Group Treatment Trials Research Articles

Smoking prevalence and association with sociodemographic variables in cancer clinical trial participants.

Tobacco use (smoking) causes adverse clinical outcomes among patients with cancer, including increased cancer-related mortality. In participants in cancer clinical trials, the prevalence of tobacco use and the factors associated with tobacco use are not well described. Data were examined from participants enrolled in SWOG cancer clinical treatment trials between 2016 and 2022 who reported their smoking status at trial enrollment. Baseline variables (smoking status, insurance type, zip code, and demographic factors) were obtained from patient registration forms. Bivariate and multivariable associations were examined via logistic regression. Among 4326 patients enrolled in 29 trials, 48.1% reported currently/previously smoking, including 12.4% currently, 4.9% recently, and 30.7% formerly. Ever smoking was more commonly reported in males, patients aged ≥65 years, patients with Medicaid or no insurance, patients from areas of high socioeconomic deprivation, and rural patients. Patients of Hispanic ethnicity and Asian and Pacific Islander patients were less likely to have ever smoked. In multivariable regression, patients with lung cancer were most likely to report ever smoking compared to patients with breast cancer (odds ratio,4.98; p<.001). In the first comprehensive evaluation of smoking status among trial participants enrolled in National Cancer Institute network group treatment trials, nearly half reported ever smoking and one in six reported current or recent smoking. Smoking was more common among vulnerable population patients defined by demographic and socioeconomic factors. Tobacco use should be routinely assessed and reported in clinical trials to help reduce the negative cancer and overall health effects of persistent tobacco use and to address disparities among patients with cancer.

Evaluating analytic models for individually randomized group treatment trials with complex clustering in nested and crossed designs.

Many individually randomized group treatment (IRGT) trials randomly assign individuals to study arms but deliver treatments via shared agents, such as therapists, surgeons, or trainers. Post-randomization interactions induce correlations in outcome measures between participants sharing the same agent. Agents can be nested in or crossed with trial arm, and participants may interact with a single agent or with multiple agents. These complications have led to ambiguity in choice of models but there have been no systematic efforts to identify appropriate analytic models for these study designs. To address this gap, we undertook a simulation study to examine the performance of candidate analytic models in the presence of complex clustering arising from multiple membership, single membership, and single agent settings, in both nested and crossed designs and for a continuous outcome. With nested designs, substantial type I error rate inflation was observed when analytic models did not account for multiple membership and when analytic model weights characterizing the association with multiple agents did not match the data generating mechanism. Conversely, analytic models for crossed designs generally maintained nominal type I error rates unless there was notable imbalance in the number of participants that interact with each agent.

A Pilot Randomized Controlled Trial of Motivation-Based Social Skills Group Treatment with Parent Training.

Despite the popularity of social skills groups, there remains a need for empirical investigation of treatment effects, especially when targeting pivotal aspects of social functioning such as initiations to peers. The goal of the present study was to conduct a randomized controlled trial of a 12-week social intervention (SUCCESS), which combined an inclusive social group with a parent education program. Twenty-five 4- to 6-year-olds with Autism Spectrum Disorder (ASD) were randomized to SUCCESS (N = 11) or to treatment as usual (N = 14). Combining a peer group model with a parent training program, the SUCCESS intervention used naturalistic behavioral techniques (e.g., environmental arrangement, natural reinforcement) to increase social initiations to peers. After 12 weeks, children participating in the SUCCESS program made more frequent initiations to peers than children in the treatment-as-usual group, including more prompted and unprompted initiations to request. Additional gains in clinician-rated social functioning were observed in children randomized to SUCCESS, while differential treatment effects were not detected in parent-rated measures. However, lower baseline social motivation was associated with greater parent-reported initiation improvement. This study provides preliminary support for the efficacy of a naturalistic, behavioral social skills intervention to improve peer initiations for children with ASD. The findings suggest that using a motivation-based social skills group was effective in increasing both prompted and spontaneous initiations to peers, and highlights the need for further research into the role of baseline social motivation in predicting social skills treatment response.

