First impressions count: Therapists' impression on patients' motivation and helping alliance predicts psychotherapy dropout.

Objective: With meta-analytically estimated rates of about 25%, dropout in psychotherapies is a major concern for individuals, clinicians, and the healthcare system at large. To be able to counteract dropout in psychotherapy, accurate insights about its predictors are needed.

Method: We compared logistic regression models with two machine learning algorithms (elastic net regressions and gradient boosting machines) in the prediction of therapy dropout in two large inpatient samples ( = 1,691 and  = 12,473) using baseline and initial process variables reported by patients and therapists.

Ant colony optimization for parallel test assembly.

Ant colony optimization (ACO) algorithms have previously been used to compile single short scales of psychological constructs. In the present article, we showcase the versatility of the ACO to construct multiple parallel short scales that adhere to several competing and interacting criteria simultaneously. Based on an initial pool of 120 knowledge items, we assembled three 12-item tests that (a) adequately cover the construct at the domain level, (b) follow a unidimensional measurement model, (c) allow reliable and (d) precise measurement of factual knowledge, and (e) are gender-fair.

Model Specification Searches in Structural Equation Modeling Using Bee Swarm Optimization.

Metaheuristics are optimization algorithms that efficiently solve a variety of complex combinatorial problems. In psychological research, metaheuristics have been applied in short-scale construction and model specification search. In the present study, we propose a bee swarm optimization (BSO) algorithm to explore the structure underlying a psychological measurement instrument.

Predicting treatment response using machine learning: A registered report.

Objective: Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively screening for patients at risk of low treatment response, gain more knowledge about risk factors and to evaluate treatments, accurate insights about predictors of treatment response in naturalistic inpatient samples are needed.

Methods: We compared the performance of different machine learning algorithms in predicting treatment response, operationalized as a substantial reduction in symptom severity as expressed in the Patient Health Questionnaire Anxiety and Depression Scale.

Public events knowledge in an age-heterogeneous sample: Reminiscence bump or bummer?

The describes an increased recollection of autobiographic experiences made in adolescence and early adulthood. It is unclear if this phenomenon can also be found in declarative knowledge of past public events. To answer this question, we assessed public events knowledge (PEK) about the past 6 decades with a 120-item knowledge test across six domains in a sample of 1,012 Germans that were sampled uniformly across the ages of 30-80 years.

Accuracy and precision of fixed and random effects in meta-analyses of randomized control trials for continuous outcomes.

Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing correlation.

The Nomological Net of Knowledge, Self-Reported Knowledge, and Overclaiming in Children.

Research on self-reported knowledge and overclaiming in children is sparse. With the current study, we aim to close this gap by developing an overclaiming questionnaire measuring self-reported knowledge and overclaiming that is tailored to children. Moreover, we examine the nomological net of self-reported knowledge and overclaiming in childhood discussing three perspectives: Overclaiming as (a) a result of deliberate self-enhancement tendencies, (b) a proxy for declarative knowledge, and (c) an indicator of creative engagement.

The Road to Hell Is Paved With Good Intentions: How Common Practices in Scale Construction Hurt Validity.

Sound scale construction is pivotal to the measurement of psychological constructs. Common item sampling procedures emphasize aspects of reliability to the disadvantage of aspects of validity, which are less tangible. We use a health knowledge test as an example to demonstrate how item sampling strategies that focus on either factor saturation or construct coverage influence scale composition and demonstrate how to find a trade-off between these two opposing needs.

Mapping established psychopathology scales onto the Hierarchical Taxonomy of Psychopathology (HiTOP).

The Hierarchical Taxonomy of Psychopathology (HiTOP) organizes phenotypes of mental disorder based on empirical covariation, offering a comprehensive organizational framework from narrow symptoms to broader patterns of psychopathology. We argue that established self-report measures of psychopathology from the pre-HiTOP era should be systematically integrated into HiTOP to foster cumulative research and further the understanding of psychopathology structure. Hence, in this study, we mapped 92 established psychopathology (sub)scales onto the current HiTOP working model using data from an extensive battery of self-report assessments that was completed by community participants and outpatients (N = 909).

Dynamic interplay of cognitive functioning and depressive symptoms in patients with Parkinson's disease.

Objective: We examine the trajectories of and the dynamic interplay between cognitive functioning and depressive symptoms in patients with Parkinson's disease (PD) in comparison to healthy controls (HC) from an intraindividual perspective.

Method: The DeNoPa study is a single-center, observational, longitudinal study with biennial follow-ups over 8 years. The present analyses are based on 123 PD (79 male) and 107 HC (64 male) with a mean age of 64.

Detecting Careless Responding in Survey Data Using Stochastic Gradient Boosting.

Careless responding is a bias in survey responses that disregards the actual item content, constituting a threat to the factor structure, reliability, and validity of psychological measurements. Different approaches have been proposed to detect aberrant responses such as probing questions that directly assess test-taking behavior (e.g.

Structural invariance of declarative knowledge across the adult lifespan.

The differentiation-dedifferentiation hypothesis of general cognitive ability has been widely studied, but comparable research on crystallized intelligence is scarce. To close this gap, we conducted an empirical test of the age differentiation hypothesis of declarative knowledge as proposed in Cattell's investment theory, which predicts that knowledge differentiates into diverse forms after compulsory education ends. Thereto, a cross-sectional sample of 1,629 participants aged 18-70 years ( = 45.

The Structure of the Toronto Alexithymia Scale (TAS-20): A Meta-Analytic Confirmatory Factor Analysis.

Alexithymia is defined as the inability of persons to describe their emotional states, to identify the feelings of others, and a utilitarian type of thinking. The most popular instrument to assess alexithymia is the Toronto Alexithymia Scale (TAS-20). Despite its widespread use, an ongoing controversy pertains to its internal structure.

A Reappraisal of the Threshold Hypothesis of Creativity and Intelligence.

Intelligence has been declared as a necessary but not sufficient condition for creativity, which was subsequently (erroneously) translated into the so-called threshold hypothesis. This hypothesis predicts a change in the correlation between creativity and intelligence at around 1.33 standard deviations above the population mean.

Caught in the Act: Predicting Cheating in Unproctored Knowledge Assessment.

Cheating is a serious threat in unproctored ability assessment, irrespective of countermeasures taken, anticipated consequences (high vs. low stakes), and test modality (paper-pencil vs. computer-based).

Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge.

Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants.

A confirmatory examination of age-associated personality differences: Deriving age-related measurement-invariant solutions using ant colony optimization.

Objective: The goal of this study was to examine age-associated personality differences using a measurement-invariant representation of the higher-order structure of the Five-Factor Model.

Method: We reanalyzed the German NEO-PI-R norm sample (N = 11,724) and applied ant colony optimization in a multigroup confirmatory factor analysis setting in order to select three items per first-order factor that would optimize model fit and measurement invariance across 18 age groups ranging from 16 to 65 years of age.

Results: Ant colony optimization substantially improved absolute and relative model fit under measurement invariance constraints.

Cognitive Abilities Explain Wording Effects in the Rosenberg Self-Esteem Scale.

There is consensus that the 10 items of the (RSES) reflect wording effects resulting from positively and negatively keyed items. The present study examined the effects of cognitive abilities on the factor structure of the RSES with a novel, nonparametric latent variable technique called . In a nationally representative German large-scale assessment including 12,437 students competing measurement models for the RSES were compared: a bifactor model with a common factor and a specific factor for all negatively worded items had an optimal fit.

Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm.

The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems.