Differential constellations of dissociative symptoms and their association with childhood trauma - a latent profile analysis.

Background: While several studies documented a positive correlation between childhood maltreatment severity and dissociation severity, it is currently unknown whether specific dissociative symptoms cluster together among individuals with childhood trauma histories ranging from none to severe.Objective: We aimed to explore symptom constellations across the whole spectrum of dissociative processing from patients with severe dissociative disorders to healthy controls and relate these to maltreatment severity and sociodemographic characteristics.Methods: We employed latent profile analysis to explore symptom profiles based on five subscales, measuring absorption, depersonalization, derealization, somatoform and identity alteration, based on the 20 items of the German short version of the Dissociative Experiences Scale-II (Fragebogen zu Dissoziativen Symptomen-20) in a large aggregate sample (n = 3,128) overrepresenting patients with trauma-related disorders. We then related these profiles to maltreatment severity as measured by the five subscales of the Childhood Trauma Questionnaire as well as sociodemographic characteristics.Results: Based on the five FDS subscales, six clusters differentiated by symptom severity, but not symptom constellations, were identified. Somatoform dissociation varied in accordance with the remaining symptom clusters. The cluster with the highest overall symptom severity entailed nearly all subjects diagnosed with Dissociative Identity Disorder and was characterized by extreme levels of childhood maltreatment. Both abuse and neglect were predictive of cluster membership throughout.Conclusions: The higher the severity of dissociative processing in a cluster, the more subjects reported high severity and multiplicity of childhood maltreatment. However, some subjects remain resilient to the development of dissociative processing although they experience extreme childhood maltreatment.

Dissociative symptoms, including identity alterations, are closely related to the severity of experienced childhood abuse.Somatoform dissociation occurs on all levels of overall dissociation severity.Some subjects with a history extreme childhood maltreatment do not develop dissociative symptoms, while some subjects with extreme dissociative symptoms do not report any childhood maltreatment.

Moving across disorders: A cross-sectional study of cognition in early onset ataxia and dystonia.

BACKGROUND: Early onset ataxia (EOA) and Early Onset Dystonia (EOD) are movement disorders developing in young people (age <25 per definition). These disorders result from dysfunctional networks involving the cerebellum and basal ganglia. As these structures are also important for cognition, cognitive deficits can be expected in EOA and EOD. EOA and EOD sometimes co-occur, but in those cases the predominant phenotype is determining. A pending question is whether predominantly EOA and EOD have different profiles of cognitive impairment. OBJECTIVES: We investigated whether cognitive functions were impaired in patients with either predominant EOA or predominant EOD and whether cognitive profiles differed between both patient groups. METHODS: The sample consisted of 26 EOA and 26 EOD patients with varying etiology but similar duration and severity of the disorder. Patient samples were compared to a group of 26 healthy controls, all matched on age and gender. All participants underwent neuropsychological testing for verbal intelligence, memory, working memory, attention/cognitive speed, executive functions, emotion recognition and language. RESULTS: EOA and EOD patients both performed significantly worse than healthy controls on tests of verbal intelligence, working memory and executive functions. Additionally, attention/cognitive speed and emotion recognition were impaired in the EOA group. Compared to EOD, EOA patients performed worse on attention/cognitive speed and verbal intelligence. CONCLUSIONS: Our results show overall similar profiles of cognitive deficits in both patient groups, but deficits were more pronounced in the patients with EOA. This suggests that more severe cognitive impairment is related to more severe cerebellar network dysfunction.

Mixture multilevel vector-autoregressive modeling.

With the rising popularity of intensive longitudinal research, the modeling techniques for such data are increasingly focused on individual differences. Here we present mixture multilevel vector-autoregressive modeling, which extends multilevel vector-autoregressive modeling by including a mixture, to identify individuals with similar traits and dynamic processes. This exploratory model identifies mixture components, where each component refers to individuals with similarities in means (expressing traits), autoregressions, and cross-regressions (expressing dynamics), while allowing for some interindividual differences in these attributes. Key issues in modeling are discussed, where the issue of centering predictors is examined in a small simulation study. The proposed model is validated in a simulation study and used to analyze the affective data from the COGITO study. These data consist of samples for two different age groups of over 100 individuals each who were measured for about 100 days. We demonstrate the advantage of exploratory identifying mixture components by analyzing these heterogeneous samples jointly. The model identifies three distinct components, and we provide an interpretation for each component motivated by developmental psychology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A comprehensive model framework for between-individual differences in longitudinal data.

