Psych, Volume 3, Issue 4 (December 2021) – 22 articles

The purpose of this study was to examine the potential differences between Albanian migrants and Greeks in the islands of Paros and Antiparos with regard to seeking help from the local public mental health service, namely the Mobile Mental Health Unit of NE Cyclades Islands (EPAPSY-NGO). The study’s instruments include the Global Assessment of Functioning (GAF) and a questionnaire for recording psychosocial profile data and information concerning contact with the services. The results showed that significantly less Albanian migrants contacted the mental health services in the past in comparison to Greeks. When using the service, the Albanians were more likely to see a psychiatrist in the Unit, rather than a psychologist-psychotherapist, and they more often received prescriptions for medication. There was a significantly higher dropout rate among Albanian migrants. This study highlights the different aspects of access and use of mental health services among Albanian migrants compared with native residents. Further research should focus on the factors related to early dropouts and difficulties accessing mental health services in rural areas, in order to develop more focused and effective interventions and improve the quality of care provided. Full article

Automated essay scoring (AES) is gaining increasing attention in the education sector as it significantly reduces the burden of manual scoring and allows ad hoc feedback for learners. Natural language processing based on machine learning has been shown to be particularly suitable for text classification and AES. While many machine-learning approaches for AES still rely on a bag of words (BOW) approach, we consider a transformer-based approach in this paper, compare its performance to a logistic regression model based on the BOW approach, and discuss their differences. The analysis is based on 2088 email responses to a problem-solving task that were manually labeled in terms of politeness. Both transformer models considered in the analysis outperformed without any hyperparameter tuning of the regression-based model. We argue that, for AES tasks such as politeness classification, the transformer-based approach has significant advantages, while a BOW approach suffers from not taking word order into account and reducing the words to their stem. Further, we show how such models can help increase the accuracy of human raters, and we provide a detailed instruction on how to implement transformer-based models for one’s own purposes. Full article

Background: The pandemic caused by the sars-cov2 coronavirus can be considered the biggest international public health crisis. Outbreaks of emerging diseases can trigger fear reactions. Strict adherence to the strategies can cause harmful consequences, particularly for people with pathology on the spectrum of obsessive-compulsive disorder. Case presentation: We describe the clinical case of a woman, with a history of anxiety disorder, who develops obsessive-compulsive symptoms, she started cognitive behavioral therapy and pharmacological therapy, with appropriate follow-up. Conclusions: The intense focus on the risk of contamination and the adoption of new hygienic behaviors can be internalized as normative and become an enhancing trigger for obsessive thinking and compulsive behaviors. It is an important focus on prevention, early intervention and adequate follow-up, through measures to promote mental health. Full article

A large body of research suggests that during learning motor skills, focusing on environmental effects of the movement (external focus) generally leads to better performance than focusing on one’s own body (internal focus). The functionality hypothesis states, in contrast, that the superiority of any attentional focus is task dependent. The present study aimed to test the predictions of the latter and searched for underlying mechanisms and task characteristics for one or the other focus being more functional. In Experiment 1, we examined whether the internal focus is superior in a difficult body-oriented balance task. In Experiment 2, we added visual feedback and investigated whether this would enhance the functionality of the external focus. In both experiments, the participants stood one-legged on a balance board and had to shift their centre of pressure (COP) to predefined target points. Per instruction, they were asked to interpret their attentional focus on the COP as either internal (the sole of the foot) or external (the platform). In Experiment 1, the external focus was induced through a mental image. The internal focus group performed significantly better, thereby supporting the functionality hypothesis. In Experiment 2, the COP was dynamically visualized on a screen. The internal focus superiority vanished. We suggest that the internal focus is more functional in motor-learning situations that provide more effect information through body-internal senses than through body-external senses. In these cases, the external focus hampers learning because it is associated with additional cognitive load. Full article

