A tutorial on estimating dynamic treatment regimes from observational longitudinal data using lavaan.

Psychological and behavioral scientists develop interventions toward addressing pressing societal challenges. But such endeavors are complicated by treatments that change over time as individuals' needs and responses evolve. For instance, students initially in a multiyear mentoring program to improve future academic outcomes may not continue with the program after interim school engagement improves.

Structural after measurement (SAM) approaches for accommodating latent quadratic and interaction effects.

Established strategies commonly used to address latent quadratic and interaction effects within structural equation models, such as the unconstrained product indicator (UPI) approach or the latent moderated structural equations (LMS) approach, tend to perform effectively in models featuring only a limited number of nonlinear effects. However, as the complexity of the model increases with a higher number of nonlinear terms, the feasibility of joint or one-step methods such as UPI and LMS progressively diminishes. In response to this challenge, this paper advocates the adoption of structural after measurement (SAM) approaches to overcome this limitation.

Does Adjusting for Causal Intermediate Confounders Resolve the Perinatal Crossover Paradox?

Background: Mediation analyses of the pre-eclampsia-perinatal outcome association through preterm birth (PTB) have produced paradoxical findings. For example, pre-eclamptic births at preterm gestations show a lower risk of adverse outcomes than normotensive births. These results have been explained by unmeasured baseline confounding between PTB and outcomes, with PTB as the sole mediator.

Explaining how a psychosocial intervention (PROACTIVE) based on behavioural activation improved outcomes of depression in older adults living in deprived regions of Brazil: The mediating roles of reduced loneliness and stepped care.

Background: The PROACTIVE trial was a task-shared, stepped and collaborative care, psychosocial intervention based on psychoeducation and behavioural activation in 715 participants (60-94 years; mean (SD) 68·6 (6.9) years; 74·1 % female), that was highly effective at improving recovery from depression among older adults in Brazil. Here we investigate mediators of the intervention's effectiveness.

Causal effects of competing obstetrical interventions: mediators of placental abruption and perinatal mortality.

Placental abruption, the premature placental separation, confers increased perinatal mortality risk with preterm delivery as an important pathway through which the risk appears mediated. Although pregnancies complicated by abruption are often delivered through an obstetrical intervention, many deliver spontaneously. We examined the contributions of clinician-initiated (PTDIND) and spontaneous (PTDSPT) preterm delivery at < 37 weeks as competing causal mediators of the abruption-perinatal mortality association.

Parametric g-formula for Testing Time-Varying Causal Effects: What It Is, Why It Matters, and How to Implement It in Lavaan.

Psychologists leverage longitudinal designs to examine the causal effects of a focal predictor (i.e., treatment or exposure) over time.

Estimating curvilinear time-varying treatment effects: Combining g-estimation of structural nested mean models with time-varying effect models for longitudinal causal inference.

Longitudinal designs can fortify causal inquiries of a focal predictor (i.e., treatment) on an outcome.

Person-specific priorities in solitude.

Objective: People value solitude in varying degrees. Theories and studies suggest that people's appreciation of solitude varies considerably across persons (e.g.

Understated gender disparities due to outcome-dependent selection: Commentary on Mackelprang et al. (2023).

What is the gender gap in invited publications in high-impact psychology journals? To answer this critical question, Mackelprang et al. (2023) examined invited publications in five high-impact psychology journals. They first calculated the share of women among authors of the invited publications (35.

Reductions in kinesiophobia and distress after pain neuroscience education and exercise lead to favourable outcomes: a secondary mediation analysis of a randomized controlled trial in primary care.

Pain neuroscience education combined with exercise (PNE + exercise) is an effective treatment for patients with chronic spinal pain. Yet, however, little is known about its underlying therapeutic mechanisms. Thus, this study aimed to provide the first insights by performing a novel mediation analysis approach in a published randomized controlled trial in primary care where PNE + exercise was compared with standard physiotherapy.

A Small Sample Correction for Factor Score Regression.

Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error in the factor scores. The method of Croon (MOC) is a well-known bias correction technique.

Estimating time-varying treatment effects in longitudinal studies.

Longitudinal study designs are frequently used to investigate the effects of a naturally observed predictor (treatment) on an outcome over time. Because the treatment at each time point or wave is not randomly assigned, valid inferences of its causal effects require adjusting for covariates that confound each treatment-outcome association. But adjusting for covariates which are inevitably time-varying is fraught with difficulties.

