Parent-child interactive behavior in a German sample of parents with and without a mental illness: model replication and adaption of the Coding Interactive Behavior system.

Studies using observational measures often fail to meet statistical standards for both reliability and validity. The present study examined the psychometric properties of the Coding Interactive Behavior (CIB) System within a German sample of parent-child dyads. The sample consisted of 149 parents with and without a mental illness and their children [n experimental group (EG) = 75, n control group (CG) = 74] who participated in the larger Children of Mentally Ill Parents at Risk Evaluation (COMPARE) study. The age of the children ranged from 3 to 12 years (M = 7.99, SD = 2.5). Exploratory factor analysis supported a five-factor model of the CIB with items describing 1) parental sensitivity/reciprocity, 2) parental intrusiveness, 3) child withdrawal, 4) child involvement, and 5) parent limit setting/child compliance. Compared to international samples, the model was reduced by two independent dyadic factors. Testing for predictive validity identified seven items with predictive power to differentiate parental group membership. The CIB factors did not seem to be sufficiently sensitive to illustrate differences in interaction within a sample of parents with various mental illnesses. To apply the CIB to the described sample or similar ones in the future, additional measurement instruments may be necessary.

Beta-binomial meta-analysis of individual differences based on sample means and standard deviations: Studying reliability of sum scores of binary items.

Individual differences are studied with a multitude of test instruments. Meta-analysis of tests is useful to understand whether individual differences in certain populations can be detected with the help of a class of tests. A method for the quantitative meta-analytical evaluation of test instruments with dichotomous items is introduced. The method assumes beta-binomially distributed test scores, an assumption that has been demonstrated to be plausible in many settings. With this assumption, the method only requires sample means and standard deviations of sum scores (or equivalently means and standard deviations of percent-correct scores), in contrast to methods that use estimates of reliability for a similar purpose. Two parameters are estimated for each sample: mean difficulty and an overdispersion parameter which can be interpreted as the test's ability to detect individual differences. The proposed bivariate meta-analytical approach (random or fixed effects) pools the two parameters simultaneously and allows to perform meta-regression. The bivariate pooling yields a between-sample correlation of mean difficulty parameters and overdispersion parameters. As a side product, reliability estimates are obtained which can be employed to disattenuate correlation coefficients for insufficient reliability when no other estimates are available. A worked example illustrates the method and R code is provided. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Understanding Ability and Reliability Differences Measured with Count Items: The Distributional Regression Test Model and the Count Latent Regression Model.

In psychology and education, tests (e.g., reading tests) and self-reports (e.g., clinical questionnaires) generate counts, but corresponding Item Response Theory (IRT) methods are underdeveloped compared to binary data. Recent advances include the Two-Parameter Conway-Maxwell-Poisson model (2PCMPM), generalizing Rasch's Poisson Counts Model, with item-specific difficulty, discrimination, and dispersion parameters. Explaining differences in model parameters informs item construction and selection but has received little attention. We introduce two 2PCMPM-based explanatory count IRT models: The Distributional Regression Test Model for item covariates, and the Count Latent Regression Model for (categorical) person covariates. Estimation methods are provided and satisfactory statistical properties are observed in simulations. Two examples illustrate how the models help understand tests and underlying constructs.

Short-time AOIs-based representative scanpath identification and scanpath aggregation.

A new algorithm to identify a representative scanpath in a sample is presented and evaluated with eye-tracking data. According to Gestalt theory, each fixation of the scanpath should be on an area of interest (AOI) of the stimuli. As with existing methods, we first identify the AOIs and then extract the fixations of the representative scanpath from the AOIs. In contrast to existing methods, we propose a new concept of short-time AOI and extract the fixations of representative scanpath from the short-time AOIs. Our method outperforms the existing methods on two publicly available datasets. Our method can be applied to arbitrary visual stimuli, including static stimuli without natural segmentation, as well as dynamic stimuli. Our method also provides a solution for issues caused by the selection of scanpath similarity.

Effects of digital cognitive behavioral therapy for depression on suicidal thoughts and behavior: Protocol for a systematic review and meta-analysis of individual participant data.