Computational reproducibility is the ability to obtain identical results from the same data with the same computer code. It is a building block for transparent and cumulative science because it enables the originator and other researchers, on other computers and later in time, to reproduce and thus understand how results came about, while avoiding a variety of errors that may lead to erroneous reporting of statistical and computational results. In this tutorial, we demonstrate how the R package repro supports researchers in creating fully computationally reproducible research projects with tools from the software engineering community. Building upon this notion of fully automated reproducibility, we present several applications including the preregistration of research plans with code (Preregistration as Code, PAC). PAC eschews all ambiguity of traditional preregistration and offers several more advantages. Making technical advancements that serve reproducibility more widely accessible for researchers holds the potential to innovate the research process and to help it become more productive, credible, and reliable. Full article

Cognitive diagnosis models (CDMs) have increasingly been applied in education and other fields. This article provides an overview of a widely used CDM, namely, the G-DINA model, and demonstrates a hands-on example of using multiple R packages for a series of CDM analyses. This overview involves a step-by-step illustration and explanation of performing Q-matrix evaluation, CDM calibration, model fit evaluation, item diagnosticity investigation, classification reliability examination, and the result presentation and visualization. Some limitations of conducting CDM analysis in R are also discussed. Full article

Cyberbullying is currently considered as a widespread problem among children and adolescents; in particular, the risks of cyberbullying have recently been examined. The empirical analyses of the present work are based on data from a German longitudinal study. The self-reports of adolescents from Dortmund and Nuremberg on both cyberbullying and individual and contextual characteristics were taken into account. The two-wave panel encompasses N = 871 adolescents (44.5% male); the average age was M = 15.1 years (SD = 0.83) at t1. Data on cyberbullying refer to sending insults or threats to others via the Internet, spreading rumours or talking badly about others via the Internet, and sending private e-mails, photos or similar from others in order to embarrass or ridicule the persons concerned. Other characteristics relate to single aspects of psychopathy (egocentric egotism, low self-control, empathy deficits), acceptance of violence, and delinquent peers. The path analytical findings illustrate the predictive relationships between both individual and contextual risks and cyberbullying in adolescence. The empirical results are discussed, among others, from the perspective of developmental and life-course criminology. Full article

The Assertive Community Treatment (ACT) model of care has been long considered to be effective in the management of patients with severe mental illness (SMI) in most Western countries. The implementation of the original ACT model may be particularly challenging in rural and remote communities with small and dispersed populations and lack of adequate mental health services. Rural programs may have to adapt the model and modify the ACT fidelity standards to accommodate these limitations, and this is the rationale for the introduction of more flexible, hybrid ACT models. In rural Greece, the so called Mobile Mental Health Units (MMHUs) are well-established community mental health services. For patients with SMI that have difficulties engaging with treatment services, the new hybrid ACT model has been recently launched. The objective of this manuscript is to present the recently launched hybrid ACT model in rural areas in Greece and to explore the challenges and limitations in its implementation from the experience of a team of mental health professionals with ACT experience. Referral criteria have not been strictly set, but the number of previous relapses and hospitalizations is taken under consideration, as well as the history of poor treatment adherence and disengagement from mental health services. The main limitation in the implementation of the hybrid ACT service is that it has been introduced in several areas in the absence of a pre-existing community mental health service. This may impact referrals and limit focus on the difficult cases of patients with SMI, thus making the evaluation of the model inapplicable. Full article

In recent years serious mental health issues, such as schizophrenia spectrum disorders and bipolar disorder, have been treated in the community by community-based mental health services. In the present study our goal was to estimate the modification in the number of hospitalizations and duration of admissions in either psychotic patients or patients with bipolar disorder, treated by a Mobile Mental Health Unit in the islands of Kefalonia, Zakynthos and Ithaca (MMHU-KZI). Data were collected from a total of 108 patients with schizophrenia spectrum disorders and bipolar disorder. For each patient comparison was made for the same time interval prior and after engagement to treatment with the MMHU-KZI and not for the total hospitalizations that patients had in their history. There was a statistically significant reduction (45.9%) in hospitalizations after treatment engagement with the MMHU-KZI, as the Wilcoxon signed ranks test indicated. Furthermore, a major decrease (54.5%) of hospitalization days was noted after treatment engagement with the unit. This pattern of mental health provision may be beneficial for the reduction of the number and duration of psychiatric hospitalizations. Despite the beneficial contribution of community-based mental health units, hospital based treatment should always be available, since severe relapses are better treated in inpatient setting. Full article