Across different fields of research, the similarities and differences between various longitudinal models are not always eminently clear due to differences in data structure, application area, and terminology. Here we propose a comprehensive model framework that will allow simple comparisons between longitudinal models, to ease their empirical application and interpretation. At the within-individual level, our model framework accounts for various attributes of longitudinal data, such as growth and decline, cyclical trends, and the dynamic interplay between variables over time. At the between-individual level, our framework contains continuous and categorical latent variables to account for between-individual differences. This framework encompasses several well-known longitudinal models, including multilevel regression models, growth curve models, growth mixture models, vector-autoregressive models, and multilevel vector-autoregressive models. The general model framework is specified and its key characteristics are illustrated using famous longitudinal models as concrete examples. Various longitudinal models are reviewed and it is shown that all these models can be united into our comprehensive model framework. Extensions to the model framework are discussed. Recommendations for selecting and specifying longitudinal models are made for empirical researchers who aim to account for between-individual differences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Trajectories of Emotion Recognition Training in Virtual Reality and Predictors of Improvement for People with a Psychotic Disorder.

Meta-analyses have found that social cognition training (SCT) has large effects on the emotion recognition ability of people with a psychotic disorder. Virtual reality (VR) could be a promising tool for delivering SCT. Presently, it is unknown how improvements in emotion recognition develop during (VR-)SCT, which factors impact improvement, and how improvements in VR relate to improvement outside VR. Data were extracted from task logs from a pilot study and randomized controlled trials on VR-SCT (n = 55). Using mixed-effects generalized linear models, we examined the: (a) effect of treatment session (1-5) on VR accuracy and VR response time for correct answers; (b) main effects and moderation of participant and treatment characteristics on VR accuracy; and (c) the association between baseline performance on the Ekman 60 Faces task and accuracy in VR, and the interaction of Ekman 60 Faces change scores (i.e., post-treatment - baseline) with treatment session. Accounting for the task difficulty level and the type of presented emotion, participants became more accurate at the VR task (b = 0.20, p < 0.001) and faster (b = -0.10, p < 0.001) at providing correct answers as treatment sessions progressed. Overall emotion recognition accuracy in VR decreased with age (b = -0.34, p = 0.009); however, no significant interactions between any of the moderator variables and treatment session were found. An association between baseline Ekman 60 Faces and VR accuracy was found (b = 0.04, p = 0.006), but no significant interaction between difference scores and treatment session. Emotion recognition accuracy improved during VR-SCT, but improvements in VR may not generalize to non-VR tasks and daily life.

Does a three-dimensional Impact Message Inventory-Circumplex (IMI-C) enclose an indirect measure of reactance?

Clinicians can rely on the Impact Message Inventory-Circumplex (IMI-C) to map their emotional reactions to their patients' communication style in octant and main dimension scores on the two-dimensional interpersonal circle, based on affiliation (AFF) and control (CON) as the underlying main dimensions. However, modern emotion theories distinguish three, rather than two, robust dimensions of emotional experience and the perception of interpersonal behaviours: (1) positive versus negative evaluation (related to AFF), (2) strong versus weak (related to CON) and (3) active versus passive (arousal). In a large Dutch patient sample (N = 1,001), we first tested whether the two-dimensional circumplex structure of the IMI-C could be replicated using Browne's circumplex model. Then we explored whether a third dimension could be retrieved from therapists' IMI-C responses using exploratory factor analysis, followed by orthogonal target rotation towards a partially specified target matrix, with the first two factors specified according to the circumplex structure, and the other factor(s) left free. The two-dimensional circumplex of the IMI-C could be validated to a fair extent. Using exploratory factor models, we found supporting evidence for a third factor, which could be interpreted as reflecting reactance ('active' vs. 'passive' opposition). We recommend to extend the current two-dimensional interpretation to a three-dimensional interpretation of IMI-C responses, by adding a reactance dimension.

