The Relationship Between a Lifetime History of Sexual Victimization and Perinatal Depression: A Systematic Review and Meta-Analysis

Background: The association between a lifetime history of sexual victimization and the well-being of women during the perinatal period has received increasing attention. However, research investigating this relationship has yet to be systematically reviewed or quantitatively synthesized. Aim: This systematic review and meta-analysis aims to calculate the pooled effect size estimate of the statistical association between a lifetime history of sexual victimization and perinatal depression (PND). Method: Four bibliographic databases were systematically searched, and reference harvesting was conducted to identify peer-reviewed articles that empirically examined associations between a lifetime history of sexual victimization and PND. A random effects model was used to ascertain an overall pooled effect size estimate in the form of an odds ratio and corresponding 95% confidence intervals (CIs). Subgroup analyses were also conducted to assess whether particular study features and sample characteristic (e.g., race and ethnicity) influenced the magnitude of effect size estimates. Results: This review included 36 studies, with 45 effect size estimates available for meta-analysis. Women with a lifetime history of sexual victimization had 51% greater odds of experiencing PND relative to women with no history of sexual victimization ( OR = 1.51, 95% CI [1.35, 1.67]). Effect size estimates varied considerably according to the PND instrument used in each study and the racial/ethnic composition of each sample. Conclusion: Findings provide compelling evidence for an association between a lifetime history of sexual victimization and PND. Future research should focus on screening practices and interventions that identify and support survivors of sexual victimization perinatally.

Analytic and bootstrap confidence intervals for the common-language effect size estimate

Evaluating how an effect-size estimate performs between two continuous variables based on the common-language effect size (CLES) has received increasing attention. While Blomqvist (1950; https://doi.org/10.1214/aoms/1177729754) developed a parametric estimator (q') for the CLES, there has been limited progress in further refining CLES. This study: a) extends Blomqvist’s work by providing a mathematical foundation for Bp (a non-parametric version of CLES) and an analytic approach for estimating its standard error; and b) evaluates the performance of the analytic and bootstrap confidence intervals (CIs) for Bp. The simulation shows that the bootstrap bias-corrected-and-accelerated interval (BCaI) has the best protected Type 1 error rate with a slight compromise in Power, whereas the analytic-t CI has the highest overall Power but with a Type 1 error slightly larger than the nominal value. This study also uses a real-world data-set to demonstrate the applicability of the CLES in measuring the relationship between age and sexual compulsivity.

EMDR for Depression: A Meta-Analysis and Systematic Review

The literature on the efficacy of eye movement desensitization and reprocessing (EMDR) for treating depression is heterogeneous due to research design, quality issues, and trials methodology. The current meta-analysis seeks to examine EMDR for depression with the aim of answering the aforementioned limitations. Thirty-nine studies were included for analysis after a review of the relevant literature. Univariate meta-regressions were run to examine dose-response and the effect of moderating variables. Subanalysis for primary and secondary depression showed a large, significant, and heterogeneous effect-size estimates, where EMDR significantly improved symptoms of depression in contrast to all control types. At post hoc, data were reexamined and a significant and large, yet heterogeneous, effect-size estimate emerged between the EMDR and control arm after the removal of two outliers [Hedges' g = 0.70, 95% CI =0.50–0.89, p-value < .01, I2 = 70%, K = 37]. This is the first meta-analysis examining for the effect of EMDR comparing to various control modalities on depression with dose-response. We found (a) that studies were balanced at onset in terms of depression severity, and (b) a large and significant effect of EMDR on depression at the end of trials. Additionally, the significance of the aggregate effect-size estimate at the end of trials was unchanged by the intake of psychotropic medications, reported demographic variables, or EMDR methodology.

Reconstruction of brown bear population dynamics in Slovenia in the period 1998-2019: a new approach combining genetics and long-term mortality data

Reliable data and methods for assessing changes in wildlife population size over time are necessary for management and conservation. For most species, assessing abundance is an expensive and labor-intensive task that is not affordable on a frequent basis. We present a novel approach to reconstructing brown bear population dynamics in Slovenia in the period 1998-2019, based on the combination of two CMR non-invasive genetic estimates (in 2007 and 2015) and long-term mortality records, to show how the latter can help the study of population dynamics in combination with point-in-time estimates. The spring (i.e. including newborn cubs) population size estimate was 383 (CI: 336-432) bears in 1998 and 971 (CI: 825-1161) bears in 2019. In this period, the average annual population growth rate was 4.5 %. The predicted population size differed by just 7 % from the non-invasive genetic size estimate after eight years, suggesting that the method is reliable. It can predict the evolution of the population size under different management scenarios and provide information on key parameters, e.g. background mortality and the sex- and age-structure of the population. Our approach can be used for several other wildlife species, but it requires reliable mortality data over time.

Design and Analysis of Replication Studies

Issues surrounding the importance and interpretation of replication research have generated considerable debate and controversy in recent years. Some of the controversy can be attributed to imprecise and inadequate specifications of the statistical criteria needed to assess replication and nonreplication. Two types of statistical replication evidence and four types of statistical nonreplication evidence are described. In addition, three types of inconclusive statistical replication evidence are described. An important benefit of a replication study is the ability to combine an effect-size estimate from the original study with an effect-size estimate from the follow-up study to obtain a more precise and generalizable effect-size estimate. The sample size in the follow-up study is an important design consideration, and some methods for determining the follow-up sample size requirements are discussed. R functions are provided that can be used to analyze results from a replication study. R functions to determine the appropriate sample size in the follow-up study also are provided.