Bayesian MCMC is a widely used model estimation technique, and software from the BUGS family, such as JAGS, have been popular for over two decades. Recently, Stan entered the market with promises of higher efficiency fueled by advanced and more sophisticated algorithms. With this study, we want to contribute empirical results to the discussion about the sampling efficiency of JAGS and Stan. We conducted three simulation studies in which we varied the number of warmup iterations, the prior informativeness, and sample sizes and employed the multi-level intercept-only model in the covariance- and mean-based and in the classic parametrization. The target outcome was MCMC efficiency measured as effective sample size per second (ESS/s). Based on our specific (and limited) study setup, we found that (1) MCMC efficiency is much higher for the covariance- and mean-based parametrization than for the classic parametrization, (2) Stan clearly outperforms JAGS when the covariance- and mean-based parametrization is used, and that (3) JAGS clearly outperforms Stan when the classic parametrization is used. Full article

John L. Holland’s theory of vocational choice is one of the most prominent career theories and is used by both researchers and practitioners around the world. The theory states that people should seek work environments that fit their vocational interests in order to be satisfied and successful. Its application in research and practice requires the determination of coefficients, which quantify its core concepts such as person-environment fit. The recently released R package holland aims at providing a holistic collection of the references, descriptions and calculations of the most important coefficients. The current paper presents the package and examines it in terms of its application for research and practice. For this purpose, the functions of the package are applied and discussed. Furthermore, recommendations are made in the case of multiple coefficients for the same theoretical concept and features that future releases should include are discussed. The R package holland is a promising computational environment providing multiple coefficients for Holland’s most important theoretical concepts. Full article

The SKT (Syndrom-Kurz-Test) is a well-established short cognitive performance test for the detection of attention and memory deficits in Germany. The goal of this paper is to test whether the SKT could be applied to English-speaking populations to screen cognitive impairments in the US, Australia, and Ireland. A regression-based continuous norming technique was applied. Standardized test results obtained from German-speaking (n = 1056) and English-speaking (n = 285) samples were compared. Both samples consisted of cognitively unimpaired, community-dwelling, and independently living volunteers (non-patients) over 60 years of age. Means, medians, and standard deviations of raw scores were calculated. A high similarity in the raw value distributions of the criterion variables and a comparison of German and English multiple regression residuals indicated the equivalence among the samples. In addition, the obtained multiple regression equations for predicting the subtest scores including the explained variances (R²) were highly comparable. Age and intelligence turned out to be the most important and necessary predictors for each subtest performance. The results suggest that the new regression-based norming of the SKT can be validly used in the three English-speaking countries. Full article

Synthetic datasets simultaneously allow for the dissemination of research data while protecting the privacy and confidentiality of respondents. Generating and analyzing synthetic datasets is straightforward, yet, a synthetic data analysis pipeline is seldom adopted by applied researchers. We outline a simple procedure for generating and analyzing synthetic datasets with the multiple imputation software mice (Version 3.13.15) in R. We demonstrate through simulations that the analysis results obtained on synthetic data yield unbiased and valid inferences and lead to synthetic records that cannot be distinguished from the true data records. The ease of use when synthesizing data with mice along with the validity of inferences obtained through this procedure opens up a wealth of possibilities for data dissemination and further research on initially private data. Full article