INTRODUCTION: Digital cognitive behavioral therapy (i-CBT) interventions for the treatment of depression have been extensively studied and shown to be effective in the reduction of depressive symptoms. However, little is known about their effects on suicidal thoughts and behaviors (STB). Information on the impact of digital interventions on STB are essential for patients' safety because most digital interventions are self-help interventions without direct support options in case of a suicidal crisis. Therefore, we aim to conduct a meta-analysis of individual participant data (IPDMA) to investigate the effects of i-CBT interventions for depression on STB and to explore potential effect moderators. METHODS: Data will be retrieved from an established and annually updated IPD database of randomized controlled trials investigating the effectiveness of i-CBT interventions for depression in adults and adolescents. We will conduct a one-stage and a two-stage IPDMA on the effects of these interventions on STB. All types of control conditions are eligible. STB can be measured using specific scales (e.g., Beck scale suicide, BSS) or single items from depression scales (e.g., item 9 of the PHQ-9) or standardized clinical interviews. Multilevel linear regression will be used for specific scales, and multilevel logistic regression will be used for treatment response or deterioration, operationalized as a change in score by at least one quartile from baseline. Exploratory moderator analyses will be conducted at participant, study, and intervention level. Two independent reviewers will assess the risk of bias using the Cochrane Risk of Bias Tool 2. CONCLUSION: This IPDMA will harness the available data to assess the effects (response and deterioration) of i-CBT interventions for depression interventions on STB. Information about changes in STB is essential to estimate patients' safety when engaging in digital treatment formats. TRIAL REGISTRATION: We will pre-register this study with the open science framework after article acceptance to ensure consistency between online registration and the published trial protocol.

The Effects of Internet-Based Cognitive Behavioral Therapy for Suicidal Ideation or Behaviors on Depression, Anxiety, and Hopelessness in Individuals With Suicidal Ideation: Systematic Review and Meta-Analysis of Individual Participant Data.

BACKGROUND: Suicide is a global public health problem. Digital interventions are considered a low-threshold treatment option for people with suicidal ideation or behaviors. Internet-based cognitive behavioral therapy (iCBT) targeting suicidal ideation has demonstrated effectiveness in reducing suicidal ideation. However, suicidal ideation often is related to additional mental health problems, which should be addressed for optimal care. Yet, the effects of iCBT on related symptoms, such as depression, anxiety, and hopelessness, remain unclear. OBJECTIVE: We aimed to analyze whether digital interventions targeting suicidal ideation had an effect on related mental health symptoms (depression, anxiety, and hopelessness). METHODS: We systematically searched CENTRAL, PsycInfo, Embase, and PubMed for randomized controlled trials that investigated guided or unguided iCBT for suicidal ideation or behaviors. Participants reporting baseline suicidal ideation were eligible. Individual participant data (IPD) were collected from eligible trials. We conducted a 1-stage IPD meta-analysis on the effects on depression, anxiety, and hopelessness-analyzed as 2 indices: symptom severity and treatment response. RESULTS: We included IPD from 8 out of 9 eligible trials comprising 1980 participants with suicidal ideation. iCBT was associated with significant reductions in depression severity (b=-0.17; 95% CI -0.25 to -0.09; P<.001) and higher treatment response (ie, 50% reduction of depressive symptoms; b=0.36; 95% CI 0.12-0.60; P=.008) after treatment. We did not find significant effects on anxiety and hopelessness. CONCLUSIONS: iCBT for people with suicidal ideation revealed significant effects on depression outcomes but only minor or no effects on anxiety and hopelessness. Therefore, individuals with comorbid symptoms of anxiety or hopelessness may require additional treatment components to optimize care. Studies that monitor symptoms with higher temporal resolution and consider a broader spectrum of factors influencing suicidal ideation are needed to understand the complex interaction of suicidality and related mental health symptoms.

Crohn's Disease as a Possible Risk Factor for Failed Healing in Ileocolic Anastomoses.