Hierarchical Bayesian modeling of heterogeneous outcome variance in cluster randomized trials.

Heterogeneous outcome correlations across treatment arms and clusters have been increasingly acknowledged in cluster randomized trials with binary endpoints, where analytical methods have been developed to study such heterogeneity. However, cluster-specific outcome variances and correlations have yet to be studied for cluster randomized trials with continuous outcomes. This article proposes models fitted in the Bayesian setting with hierarchical variance structure to quantify heterogeneous variances across clusters and explain it with cluster-level covariates when the outcome is continuous. The models can also be extended to analyzing heterogeneous variances in individually randomized group treatment trials, with arm-specific cluster-level covariates, or in partially nested designs. Simulation studies are carried out to validate the performance of the newly introduced models across different settings. Simulations showed that overall the newly introduced models have good performance, reporting low bias and approximately 95% coverage for the intraclass correlation coefficients and regression parameters in the variance model. When variances are heterogeneous, our proposed models had improved model fit over models with homogeneous variances. When used to analyze data from the Kerala Diabetes Prevention Program study, our models identified heterogeneous variances and intraclass correlation coefficients across clusters and examined cluster-level characteristics associated with such heterogeneity. We proposed new hierarchical Bayesian variance models to accommodate cluster-specific variances in cluster randomized trials. The newly developed methods inform the understanding of how an intervention strategy is implemented and disseminated differently across clusters and can help improve future trial design.

Enhancing Lifestyles in the Metabolic syndrome (ELM) multisite behavioral efficacy trial. Design and baseline cohort

BackgroundPrevalence of metabolic syndrome (MetS) increased from one-quarter to one-third of the U.S. adult population over 8 years and is spreading to young adults and Asian and Hispanic Americans. Diagnosed when >3 out of 5 cardiometabolic risk factors are present, there is widespread agreement that its fundamental roots are in a lifestyle characterized by poor dietary quality and physical inactivity. Past lifestyle trials for MetS produce benefits that have limited sustainability, suggesting the need for new treatment approaches. MethodsThis is the design and baseline cohort of the Enhancing Lifestyles in the Metabolic Syndrome (ELM) multi-site trial. The trial tests the hypothesis that a habit-based lifestyle treatment offered over 6 months, followed by 18 monthly maintenance contacts, can produce 4 new diet, physical activity, and mindfulness habits and, if so, sustained MetS remission. The design is an individually randomized, partially clustered group treatment trial of 618 participants with the MetS recruited from 5 sites in the U.S. and randomized to a small group lifestyle treatment or an enhanced standard of care education comparator. The primary outcome is MetS remission at 24 months. Secondary outcomes compare arms at 6, 15, and 24 months on MetS components, lifestyle targets, weight, body mass index, hemoglobin A1c, LDL cholesterol, medications, quality of life, psychosocial factors, and cost-effectiveness. ResultsThe cohort of 618 participants was recruited by screening 14,817 over 2.5 years (screening to enrollment ratio 24:1). Recruitment exceeded the target of 600 despite 2 COVID-19 pauses. The mean age was 55.5 years, 24.3% were male, 25.5% were a racial minority, 9.7% identified as Hispanic, and 83.0% were classified as obese (body mass index >30). The most common MetS components were abdominal obesity (97.7%) and elevated blood pressure or antihypertensive medication (86.2%). ConclusionsThe geographic, sociodemographic, and clinical diversity of the cohort, combined with rigorous behavioral efficacy trial methods, will provide a conclusive answer to the question of whether this habit-based lifestyle program can produce sustained 24-month remission of the MetS and thereby help to curb a significant and growing public health problem.

Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations.