Investigating Recovery After Subarachnoid Hemorrhage With the Imaging, Cognition and Outcome of Neuropsychological Functioning After Subarachnoid Hemorrhage (ICONS) Study: Protocol for a Longitudinal, Prospective Cohort Study.

BACKGROUND: A subarachnoid hemorrhage is a hemorrhage in the subarachnoid space that is often caused by the rupture of an aneurysm. Patients who survive a subarachnoid hemorrhage have a high risk of complications and a negative long-term outcome. OBJECTIVE: The aim of the Imaging, Cognition and Outcome of Neuropsychological functioning after Subarachnoid hemorrhage (ICONS) study is to investigate whether and to what extent deficits exist in multiple domains after subarachnoid hemorrhage, including cognition, emotion and behavior, and to investigate whether brain damage can be detected in patients with subarachnoid hemorrhage. We aim to determine which early measures of cognition, emotion and behavior, and brain damage in the subacute stage play a role in long-term recovery after subarachnoid hemorrhage. Recovery is defined as functioning at a societal participation level, with a focus on resuming and maintaining work, leisure activities, and social relationships over the long term. METHODS: The ICONS study is an observational, prospective, single-center cohort study. The study includes patients with subarachnoid hemorrhage admitted to the Neurosurgery Unit of the University Medical Centre Groningen in the Netherlands. The inclusion criteria include diagnosis of an aneurysmal subarachnoid hemorrhage or an angiographically negative subarachnoid hemorrhage, sufficient ability in the Dutch language, and age older than 18 years. Patients will undergo neuropsychological assessment and magnetic resonance imaging 6 months after the subarachnoid hemorrhage. Furthermore, patients will be asked to fill in questionnaires on multiple psychosocial measures and undergo a structured interview at 6 months, 1 year, and 2 years after the subarachnoid hemorrhage. The primary outcome measure of the ICONS study is societal participation 1 year after the subarachnoid hemorrhage, measured with the Dutch version of the Impact on Participation and Autonomy questionnaire. RESULTS: The study was launched in December 2019 and recruitment is expected to continue until June 2023. At the time of the acceptance of this paper, 76 patients and 69 healthy controls have been included. The first results are expected in early 2023. CONCLUSIONS: The ICONS study is the first to collect and combine data after subarachnoid hemorrhage in a variety of domains, including cognition, emotion and behavior, and brain damage. The results will contribute to a more comprehensive understanding of the consequences of both aneurysmal subarachnoid hemorrhage and angiographically negative subarachnoid hemorrhage, which may ultimately optimize timely treatment for this patient group by setting realistic and attainable goals to improve daily functioning. TRIAL REGISTRATION: Netherlands Trial Register NL7803; https://trialsearch.who.int/Trial2.aspx?TrialID=NL7803. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/38190.

The reward and punishment responsivity and motivation questionnaire (RPRM-Q): A stimulus-independent self-report measure of reward and punishment sensitivity that differentiates between responsivity and motivation.

Reward and punishment sensitivity seem important traits in understanding behavior in general and psychopathology in particular. Though the definitions used for reward and punishment sensitivity differentiate between responsivity and motivation, the measures thus far used to assess these constructs do not. Further, specificity of the type of reward (e.g., drugs) and punishment (e.g., spiders) in questionnaires might result in measurement bias especially when examining the relationship with psychopathology. Therefore, we developed a stimulus-independent multidimensional questionnaire of reward and punishment sensitivity that differentiates between responsivity and motivation. This study addresses the psychometric qualities of this newly developed reward and punishment responsivity and motivation questionnaire (RPRM-Q). On the basis of exploratory ordinal factor analysis (N = 273) that was used to examine the quality of the initial pool of 39 items, the number of items was reduced to 18. Confirmatory ordinal factor analysis on the remaining items in an independent sample (N = 328) supported a 18-item four-factor model, and showed acceptable to good internal reliability. The relationship between the subscales of the RPRM-Q and often used questionnaires was examined in the combined sample (N = 601), which showed some first support for the ability of the new questionnaire to differentiate between responsivity and motivation to approach/avoid. The findings indicate that the RPRM-Q might be a helpful instrument to further test the relevance of punishment and reward sensitivity in psychopathology.

