Longitudinal and repeated cross-sectional cluster-randomization designs using mixed effects regression for binary outcomes: bias and coverage of frequentist and Bayesian methods

Predictors of mental health among U.S. adults during COVID-19 early pandemic, mid- pandemic, and post-vaccine eras

BACKGROUND

A collective trauma like COVID-19 impacts individuals differently due to socio-contextual and individual characteristics. Younger adults, minorities, affiliates of certain political parties, and residents of some regions of the United States reported experiencing poorer mental health during the pandemic. Being diagnosed with COVID-19, or losing a friend/family to it, was related to more adverse mental health symptoms. While the negative impact of COVID-19 on health outcomes has been studied, mental health changes during this pandemic need further exploration.

METHODS

In a study of 8,612 U.S. households, using three surveys collected from a nationally representative panel between May 2020 and October 2021, using a repeated cross-sectional design, a linear mixed effect regression model was performed to investigate factors associated with the mental health status, based on the Mental Health Inventory-5, of individuals throughout different phases of the COVID-19 pandemic, and whether an improvement over time, especially after vaccines became available, was observed.

RESULTS

An overall improvement in mental health was observed after vaccines became available. Individuals with no COVID-related death in their household, those not wearing masks, those identifying as members of the Republican Party, race/ethnicities other than Asian, men, older adults, and residents of the South were less likely than others to report mental health challenges.

CONCLUSIONS

Our results highlight the need for widespread mental health interventions and health promotion to address challenges during the COVID-19 pandemic and beyond. Due to the worse mental health observed among Asians, younger adults, women, low-income families, those with a higher level of concern for COVID-19, people who lost someone to COVID-19, and/or individuals with histories of opioid use disorder and criminal legal involvement, over the period of this study, targeted attention needs to be given to the mental health of these groups.

Turbidity buffers coral bleaching under extreme wind and rainfall conditions

Coral reefs in turbid waters have been hypothesized to be a refuge from climate change. These naturally occurring communities were brought into the spotlight because some of their species exhibited record levels of resistance to marine heatwaves (MHWs) by disturbance-tolerant corals. However, long-term monitoring data on the drivers of coral bleaching in these extreme reef habitats are scarce. Here, we describe the population structure and bleaching rates of a widespread and resilient coral (Siderastrea stellata). We examine the links between environmental factors, namely, rainfall, wind speed, turbidity, solar irradiance, sea surface temperature, MHWs, and coral bleaching status under the worst recorded drought cycle in the Tropical South Atlantic (2013-2015). We examined 2880 colonies, most of which (∼93%) fit in the size group of 2-10 cm, with a small number (∼1%) of larger and older colonies (>20 cm). The results indicated the absence of MHWs and normal sea surface temperature variations (between 26.6 °C and 29.3 °C), however, we detected an extreme rainfall deficit (30-40% less annual volume precipitation). In general, a high proportion (44-84%) of bleached colonies was found throughout the months when turbidity decreased. Siderastrea is the only reef-building coral that comprises this seascape with encrusting and low-relief colonies. During drought periods, cloudiness is reduced, turbidity and wind speed are reduced, and solar irradiance increase, driving coral bleaching in turbid reefs. However, episodic rainfall and higher wind speeds increase turbidity and decrease coral bleaching. Our hypothesis is that turbidity decreases during drought periods which increases bleaching risk to corals even without thermal stress. Our results suggest that turbidity may have related to wind and rainfall to provoke the coral bleaching phenomenon.

Increasing antiretroviral therapy adherence and retention in care among adults living with HIV in Philadelphia: a study protocol for a stepped-wedge cluster-randomised type 2 hybrid effectiveness-implementation trial of managed problem-solving plus (MAPS+) delivered by community health workers

INTRODUCTION

To end the HIV epidemic in Philadelphia, implementation of evidence-based practices (EBP) to increase viral suppression and retention in HIV care is critical. Managed problem solving (MAPS), an EBP for antiretroviral therapy adherence, follows a problem-solving approach to empower people living with HIV (PWH) to manage their health. To overcome barriers to care experienced by PWH in Philadelphia, the EBP was adapted to include a focus on care retention and delivery by community health workers (CHWs). The adapted intervention is MAPS+. To maximise the clinical impact and reach of the intervention, evaluation of the effectiveness and implementation of MAPS+ is necessary.