Data-driven covariate selection for confounding adjustment by focusing on the stability of the effect estimator.

Valid inference of cause-and-effect relations in observational studies necessitates adjusting for common causes of the focal predictor (i.e., treatment) and the outcome.

Adjusting for Baseline Measurements of the Mediators and Outcome as a First Step Toward Eliminating Confounding Biases in Mediation Analysis.

Mediation analysis prevails for researchers probing the etiological mechanisms through which treatment affects an outcome. A central challenge of mediation analysis is justifying sufficient baseline covariates that meet the causal assumption of no unmeasured confounding. But current practices routinely overlook this assumption.

A structural after measurement approach to structural equation modeling.

In structural equation modeling (SEM), the measurement and structural parts of the model are usually estimated simultaneously. In this article, we revisit the long-standing idea that we should first estimate the measurement part, and then estimate the structural part. We call this the "structural-after-measurement" (SAM) approach to SEM.

Evaluating sensitivity to classification uncertainty in latent subgroup effect analyses.

Background: Increasing attention is being given to assessing treatment effect heterogeneity among individuals belonging to qualitatively different latent subgroups. Inference routinely proceeds by first partitioning the individuals into subgroups, then estimating the subgroup-specific average treatment effects. However, because the subgroups are only latently associated with the observed variables, the actual individual subgroup memberships are rarely known with certainty in practice and thus have to be imputed.

Do cues of infectious disease shape people's affective responses to social exclusion?

Social exclusion triggers aversive reactions (e.g., increased negative affect), but being excluded may bring substantial benefits by reducing pathogen exposure associated with social interactions.

Understanding Etiologic Pathways Through Multiple Sequential Mediators: An Application in Perinatal Epidemiology.

Background: Causal mediation analysis facilitates decomposing the total effect into a direct effect and an indirect effect that operates through an intermediate variable. Recent developments in causal mediation analysis have clarified the process of evaluating how-and to what extent-different pathways via multiple causally ordered mediators link the exposure to the outcome.

Methods: Through an application of natural effect models for multiple mediators, we show how placental abruption might affect perinatal mortality using small for gestational age (SGA) birth and preterm delivery as two sequential mediators.

Association Between Dietary Protein Intake and Sleep Quality in Middle-Aged and Older Adults in Singapore.

Poor sleep has been associated with the increased risk of developing detrimental health conditions. Diet and certain nutrients, such as dietary protein (PRO) may improve sleep. This cross-sectional study aimed to investigate the relationship between PRO intake, their amino acid components, and sources with sleep quality in middle-aged and older adults residing in Singapore.

Identification of causal intervention effects under contagion.

Defining and identifying causal intervention effects for transmissible infectious disease outcomes is challenging because a treatment - such as a vaccine - given to one individual may affect the infection outcomes of others. Epidemiologists have proposed causal estimands to quantify effects of interventions under contagion using a two-person partnership model. These simple conceptual models have helped researchers develop causal estimands relevant to clinical evaluation of vaccine effects.

Nonlinear effect of social interaction quantity on psychological well-being: Diminishing returns or inverted U?

Social contact is an important ingredient of a happy and satisfying life. But is more social contact necessarily better? Although it is well-established that increasing the quantity of social interactions on the low end of its spectrum promotes psychological well-being, the effect of interaction quantity on the high end remains largely unexplored. We propose that the effect of interaction quantity is nonlinear; specifically, at high levels of interaction quantity, its positive effects may be reduced (Diminishing Returns Hypothesis) or even reversed (Inverted U Hypothesis).

Disentangling indirect effects through multiple mediators without assuming any causal structure among the mediators.

hen multiple mediators exist on the causal pathway from treatment to outcome, path analysis prevails for disentangling indirect effects along paths linking possibly several mediators. However, separately evaluating each indirect effect along different posited paths demands stringent assumptions, such as correctly specifying the mediators' causal structure, and no unobserved confounding among the mediators. These assumptions may be unfalsifiable in practice and, when they fail to hold, can result in misleading conclusions about the mediators.

The impact of tryptophan supplementation on sleep quality: a systematic review, meta-analysis, and meta-regression.

Context: L-tryptophan (Trp) has been documented to aid sleep, but a systematic compilation of its effect on sleep quality is still limited.

Objective: We assessed the effect of Trp supplementation on sleep quality via meta-analysis and meta-regression. The effects of daily Trp dose (<1 g and ≥1 g) were also assessed.