Anastomotic leakage (AL) after colorectal resections is a serious complication in abdominal surgery. Especially in patients with Crohn's disease (CD), devastating courses are observed. Various risk factors for the failure of anastomotic healing have been identified; however, whether CD itself is independently associated with anastomotic complications still remains to be validated. A retrospective analysis of a single-institution inflammatory bowel disease (IBD) database was conducted. Only patients with elective surgery and ileocolic anastomoses were included. Patients with emergency surgery, more than one anastomosis, or protective ileostomies were excluded. For the investigation of the effect of CD on AL 141, patients with CD-type L1, B1-3 were compared to 141 patients with ileocolic anastomoses for other indications. Univariate statistics and multivariate analysis with logistic regression and backward stepwise elimination were performed. CD patients had a non-significant higher percentage of AL compared to non-IBD patients (12% vs. 5%, p = 0.053); although, the two samples differed in terms of age, body mass index (BMI), Charlson comorbidity index (CCI), and other clinical variables. However, Akaike information criterion (AIC)-based stepwise logistic regression identified CD as a factor for impaired anastomotic healing (final model: p = 0.027, OR: 17.043, CI: 1.703-257.992). Additionally, a CCI ≥ 2 (p = 0.010) and abscesses (p = 0.038) increased the disease risk. The alternative point estimate for CD as a risk factor for AL based on propensity score weighting also resulted in an increased risk, albeit lower (p = 0.005, OR 7.36, CI 1.82-29.71). CD might bear a disease-specific risk for the impaired healing of ileocolic anastomoses. CD patients are prone to postoperative complications, even in absence of other risk factors, and might benefit from treatment in dedicated centers.

Interactions of scores derived from two groups of variables: Alternating lasso regularization avoids overfitting and finds interpretable scores.

Regression models with interaction terms are common models for moderating relationships. When effects of several predictors from one group-for example, genetic variables-are potentially moderated by several predictors from another-for example, environmental variables-many interaction terms result. This complicates model interpretation, especially when coefficient signs point in different directions. By first forming a score for each group of predictors, the interaction model's dimension is severely reduced. The hierarchical score model is an elegant one-step approach: Score weights and regression model coefficients are estimated simultaneously by an alternating optimization (AO) algorithm. Especially in high dimensional settings, scores remain an effective technique to reduce interaction model dimension, and we propose regularization to ensure sparsity and interpretability of the score weights. A nontrivial extension of the original AO algorithm is presented, which adds a lasso penalty, resulting in the alternating lasso optimization algorithm (ALOA). The hierarchical score model with ALOA is an interpretable statistical learning technique for moderation in potentially high dimensional applications, and encompasses generalized linear models for the main interaction model. In addition to the lasso regularization, a screening procedure called regularization and residualization (RR) is proposed to avoid spurious interactions. ALOA tuning parameter choice and the RR screening procedure are investigated by simulations, and two illustrative applications to depression risk are provided. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Digital cognitive-behavioural therapy to reduce suicidal ideation and behaviours: a systematic review and meta-analysis of individual participant data.

QUESTION: Digital interventions based on cognitive-behavioural therapy (iCBT) is associated with reductions in suicidal ideation. However, fine-grained analyses of effects and potential effect-moderating variables are missing. This study aimed to investigate the effectiveness of iCBT on suicidal ideation, effect moderators, effects on suicide attempts and predictors of adherence. STUDY SELECTION AND ANALYSIS: We systematically searched CENTRAL, PsycINFO, Embase and PubMed for randomised controlled trials that investigated iCBT for suicidal ideation or behaviours. Participants reporting baseline suicidal ideation were eligible. We conducted a one-stage individual participant data (IPD) meta-analysis. Suicidal ideation was the primary outcome, analysed as three indices: severity of suicidal ideation, reliable changes and treatment response. FINDINGS: We included IPD from nine out of ten eligible trials (2037 participants). iCBT showed significant reductions of suicidal ideation compared with control conditions across all indices (severity: b=-0.247, 95% CI -0.322 to -0.173; reliable changes: b=0.633, 95% CI 0.408 to 0.859; treatment response: b=0.606, 95% CI 0.410 to 0.801). In iCBT, the rate of reliable improvement was 40.5% (controls: 27.3%); the deterioration rate was 2.8% (controls: 5.1%). No participant-level moderator effects were identified. The effects on treatment response were higher for trials with waitlist-controls compared with active controls. There were insufficient data on suicide attempts. Human support and female gender predicted treatment adherence. The main source of potential bias was missing outcome data. CONCLUSIONS: The current evidence indicates that iCBT is effective in reducing suicidal ideation irrespective of age, gender and previous suicide attempts. Future studies should rigorously assess suicidal behaviour and drop-out reasons.

