Directed Acyclic Graphs in Decision-Analytic Modeling: Bridging Causal Inference and Effective Model Design in Medical Decision Making.

Our commentary proposes the application of directed acyclic graphs (DAGs) in the design of decision-analytic models, offering researchers a valuable and structured tool to enhance transparency and accuracy by bridging the gap between causal inference and model design in medical decision making.The practical examples in this article showcase the transformative effect DAGs can have on model structure, parameter selection, and the resulting conclusions on effectiveness and cost-effectiveness.This methodological article invites a broader conversation on decision-modeling choices grounded in causal assumptions.

Evaluating hypothetical prevention strategies for internalizing symptoms in the general population and at-risk children.

Objective: Specific modifiable factors (e.g., screen time [ST], sleep duration, physical activity, or social connections) are targets for reducing depression risk in adults.

Gender issues in myopia: a changing paradigm in generations.

Myopia is becoming an important cause of visual impairment. Determining risk profiles will help to develop targeted prevention strategies. This study aims to explore the difference in myopia development between genders in two cohorts representing different generations, and to assess whether hypothetical interventions targeting education or lifestyle factors would reduce a gender gap.

Impact of COVID-19 mitigation measures on perinatal outcomes in the Netherlands.

Objective: Investigate the acute impact of COVID-19 mitigation measures implemented in March 2020 on a comprehensive range of perinatal outcomes.

Study Design: National registry-based quasi-experimental study.

Methods: We obtained data from the Dutch Perinatal Registry (2010-2020) which was linked to multiple population registries containing sociodemographic variables.

Effect of COVID-19 lockdown on maternity care and maternal outcome in the Netherlands: a national quasi-experimental study.

Objectives: The COVID-19 pandemic and associated lockdowns disrupted health care worldwide. High-income countries observed a decrease in preterm births during lockdowns, but maternal pregnancy-related outcomes were also likely affected. This study investigates the effect of the first COVID-19 lockdown (March-June 2020) on provision of maternity care and maternal pregnancy-related outcomes in the Netherlands.