Background: the prevalence of current smokers in patients with coronary syndrome is high. This risk behaviour significantly increases the risk of cardiovascular complications. In the recommendations for the management of cardiovascular diseases, psychosocial and psychological factors are still neglected in practice. The aim of study was to verify the prevalence of tobacco use in hospitalized patients with coronary syndrome, notably to verify the type-D personality and tobacco use in the groups obtained from the evaluation of the DS14 scale. Methods: in this cross-sectional study, we addressed 100 hospitalized patients with coronary syndrome. Results: in the cohort, 48% patient were current smokers, 21% were never smokers, 24% were former smokers, 4% were occasional smokers, and 3% were quitters. Based on the evaluation of DS14, 21% of patients were classified as type-D personality and 38% as non-type-D; we identified two subtypes: the NA group at 23% and the SI group at 18%. In the group of the current smokers, 81% declared that they wanted to quit smoking, 15% of the patients were undecided, and 4% of current smokers did not want to quit. Conclusions: cardiac patients are aware that their disease is related to smoking; despite the severity of their disease, patients’ motivation to change their risky behaviour is low. Full article

The presence of missing responses in assessment settings is inevitable and may yield biased parameter estimates in psychometric modeling if ignored or handled improperly. Many methods have been proposed to handle missing responses in assessment data that are often dichotomous or polytomous. Their applications remain nominal, however, partly due to that (1) there is no sufficient support in the literature for an optimal method; (2) many practitioners and researchers are not familiar with these methods; and (3) these methods are usually not employed by psychometric software and missing responses need to be handled separately. This article introduces and reviews the commonly used missing response handling methods in psychometrics, along with the literature that examines and compares the performance of these methods. Further, the use of the TestDataImputation package in R is introduced and illustrated with an example data set and a simulation study. Corresponding R codes are provided. Full article

Introduction: Patients with atopic dermatitis (AD) have several potential stressors including the symptoms of the disease itself, the stigmatization due to their appearance, and emotional and psychological strain. Psychological factors and stress can trigger and exacerbate the symptoms of skin diseases and there is evidence that stress has a relevant clinical effect on the function of skin cells in vivo. Our objective was to evaluate in a pilot study the feasibility, acceptance, and effectiveness of a Mindfulness-Based Stress Reduction (MBSR) programme in AD patients in a clinical setting. Methods: 10 patients took part in an 8-week MBSR programme, which included, e.g., mindful and conscious awareness of the body and bodywork, and seated meditation. We assessed sociodemographics and disease related variables with standardized measures at predefined time points including Score of Atopic Dermatitis, Patient Oriented Eczema Measure, Dermatology Life Quality Index, Perceived Stress Questionnaire, Freiburg Mindfulness Inventory (FMI), and others. Participants also gave qualitative feedback regarding the effects of the intervention. Results: The mean age was 53.10 years (SD = 15.04), seven patients were female, and disease duration was 36.6 years (SD = 25.5). Calculating pre-post effect sizes (Cohen’s d), the FMI indicated significant improvement in the “presence” and “acceptance” subscales. There was also tendency for less stress. This was confirmed by the qualitative statements of the participants. Conclusions: The MBSR programme is feasible and acceptable for AD patients. Considering the long disease history and the severity of disease burden, the effects of this intervention seem promising as an adjunct to conventional treatments for patients with AD. Full article

Misophonia involves a strong emotional response to certain sounds and can cause significant distress and functional impairment. The aim of this study was to present and psychometrically evaluate a new, multidimensional measure of misophonia, the S-Five. The study also aimed to present and test a supplementary tool, a checklist of triggers that measure the nature and intensity of reactions. The stages of development for the measure are described. Psychometric testing on the final version of the tool was conducted using a sample of 828 individuals who identified with having misophonia. Analyses included factor structure assessment, measurement invariance testing, reliability (test–retest and internal consistency), and (concurrent) convergent validity assessment. Five factors emerged in the S-Five as dimensions of the experience of misophonia: internalising appraisals, externalising appraisals, sense of emotional threat, outbursts, and impact. No measurement bias was identified with respect to gender and age. All reliability and validity indices were satisfactory. The S-Five is a multidimensional measurement scale with satisfactory psychometric properties and will be a valuable tool for improving understanding of misophonia in research and clinical settings. Full article

