric tests were chosen to investigate gaze behavior across the diagnostic groups with Autism Spectrum Disorder, Oppositional Defiant Disorder/Conduct Disorder, and Typically Developing individuals. Furthermore, we used Spearman correlations to investigate the links with psychopathy, callous, and unemotional traits and subtypes of aggression as assessed by questionnaires. The relative total fixation duration to the eyes was decreased in both the Autism Spectrum Disorder group and the Oppositional Defiant Disorder/Conduct Disorder group for several emotional expressions. In both the Autism Spectrum Disorder and the Oppositional Defiant Disorder/Conduct Disorder group, increased time to first fixation on the eyes of fearful faces only was nominally significant. The time to first fixation on the eyes was nominally correlated with psychopathic traits and proactive aggression. The current findings do not support strong claims for differential cross-disorder eye-gazing deficits and for a role of shared underlying psychopathic traits, callous-unemotional traits, and aggression subtypes. Our data provide valuable and novel insights into gaze timing distributions when looking at the eyes of a fearful face.

A new setup for the quantitative analysis of drying by the use of gas-phase FTIR-spectroscopy

Drying rates are important for the manufacture of thin films and in specific for the production of electrodes used in electrochemical devices such as fuel cells and electrolyzers. The known procedures to investigate time-dependent sample compositions and selective evaporation rates are insufficient to obtain mean information about the full area instead of a single point analysis. Therefore, a new setup is presented using gas-phase Fourier-transform infrared spectroscopy. This method analyzes the gas-phase composition to recalculate the layer composition in electrode fabrication at any time during drying. According to the golden rule of measurement technology, manufacturer specifications are often overestimated. Therefore, our alternative procedures were used to evaluate the precision of devices used. The calculated measurement precision is confirmed by validation. The expected deviation is quantified to be less than 2% for the common application. Further on, the relative test-retest standard deviation is determined to be 0.3%-0.4%. As a result of the error propagation, the measurement precision is limited by the background gas flow rate precision for common application. At low volume fractions, the influence of the substance flow rate deviations becomes significant. However, further studies will focus on increasing the gas flow rate precision.

[Behavioural standard or coercive measure? Some considerations regarding the special issue on ROM]

BACKGROUND

The cost of mental health care has possibly risen more than costs in other sectors of health care in the Netherlands. In an attempt to control the rising costs, new policies have been implemented that include the introduction of selective financial penalties for those in need of mental health care as well as the start of performance-based mental health care reimbursement. In order to achieve the latter goal, a nation-wide large-scale data collection was introduced based on clinical routine outcome monitoring (ROM) data, with a view to using these data for benchmarking.

AIM

Closer inspection of the benchmarking efforts in terms of scientific validity.

METHOD

Qualitative review and analysis.

RESULTS

Analysis shows that the type of ROM data that is collected in the Netherlands is valid for tracking the outcomes of individual patients, but unsuitable for performance comparisons between institutions for reasons of case-mix, instrument-mix, bias and lack of sensitivity.

CONCLUSION

Attempts to introduce benchmarking based on rom will probably have a negative impact on the practice of mental health care in the Netherlands. More input from mental health professionals and scientists is required in order to identify more rational and efficient ways of spending scarce resources.