METHODS AND ANALYSIS

This manuscript describes the protocol for a stepped-wedge cluster-randomised type 2 hybrid effectiveness-implementation trial in 10 clinics in Philadelphia. This research incorporates innovative approaches to accomplish three objectives: (1) to evaluate the effectiveness of the CHW-led MAPS+ intervention to improve viral suppression and retention in care 1 year after the individual implementation period (N=390 participants), (2) to examine the effect of the menu of implementation strategies on reach and implementation cost and (3) to examine processes, mechanisms, and sustainment of the implementation strategies for MAPS+ (N=56 participants). Due to various factors (eg, COVID-19), protocol modifications have occurred.

ETHICS AND DISSEMINATION

The institutional review board (IRB) at the city of Philadelphia serves as the primary IRB; initial approval was granted on 21 December 2020. The University of Pennsylvania and Northwestern University executed reliance agreements. A safety monitoring committee comprised experts in implementation science, biostatistics and infectious diseases oversee this study. This research will offer insights into achieving the goals to end the HIV epidemic in Philadelphia as well as implementation efforts of MAPS+ and other behavioural interventions aimed at increasing medication adherence and retention in care. Dissemination will include deliverables (eg, peer-reviewed manuscripts and lay publications) to reach multiple constituents.

TRIAL REGISTRATION NUMBER

NCT04560621.

Study protocol for a type III hybrid effectiveness-implementation trial of strategies to implement firearm safety promotion as a universal suicide prevention strategy in pediatric primary care

Background

Insights from behavioral economics, or how individuals’ decisions and behaviors are shaped by finite cognitive resources (e.g., time, attention) and mental heuristics, have been underutilized in efforts to increase the use of evidence-based practices in implementation science. Using the example of firearm safety promotion in pediatric primary care, which addresses an evidence-to-practice gap in universal suicide prevention, we aim to determine: is a less costly and more scalable behavioral economic-informed implementation strategy (i.e., “Nudge”) powerful enough to change clinician behavior or is a more intensive and expensive facilitation strategy needed to overcome implementation barriers?

Methods

The Adolescent and child Suicide Prevention in Routine clinical Encounters (ASPIRE) hybrid type III effectiveness-implementation trial uses a longitudinal cluster randomized design. We will test the comparative effectiveness of two implementation strategies to support clinicians’ use of an evidence-based firearm safety practice, S.A.F.E. Firearm, in 32 pediatric practices across two health systems. All pediatric practices in the two health systems will receive S.A.F.E. Firearm materials, including training and cable locks. Half of the practices (k = 16) will be randomized to receive Nudge; the other half (k = 16) will be randomized to receive Nudge plus 1 year of facilitation to target additional practice and clinician implementation barriers (Nudge+). The primary implementation outcome is parent-reported clinician fidelity to the S.A.F.E Firearm program. Secondary implementation outcomes include reach and cost. To understand how the implementation strategies work, the primary mechanism to be tested is practice adaptive reserve, a self-report practice-level measure that includes relationship infrastructure, facilitative leadership, sense-making, teamwork, work environment, and culture of learning.

Discussion

The ASPIRE trial will integrate implementation science and behavioral economic approaches to advance our understanding of methods for implementing evidence-based firearm safety promotion practices in pediatric primary care. The study answers a question at the heart of many practice change efforts: which strategies are sufficient to support change, and why? Results of the trial will offer valuable insights into how best to implement evidence-based practices that address sensitive health matters in pediatric primary care.

Trial registration

ClinicalTrials.gov, NCT04844021. Registered 14 April 2021.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13012-021-01154-8.

Review of Recent Methodological Developments in Group-Randomized Trials: Part 2-Analysis

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have updated that review with developments in analysis of the past 13 years, with a companion article to focus on developments in design. We discuss developments in the topics of the earlier review (e.g., methods for parallel-arm GRTs, individually randomized group-treatment trials, and missing data) and in new topics, including methods to account for multiple-level clustering and alternative estimation methods (e.g., augmented generalized estimating equations, targeted maximum likelihood, and quadratic inference functions). In addition, we describe developments in analysis of alternative group designs (including stepped-wedge GRTs, network-randomized trials, and pseudocluster randomized trials), which require clustering to be accounted for in their design and analysis.

Practice-tailored facilitation to improve pediatric preventive care delivery: a randomized trial

OBJECTIVE

Evolving primary care models require methods to help practices achieve quality standards. This study assessed the effectiveness of a Practice-Tailored Facilitation Intervention for improving delivery of 3 pediatric preventive services.