Individually randomized group treatment (IRGT) trials, in which the clustering of outcome is induced by group-based treatment delivery, are increasingly popular in public health research. IRGT trials frequently incorporate longitudinal measurements, of which the proper sample size calculations should account for correlation structures reflecting both the treatment-induced clustering and repeated outcome measurements. Given the relatively sparse literature on designing longitudinal IRGT trials, we propose sample size procedures for continuous and binary outcomes based on the generalized estimating equations approach, employing the block exchangeable correlation structures with different correlation parameters for the treatment arm and for the control arm, and surveying five marginal mean models with different assumptions of time effect: no-time constant treatment effect, linear-time constant treatment effect, categorical-time constant treatment effect, linear time by treatment interaction, and categorical time by treatment interaction. Closed-form sample size formulas are derived for continuous outcomes, which depends on the eigenvalues of the correlation matrices; detailed numerical sample size procedures are proposed for binary outcomes. Through simulations, we demonstrate that the empirical power agrees well with the predicted power, for as few as eight groups formed in the treatment arm, when data are analyzed using the matrix-adjusted estimating equations for the correlation parameters with a bias-corrected sandwich variance estimator.

Designing multicenter individually randomized group treatment trials.

In an individually randomized group treatment (IRGT) trial, participant outcomes can be positively correlated due to, for example, shared therapists in treatment delivery. Oftentimes, because of limited treatment resources or participants at one location, an IRGT trial can be carried out across multiple centers. This design can be subject to potential correlations in the participant outcomes between arms within the same center. While the design of a single-center IRGT trial has been studied, little is known about the planning of a multicenter IRGT trial. To address this gap, this paper provides analytical sample size formulas for designing multicenter IRGT trials with a continuous endpoint under the linear mixed model framework. We found that accounting for the additional center-level correlation at the design stage can lead to sample size reduction, and the magnitude of reduction depends on the amount of between-therapist correlation. However, if the variance components of therapist-level random effects are considered as input parameters in the design stage, accounting for the additional center-level variance component has no impact on the sample size estimation. We presented our findings through numeric illustrations and performed simulation studies to validate our sample size procedures under different scenarios. Optimal design configurations under the multicenter IRGT trials have also been discussed, and two real-world trial examples are drawn to illustrate the use of ourmethod.

Evaluation of the Early Adolescent Skills for Emotions (EASE) intervention in Lebanon: A randomized controlled trial

BackgroundThere is a need for scalable evidence-based psychological interventions for young adolescents experiencing high levels of psychological distress in humanitarian settings and low- and middle-income countries. Poor mental health during adolescence presents a serious public health concern as it is a known predictor of persistent mental disorders in adulthood. This study evaluates the effectiveness of a new group-based intervention developed by the World Health Organization (Early Adolescent Skills for Emotions; EASE), implemented by non-specialists, to reduce young adolescents' psychological distress among mostly Syrian refugees in Lebanon. MethodsWe conducted a two-arm, single-blind, individually randomized group treatment trial. Adolescents aged 10 to 14 years who screened positive for psychological distress using the Pediatric Symptom Checklist (PSC) were randomly allocated to EASE or enhanced treatment as usual (ETAU) (1:1.6). ETAU consisted of a single scripted psycho-education home-visit session with the adolescent and their caregivers. EASE consists of seven group sessions with adolescents and three sessions with caregivers. The primary outcome was adolescent-reported psychological distress as measured with the PSC (internalizing, externalizing, and attentional symptoms). Secondary outcomes included depression, posttraumatic stress, well-being, functioning, and caregivers' parenting and distress. All outcomes were assessed at baseline, endline, and 3 months (primary time point) and 12 months follow-up. ResultsDue to the COVID-19 pandemic and other adversities in Lebanon at the time of this research, the study was prematurely terminated, resulting in an under-powered trial sample (n = 198 enrolled compared to n = 445 targeted). We screened 604 children for eligibility. The 198 enrolled adolescents were assigned to EASE (n = 80) and ETAU (n = 118), with retention rates between 76.1 and 88.4% across all timepoints. Intent-to-treat analyses demonstrated no between-group differences on any of the outcome measures between the EASE and ETAU. We did observe a significant improvement on the primary outcome equally in the EASE and ETAU groups (−0.90, 95% CI: −3.6, 1.8; p = .52), − a trend that was sustained at three months follow-up. Sub-group analyses, for those with higher depression symptoms at baseline, showed ETAU outperformed EASE on reducing depression symptoms (difference in mean change = 2.7, 95% CI: 0.1, 5.3; p = .04; d = 0.59) and internalizing problems (difference in mean change 1.0, 95% CI: 0.08, 1.9; p = .03; d = 0.56) . ConclusionNo conclusions can be drawn about the comparative effectiveness of the intervention given that the sample was underpowered as a result of early termination. Both EASE and single session psycho-education home visits resulted in meaningful improvements in reducing psychological distress. We did not identify any indications in the data suggesting that EASE was more effective than a single session family intervention in the context of the COVID-19 pandemic and other crises in Lebanon. Fully powered research is needed to evaluate the effectiveness of EASE.