Normative data for the self-reported and parent-reported Strengths and Difficulties Questionnaire (SDQ) for ages 12-17.

BACKGROUND: The Strengths and Difficulties Questionnaire (SDQ) is widely used to screen for psychosocial problems among adolescents. As the severity of such problems is known to be related to age and gender, screening could be improved by interpreting SDQ scale scores with age-specific and perhaps gender-specific norms. Up to now, such norms are lacking. The aim of the current study is to present gender-specific and joint normative data per year of age for the Dutch self-reported and parent-reported SDQ versions for use among 12- to 17-year-old adolescents. METHODS: The norm groups for the self-reported and parent-reported SDQ versions consisted of 993 adolescents and 736 parents, respectively, from the general Dutch population. Per SDQ version, both gender-specific norms and joint norms (percentiles and cutoffs) per year of age were calculated through regression-based norming (Rigby in J Roy Stat Soc Ser C 54:507, 2005). Additionally, these norms were compared to the widely used British norms that are neither age-specific nor gender-specific. RESULTS: By design, gender-specific 'abnormal' cutoffs (i.e., cutoffs aimed at identifying max. 10% of the most extremely scoring males and max. 10% of the most extremely scoring females) resulted in about equal percentages of 'abnormal' scoring male and female adolescents per SDQ scale. In contrast, joint 'abnormal' cutoffs (i.e., cutoffs aimed at identifying max. 10% of the most extremely scoring adolescents) resulted in relatively more male (7.6 to 13.6%, depending on age) than female (3.3 to 8.9%, depending on age) adolescents as scoring 'abnormal' on scales measuring externalizing behavior (self-reported and parent-reported SDQ versions), and relatively more female (3.9 to 14.3%, depending on age) than male (1.8 to 6.9%, depending on age) adolescents as scoring 'abnormal' on scales measuring internalizing behavior (self-reported SDQ version). In both types of norms, minor age effects were present. Among Dutch adolescents, the British norms yielded detection rates much lower than the expected 10%. CONCLUSIONS: Our findings indicate that detection rates depend on the reference group that is used (British or Dutch general adolescent population; specific gender group or not). The normative data in this paper facilitate the comparison of an adolescent's scores to different reference groups, and allow for cross-country/cultural comparisons of adolescents' psychosocial behavior.

Treating Speech Anxiety in Youth: A Randomized Controlled Microtrial Testing the Efficacy of Exposure Only Versus Exposure Combined With Anxiety Management Strategies.

CBT for anxious youth usually combines anxiety management strategies (AMS) with exposure, with exposure assumed to be critical for treatment success. To limit therapy time while retaining effectiveness, one might optimize CBT by restricting treatment to necessary components. This study tested whether devoting all sessions to exposure is more effective in reducing speech anxiety in youth than devoting half to AMS including cognitive or relaxation strategies and half to exposure. After a 6-week waitlist period, adolescents with speech anxiety (N = 65; age 12-15; 42 girls) were randomized to a 5-session in-school group-based CBT training consisting of either (1) exposure-only (EXP+EXP) or (2) cognitive strategies followed by exposure (COG+EXP) or (3) relaxation strategies followed by exposure (REL+EXP). Clinical interviews, speech tests, and self-report measures were assessed at pretest, posttest, and follow-up. For all conditions (a) the intervention period resulted in a stronger decline of speech anxiety than waitlist period; (b) there was a large sized reduction of speech anxiety that was maintained at six-week follow-up; (c) there was no meaningful difference in the efficacy of EXP+EXP versus COG+EXP or REL+EXP. These findings suggest that devoting all sessions to exposure is not more effective than combining exposure with AMS. AMS appeared neither necessary for CBT to be effective, nor necessary for youth to tolerate exposure. This indicates that CBT can be optimized by restricting treatment to exposure.

Trajectories of Fatigue, Psychological Distress, and Coping Styles After Mild Traumatic Brain Injury: A 6-Month Prospective Cohort Study.

