Non-fear emotions in changes in posttraumatic stress disorder symptoms during treatment.

BACKGROUND AND OBJECTIVES: Posttraumatic stress disorder (PTSD) is not only associated with fear but also with other emotions. The present study aimed to examine if changes in shame, guilt, anger, and disgust predicted changes in PTSD symptoms during treatment, while also testing if PTSD symptoms, in turn, predicted changes in these emotions. METHODS: Participants (N = 155) with childhood-related PTSD received a maximum of 12 sessions of eye movement desensitization and reprocessing or imagery rescripting. The data was analyzed using Granger causality models across 12 treatment sessions and 6 assessment sessions (up until one year after the start of treatment). Differences between the two treatments were explored. RESULTS: Across treatment sessions, shame, and disgust showed a reciprocal relationship with PTSD symptoms, while changes in guilt preceded PTSD symptoms. Across assessments, anger was reciprocally related to PTSD, suggesting that anger might play a more important role in the longer term. LIMITATIONS: The individual emotion items were not yet validated, and the CAPS was not administered at all assessments. CONCLUSIONS: These findings partly differ from earlier studies that suggested a unidirectional relationship in which changes in emotions preceded changes in PTSD symptoms during treatment. This is in line with the idea that non-fear emotions do play an important role in the treatment of PTSD and constitute an important focus of treatment and further research.

Group schema therapy for cluster-C personality disorders: A multicentre open pilot study.

BACKGROUND: Group schema therapy (GST) is increasingly popular as a treatment for personality disorders (PDs), including Cluster-C PDs. Individual ST has proven to be effective for Cluster-C PD patients, while the evidence for GST is limited. This study aimed to investigate the effectiveness of GST for Cluster-C PD. Moreover, differences between the specific Cluster-C PDs (avoidant PD, dependent PD and obsessive-compulsive PD) were explored. METHODS: A multicentre open trial was conducted, including 137 patients with a Cluster-C PD (avoidant PD: n = 107, dependent PD: n = 11 and obsessive-compulsive PD: n = 19). Patients received 30 weekly GST sessions with a maximum of 180 min of individual ST and five optional monthly booster sessions. Outcome measures including Cluster-C PD severity, general psychopathological symptoms, quality of life, functional impairment, happiness, PD-related beliefs, self-esteem, self-ideal discrepancy, schemas and schema modes were assessed at baseline until 2-year follow-up with semi-structured interviews and self-report measures. Change over time and differences between the specific Cluster-C PDs were analysed with mixed regression analyses. RESULTS: The outcome measures showed significant improvements for all Cluster-C PDs, with medium to large effect sizes after 2 years. A treatment dropout rate of 11.7% was found. There were some indications for differences between the Cluster-C PDs in severity at baseline, change trajectories and effectiveness of GST. CONCLUSIONS: This study demonstrated that GST is a promising treatment for Cluster-C PDs. The following step is a randomized controlled trial to further document the (cost-)effectiveness of GST.

Dropout from psychological treatment for borderline personality disorder: a multilevel survival meta-analysis.

BACKGROUND: Dropout from psychotherapy for borderline personality disorder (BPD) is a notorious problem. We investigated whether treatment, treatment format, treatment setting, substance use exclusion criteria, proportion males, mean age, country, and other variables influenced dropout. METHODS: From Pubmed, Embase, Cochrane, Psycinfo and other sources, 111 studies (159 treatment arms, N = 9100) of psychotherapy for non-forensic adult patients with BPD were included. Dropout per quarter during one year of treatment was analyzed on participant level with multilevel survival analysis, to deal with multiple predictors, nonconstant dropout chance over time, and censored data. Multiple imputation was used to estimate quarter of drop-out if unreported. Sensitivity analyses were done by excluding DBT-arms with deviating push-out rules. RESULTS: Dropout was highest in the first quarter of treatment. Schema therapy had the lowest dropout overall, and mentalization-based treatment in the first two quarters. Community treatment by experts had the highest dropout. Moreover, individual therapy had lowest dropout, group therapy highest, with combined formats in-between. Other variables such as age or substance-use exclusion criteria were not associated with dropout. CONCLUSION: The findings do not support claims that all treatments are equal, and indicate that efforts to reduce dropout should focus on early stages of treatment and on group treatment.