Sample size considerations for assessing treatment effect heterogeneity in randomized trials with heterogeneous intracluster correlations and variances.

An important consideration in the design and analysis of randomized trials is the need to account for outcome observations being positively correlated within groups or clusters. Two notable types of designs with this consideration are individually randomized group treatment trials and cluster randomized trials. While sample size methods for testing the average treatment effect are available for both types of designs, methods for detecting treatment effect modification are relatively limited. In this article, we present new sample size formulas for testing treatment effect modification based on either a univariate or multivariate effect modifier in both individually randomized group treatment and cluster randomized trials with a continuous outcome but any types of effect modifier, while accounting for differences across study arms in the outcome variance, outcome intracluster correlation coefficient (ICC) and the cluster size. We consider cases where the effect modifier can be measured at either the individual level or cluster level, and with a univariate effect modifier, our closed-form sample size expressions provide insights into the optimal allocation of groups or clusters to maximize design efficiency. Overall, our results show that the required sample size for testing treatment effect heterogeneity with an individual-level effect modifier can be affected by unequal ICCs and variances between arms, and accounting for such between-arm heterogeneity can lead to more accurate sample size determination. We use simulations to validate our sample size formulas and illustrate their application in the context of two real trials: an individually randomized group treatment trial (the AWARE study) and a cluster randomized trial (the K-DPP study).

Metabolic profile in women with bulimia nervosa or binge-eating disorder before and after treatment: secondary analysis from the randomized PED-t trial

PurposeChaotic eating and purging behavior pose a risk to the metabolic health of women with bulimia nervosa (BN) and binge-eating disorder (BED). This study reports on one-year changes in blood markers of metabolic health and thyroid hormones in women with BN or BED attending two different treatments.MethodsThese are secondary analyses from a randomized controlled trial of 16-week group treatment of either physical exercise and dietary therapy (PED-t) or cognitive behavior therapy (CBT). Blood samples collected at pre-treatment, week eight, post-treatment, and at 6- and 12-month follow-ups were analyzed for glucose, lipids (triglycerides (TG), total cholesterol (TC), LDL cholesterol (LDL-c), HDL cholesterol (HDL-c), apolipoprotein A (ApoA) and apolipoprotein B (ApoB) lipoproteins), and thyroid hormones (thyroxine (T4), thyroid stimulating hormone (TSH), and thyroperoxidase antibodies).ResultThe average levels of blood glucose, lipids and thyroid hormones were within the recommended range, but clinical levels of TC and LDL-c were detected in 32.5% and 39.1%, respectively. More women with BED compared with BN had low HDL-c, and a larger increase over time in TC and TSH. No significant differences occurred between PED-t and CBT at any measurement. Exploratory moderator analyses indicated a more unfavorable metabolic response at follow-up among treatment non-responders.ConclusionThe proportion of women with impaired lipid profiles and unfavorable lipid changes, suggests active monitoring with necessary management of the metabolic health of women with BN or BED, as recommended by metabolic health guidelines.Level of evidence: Level I: Evidence obtained from a randomized, experimental trial.Trial registration number: This trial was prospectively registered in the Norwegian Regional Committee for Medical and Health Research Ethics on December 16, 2013, with the identifier number 2013/1871, and in Clinical Trials on February 17, 2014, with the identifier number NCT02079935.

Secret Agent Society: A Randomized Controlled Trial of a Transdiagnostic Youth Social Skills Group Treatment.