OBJECTIVE: To analyze fatigue after mild traumatic brain injury (TBI) with latent class growth analysis (LCGA) to determine distinct recovery trajectories and investigate influencing factors, including emotional distress and coping styles. DESIGN: An observational cohort study design with validated questionnaires assessing fatigue, anxiety, depression, posttraumatic stress, and coping at 2 weeks and 3 and 6 months postinjury. SETTING: Three level 1 trauma centers. PARTICIPANTS: Patients with mild TBI (N=456). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Fatigue was measured with the fatigue severity subscale of the Checklist Individual Strength, including 8 items (sum score, 8-56). Subsequently, 3 clinical categories were created: high (score, 40-56), moderate (score, 26-38), and low (score, 8-25). RESULTS: From the entire mild TBI group, 4 patient clusters with distinct patterns for fatigue, emotional distress, and coping styles were found with LCGA. Clusters 1 and 2 showed favorable recovery from fatigue over time, with low emotional distress and the predominant use of active coping in cluster 1 (30%) and low emotional distress and decreasing passive coping in cluster 2 (25%). Clusters 3 and 4 showed unfavorable recovery, with persistent high fatigue and increasing passive coping together with low emotional distress in cluster 3 (27%) and high emotional distress in cluster 4 (18%). Patients with adverse trajectories were more often women and more often experiencing sleep disturbances and pain. CONCLUSIONS: The prognosis for recovery from posttraumatic fatigue is favorable for 55% of mild TBI patients. Patients at risk for chronic fatigue can be signaled in the acute phase postinjury based on the presence of high fatigue, high passive coping, and, for a subgroup of patients, high emotional distress. LCGA proved to be a highly valuable and multipurpose statistical method to map distinct courses of disease-related processes over time.

White matter microstructure of the neural emotion regulation circuitry in mild traumatic brain injury.

Emotion regulation is related to recovery after mild traumatic brain injury (mTBI). This longitudinal tractography study examined white matter tracts subserving emotion regulation across the spectrum of mTBI, with a focus on persistent symptoms. Four groups were examined: (a) symptomatic (n = 33) and (b) asymptomatic (n = 20) patients with uncomplicated mTBI (i.e., no lesions on computed tomography [CT]), (c) patients with CT-lesions in the frontal areas (n = 14), and (d) healthy controls (HC) (n = 20). Diffusion and conventional MRI were performed approximately 1- and 3-months post-injury. Whole-brain deterministic tractography followed by region of interest analyses was used to identify forceps minor (FM), uncinate fasciculus (UF), and cingulum bundle as tracts of interest. An adjusted version of the ExploreDTI Atlas Based Tractography method was used to obtain reliable tracts for every subject. Mean fractional anisotropy (FA), mean, radial and axial diffusivity (MD, RD, AD), and number of streamlines were studied per tract. Linear mixed models showed lower FA, and higher MD, and RD of the right UF in asymptomatic patients with uncomplicated mTBI relative to symptomatic patients and HC. Diffusion alterations were most pronounced in the group with frontal lesions on CT, particularly in the FM and UF; these effects increased over time. Within the group of patients with uncomplicated mTBI, there were no associations of diffusion measures with the number of symptoms nor with lesions on conventional MRI. In conclusion, mTBI can cause microstructural changes in emotion regulation tracts, however, no explanation was found for the presence of symptoms.

Insight Into Individual Differences in Emotion Dynamics With Clustering.

Studying emotion dynamics through time series models is becoming increasingly popular in the social sciences. Across individuals, dynamics can be rather heterogeneous. To enable comparisons and generalizations of dynamics across groups of individuals, one needs sophisticated tools that express the essential similarities and differences. A way to proceed is to identify subgroups of people who are characterized by qualitatively similar emotion dynamics through dynamic clustering. So far, these methods assume equal generating processes for individuals per cluster. To avoid this overly restrictive assumption, we outline a probabilistic clustering approach based on a mixture model that clusters on individuals' vector autoregressive coefficients. We evaluate the performance of the method and compare it with a nonprobabilistic method in a simulation study. The usefulness of the methods is illustrated using 366 ecological momentary assessment time series with external measures of depression and anxiety.

A tutorial on regression-based norming of psychological tests with GAMLSS.