Multistage tests are a widely used and efficient type of test presentation that aims to provide accurate ability estimates while keeping the test relatively short. Multistage tests typically rely on the psychometric framework of item response theory. Violations of item response models and other assumptions underlying a multistage test, such as differential item functioning, can lead to inaccurate ability estimates and unfair measurements. There is a practical need for methods to detect problematic model violations to avoid these issues. This study compares and evaluates three methods for the detection of differential item functioning with regard to continuous person covariates in data from multistage tests: a linear logistic regression test and two adaptations of a recently proposed score-based DIF test. While all tests show a satisfactory Type I error rate, the score-based tests show greater power against three types of DIF effects. Full article

The “Ising model” refers to both the statistical and the theoretical use of the same equation. In this article, we introduce both uses and contrast their differences. We accompany the conceptual introduction with a survey of Ising-related software packages in R. Since the model’s different uses are best understood through simulations, we make this process easily accessible with fully reproducible examples. Using simulations, we show how the theoretical Ising model captures local-alignment dynamics. Subsequently, we present it statistically as a likelihood function for estimating empirical network models from binary data. In this process, we give recommendations on when to use traditional frequentist estimators as well as novel Bayesian options. Full article

Sparse estimation through regularization is gaining popularity in psychological research. Such techniques penalize the complexity of the model and could perform variable/path selection in an automatic way, and thus are particularly useful in models that have small parameter-to-sample-size ratios. This paper gives a detailed tutorial of the R package regsem, which implements regularization for structural equation models. Example R code is also provided to highlight the key arguments of implementing regularized structural equation models in this package. The tutorial ends by discussing remedies of some known drawbacks of a popular type of regularization, computational methods supported by the package that can improve the selection result, and some other practical issues such as dealing with missing data and categorical variables. Full article

The association between two ordinal variables can be expressed with a polychoric correlation coefficient. This coefficient is conventionally based on the assumption that responses to ordinal variables are generated by two underlying continuous latent variables with a bivariate normal distribution. When the underlying bivariate normality assumption is violated, the estimated polychoric correlation coefficient may be biased. In such a case, we may consider other distributions. In this paper, we aimed to provide an illustration of fitting various bivariate distributions to empirical ordinal data and examining how estimates of the polychoric correlation may vary under different distributional assumptions. Results suggested that the bivariate normal and skew-normal distributions rarely hold in the empirical datasets. In contrast, mixtures of bivariate normal distributions were often not rejected. Full article

Objectives: Family and other informal caregivers of individuals with dementia can be at increased risk for a significant decline in wellbeing or their ability to continue to provide care. There is extensive literature on the multifactorial elements contributing to risk, but frontline practitioners may be uncertain how to apply their knowledge of risk to an assessment of individual caregivers during clinical encounters. We developed a new one-page guided interview tool (the Dementia Caregiver Interview Guide, or DCIG) to guide practitioners to: (1) systematically assess known factors associated with high caregiver risk in a clinical interview format and (2) concisely document their judgement regarding risk of decompensation arising from caregiver stress. This semi-structured interview format collects detailed information while promoting a collaborative communication process. This study evaluated the validity of risk-assessment using the DCIG. Methods: A convenience sample of 50 caregivers was recruited during routine intake at the Reitman Centre at Sinai Health in Toronto, Canada. Risk was assessed using both the DCIG and the Caregiver Risk Screen (CRS). Total scores on the two tools were compared to establish concurrent and discriminant validity for the DCIG. Results: The DCIG correlated positively with the CRS (Spearman’s rho = 0.737; p < 0.001) and identified caregivers at risk at a moderate level of agreement with the CRS (Cohen’s Kappa = 0.559). Conclusions: The DCIG allows clinicians to efficiently identify caregivers’ level of risk for functional and emotional decline or decompensation in a client-centered, naturalistic manner. Full article