Group programs are key for targeting social skills (SS) for children with developmental disorders and/or mental illness. Despite promising evidence regarding efficacy of group treatments, there are several limitations to current research regarding generalizability and effectiveness across diagnoses. This randomized control trial assessed whether the Secret Agent Society (SAS) group program was superior to treatment as usual (TAU) in improving social-emotional functioning for children with Attention Deficit-Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), and/or anxiety. Eighty-nine youth (8-12) with ADHD, ASD, and/or an anxiety disorder receiving treatment at hospital-based outpatient clinics were randomized to receive SAS (n = 47) or TAU (n = 42) over a three-month period, at which point TAU participants were offered the SAS intervention. Parent report showed significant improvement in Emotion Regulation (ER) and Social Skills (SS) for youth in SAS vs. TAU (Fs ≥ 6.79, ps ≤ 01). Gains for the SAS condition were maintained at 6-months. Intent-to-treat analysis of teacher report indicated youth in SAS had positive gains in SS (F = 0.41, p = 0.475) and ER (F = 0.99, p = 0.322), though not significantly better than youth in TAU. Clinically reliable improvement rates were significantly higher for SAS participants than TAU for parent and teacher reported SS and ER. Improvements were significant for youth with single and comorbid diagnoses. Results suggest that SAS was superior to TAU in improving SS and ER for youth aged 8-12 with ADHD, ASD, and/or anxiety. Gains maintained in the medium-term. Trial registration number NCT02574273, registered 10/12/2015.

A group-based mental health intervention for Tanzanian youth living with HIV: Secondary analysis of a pilot trial.

Background:Youth living with human immunodeficiency virus (YLWH) are vulnerable to incomplete adherence to antiretroviral therapy in the context of stigma, decreased hope for future, and mental health challenges. Despite these challenges, few mental health interventions have been developed to support YLWH. Previous randomized results from the Sauti ya Vijana (SYV; “The Voice of Youth”) mental health intervention were indicative of the intervention's benefits in promoting virologic suppression.Methods:SYV is a group-based mental health and life skills intervention (pilot, individually randomized group treatment trial) developed alongside YLWH. SYV was comprised of 10, 90-minute sessions based on evidence-based treatment models designed to improve coping, social support, and hope for future as a pathway to improved adherence and virologic suppression. At baseline, YLWH 12 to 24 years of age were randomized to SYV or standard of care. Participants included in this secondary analysis were enrolled in SYV's crossover waves due to either being randomized to standard of care or inability to attend an earlier group, and therefore delayed intervention exposure. Measured outcomes included self-reported mental health measures, self-reported human immunodeficiency virus measures (stigma and adherence), and human immunodeficiency virus ribonucleic acid. Data was collected at baseline, preintervention, and postintervention timepoints. Participants were included if they attended a crossover wave and had data at all 3 timepoints.Results:Twenty-one crossover participants met inclusion criteria. Mean scores of self-reported mental health questionnaires were in an asymptomatic range both pre- and postintervention. Viral suppression was N = 15 (71%) preintervention compared to N = 17 (81%) postintervention. The participants who became virologically suppressed had no change in antiretroviral therapy.Conclusions:Despite the small sample size, findings from this study demonstrate that mental wellbeing may be an important pathway to improved HIV outcomes for YLWH. The same trend toward virologic suppression pre- to postintervention was demonstrated in the randomized pilot trial and suggests that SYV holds promise to improve HIV outcomes. Data from this analysis support the fully powered trial that is now underway.

Influential methods reports for group-randomized trials and related designs.