Meta-analysis of diagnostic cell-free circulating microRNAs for breast cancer detection.

BACKGROUND: Breast cancer (BC) is the most frequently diagnosed cancer among women. Numerous studies explored cell-free circulating microRNAs as diagnostic biomarkers of BC. As inconsistent and rarely intersecting microRNA panels have been reported thus far, we aim to evaluate the overall diagnostic performance as well as the sources of heterogeneity between studies. METHODS: Based on the search of three online search engines performed up to March 21st 2022, 56 eligible publications that investigated diagnostic circulating microRNAs by utilizing Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) were obtained. Primary studies' potential for bias was evaluated with the revised tool for the quality assessment of diagnostic accuracy studies (QUADAS-2). A bivariate generalized linear mixed-effects model was applied to obtain pooled sensitivity and specificity. A novel methodology was utilized in which the sample and study models' characteristics were analysed to determine the potential preference of studies for sensitivity or specificity. RESULTS: Pooled sensitivity and specificity of 0.85 [0.81-0.88] and 0.83 [0.79-0.87] were obtained, respectively. Subgroup analysis showed a significantly better performance of multiple (sensitivity: 0.90 [0.86-0.93]; specificity: 0.86 [0.80-0.90]) vs single (sensitivity: 0.82 [0.77-0.86], specificity: 0.83 [0.78-0.87]) microRNA panels and a comparable pooled diagnostic performance between studies using serum (sensitivity: 0.87 [0.81-0.91]; specificity: 0.83 [0.78-0.87]) and plasma (sensitivity: 0.83 [0.77-0.87]; specificity: 0.85 [0.78-0.91]) as specimen type. In addition, based on bivariate and univariate analyses, miRNA(s) based on endogenous normalizers tend to have a higher diagnostic performance than miRNA(s) based on exogenous ones. Moreover, a slight tendency of studies to prefer specificity over sensitivity was observed. CONCLUSIONS: In this study the diagnostic ability of circulating microRNAs to diagnose BC was reaffirmed. Nonetheless, some subgroup analyses showed between-study heterogeneity. Finally, lack of standardization and of result reproducibility remain the biggest issues regarding the diagnostic application of circulating cell-free microRNAs.

Rotate and Project: Measurement of the Intended Concept with Unidimensional Item Response Theory from Multidimensional Ordinal Items.

What to do when item response data are multidimensional but a unidimensional model is preferred in terms of statistical simplicity and ease of interpretability? The projection method for the compensatory logistic multidimensional item response model for dichotomous data leads to a two parameter logistic model with local item dependence. Despite the local item dependence, the model is unidimensional for many practical purposes. Here, Ip's projection method is generalized to the case of the graded response model for polytomous variables, extending the applicability of the method to Likert-type response formats. A secondary aim of the paper is the study of rotation techniques intended for use prior to projection. In contrast to rotations aiming at a simple structure of factor loadings, the proposed techniques increase the variance explained before or after projection, facilitate the interpretation of the projected dimension by variants of target rotations or a mix of both. The method is illustrated with an application to the Highly Sensitive Person Scale and R code is provided.

Fisher transformation based confidence intervals of correlations in fixed- and random-effects meta-analysis.