Threat learning impairs subsequent associative inference.

Despite it being widely acknowledged that the most important function of memory is to facilitate the prediction of significant events in a complex world, no studies to date have investigated how our ability to infer associations across distinct but overlapping experiences is affected by the inclusion of threat memories. To address this question, participants (n = 35) encoded neutral predictive associations (A → B). The following day these memories were reactivated by pairing B with a new aversive or neutral outcome (B → CTHREAT/NEUTRAL) while pupil dilation was measured as an index of emotional arousal. Then, again 1 day later, the accuracy of indirect associations (A → C?) was tested. Associative inferences involving a threat learning memory were impaired whereas the initial memories were retroactively strengthened, but these effects were not moderated by pupil dilation at encoding. These results imply that a healthy memory system may compartmentalize episodic information of threat, and so hinders its recall when cued only indirectly. Malfunctioning of this process may cause maladaptive linkage of negative events to distant and benign memories, and thereby contribute to the development of clinical intrusions and anxiety.

Design of an RCT on cost-effectiveness of group schema therapy versus individual schema therapy for patients with Cluster-C personality disorder: the QUEST-CLC study protocol.

BACKGROUND: Given the high prevalence of Cluster-C Personality Disorders (PDs) in clinical populations, disease burden, high societal costs and poor prognosis of comorbid disorders, a major gain in health care can be achieved if Cluster-C PDs are adequately treated. The only controlled cost-effectiveness study published so far found Individual Schema Therapy (IST) to be superior to Treatment as Usual (TAU). Group ST (GST) might improve cost-effectiveness as larger numbers can be treated in (>50%) less time compared to IST. However, to date there is no RCT supporting its (cost-) effectiveness. The overall aim of this study is to assess the evidence for GST for Cluster-C PDs and to improve treatment allocation for individual patients. Three main questions are addressed: 1) Is GST for Cluster-C PDs (cost-)effective compared to TAU? 2) Is GST for Cluster-C PDs (cost-) effective compared to IST? 3) Which patient-characteristics predict better response to GST, IST, or TAU? METHODS: In a multicenter RCT, the treatment conditions GST, IST, and TAU are compared in 378 Cluster-C PD patients within 10 sites. GST and IST follow treatment protocols and are completed within 1 year. TAU is the optimal alternative treatment available at the site according to regular procedures. Severity of the Cluster-C PD is the primary outcome, assessed with clinical interviews by independent raters blind for treatment. Functioning and wellbeing are important secondary outcomes. Assessments take place at week 0 (baseline), 17 (mid-GST), 34 (post-GST), 51 (post-booster sessions of GST), and 2 years (FU). Patient characteristics predicting better response to a specific treatment are studied, e.g., childhood trauma, autistic features, and introversion. A tool supporting patients and clinicians in matching treatment to patient will be developed. An economic evaluation investigates the cost-effectiveness and cost-utility from a societal perspective. A process evaluation by qualitative methods explores experiences of participants, loved ones and therapists regarding recovery, quality of life, and improving treatment. DISCUSSION: This study will determine the (cost-)effectiveness of treatments for Cluster-C PDs regarding treatment type as well as optimal matching of patient to treatment and deliver insight into which aspects help Cluster-C-PD patients recover and create a fulfilling life. TRIAL REGISTRATION: Dutch Trial Register: NL9209 . Registered on 28-01-2021.

Towards optimal treatment selection for borderline personality disorder patients (BOOTS): a study protocol for a multicenter randomized clinical trial comparing schema therapy and dialectical behavior therapy.

