Do the elderly and those with comorbid chronic physical conditions have improved access to outpatient psychotherapy post structural reforms in Germany? Results of the ES-RiP study.

Background: In 2017, a reform of the German outpatient psychotherapy guideline was carried out, aiming to reduce waiting times and facilitate low-threshold access. This study analyzes the extent to which the implementation of the two new service elements 'psychotherapeutic consultation times' and 'acute short-term psychotherapeutic interventions' improved psychotherapeutic care for patients with mental disorders and chronic physical conditions (cMPs), for patients with mental disorders without chronic physical conditions (MnoP), and elderly patients. Methods: In a quantitative secondary analysis, we analyzed health insurance data of patients with psychotherapy billing codes obtained from the National Association of Statutory Health Insurance Physicians (KBV) for the years 2015-2019, evaluating descriptive statistical parameters for specific patient groups and care services. Results: Between 2015 and 2019, the number of mentally ill receiving psychotherapy at least once in the corresponding year increased by 30.7%. Among these, the proportion of cMPs-patients increased from 26.8% to 28.2% (+1.4%), while that of MnoP-patients decreased from 68.3% to 66.4% (-1.9%). The number of elderly people receiving treatment also increased. Conclusion: Since increases and decreases in the percentage shares occur evenly over the years investigated, it is questionable whether the reform in 2017 has had a direct influence on these changes. Study registration: ID DRKS00020344, URL: https://www.bfarm.de/DE/Das-BfArM/Aufgaben/Deutsches-Register-Klinischer-Studien/_node.html.

Impact of COVID-19 Infections among Unvaccinated Patients with Congenital Heart Disease: Results of a Nationwide Analysis in the First Phase of the Pandemic.

Background: The outcome data and predictors for mortality among patients with congenital heart disease (CHD) affected by COVID-19 are limited. A more detailed understanding may aid in implementing targeted prevention measures in potential future pandemic events. Methods: Based on nationwide administrative health insurance data, all the recorded in-hospital cases of patients with CHD with COVID-19 in 2020 were analyzed. The demographics, treatment details, as well as 30-day mortality rate were assessed. The associations of the patients' characteristics with death were assessed using multivariable logistic regression analysis. Results: Overall, 403 patients with CHD were treated in- hospital for COVID-19 in 2020. Of these, 338 patients presented with virus detection but no pneumonia whilst, 65 patients suffered from associated pneumonia. The cohort of patients with pneumonia was older (p = 0.04) and presented with more cardiovascular comorbidities such as diabetes mellitus (p = 0.08), although this parameter did not reach a statistically significant difference. The 30-day mortality rate was associated with highly complex CHD (odds ratio (OR) 7.81, p = 0.04) and advanced age (OR 2.99 per 10 years, p = 0.03). No child died of COVID-related pneumonia in our dataset. Conclusions: COVID-19 infection with associated pneumonia chiefly affected the older patients with CHD. Age and the complexity of CHD were identified as additional predictors of mortality. These aspects might be helpful to retrospectively audit the recommendations and guide health politics during future pandemic events.

Reducing the Risks of Esophagectomies: A Retrospective Comparison of Hybrid versus Full-Robotic-Assisted Minimally Invasive Esophagectomy (RAMIE) Approaches.

This retrospective analysis aimed to assess and compare the short-term perioperative outcomes and morbidity of hybrid and full-Robotic-Assisted Minimally Invasive Esophagectomy (RAMIE) surgical techniques. A total of 168 robotic-assisted Ivor Lewis esophagectomy procedures performed at Muenster University Hospital were included in the study, with 63 cases in the hybrid group and 105 cases in the full-robotic group. Demographic factors, comorbidities, and tumor stages showed no significant differences between the two groups. However, the full-RAMIE technique demonstrated superiority in terms of overall operative time, postoperative pain levels, and patient morphine consumption. Additionally, the full-RAMIE group exhibited better perioperative outcomes, with significantly shorter ICU stays and fewer occurrences of pneumonias and severe complications. While there was a trend favoring the full-RAMIE technique in terms of severe postoperative complications and anastomotic insufficiencies, further research is required to establish it as the gold standard surgical technique for Ivor Lewis esophagectomy.

Minimum Distance Estimation of Multidimensional Diffusion-Based Item Response Theory Models.

Diffusion-based item response theory models are models for responses and response times on psychological tests, which can be used as measurement models in the same way as standard item response theory models (Tuerlinckx, Molenaar, & van der Maas, 2016). Their range of application, however, is narrowed by the fact that multidimensional versions of the model are not easy to fit. Marginal maximum likelihood estimation (e.g., Molenaar, Tuerlinckx, & van der Maas, 2015a) is computationally intensive and infeasible for multidimensional versions. The weighted least squares estimator of Ranger, Kuhn, and Szardenings (2016) is inefficient. Here, we propose an alternative estimator that is more efficient than the least squares estimator and less demanding than the maximum likelihood estimator. The estimator is based on minimum distance estimation and consists in modeling the sample quantiles and sample covariances. The performance of the estimator is investigated in a simulation study. The simulation study corroborates that the estimator performs well. The application of the estimator is demonstrated with real data.

A New Perspective on the Multidimensionality of Divergent Thinking Tasks.