Meta-analyses of correlation coefficients are an important technique to integrate results from many cross-sectional and longitudinal research designs. Uncertainty in pooled estimates is typically assessed with the help of confidence intervals, which can double as hypothesis tests for two-sided hypotheses about the underlying correlation. A standard approach to construct confidence intervals for the main effect is the Hedges-Olkin-Vevea Fisher-z (HOVz) approach, which is based on the Fisher-z transformation. Results from previous studies (Field, 2005, Psychol. Meth., 10, 444; Hafdahl and Williams, 2009, Psychol. Meth., 14, 24), however, indicate that in random-effects models the performance of the HOVz confidence interval can be unsatisfactory. To this end, we propose improvements of the HOVz approach, which are based on enhanced variance estimators for the main effect estimate. In order to study the coverage of the new confidence intervals in both fixed- and random-effects meta-analysis models, we perform an extensive simulation study, comparing them to established approaches. Data were generated via a truncated normal and beta distribution model. The results show that our newly proposed confidence intervals based on a Knapp-Hartung-type variance estimator or robust heteroscedasticity consistent sandwich estimators in combination with the integral z-to-r transformation (Hafdahl, 2009, Br. J. Math. Stat. Psychol., 62, 233) provide more accurate coverage than existing approaches in most scenarios, especially in the more appropriate beta distribution simulation model.

Statistical modeling of dynamic eye-tracking experiments: Relative importance of visual stimulus elements for gaze behavior in the multi-group case.

This paper presents a model that allows group comparisons of gaze behavior while watching dynamic video stimuli. The model is based on the approach of Coutrot and Guyader (2017) and allows linear combinations of feature maps to form a master saliency map. The feature maps in the model are, for example, the dynamically salient contents of a video stimulus or predetermined areas of interest. The model takes into account temporal aspects of the stimuli, which is a crucial difference to other common models. The multi-group extension of the model introduced here allows to obtain relative importance plots, which visualize the effect of a specific feature of a stimulus on the attention and visual behavior for two or more experimental groups. These plots are interpretable summaries of data with high spatial and temporal resolution. This approach differs from many common methods for comparing gaze behavior between natural groups, which usually only include single-dimensional features such as the duration of fixation on a particular part of the stimulus. The method is illustrated by contrasting a sample of a group of persons with particularly high cognitive abilities (high achievement on IQ tests) with a control group on a psycholinguistic task on the conceptualization of motion events. In the example, we find no substantive differences in relative importance, but more exploratory gaze behavior in the highly gifted group. The code, videos, and eye-tracking data we used for this study are available online.

Interests, Motives, and Psychological Burdens in Times of Crisis and Lockdown: Google Trends Analysis to Inform Policy Makers.

BACKGROUND: In the face of the COVID-19 pandemic, the German government and the 16 German federal states implemented a variety of nonpharmaceutical interventions (NPIs) to decelerate the spread of the SARS-CoV-2 virus and thus prevent a collapse of the health care system. These measures comprised, among others, social distancing, the temporary closure of shops and schools, and a ban of large public gatherings and meetings with people not living in the same household. OBJECTIVE: It is fair to assume that the issued NPIs have heavily affected social life and psychological functioning. We therefore aimed to examine possible effects of this lockdown in conjunction with daily new infections and the state of the national economy on people's interests, motives, and other psychological states. METHODS: We derived 249 keywords from the Google Trends database, tapping into 27 empirically and rationally selected psychological domains. To overcome issues with reliability and specificity of individual indicator variables, broad factors were derived by means of time series factor analysis. All domains were subjected to a change point analysis and time series regression analysis with infection rates, NPIs, and the state of the economy as predictors. All keywords and analyses were preregistered prior to analysis. RESULTS: With the pandemic arriving in Germany, significant increases in people's search interests were observed in virtually all domains. Although most of the changes were short-lasting, each had a distinguishable onset during the lockdown period. Regression analysis of the Google Trends data confirmed pronounced autoregressive effects for the investigated variables, while forecasting by means of the tested predictors (ie, daily new infections, NPIs, and the state of economy) was moderate at best. CONCLUSIONS: Our findings indicate that people's interests, motives, and psychological states are heavily affected in times of crisis and lockdown. Specifically, disease- and virus-related domains (eg, pandemic disease, symptoms) peaked early, whereas personal health strategies (eg, masks, homeschooling) peaked later during the lockdown. Domains addressing social life and psychosocial functioning showed long-term increases in public interest. Renovation was the only domain to show a decrease in search interest with the onset of the lockdown. As changes in search behavior are consistent over multiple domains, a Google Trends analysis may provide information for policy makers on how to adapt and develop intervention, information, and prevention strategies, especially when NPIs are in effect.