BACKGROUND: Specialized evidence-based treatments have been developed and evaluated for borderline personality disorder (BPD), including Dialectical Behavior Therapy (DBT) and Schema Therapy (ST). Individual differences in treatment response to both ST and DBT have been observed across studies, but the factors driving these differences are largely unknown. Understanding which treatment works best for whom and why remain central issues in psychotherapy research. The aim of the present study is to improve treatment response of DBT and ST for BPD patients by a) identifying patient characteristics that predict (differential) treatment response (i.e., treatment selection) and b) understanding how both treatments lead to change (i.e., mechanisms of change). Moreover, the clinical effectiveness and cost-effectiveness of DBT and ST will be evaluated. METHODS: The BOOTS trial is a multicenter randomized clinical trial conducted in a routine clinical setting in several outpatient clinics in the Netherlands. We aim to recruit 200 participants, to be randomized to DBT or ST. Patients receive a combined program of individual and group sessions for a maximum duration of 25 months. Data are collected at baseline until three-year follow-up. Candidate predictors of (differential) treatment response have been selected based on the literature, a patient representative of the Borderline Foundation of the Netherlands, and semi-structured interviews among 18 expert clinicians. In addition, BPD-treatment-specific (ST: beliefs and schema modes; DBT: emotion regulation and skills use), BPD-treatment-generic (therapeutic environment characterized by genuineness, safety, and equality), and non-specific (attachment and therapeutic alliance) mechanisms of change are assessed. The primary outcome measure is change in BPD manifestations. Secondary outcome measures include functioning, additional self-reported symptoms, and well-being. DISCUSSION: The current study contributes to the optimization of treatments for BPD patients by extending our knowledge on "Which treatment - DBT or ST - works the best for which BPD patient, and why?", which is likely to yield important benefits for both BPD patients (e.g., prevention of overtreatment and potential harm of treatments) and society (e.g., increased economic productivity of patients and efficient use of treatments). TRIAL REGISTRATION: Netherlands Trial Register, NL7699 , registered 25/04/2019 - retrospectively registered.

Postural freezing relates to startle potentiation in a human fear-conditioning paradigm.

Freezing to impending threat is a core defensive response. It has been studied primarily using fear conditioning in non-human animals, thwarting advances in translational human anxiety research that has used other indices, such as skin conductance responses. Here we examine postural freezing as a human conditioning index for translational anxiety research. We employed a mixed cued/contextual fear-conditioning paradigm where one context signals the occurrence of the US upon the presentation of the CS, and another context signals that the CS is not followed by the US. Critically, during the following generalization phase, the CS is presented in a third and novel context. We show that human freezing is highly sensitive to fear conditioning, generalizes to ambiguous contexts, and amplifies with threat imminence. Intriguingly, stronger parasympathetically driven freezing under threat, but not sympathetically mediated skin conductance, predicts subsequent startle magnitude. These results demonstrate that humans show fear-conditioned animal-like freezing responses, known to aid in active preparation for unexpected attack, and that freezing captures real-life anxiety expression. Conditioned freezing offers a promising new, non-invasive, and continuous, readout for human fear conditioning, paving the way for future translational studies into human fear and anxiety.

Effectiveness of Psychological Treatments for Borderline Personality Disorder and Predictors of Treatment Outcomes: A Multivariate Multilevel Meta-Analysis of Data from All Design Types.