A norm-referenced score expresses the position of an individual test taker in the reference population, thereby enabling a proper interpretation of the test score. Such normed scores are derived from test scores obtained from a sample of the reference population. Typically, multiple reference populations exist for a test, namely when the norm-referenced scores depend on individual characteristic(s), as age (and sex). To derive normed scores, regression-based norming has gained large popularity. The advantages of this method over traditional norming are its flexible nature, yielding potentially more realistic norms, and its efficiency, requiring potentially smaller sample sizes to achieve the same precision. In this tutorial, we introduce the reader to regression-based norming, using the generalized additive models for location, scale, and shape (GAMLSS). This approach has been useful in norm estimation of various psychological tests. We discuss the rationale of regression-based norming, theoretical properties of GAMLSS and their relationships to other regression-based norming models. Based on 6 steps, we describe how to: (a) design a normative study to gather proper normative sample data; (b) select a proper GAMLSS model for an empirical scale; (c) derive the desired normed scores for the scale from the fitted model, including those for a composite scale; and (d) visualize the results to achieve insight into the properties of the scale. Following these steps yields regression-based norms with GAMLSS for a psychological test, as we illustrate with normative data of the intelligence test IDS-2. The complete R code and data set is provided as online supplemental material. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training.

With Latent Class Analysis applied on data of 98 children with autism spectrum disorder (ASD) (9-12 years; 17 girls) participating in social skills training (SST) in a randomized controlled trial (Dekker et al. 2019), four subgroups were detected, based on social-communicative skills before, and response patterns to training. Two subgroups improved after SST. Characterizing the subgroups based on participant and intervention characteristics showed that improvement was related to lower parent-reported perceived difficulty of social-communicative skills at start, higher verbal ability, younger age and milder symptoms of ASD and anxiety. The lowest performing non-improving subgroup participated more often in SST without parent/teacher involvement, compared to all other subgroups. Response to SST in ASD seems to vary depending on participant characteristics.

Clinical, societal and personal recovery in schizophrenia spectrum disorders across time: states and annual transitions.

BACKGROUND: Recovery in schizophrenia is a complex process, involving clinical, societal and personal recovery. Until now, studies analysed these domains separately, without examining their mutual relations and changes over time. AIMS: This study aimed to examine different states of recovery and transition rates between states. METHOD: The Pharmacotherapy Monitoring and Outcome Survey (2006-2017) yearly assesses patients with schizophrenia in the Northern Netherlands. Data from 2327 patients with one up to 11 yearly measurements on clinical, societal and personal recovery were jointly analysed with a mixture latent Markov model (MLMM). RESULTS: The selected MLMM had four states that differed in degree and pattern of recovery outcomes. Patients in state 1 were least recovered on any domain (16% of measurements), and partly recovered in states 2 (25%; featured by negative symptoms) and 3 (21%; featured by positive symptoms). Patients in state 4 (38%) were most recovered, except for work, study and housekeeping. At the subsequent measurement, the probability of remaining in the same state was 77-89%, transitioning to a better state was 4-12% and transitioning to a worse state was 4-6%; no transitions occurred between states 1 and 4. Female gender, shorter illness duration and less schizophrenia were more prevalent in better states. CONCLUSIONS: Quite a high recovery rate was present among a substantial part of the measurements (38%, state 4), with a high probability (89%) of remaining in this state. Transition rates in the other states might increase to a more favourable state by focusing on adequate treatment of negative and positive symptoms and societal problems.

Bias-Variance Trade-Off in Continuous Test Norming.

In continuous test norming, the test score distribution is estimated as a continuous function of predictor(s). A flexible approach for norm estimation is the use of generalized additive models for location, scale, and shape. It is unknown how sensitive their estimates are to model flexibility and sample size. Generally, a flexible model that fits at the population level has smaller bias than its restricted nonfitting version, yet it has larger sampling variability. We investigated how model flexibility relates to bias, variance, and total variability in estimates of normalized z scores under empirically relevant conditions, involving the skew Student t and normal distributions as population distributions. We considered both transversal and longitudinal assumption violations. We found that models with too strict distributional assumptions yield biased estimates, whereas too flexible models yield increased variance. The skew Student t distribution, unlike the Box-Cox Power Exponential distribution, appeared problematic to estimate for normally distributed data. Recommendations for empirical norming practice are provided.