Reliability generalization of tasks and recommendations for assessing the ability to perceive facial expressions of emotion.

Despite a strong research interest in emotion perception ability, this construct is usually assessed without sufficient consideration of measurement reliability, thus limiting its predictive utility. We present an overview of available emotion perception ability tests, followed by a brief review of test reliability concepts, including classical and modern approaches. Then, through a reliability generalization (k = 106, n total = 16,859), we evaluate which tests have high internal consistency and which design characteristics are associated with better internal consistency. We conclude with general recommendations for the psychometric evaluation of emotion perception measures and provide recommendations for best measurement practices. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Are Internet- and mobile-based interventions effective in adults with diagnosed panic disorder and/or agoraphobia? A systematic review and meta-analysis.

BACKGROUND: There is no meta-analysis that specifically evaluates the effectiveness of Internet- and mobile-based interventions (IMIs) in adults with diagnosed panic disorder and/or agoraphobia (PD/A) so far. The current meta-analysis aims to fill this gap (PROSPERO CRD 42016034016). METHODS: Systematic literature searches in six databases for randomised and controlled clinical trials investigating IMIs in adults, who met diagnostic criteria for PD/A. Study selection and data extraction were conducted independently by two reviewers. Random-effects meta-analyses, pre-planned subgroup and sensitivity analyses were conducted when appropriate. Primary outcomes were PD and A symptom severity. In addition, adherence, response, remission, quality of life, anxiety and depression symptom severity were examined. RESULTS: A total of 16 trials (1015 patients), with 21 comparisons (9 IMI vs. waitlist; 7 IMI vs. IMI; 5 IMI vs. active treatment condition), were included. IMIs revealed beneficial effects on panic (Hedges' g range -2.61 to -0.25) and agoraphobia symptom severity when compared to waitlist (pooled g = -1.15, [95%-CI = -1.56; -0.74]). Studies comparing IMIs to active controls (i.e., face-to-face CBT and applied relaxation) did not find significant differences for reductions in panic (g = -0.02, [95%-CI = -0.25; 0.21]) and agoraphobia symptom severity (g = -0.10, [95%-CI = -0.39; 0.19]). Furthermore, IMIs were superior to waitlist controls regarding anxiety and depression symptom severity and quality of life. LIMITATIONS: Tests for publication bias were not feasible due to the limited number of trials per comparison, and the risk of bias assessment indicated some methodological shortcomings. CONCLUSIONS: Findings from this meta-analytic review provide support for the effectiveness of IMIs in patients with verified PD/A. However, before IMIs can be included in treatment guidelines for PD/A, future high quality research is needed that substantiates and extends the evidence base, especially in regard to intervention safety.

Effectiveness of Internet- and Mobile-Based Cognitive Behavioral Therapy to Reduce Suicidal Ideation and Behaviors: Protocol for a Systematic Review and Meta-Analysis of Individual Participant Data.

Internet- and mobile-based cognitive behavioral therapy (iCBT) might reduce suicidal ideation. However, recent meta-analyses found small effect sizes, and it remains unclear whether specific subgroups of participants experience beneficial or harmful effects. This is the study protocol for an individual participant meta-analysis (IPD-MA) aiming to determine the effectiveness of iCBT on suicidal ideation and identify moderators. We will systematically search CENTRAL, PsycINFO, Embase, and Pubmed for randomized controlled trials examining guided or self-guided iCBT for suicidality. All types of control conditions are eligible. Participants experiencing suicidal ideation will be included irrespective of age, diagnoses, or co-interventions. We will conduct a one-stage IPD-MA with suicidal ideation as the primary outcome, using a continuous measure, reliable improvement and deterioration, and response rate. Moderator analyses will be performed on participant-, study-, and intervention-level. Two independent reviewers will assess risk of bias and the quality of evidence using Cochrane's Risk of Bias Tool 2 and GRADE. This review was registered with OSF and is currently in progress. The IPD-MA will provide effect estimates while considering covariates and will offer novel insights into differential effects on a participant level. This will help to develop more effective, safe, and tailored digital treatment options for suicidal individuals.

