Estimating Mediation Effects in ABAB Reversal Designs.

Single-Case Experimental Designs (SCEDs), or N-of-1 trials, are commonly used to estimate intervention effects in many disciplines including in the treatment of youth mental health problems. SCEDs consist of repeated measurements of an outcome over time for a single case (e.g.

Why You Should Not Estimate Mediated Effects Using the Difference-in-Coefficients Method When the Outcome is Binary.

Despite previous warnings against the use of the difference-in-coefficients method for estimating the indirect effect when the outcome in the mediation model is binary, the difference-in-coefficients method remains readily used in a variety of fields. The continued use of this method is presumably because of the lack of awareness that this method conflates the indirect effect estimate and non-collapsibility. In this paper, we aim to demonstrate the problems associated with the difference-in-coefficients method for estimating indirect effects for mediation models with binary outcomes.

What CBT Modules Work Best for Whom? Identifying Subgroups of Depressed Youths by Their Differential Response to Specific Modules.

Prior research suggests that the effects of specific cognitive-behavioral therapy (CBT) modules on symptom outcomes can be estimated. We conducted a study utilizing idiographic and nomothetic methods to clarify which CBT modules are most effective for youth depression, and for whom they are most effective. Thirty-five youths received modular CBT for depression.

Comparative genomics of Giardia duodenalis sub-assemblage AI beaver (Be-2) and human (WB-C6) strains show remarkable homozygosity, sequence similarity, and conservation of VSP genes.

Giardia duodenalis, a major cause of waterborne infection, infects a wide range of mammalian hosts and is subdivided into eight genetically well-defined assemblages named A through H. However, fragmented genomes and a lack of comparative analysis within and between the assemblages render unclear the molecular mechanisms controlling host specificity and differential disease outcomes. To address this, we generated a near-complete de novo genome of AI assemblage using the Oxford Nanopore platform by sequencing the Be-2 genome.

Breaking the silence of sharing data in medical research.

Data sharing is highly advocated in the scientific community, with numerous organizations, funding agencies, and journals promoting transparency and collaboration. However, limited research exists on actual data sharing practices. We conducted a comprehensive analysis of the intent to share individual participant data (IPD) in a total of 313,990 studies encompassing clinical trials and observational studies obtained from ClinicalTrials.

Exploring a Potential Interaction Between the Effect of Specific Maternal Smoking Patterns and Comorbid Antenatal Depression in Causing Postpartum Depression.

Purpose: To explore a potential interaction between the effect of specific maternal smoking patterns and the presence of antenatal depression, as independent exposures, in causing postpartum depression (PPD).

Methods: This case-control study of participants with singleton term births (N = 51220) was based on data from the 2017-2018 Pregnancy Risk Assessment Monitoring System. Multivariable log-binomial regression models examined the main effects of smoking patterns and self-reported symptoms of antenatal depression on the risk of PPD on the adjusted risk ratio (aRR) scale and tested a two-way interaction adjusting for covariates selected in a directed acyclic graph (DAG).

A data-driven approach to choosing privacy parameters for clinical trial data sharing under differential privacy.

Objectives: Clinical trial data sharing is crucial for promoting transparency and collaborative efforts in medical research. Differential privacy (DP) is a formal statistical technique for anonymizing shared data that balances privacy of individual records and accuracy of replicated results through a "privacy budget" parameter, ε. DP is considered the state of the art in privacy-protected data publication and is underutilized in clinical trial data sharing.

A novel approach to estimate moderated treatment effects and moderated mediated effects with continuous moderators.

Moderation analysis is used to study under what conditions or for which subgroups of individuals a treatment effect is stronger or weaker. When a moderator variable is categorical, such as assigned sex, treatment effects can be estimated for each group resulting in a treatment effect for males and a treatment effect for females. If a moderator variable is a continuous variable, a strategy for investigating moderated treatment effects is to estimate conditional effects (i.

Acculturative Stress and Self-rated Health among Hispanic Emerging Adults: Examining the Moderating Effects of the Social Environment and Social Support.

Little is known about the impact of sociocultural stressors such as acculturative stress on self-rated health among Hispanics. We aimed to examine (a) associations between acculturative stress and self-rated health, and (b) the moderating effects of the community of settlement (i.e.

Do specific modules of cognitive behavioral therapy for depression have measurable effects on youth internalizing symptoms? An idiographic analysis.

Objective: Understanding the efficacy of each module of cognitive behavioral therapy (CBT) may inform efforts to improve outcomes for youth depression, but effects of specific modules have been difficult to examine. Idiographic interrupted time series models offer a robust way to estimate module effects on an individual's symptoms. This study examined the association of specific CBT modules for depression on internalizing symptoms among depressed youths who received modular CBT in a randomized trial.

Accommodating a Latent XM Interaction in Statistical Mediation Analysis.

Statistical mediation analysis is used in the social sciences and public health to uncover potential mechanisms, known as mediators, by which a treatment led to a change in an outcome. Recently, the estimation of the treatment-by-mediator interaction (i.e.

Time lags and time interactions in mixed effects models impacted longitudinal mediation effect estimates.

Objectives: Longitudinal mediation effects can be estimated with mixed effects models. Mixed effects models are versatile, as they accommodate the estimation of contemporaneous, lagged, time-independent, and time-dependent effects. However, the inclusion of time lags and time interactions in mixed effects models for longitudinal mediation analysis has received little attention.