We examined the effectiveness of psychotherapies for adult Borderline Personality Disorder (BPD) in a multilevel meta-analysis, including all trial types (PROSPERO ID: CRD42020111351). We tested several predictors, including trial- and outcome type (continuous or dichotomous), setting, BPD symptom domain and mean age. We included 87 studies (N = 5881) from searches between 2013 and 2019 in four databases. We controlled for differing treatment lengths and a logarithmic relationship between treatment duration and effectiveness. Sensitivity analyses were conducted by excluding outliers and by prioritizing total scale scores when both subscale and total scores were reported. Schema Therapy, Mentalization-Based Treatment and reduced Dialectical Behavior Therapy were associated with higher effect sizes than average, and treatment-as-usual with lower effect sizes. General severity and affective instability showed the strongest improvement, dissociation, anger, impulsivity and suicidality/self-injury the least. Treatment effectiveness decreased as the age of participants increased. Dichotomous outcomes were associated to larger effects, and analyses based on last observation carried forward to smaller effects. Compared to the average, the highest reductions were found for certain specialized psychotherapies. All BPD domains improved, though not equally. These findings have a high generalizability. However, causal conclusions cannot be drawn, although the design type did not influence the results.

Subtypes of smokers in a randomized controlled trial of a web-based smoking cessation program and their role in predicting intervention non-usage attrition: Implications for the development of tailored interventions.

INTRODUCTION: Web-based smoking interventions hold potential for smoking cessation; however, many of them report low intervention usage (i.e., high levels of non-usage attrition). One strategy to counter this issue is to tailor such interventions to user subtypes if these can be identified and related to non-usage attrition outcomes. The aim of this study was two-fold: (1) to identify and describe a smoker typology in participants of a web-based smoking cessation program and (2) to explore subtypes of smokers who are at a higher risk for non-usage attrition (i.e., early dropout times). METHODS: We conducted secondary analyses of data from a large randomized controlled trial (RCT) that investigated effects of a web-based Cognitive Bias Modification intervention in adult smokers. First, we conducted a two-step cluster analysis to identify subtypes of smokers based on participants' baseline characteristics (including demographics, psychological and smoking-related variables, N = 749). Next, we conducted a discrete-time survival analysis to investigate the predictive value of the subtypes on time until dropout. RESULTS: We found three distinct clusters of smokers: Cluster 1 (25.2%, n = 189) was characterized by participants being relatively young, highly educated, unmarried, light-to-moderate smokers, poly-substance users, and relatively high scores on sensation seeking and impulsivity; Cluster 2 (41.0%, n = 307) was characterized by participants being older, with a relatively high socio-economic status (SES), moderate-to-heavy smokers and regular drinkers; Cluster 3 (33.8%, n = 253) contained mostly females of older age, and participants were further characterized by a relatively low SES, heavy smoking, and relatively high scores on hopelessness, anxiety sensitivity, impulsivity, depression, and alcohol use. Additionally, Cluster 1 was more likely to drop out at the early stage of the intervention compared to Cluster 2 (adjusted Hazard Ratio (HR adjusted) = 1.51, 95% CI = [1.25, 1.83]) and Cluster 3 (HR adjusted = 1.52, 95% CI = [1.25, 1.86]). CONCLUSIONS: We identified three clusters of smokers that differed on a broad range of characteristics and on intervention non-usage attrition patterns. This highlights the heterogeneity of participants in a web-based smoking cessation program. Also, it supports the idea that such interventions could be tailored to these subtypes to prevent non-usage attrition. The subtypes of smokers identified in this study need to be replicated in the field of e-health outside the context of RCT; based on the smoker subtypes identified in this study, we provided suggestions for developing tailored web-based smoking cessation intervention programs in future research.

Moderate acute alcohol use impairs intentional inhibition rather than stimulus-driven inhibition.