This article identifies the most influential methods reports for group-randomized trials and related designs published through 2020. Many interventions are delivered to participants in real or virtual groups or in groups defined by a shared interventionist so that there is an expectation for positive correlation among observations taken on participants in the same group. These interventions are typically evaluated using a group- or cluster-randomized trial, an individually randomized group treatment trial, or a stepped wedge group- or cluster-randomized trial. These trials face methodological issues beyond those encountered in the more familiar individually randomized controlled trial. PubMed was searched to identify candidate methods reports; that search was supplemented by reports known to the author. Candidate reports were reviewed by the author to include only those focused on the designs of interest. Citation counts and the relative citation ratio, a new bibliometric tool developed at the National Institutes of Health, were used to identify influential reports. The relative citation ratio measures influence at the article level by comparing the citation rate of the reference article to the citation rates of the articles cited by other articles that also cite the reference article. In total, 1043 reports were identified that were published through 2020. However, 55 were deemed to be the most influential based on their relative citation ratio or their citation count using criteria specific to each of the three designs, with 32 group-randomized trial reports, 7 individually randomized group treatment trial reports, and 16 stepped wedge group-randomized trial reports. Many of the influential reports were early publications that drew attention to the issues that distinguish these designs from the more familiar individually randomized controlled trial. Others were textbooks that covered a wide range of issues for these designs. Others were "first reports" on analytic methods appropriate for a specific type of data (e.g. binary data, ordinal data), for features commonly encountered in these studies (e.g. unequal cluster size, attrition), or for important variations in study design (e.g. repeated measures, cohort versus cross-section). Many presented methods for sample size calculations. Others described how these designs could be applied to a new area (e.g. dissemination and implementation research). Among the reports with the highest relative citation ratios were the CONSORT statements for each design. Collectively, the influential reports address topics of great interest to investigators who might consider using one of these designs and need guidance on selecting the most appropriate design for their research question and on the best methods for design, analysis, and sample size.

Methodological challenges in pragmatic trials in Alzheimer's disease and related dementias: Opportunities for improvement.

We need more pragmatic trials of interventions to improve care and outcomes for people living with Alzheimer's disease and related dementias. However, these trials present unique methodological challenges in their design, analysis, and reporting-often, due to the presence of one or more sources of clustering. Failure to account for clustering in the design and analysis can lead to increased risks of Type I and Type II errors. We conducted a review to describe key methodological characteristics and obtain a "baseline assessment" of methodological quality of pragmatic trials in dementia research, with a view to developing new methods and practical guidance to support investigators and methodologists conducting pragmatic trials in this field. We used a published search filter in MEDLINE to identify trials more likely to be pragmatic and identified a subset that focused on people living with Alzheimer's disease or other dementias or included them as a defined subgroup. Pairs of reviewers extracted descriptive information and key methodological quality indicators from each trial. We identified N = 62 eligible primary trial reports published across 36 different journals. There were 15 (24%) individually randomized, 38 (61%) cluster randomized, and 9 (15%) individually randomized group treatment designs; 54 (87%) trials used repeated measures on the same individual and/or cluster over time and 17 (27%) had a multivariate primary outcome (e.g. due to measuring an outcome on both the patient and their caregiver). Of the 38 cluster randomized trials, 16 (42%) did not report sample size calculations accounting for the intracluster correlation and 13 (34%) did not account for intracluster correlation in the analysis. Of the 9 individually randomized group treatment trials, 6 (67%) did not report sample size calculations accounting for intracluster correlation and 8 (89%) did not account for it in the analysis. Of the 54 trials with repeated measurements, 45 (83%) did not report sample size calculations accounting for repeated measurements and 19 (35%) did not utilize at least some of the repeated measures in the analysis. No trials accounted for the multivariate nature of their primary outcomes in sample size calculation; only one did so in the analysis. There is a need and opportunity to improve the design, analysis, and reporting of pragmatic trials in dementia research. Investigators should pay attention to the potential presence of one or more sources of clustering. While methods for longitudinal and cluster randomized trials are well developed, accessible resources and new methods for dealing with multiple sources of clustering are required. Involvement of a statistician with expertise in longitudinal and clustered designs is recommended.

Impact of complex, partially nested clustering in a three-arm individually randomized group treatment trial: A case study with the wHOPE trial.