Comparison of random-effects meta-analysis models for the relative risk in the case of rare events: A simulation study.

Pooling the relative risk (RR) across studies investigating rare events, for example, adverse events, via meta-analytical methods still presents a challenge to researchers. The main reason for this is the high probability of observing no events in treatment or control group or both, resulting in an undefined log RR (the basis of standard meta-analysis). Other technical challenges ensue, for example, the violation of normality assumptions, or bias due to exclusion of studies and application of continuity corrections, leading to poor performance of standard approaches. In the present simulation study, we compared three recently proposed alternative models (random-effects [RE] Poisson regression, RE zero-inflated Poisson [ZIP] regression, binomial regression) to the standard methods in conjunction with different continuity corrections and to different versions of beta-binomial regression. Based on our investigation of the models' performance in 162 different simulation settings informed by meta-analyses from the Cochrane database and distinguished by different underlying true effects, degrees of between-study heterogeneity, numbers of primary studies, group size ratios, and baseline risks, we recommend the use of the RE Poisson regression model. The beta-binomial model recommended by Kuss (2015) also performed well. Decent performance was also exhibited by the ZIP models, but they also had considerable convergence issues. We stress that these recommendations are only valid for meta-analyses with larger numbers of primary studies. All models are applied to data from two Cochrane reviews to illustrate differences between and issues of the models. Limitations as well as practical implications and recommendations are discussed; a flowchart summarizing recommendations is provided.

Comparing effects of detached mindfulness and cognitive restructuring in obsessive-compulsive disorder using ecological momentary assessment.

Ecological momentary assessment (EMA) has been shown to be a valid and sensitive measure of treatment effects in obsessive-compulsive disorder (OCD). As part of a clinical trial, this EMA study deals with a comparison of two treatment conditions, that is, cognitive restructuring (CR) and detached mindfulness (DM). EMA data from n = 39 OCD patients were available from a randomized clinical trial on the effectiveness of CR and DM. Smartphone-based EMA sampling spread over 4 days each before and after treatment, with 10 random prompts per day and a 2-week intervention of either CR or DM. We tracked CR strategies (e.g., questioning an appraisal by re-evaluating risk), DM strategies (e.g., allowing one's thoughts to come and go), and application of newly learned strategies during Post-Treatment EMA. Although there was a trend towards DM strategies being applied more often during Pre-Treatment EMA than CR strategies, we did not find differences during Post-Treatment EMA between CR and DM regarding frequency or difficulty of application and experienced relief. As expected, we found a clear pre-post increase for all CR and DM behaviours except for one DM item. However, we did not find a treatment-specific increase of CR and DM behaviours; that is, both interventions equally well promoted a seemingly general treatment effect. Despite the ecological validity of EMA, however, social desirability effects cannot be ruled out, so that this conclusion must be handled cautiously. Further research is needed to replicate and generalize our results.

Everyday emotional dynamics in major depression.

The present study aimed to investigate the everyday emotional dynamics of depressed individuals, especially the role of emotional inertia, emotional context insensitivity, and emotional variability and instability. Using ecological momentary assessment, 40 currently depressed individuals and 40 healthy controls reported on their current emotional state and current activities 10 times a day for 4 consecutive days. There were no differences in the dynamics of positive affect (PA) between depressed and healthy subjects. Depressed participants' negative affect (NA), however, was found to be more inert than in healthy controls, while at the same time being more variable and more reactive to positive events. There was also an association between emotional instability and depression, but this was rendered nonsignificant when analyses were controlled for emotional variability. Altogether, emotional dynamics of NA appear to be more prominently disturbed in depression compared to PA. Results support earlier findings on NA emotional variability as well as inertia in depressed patients. In addition, there was some evidence for a mood brightening effect in depression. (PsycINFO Database Record (c) 2020 APA, all rights reserved).