Epidemiologic Reviews

Clinical trials are considered the gold standard for establishing efficacy of health interventions, determining which interventions are brought to scale in health care and public health programs. Digital clinical trials, broadly defined as trials that have partial to full integration of technology across implementation, interventions, and/or data collection, are valued for increased efficiencies as well as testing of digitally-delivered interventions. While recent reviews describe the advantages, disadvantages and recommendations for improving scientific rigor in the conduct of digital clinical trials, little to none have investigated how digital clinical trials address the digital divide, whether they are equitably accessible, and if trial outcomes are potentially beneficial only to those with optimal and consistent access to technology...

Prospective economic evaluations conducted alongside clinical trials have become an increasingly popular approach in evaluating the cost-effectiveness of a public health initiative or treatment intervention. These types of economic studies provide improved internal validity and accuracy of cost and effectiveness estimates of health interventions and have the advantage of jointly observing health and economics outcomes of trial participants compared to simulation or decision-analytic models. However, missing data due to incomplete response or patient attrition, and sampling uncertainty are common concerns in econometric analysis of clinical trials...

In clinical trials, harms (adverse events) are often reported by simply counting the number of people who experienced each event. Reporting only frequencies ignores other dimensions of the data that are important for stakeholders, including severity, seriousness, rate (recurrence), timing, and groups of related harms. Additionally, application of selection criteria to harms prevents most from being reported. Visualization of data could improve communication of multidimensional data. We replicated and compared the characteristics of six different approaches for visualizing harms-Dot Plot, Stacked Bar Chart, Volcano Plot, Heatmap, Treemap, and Tendril Plot...

In trials of infectious disease interventions, rare outcomes and unpredictable spatiotemporal variation can introduce bias, reduce statistical power, and prevent conclusive inferences. Spillover effects can complicate inference if individual randomization is used to gain efficiency. Ring trials are a type of cluster-randomized trial that may increase efficiency and minimize bias, particularly in emergency and elimination settings with strong clustering of infection. They can be used to evaluate ring interventions, which are delivered to individuals in proximity to or contact with index cases...

Although observational studies have identified modifiable risk factors for Alzheimer's disease and related dementias (ADRD), randomized controlled trials (RCTs) of risk factor modification for ADRD prevention have been inconsistent or inconclusive. This suggests a need to improve translation between observational studies and RCTs. However, many common features of observational studies reduce their relevance to designing related RCTs. Observational studies routinely differ from RCTs with respect to eligibility criteria, study population, length of follow-up, treatment conditions, outcomes, and effect estimates...

The uveitides consist of over 30 diseases characterized by intraocular inflammation. Non-infectious intermediate, posterior, and panuveitides typically are treated with oral corticosteroids and immunosuppression with a similar treatment approach for most diseases. Because non-infectious intermediate, posterior and panuveitides collectively are considered a rare disease, single disease trials are difficult to impractical to recruit, and most trials have included several different diseases for a given protocol treatment(s)...

The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models are a tool to help us understand and address thiscomplex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings; created a database of model parameters used for model calibration; and evaluated study transparency and reproducibility...

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Quantitative bias analysis can be used to empirically assess how far study estimates are from the truth (i.e., an estimate that is free of bias). These methods can be used to explore the potential impact of confounding bias, selection bias (collider stratification bias), and information bias. Quantitative bias analysis includes methods that can be used to check the robustness of study findings to multiple types of bias and methods that use simulation studies to generate data and understand the hypothetical impact of specific types of bias in a simulated data set...

Measurement error, although ubiquitous, is uncommonly acknowledged and rarely assessed or corrected in epidemiological studies. This review offers a straight-forward guide to common problems caused by measurement error in research studies and a review of several accessible bias correction methods for epidemiologists and data analysts. While most correction methods require criterion validation including a gold standard, these are also ways to evaluate the impact of measurement error and potentially correct for it without such data...

Extensive empirical health research leverages variation in the timing and location of policy changes as quasi-experiments. Multiple social policies may be adopted simultaneously in the same locations, creating co-occurrence which must be addressed analytically for valid inferences. The pervasiveness and consequences of co-occurring policies have received limited attention. We analyzed a systematic sample of 13 social policy databases covering diverse domains including poverty, paid family leave, and tobacco...