In the presented work, a shift of perspective with respect to the dimensionality of divergent thinking (DT) tasks is introduced moving from the question of multidimensionality across DT scores (i.e., fluency, flexibility, or originality) to the question of multidimensionality within one holistic score of DT performance (i.e., snapshot ratings of creative quality). We apply IRTree models to test whether unidimensionality assumptions hold in different task instructions for snapshot scoring of DT tests across Likert-scale points and varying levels of fluency. It was found that evidence for unidimensionality across scale points was stronger with be-creative instructions as compared to be-fluent instructions which suggests better psychometric quality of ratings when be-creative instructions are used. In addition, creative quality latent variables pertaining to low-fluency and high-fluency ideational pools shared around 50% of variance which suggests both strong overlap, and evidence for differentiation. The presented approach allows to further examine the psychometric quality of subjective ratings and to examine new questions with respect to within-item multidimensionality in DT.

Does the early social environment prepare individuals for the future? A match-mismatch experiment in female wild cavies.

BACKGROUND: The social environment that mothers experience during pregnancy and lactation has a strong effect on the developing offspring. Whether offspring can be adaptively shaped to match an environment that is similar to the maternal one is still a major question in research. Our previous work in wild cavies showed that females whose mothers lived in a stable social environment with few social challenges during pregnancy and lactation (SE-daughters) developed different behavioral phenotypes than females whose mothers lived in an unstable social environment with frequent social challenges during pregnancy and lactation (UE-daughters). In the present study we investigated whether SE-daughters are better adapted to a stable social environment, similar to their maternal one, than are UE-daughters, for which the stable social environment represents a mismatch with their maternal one. For this purpose, we established pairs of one UE- and one SE-daughter and housed them together under stable social conditions for one week. Dominance ranks, behavioral profiles, glucocorticoid levels, cortisol responsiveness and body weight changes were compared between the groups. We hypothesized that SE-daughters fare better in a stable social setting compared to UE-daughters. RESULTS: After one week of cohabitation in the stable social condition, UE-daughters had higher glucocorticoid levels, tended to gain less body weight within the first three days and displayed higher frequencies of energy-demanding behaviors such as rearing and digging than SE-daughters. However, there was no difference in cortisol responsiveness as well as in dominance ranks between UE- and SE-daughters. CONCLUSION: Higher glucocorticoid levels and less body weight gain imply that UE-daughters had higher energy demands than SE-daughters. This high energy demand of UE-daughters is further indicated by the increased display of rearing and digging behavior. Rearing implies increased vigilance, which is far too energy demanding in a stable social condition but may confer an advantage in an unstable social environment. Hence, SE-daughters seem to better match a stable social environment, similar to their maternal one, than do UE-daughters, who encountered a mismatch to their maternal environment. This data supports the environmental matching hypothesis, stating that individuals manage the best in environments that correspond to their maternal ones.

Analysing model fit of psychometric process models: An overview, a new test and an application to the diffusion model.

Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey (Econometrica, 53, 1985, 1047) and Tauchen (J. Econometrics, 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica, 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q-diffusion model and the D-diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M2 test (Molenaar et al., J. Stat. Softw., 66, 2015, 1), the moment test (Ranger et al., Br. J. Math. Stat. Psychol., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. MODEL: , 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions.

A Diffusion Model Analysis of Magnitude Comparison in Children with and without Dyscalculia: Care of Response and Ability Are Related to Both Mathematical Achievement and Stimuli.

The respective roles of the approximate number system (ANS) and an access deficit (AD) in developmental dyscalculia (DD) are not well-known. Most studies rely on response times (RTs) or accuracy (error rates) separately. We analyzed the results of two samples of elementary school children in symbolic magnitude comparison (MC) and non-symbolic MC using a diffusion model. This approach uses the joint distribution of both RTs and accuracy in order to synthesize measures closer to ability and response caution or response conservatism. The latter can be understood in the context of the speed-accuracy tradeoff: It expresses how much a subject trades in speed for improved accuracy. We found significant effects of DD on both ability (negative) and response caution (positive) in MC tasks and a negative interaction of DD with symbolic task material on ability. These results support that DD subjects suffer from both an impaired ANS and an AD and in particular support that slower RTs of children with DD are indeed related to impaired processing of numerical information. An interaction effect of symbolic task material and DD (low mathematical ability) on response caution could not be refuted. However, in a sample more representative of the general population we found a negative association of mathematical ability and response caution in symbolic but not in non-symbolic task material. The observed differences in response behavior highlight the importance of accounting for response caution in the analysis of MC tasks. The results as a whole present a good example of the benefits of a diffusion model analysis.

Limited information estimation of the diffusion-based item response theory model for responses and response times.

Psychological tests are usually analysed with item response models. Recently, some alternative measurement models have been proposed that were derived from cognitive process models developed in experimental psychology. These models consider the responses but also the response times of the test takers. Two such models are the Q-diffusion model and the D-diffusion model. Both models can be calibrated with the diffIRT package of the R statistical environment via marginal maximum likelihood (MML) estimation. In this manuscript, an alternative approach to model calibration is proposed. The approach is based on weighted least squares estimation and parallels the standard estimation approach in structural equation modelling. Estimates are determined by minimizing the discrepancy between the observed and the implied covariance matrix. The estimator is simple to implement, consistent, and asymptotically normally distributed. Least squares estimation also provides a test of model fit by comparing the observed and implied covariance matrix. The estimator and the test of model fit are evaluated in a simulation study. Although parameter recovery is good, the estimator is less efficient than the MML estimator.