METHODS

In this cluster-randomized trial, a practice facilitator implemented practice-tailored rapid-cycle feedback/change strategies for improving obesity screening/counseling, lead screening, and dental fluoride varnish application. Thirty practices were randomized to Early or Late Intervention, and outcomes assessed for 16 419 well-child visits. A multidisciplinary team characterized facilitation processes by using comparative case study methods.

RESULTS

Baseline performance was as follows: for Obesity: 3.5% successful performance in Early and 6.3% in Late practices, P = .74; Lead: 62.2% and 77.8% success, respectively, P = .11; and Fluoride: <0.1% success for all practices. Four months after randomization, performance rose in Early practices, to 82.8% for Obesity, 86.3% for Lead, and 89.1% for Fluoride, all P < .001 for improvement compared with Late practices' control time. During the full 6-month intervention, care improved versus baseline in all practices, for Obesity for Early practices to 86.5%, and for Late practices 88.9%; for Lead for Early practices to 87.5% and Late practices 94.5%; and for Fluoride, for Early practices to 78.9% and Late practices 81.9%, all P < .001 compared with baseline. Improvements were sustained 2 months after intervention. Successful facilitation involved multidisciplinary support, rapid-cycle problem solving feedback, and ongoing relationship-building, allowing individualizing facilitation approach and intensity based on 3 levels of practice need.

CONCLUSIONS

Practice-tailored Facilitation Intervention can lead to substantial, simultaneous, and sustained improvements in 3 domains, and holds promise as a broad-based method to advance pediatric preventive care.

Repeatability of quantitative MRI measurements in normal breast tissue

PURPOSE

To evaluate the variability and repeatability of repeated magnetic resonance imaging (MRI) measurements in normal breast tissues between and within subjects.

METHODS

Eighteen normal premenopausal subjects underwent two contrast-enhanced MRI scans within 72 hours or during the same menstrual phase in two consecutive months. A subset of nine women also completed diffusion-weighted imaging (DWI). Fibroglandular tissue (FGT) density and FGT enhancement were measured on the contrast-enhanced MRI. Apparent diffusion coefficient (ADC) values were computed from DWI. Between- and within-subject coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability of all measurements was assessed by the coefficient of repeatability (CR) and Bland-Altman plots.

RESULTS

The bCV of FGT density and FGT enhancement at visit 1 and visit 2 ranged from 47% to 63%. The wCV was 13% for FGT density, 22% for FGT enhancement, and 11% for ADC. The CRs of FGT density and FGT enhancement were 0.15 and 0.19, respectively, and for ADC, it was 6.1 x 10(-4) mm(2)/s.

CONCLUSIONS

We present an estimate of the variability and repeatability of MR measurements in normal breasts. These estimates provide the basis for understanding the normal variation of healthy breast tissue in MRI and establishing thresholds for agreement between measurements.

Person mobility in the design and analysis of cluster-randomized cohort prevention trials

Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.

Performance of analytical methods for overdispersed counts in cluster randomized trials: sample size, degree of clustering and imbalance

Many different methods have been proposed for the analysis of cluster randomized trials (CRTs) over the last 30 years. However, the evaluation of methods on overdispersed count data has been based mostly on the comparison of results using empiric data; i.e. when the true model parameters are not known. In this study, we assess via simulation the performance of five methods for the analysis of counts in situations similar to real community-intervention trials. We used the negative binomial distribution to simulate overdispersed counts of CRTs with two study arms, allowing the period of time under observation to vary among individuals. We assessed different sample sizes, degrees of clustering and degrees of cluster-size imbalance. The compared methods are: (i) the two-sample t-test of cluster-level rates, (ii) generalized estimating equations (GEE) with empirical covariance estimators, (iii) GEE with model-based covariance estimators, (iv) generalized linear mixed models (GLMM) and (v) Bayesian hierarchical models (Bayes-HM). Variation in sample size and clustering led to differences between the methods in terms of coverage, significance, power and random-effects estimation. GLMM and Bayes-HM performed better in general with Bayes-HM producing less dispersed results for random-effects estimates although upward biased when clustering was low. GEE showed higher power but anticonservative coverage and elevated type I error rates. Imbalance affected the overall performance of the cluster-level t-test and the GEE's coverage in small samples. Important effects arising from accounting for overdispersion are illustrated through the analysis of a community-intervention trial on Solar Water Disinfection in rural Bolivia.