Mediation analysis aims to investigate the "mechanisms of action" behind the effects of interventions or treatments. Originally developed in psychology, a robust set of mediation methods are now used across a range of fields. Given the history and common use of mediation in mental health research, this review aimed to understand how mediation analysis is implemented in psychology and psychiatry and whether analyses adhere to, address, or justify the key underlying assumptions of their approaches. All articles (N=206) came from top academic psychiatry or psychology journals in the PsycInfo database, published in the English language from 2013-2018...

In any research study, there is an underlying research process that should begin with a clear articulation of the study's goal. The study's goal drives this process; it determines many study features including the estimand of interest, the analytic approaches that can be used to estimate it, and which coefficients, if any, should be interpreted. "Misalignment" can occur in this process when analytic approaches and/or interpretations do not match the study's goal; misalignment is potentially more likely to arise when study goals are ambiguously framed...

Simulation models are increasingly used to inform epidemiological studies and health policy, yet there is great variation in their transparency and reproducibility. This review provides an overview of applications of simulation models in health policy and epidemiology, analyzes the use of best reporting practices, and assesses the reproducibility of the models using predefined, categorical criteria. 1,613 studies were identified and analyzed. We found an exponential growth in the number of studies over the past half century, with the highest growth in dynamic modeling approaches...

The health benefits of physical activity have been widely recognized, yet traditional measures of physical activity including questionnaires and category-based assessments of volume and intensity provide only broad estimates of daily activities. Accelerometers have advanced epidemiologic research on physical activity by providing objective and continuous measurement of physical activity in free-living conditions. Wrist-worn accelerometers have become especially popular due to low participant burden. However, the validity and reliability of wrist-worn devices for adults have yet to be summarized...

Social policies have great potential to improve population health and reduce health disparities. Thus, increasing empirical research seeks to quantify the health effects of social policies by exploiting variation in the timing of policy changes across places. Multiple social policies are often adopted simultaneously or in close succession in the same locations, creating co-occurrence which must be handled analytically for valid inferences. Although this is a substantial methodological challenge for studies aiming to isolate social policy effects, limited prior work has systematically considered analytic solutions within a causal framework or assessed whether these solutions are being adopted...

Propensity score weighting and outcome regression are popular ways to adjust for observed confounders in epidemiological research. Here, we provide an introduction to matching methods, which serve the same purpose but can offer advantages in robustness and performance. A key difference between matching and weighting methods is that matching methods do not directly rely on the propensity score and so are less sensitive to its misspecification or to the presence of extreme values. Matching methods offer many options for customization, which allow a researcher to incorporate substantive knowledge and carefully manage bias/variance trade-offs in estimating the effects of nonrandomized exposures...

In many perinatal pharmacoepidemiologic studies, exposure to a medication is classified as "ever exposed" versus "never exposed" within each trimester or even over the entire pregnancy. This approach is often far from real-world exposure patterns, may lead to exposure misclassification, and fails to incorporate important aspects such as dosage, timing of exposure, and treatment duration. Alternative exposure modeling methods can better summarize complex individual level medication utilization trajectories or time-varying exposures from information on medication dosage, gestational timing of use, and frequency of use...

There has been an increased focus on the public health burden of antimicrobial resistance (AMR). This raises conceptual challenges such as determining how much harm multi-drug resistant organisms do compared to what, or how to establish the burden. In this viewpoint we will present a counterfactual framework and provide guidance to harmonize methodologies and optimize study quality. In AMR burden studies, two counterfactual approaches have been applied; the harm of drug-resistant infections relative to the harm of the same, drug-susceptible, infections (susceptible-infection counterfactual) and the total harm of drug-resistant infections relative to a situation where such infections were prevented (no-infection counterfactual)...

Effectiveness of opiate treatment programs (OTP) can be significantly influenced by co-occurring substance use, yet there are no standardized guidelines for assessing the influence of co-occurring substance use on treatment outcomes. This review aims to provide an overview on the status of the assessment of co-occurring substance use during OTP in the United States. MEDLINE/PubMed, EMBASE, PsychINFO, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were queried from database inception to November 2018 to select relevant publications of OTP that assessed participants' co-occurring substance use...