Evaluating Response Shift in Statistical Mediation Analysis.

Researchers and prevention scientists often develop interventions to target intermediate variables (known as ) that are thought to be related to an outcome. When researchers target a mediating construct measured by self-report, the meaning of self-report measure could change from pretest to posttest for the individuals who received the intervention - which is a phenomenon referred to as . As a result, any observed changes on the mediator measure across groups or across time might reflect a combination of true change on the construct and response shift.

Causal mediation effects in single case experimental designs.

Single case experimental designs (SCEDs) are used to test treatment effects in a wide range of fields and consist of repeated measurements for a single case throughout one or more baseline phases and throughout one or more treatment phases. Recently, mediation analysis has been applied to SCEDs. Mediation analysis decomposes the total treatment-outcome effect into a direct and indirect effect, and therefore aims to unravel the causal processes underlying treatment-outcome effects.

Momentary Self-regulation: Scale Development and Preliminary Validation.

Background: Self-regulation refers to a person's ability to manage their cognitive, emotional, and behavioral processes to achieve long-term goals. Most prior research has examined self-regulation at the individual level; however, individual-level assessments do not allow the examination of dynamic patterns of intraindividual variability in self-regulation and thus cannot aid in understanding potential malleable processes of self-regulation that may occur in response to the daily environment.

Objective: This study aims to develop a brief, psychometrically sound momentary self-regulation scale that can be practically administered through participants' mobile devices at a momentary level.

The Effect of Noninvariance on the Estimation of the Mediated Effect in the Two-Wave Mediation Model.

The two-wave mediation model is the most suitable model for examining mediation effects in a randomized intervention and includes measures taken at pretest and posttest. When using self-report measures, the meaning of responses may change for the treatment group over the course of the intervention and result in noninvariance across groups at posttest, a phenomenon referred to as . We investigate how the mediated effect would be impacted by noninvariance when using sum scores (i.

Statistical Mediation Analysis for Models with a Binary Mediator and a Binary Outcome: the Differences Between Causal and Traditional Mediation Analysis.

Mediation analysis is an important statistical method in prevention research, as it can be used to determine effective intervention components. Traditional mediation analysis defines direct and indirect effects in terms of linear regression coefficients. It is unclear how these traditional effects are estimated in settings with binary variables.

Risk of large for gestational age births at early, full and late term in relation to pre-pregnancy body mass index: Mediation by gestational diabetes status.

Background: Maternal pre-pregnancy body mass index (BMI) is strongly associated with infant birthweight and the risk differs in pregnancies complicated by gestational diabetes (GDM).

Objectives: To examine the risk of large for gestational age (LGA) (≥97th percentile) singleton births at early term, full term and late term in relation to maternal pre-pregnancy BMI status mediated through GDM.

Methods: We analysed data from the 2018 U.

Mediation analysis methods used in observational research: a scoping review and recommendations.

Background: Mediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation analysis based on the counterfactual framework. However, a previous review showed that for experimental studies the uptake of causal mediation analysis remains low. The aim of this paper is to review the methodological characteristics of mediation analyses performed in observational epidemiologic studies published between 2015 and 2019 and to provide recommendations for the application of mediation analysis in future studies.

Clarifying the Implicit Assumptions of Two-Wave Mediation Models the Latent Change Score Specification: An Evaluation of Model Fit Indices.

Statistical mediation analysis is used to investigate mechanisms through which a randomized intervention causally affects an outcome variable. Mediation analysis is often carried out in a pretest-posttest control group design because it is a common choice for evaluating experimental manipulations in the behavioral and social sciences. There are four different two-wave (i.

The use of traditional and causal estimators for mediation models with a binary outcome and exposure-mediator interaction.

An important recent development in mediation analysis is the use of causal mediation analysis. Causal mediation analysis decomposes the total exposure effect into causal direct and indirect effects in the presence of exposure-mediator interaction. However, in practice, traditional mediation analysis is still most widely used.

Predictors of Treatment Engagement and Outcome Among Adolescents With Attention-Deficit/Hyperactivity Disorder: An Integrative Data Analysis.

Objective: To identify patient- and treatment-level factors that predict intervention engagement and outcome for adolescents with attention-deficit/hyperactivity disorder (ADHD), guiding efforts to enhance care.

Method: Integrative data analysis was used to pool data from 4 randomized controlled trials of adolescent ADHD treatment with participants (N = 854) receiving various evidence-based behavioral therapy packages in 5 treatment arms (standard [STANDARD], comprehensive [COMP], engagement-focused [ENGAGE]), community-based usual care (UC), or no treatment (NOTX). Participants also displayed varying medication use patterns (negligible, inconsistent, consistent) during the trial.

Brief Report: Prevalence and Severity of Auditory Sensory Over-Responsivity in Autism as Reported by Parents and Caregivers.

Auditory sensory over-responsivity (aSOR) is a frequently reported sensory feature of autism spectrum disorders (ASD); however, there is little consensus regarding its prevalence and severity. This cross-sectional study uses secondary data from the Autism Diagnostic Interview-Revised (ADI-R; Item 72: undue sensitivity to noise) housed in the US National Institute of Mental Health Data Archives to identify prevalence and severity of aSOR. Of the 4104 subjects with ASD ages 2-54 (M = 9, SD = 5.