Moderate alcohol intake may impair stimulus-driven inhibition of motor actions in go/no-go and stop-signal tasks. Exposure to alcohol-related cues has been found to exacerbate this impairment. By contrast, the effect of alcohol use on intentional inhibition, or the capacity to voluntarily suspend an action, has rarely been investigated. We examined whether and how moderate alcohol intake affects stimulus-driven inhibition (stop-signal task) and intentional inhibition (chasing bottles task), during exposure to alcohol-related stimuli. One hundred and eleven participants were randomly assigned to an alcohol (male: 0.55 g/kg, female: 0.45 g/kg), placebo, or control group. For the stop-signal task, ANOVAs were performed on stop-signal reaction time (SSRT) and go RT with Pharmacological and Expectancy Effects of Alcohol, Stimulus Category (alcohol-related or neutral), and Sex as factors. For the chasing bottles task, multilevel survival analysis was performed to predict whether and when intentional inhibition was initiated, with the same factors. For the stop-signal task, Sex moderated the Pharmacological Effect of Alcohol on SSRT: only for females, alcohol consumption shortened SSRT. In the non-alcohol groups, males had shorter SSRT than females. Concerning intentional inhibition, the alcohol group initiated intentional inhibition less often, especially when stimuli were non-alcohol related. These findings indicate that (1) stimulus-driven inhibition and intentional inhibition reflect different aspects of response inhibition; (2) moderate alcohol intake negatively affects intentional inhibition (but not stimulus-driven inhibition). Speculatively, the observed impairment in intentional inhibition might underlie the lack of control over alcohol drinking behavior after a priming dose. This study highlights the potential role of intentional inhibition in the development of addiction.

Combining Web-Based Attentional Bias Modification and Approach Bias Modification as a Self-Help Smoking Intervention for Adult Smokers Seeking Online Help: Double-Blind Randomized Controlled Trial.

BACKGROUND: Automatically activated cognitive motivational processes such as the tendency to attend to or approach smoking-related stimuli (ie, attentional and approach bias) have been related to smoking behaviors. Therefore, these cognitive biases are thought to play a role in maintaining smoking behaviors. Cognitive biases can be modified with cognitive bias modification (CBM), which holds promise as an easy-access and low-cost online intervention. However, little is known about the effectiveness of online interventions combining two varieties of CBM. Targeting multiple cognitive biases may improve treatment outcomes because these biases have been shown to be relatively independent. OBJECTIVE: This study aimed to test the individual and combined effects of two web-based CBM varieties-attentional bias modification (AtBM) and approach bias modification (ApBM)-in a double-blind randomized controlled trial (RCT) with a 2 (AtBM: active versus sham) × 2 (ApBM: active versus sham) factorial design. METHODS: A total of 504 adult smokers seeking online help to quit smoking were randomly assigned to 1 of 4 experimental conditions to receive 11 fully automated CBM training sessions. To increase participants' intrinsic motivation to change their smoking behaviors, all participants first received brief, automated, tailored feedback. The primary outcome was point prevalence abstinence during the study period. Secondary outcomes included daily cigarette use and attentional and approach bias. All outcomes were repeatedly self-assessed online from baseline to the 3-month follow-up. For the examination of training effects on outcome changes, an intention-to-treat analysis with a multilevel modeling (MLM) approach was adopted. RESULTS: Only 10.7% (54/504) of the participants completed all 11 training sessions, and 8.3% (42/504) of the participants reached the 3-month follow-up assessment. MLM showed that over time, neither AtBM or ApBM nor a combination of both differed from their respective sham training in point prevalence abstinence rates (P=.17, P=.56, and P=.14, respectively), and in changes in daily cigarette use (P=.26, P=.08, and P=.13, respectively), attentional bias (P=.07, P=.81, and P=.15, respectively), and approach bias (P=.57, P=.22, and P=.40, respectively), while daily cigarette use decreased over time across conditions for all participants (P<.001). CONCLUSIONS: This RCT provides no support for the effectiveness of combining AtBM and ApBM in a self-help web-based smoking cessation intervention. However, this study had a very high dropout rate and a very low frequency of training usage, indicating an overall low acceptability of the intervention, which precludes any definite conclusion on its efficacy. We discuss how this study can inform future designs and settings of online CBM interventions. TRIAL REGISTRATION: Netherlands Trial Register NTR4678; https://www.trialregister.nl/trial/4678.

Dynamics of sleep: Exploring critical transitions and early warning signals.