Bayesian Gaussian distributional regression models for more efficient norm estimation.

A test score on a psychological test is usually expressed as a normed score, representing its position relative to test scores in a reference population. These typically depend on predictor(s) such as age. The test score distribution conditional on predictors is estimated using regression, which may need large normative samples to estimate the relationships between the predictor(s) and the distribution characteristics properly. In this study, we examine to what extent this burden can be alleviated by using prior information in the estimation of new norms with Bayesian Gaussian distributional regression. In a simulation study, we investigate to what extent this norm estimation is more efficient and how robust it is to prior model deviations. We varied the prior type, prior misspecification and sample size. In our simulated conditions, using a fixed effects prior resulted in more efficient norm estimation than a weakly informative prior as long as the prior misspecification was not age dependent. With the proposed method and reasonable prior information, the same norm precision can be achieved with a smaller normative sample, at least in empirical problems similar to our simulated conditions. This may help test developers to achieve cost-efficient high-quality norms. The method is illustrated using empirical normative data from the IDS-2 intelligence test.

The combined self- and parent-rated SDQ score profile predicts care use and psychiatric diagnoses.

The Strengths and Difficulties Questionnaire (SDQ) is widely used, based on evidence of its value for screening. This evidence primarily regards the single informant total difficulties scale and separate difficulties subscales. We assessed to what degree adolescents' SDQ profiles that combined all self- and parent-rated subscales were associated with use of care and psychiatric diagnoses, and examined the added value thereof over using only a single informant and the total scale. Cluster analysis was used to identify common SDQ profiles based on self- and parent-reports among adolescents aged 12-17 in mental healthcare (n = 4282), social care (n = 124), and the general population (n = 1293). We investigated associations of the profiles with 'care use' and 'DSM-IV diagnoses', depending on gender. We identified six common SDQ profiles: five profiles with varying types and severities of reported difficulties, pertaining to 95% of adolescents in care, and one without difficulties, pertaining to 55% of adolescents not in care. The types of reported difficulties in the profiles matched DSM-IV diagnoses for 88% of the diagnosed adolescents. The SDQ profiles were found to be more useful for predicting care use and diagnoses than SDQ scores reported by the adolescent as single informant and the total difficulties scale. The latter indicated the presence of problems among 42-63% of the adolescents in care, missing a substantial number of adolescents with reported emotional difficulties and borderline problem severity. These findings advocate the use of combined self- and parent-rated SDQ score profiles for screening.

Facilitating Recovery of Daily Functioning in People With a Severe Mental Illness Who Need Longer-Term Intensive Psychiatric Services: Results From a Cluster Randomized Controlled Trial on Cognitive Adaptation Training Delivered by Nurses.

BACKGROUND: Feasible and effective interventions to improve daily functioning in people with a severe mental illness (SMI), such as schizophrenia, in need of longer-term rehabilitation are scarce. AIMS: We assessed the effectiveness of Cognitive Adaptation Training (CAT), a compensatory intervention to improve daily functioning, modified into a nursing intervention. METHOD: In this cluster randomized controlled trial, 12 nursing teams were randomized to CAT in addition to treatment as usual (CAT; n = 42) or TAU (n = 47). Daily functioning (primary outcome) was assessed every 3 months for 1 year. Additional follow-up assessments were performed for the CAT group in the second year. Secondary outcomes were assessed every 6 months. Data were analyzed using multilevel modeling. RESULTS: CAT participants improved significantly on daily functioning, executive functioning, and visual attention after 12 months compared to TAU. Improvements were maintained after 24 months. Improved executive functioning was related to improved daily functioning. Other secondary outcomes (quality of life, empowerment, negative symptoms) showed no significant effects. CONCLUSIONS: As a nursing intervention, CAT leads to maintained improvements in daily functioning, and may improve executive functioning and visual attention in people with SMI in need of longer-term intensive psychiatric care. Given the paucity of evidence-based interventions in this population, CAT can become a valuable addition to recovery-oriented care.