Sexual well-being is an important contributor to romantic relationship quality, health, and quality of life, yet couples face significant disruptions to their sexuality during the transition to parenthood. While there is evidence of variability in the sexual well-being of new parents, distinct classes of dyadic trajectories have not been established. Sexual frequency, desire, satisfaction, and distress are each unique components of sexual well-being and may follow different patterns of change within couples. We sought to establish classes of trajectories of four aspects of sexual well-being for couples in the transition to parenthood as well as the associations among identified classes. Couples (N = 203) expecting their first child completed online standardized measures of sexual well-being at 20 and 32 weeks in pregnancy and at 3, 6, 9, and 12 months postpartum. Dyadic latent class growth analyses were conducted to identify classes of trajectories for each facet of sexual well-being, and dual trajectory analyses examined the probability of group membership across classes. Couples' sexual well-being over time was heterogeneous. Sexual frequency had two classes high (33%) and low (67%); sexual desire had three classes moderate (36%), high (25%), and discrepant (39%); sexual satisfaction had two classes high (64%) and low (36%); and sexual distress had two classes low (76%) and discrepant (24%). Overlap in classes of sexual well-being was variable such that high and low or discrepant (between partners) classes did not always co-occur. Findings provide more nuanced information about new parents' postpartum sexual health, which may facilitate early assessment and intervention. (PsycInfo Database Record (c) 2020 APA, all rights reserved).Trait self-control is important for well-being and mental and physical health. Most extant measures of self-control are limited in that they do not account for the multidimensionality and specificity of the trait. The aim of this study was to develop and validate a multidimensional and hierarchical scale of self-control in a full and a short version. The development of the Multidimensional Self-Control Scale (MSCS) and the Brief Multidimensional Self-Control Scale (BMSCS) was based on focus groups, a pilot, a main, and a validation sample (total N = 2,409). The 29-item MSCS consists of 6 first-order factors (Procrastination, Attentional Control, Impulse Control, Emotional Control, Goal Orientation, and Self-Control Strategies), 2 second-order factors (Inhibition and Initiation), and a third-order self-control factor. The 8 items in BMSCS provides a general trait self-control score. Findings from exploratory and confirmatory factor analyses supported the structures across samples, and internal consistency was acceptable. Assessment for acquiescence and sex differences indicated no major impacts on the scales. Strong convergent validity was observed with the Self-Control Scale (SCS) and the Brief Self-Control Scale (BSCS), as well as to other similar concepts. The MSCS subscales discriminated well between each other. Assessment of incremental validity of the MSCS over SCS, when controlling for sex and personality, showed significant increases in explained variance when predicting habits, hardiness, and life satisfaction. Similar significant results were observed for the BMSCS over the BSCS. Overall, results indicate that the new scales are useful measures that integrate recent theoretical and empirical findings of trait self-control. (PsycInfo Database Record (c) 2020 APA, all rights reserved).Randomized response models (RRMs) aim at increasing the validity of measuring sensitive attributes by eliciting more honest responses through anonymity protection of respondents. This anonymity protection is achieved by implementing randomization in the questioning procedure. On the other hand, this randomization increases the sampling variance and, therefore, increases sample size requirements.  https://www.selleckchem.com/products/Pyroxamide(NSC-696085).html  The present work aims at countering this drawback by combining RRMs with curtailed sampling, a sequential sampling design in which sampling is terminated as soon as sufficient information to decide on a hypothesis is collected. In contrast to nontruncated sequential designs, the curtailed sampling plan includes the definition of a maximum sample size and subsequent prevalence estimation is easy to conduct. Using this approach, resources can be saved such that the application of RRMs becomes more feasible. An R Shiny web application is provided for simplified application of the proposed procedures. (PsycInfo Database Record (c) 2020 APA, all rights reserved).Psychology researchers are rapidly adopting open science practices, yet clear guidelines on how to apply these practices to meta-analysis remain lacking. In this tutorial, we describe why open science is important in the context of meta-analysis in psychology, and suggest how to adopt the 3 main components of open science preregistration, open materials, and open data. We first describe how to make the preregistration as thorough as possible-and how to handle deviations from the plan. We then focus on creating easy-to-read materials (e.g., search syntax, R scripts) to facilitate reproducibility and bolster the impact of a meta-analysis. Finally, we suggest how to organize data (e.g., literature search results, data extracted from studies) that are easy to share, interpret, and update as new studies emerge. For each step of the meta-analysis, we provide example templates, accompanied by brief video tutorials, and show how to integrate these practices into the Open Science Framework (https//osf.io/q8stz/). (PsycInfo Database Record (c) 2020 APA, all rights reserved).Numerous psychological and educational researchers are concerned with the moderating effect of a categorical variable on the relationship between a continuous predictor and a continuous response. Despite the great interest in moderation analyses, there exist few studies that explicitly address the essential issues of effect size measure, power calculation, and sample size determination under heterogeneity of variance. This article introduces a useful effect size index for representing the moderating effects of categorical variables. Based on the extended Welch statistic, a nearly unbiased estimator and related effect size measures are presented. To facilitate power and sample size computations, different approximations are considered for the general distribution of the extended Welch test of moderating effects. Detailed numerical appraisals are conducted to examine the relative performance of the described effect size measures, power formulas, and sample size procedures under various variance structures and model configurations.