BACKGROUND AND OBJECTIVES: In standard practice, sleep is classified into distinct stages by human observers according to specific rules as for instance specified in the AASM manual. We here show proof of principle for a conceptualization of sleep stages as attractor states in a nonlinear dynamical system in order to develop new empirical criteria for sleep stages. METHODS: EEG (single channel) of two healthy sleeping participants was used to demonstrate this conceptualization. Firstly, distinct EEG epochs were selected, both detected by a MLR classifier and through manual scoring. Secondly, change point analysis was used to identify abrupt changes in the EEG signal. Thirdly, these detected change points were evaluated on whether they were preceded by early warning signals. RESULTS: Multiple change points were identified in the EEG signal, mostly in interplay with N2. The dynamics before these changes revealed, for a part of the change points, indicators of generic early warning signals, characteristic of complex systems (e.g., ecosystems, climate, epileptic seizures, global finance systems). CONCLUSIONS: The sketched new framework for studying critical transitions in sleep EEG might benefit the understanding of individual and pathological differences in the dynamics of sleep stage transitions. Formalising sleep as a nonlinear dynamical system can be useful for definitions of sleep quality, i.e. stability and accessibility of an equilibrium state, and disrupted sleep, i.e. constant shifting between instable sleep states.

A comprehensive meta-analysis of money priming.

Research on money priming typically investigates whether exposure to money-related stimuli can affect people's thoughts, feelings, motivations, and behaviors (for a review, see Vohs, 2015). Our study answers the call for a comprehensive meta-analysis examining the available evidence on money priming (Vadillo, Hardwicke, & Shanks, 2016). By conducting a systematic search of published and unpublished literature on money priming, we sought to achieve three key goals. First, we aimed to assess the presence of biases in the available published literature (e.g., publication bias). Second, in the case of such biases, we sought to derive a more accurate estimate of the effect size after correcting for these biases. Third, we aimed to investigate whether design factors such as prime type and study setting moderated the money priming effects. Our overall meta-analysis included 246 suitable experiments and showed a significant overall effect size estimate (Hedges' g = .31, 95% CI [0.26, 0.36]). However, publication bias and related biases are likely given the asymmetric funnel plots, Egger's test and two other tests for publication bias. Moderator analyses offered insight into the variation of the money priming effect, suggesting for various types of study designs whether the effect was present, absent, or biased. We found the largest money priming effect in lab studies investigating a behavioral dependent measure using a priming technique in which participants actively handled money. Future research should use sufficiently powerful preregistered studies to replicate these findings. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models.

Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interesting constructs. Response time models, in particular, assume that response time and accuracy are the observed expression of latent variables including 1) ease of processing, 2) response caution, 3) response bias, and 4) non-decision time. Inferences about these psychological factors, hinge upon the validity of the models' parameters. Here, we use a blinded, collaborative approach to assess the validity of such model-based inferences. Seventeen teams of researchers analyzed the same 14 data sets. In each of these two-condition data sets, we manipulated properties of participants' behavior in a two-alternative forced choice task. The contributing teams were blind to the manipulations, and had to infer what aspect of behavior was changed using their method of choice. The contributors chose to employ a variety of models, estimation methods, and inference procedures. Our results show that, although conclusions were similar across different methods, these "modeler's degrees of freedom" did affect their inferences. Interestingly, many of the simpler approaches yielded as robust and accurate inferences as the more complex methods. We recommend that, in general, cognitive models become a typical analysis tool for response time data. In particular, we argue that the simpler models and procedures are sufficient for standard experimental designs. We finish by outlining situations in which more complicated models and methods may be necessary, and discuss potential pitfalls when interpreting the output from response time models.

Unidimensional factor models imply weaker partial correlations than zero-order correlations.

In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.

The Dynamics of Addiction: Craving versus Self-Control.

This study deals with addictive acts that exhibit a stable pattern not intervening with the normal routine of daily life. Nevertheless, in the long term such behaviour may result in health damage. Alcohol consumption is an example of such addictive habit. The aim is to describe the process of addiction as a dynamical system in the way this is done in the natural and technological sciences. The dynamics of the addictive behaviour is described by a mathematical model consisting of two coupled difference equations. They determine the change in time of two state variables, craving and self-control. The model equations contain terms that represent external forces such as societal rules, peer influences and cues. The latter are formulated as events that are Poisson distributed in time. With the model it is shown how a person can get addicted when changing lifestyle. Although craving is the dominant variable in the process of addiction, the moment of getting dependent is clearly marked by a switch in a variable that fits the definition of addiction vulnerability in the literature. Furthermore, the way chance affects a therapeutic addiction intervention is analysed by carrying out a Monte Carlo simulation. Essential in the dynamical model is a nonlinear component which determines the configuration of the two stable states of the system: being dependent or not dependent. Under identical external conditions both may be stable (hysteresis). With the dynamical systems approach possible switches between the two states are explored (repeated relapses).

Normative comparisons for large neuropsychological test batteries: User-friendly and sensitive solutions to minimize familywise false positives.

INTRODUCTION: In neuropsychological research and clinical practice, a large battery of tests is often administered to determine whether an individual deviates from the norm. We formulate three criteria for such large battery normative comparisons. First, familywise false-positive error rate (i.e., the complement of specificity) should be controlled at, or below, a prespecified level. Second, sensitivity to detect genuine deviations from the norm should be high. Third, the comparisons should be easy enough for routine application, not only in research, but also in clinical practice. Here we show that these criteria are satisfied for current procedures used to assess an overall deviation from the norm-that is, a deviation given all test results. However, we also show that these criteria are not satisfied for current procedures used to assess test-specific deviations, which are required, for example, to investigate dissociations in a test profile. We therefore propose several new procedures to assess such test-specific deviations. These new procedures are expected to satisfy all three criteria. METHOD: In Monte Carlo simulations and in an applied example pertaining to Parkinson disease, we compare current procedures to assess test-specific deviations (uncorrected and Bonferroni normative comparisons) to new procedures (Holm, one-step resampling, and step-down resampling normative comparisons). RESULTS: The new procedures are shown to: (a) control familywise false-positive error rate, whereas uncorrected comparisons do not; (b) have higher sensitivity than Bonferroni corrected comparisons, where especially step-down resampling is favorable in this respect; (c) be user-friendly as they are implemented in a user-friendly normative comparisons website, and as the required normative data are provided by a database. CONCLUSION: These new normative comparisons procedures, especially step-down resampling, are valuable additional tools to assess test-specific deviations from the norm in large test batteries.

Modeling BAS Dysregulation in Bipolar Disorder.

Time series analysis is a technique that can be used to analyze the data from a single subject and has great potential to investigate clinically relevant processes like affect regulation. This article uses time series models to investigate the assumed dysregulation of affect that is associated with bipolar disorder. By formulating a number of alternative models that capture different kinds of theoretically predicted dysregulation, and by comparing these in both bipolar patients and controls, we aim to illustrate the heuristic potential this method of analysis has for clinical psychology. We argue that, not only can time series analysis elucidate specific maladaptive dynamics associated with psychopathology, it may also be clinically applied in symptom monitoring and the evaluation of therapeutic interventions.

Hidden multiplicity in exploratory multiway ANOVA: Prevalence and remedies.

Many psychologists do not realize that exploratory use of the popular multiway analysis of variance harbors a multiple-comparison problem. In the case of two factors, three separate null hypotheses are subject to test (i.e., two main effects and one interaction). Consequently, the probability of at least one Type I error (if all null hypotheses are true) is 14 % rather than 5 %, if the three tests are independent. We explain the multiple-comparison problem and demonstrate that researchers almost never correct for it. To mitigate the problem, we describe four remedies: the omnibus F test, control of the familywise error rate, control of the false discovery rate, and preregistration of the hypotheses.