When participants in individually randomized group treatment trials are treated by multiple clinicians or in multiple group treatment sessions throughout the trial, this induces partially nested clusters which can affect the power of a trial. We investigate this issue in the Whole Health Options and Pain Education trial, a three-arm pragmatic, individually randomized clinical trial. We evaluate whether partial clusters due to multiple visits delivered by different clinicians in the Whole Health Team arm and dynamic participant groups due to changing group leaders and/or participants across treatment sessions during treatment delivery in the Primary Care Group Education arm may impact the power of the trial. We also present a Bayesian approach to estimate the intraclass correlation coefficients. We present statistical models for each treatment arm of Whole Health Options and Pain Education trial in which power is estimated under different intraclass correlation coefficients and mapping matrices between participants and clinicians or treatment sessions. Power calculations are based on pairwise comparisons. In practice, sample size calculations depend on estimates of the intraclass correlation coefficients at the treatment sessions and clinician levels. To accommodate such complexities, we present a Bayesian framework for the estimation of intraclass correlation coefficients under different participant-to-session and participant-to-clinician mapping scenarios. We simulated continuous outcome data based on various clinical scenarios in Whole Health Options and Pain Education trial using a range of intraclass correlation coefficients and mapping matrices and used Gibbs samplers with conjugate priors to obtain posteriors of the intraclass correlation coefficients under those different scenarios. Posterior means and medians and their biases are calculated for the intraclass correlation coefficients to evaluate the operating characteristics of the Bayesian intraclass correlation coefficient estimators. Power for Whole Health Team versus Primary Care Group Education is sensitive to the intraclass correlation coefficient in the Whole Health Team arm. In these two arms, an increased number of clinicians, more evenly distributed workload of clinicians, or more homogeneous treatment group sizes leads to increased power. Our simulation study for the intraclass correlation coefficient estimation indicates that the posterior mean intraclass correlation coefficient estimator has less bias when the true intraclass correlation coefficients are large (i.e. 0.10), but when the intraclass correlation coefficient is small (i.e. 0.01), the posterior median intraclass correlation coefficient estimator is less biased. Knowledge of intraclass correlation coefficients and the structure of clustering are critical to the design of individually randomized group treatment trials with partially nested clusters. We demonstrate that the intraclass correlation coefficient of the Whole Health Team arm can affect power in the Whole Health Options and Pain Education trial. A Bayesian approach provides a flexible procedure for estimating the intraclass correlation coefficients under complex scenarios. More work is needed to educate the research community about the individually randomized group treatment design and encourage publication of intraclass correlation coefficients to help inform future trial designs.

ACTonFood. Acceptance and Commitment Therapy-Based Group Treatment Compared to Cognitive Behavioral Therapy-Based Group Treatment for Weight Loss Maintenance: An Individually Randomized Group Treatment Trial.

The purpose of this Individually Randomized Group Treatment Trial was to compare an Acceptance and Commitment Therapy-based (ACT) group intervention and a Cognitive Behavioral Therapy-based (CBT) group intervention for weight loss maintenance in a sample of adult patients with obesity seeking treatment for weight loss. One hundred and fifty-five adults (BMI: Kg/m2 = 43.8 [6.8]) attending a multidisciplinary rehabilitation program for weight loss were randomized into two conditions: ACT and CBT. Demographical, physical, and clinical data were assessed at the beginning of the program (t0), at discharge (t1), and at 6-month follow-up (t2). The following measures were administered: The Acceptance and Action Questionnaire-II (AAQ-II) and the Clinical Outcome in Routine Evaluation-Outcome Measure (CORE-OM). Generalized linear mixed models were performed to assess differences between groups. Moderation effects for gender and Eating Disorders (ED) have been considered. From baseline to discharge, no significant differences between interventions were found, with the only exception of an improvement in the CORE-OM total score and in the CORE-OM subjective wellbeing subscale for those in the CBT condition. From discharge to follow-up, ACT group participants showed significant results in terms of weight loss maintenance, CORE-OM total score, and CORE-OM and AAQ-II wellbeing, symptoms, and psychological problems subscales. Gender moderated the effects of time and intervention on the CORE-OM subscale reporting the risk for self-harm or harm of others. The presence of an eating disorder moderated the effect of time and intervention on the CORE-OM total score, on the CORE-OM symptoms and psychological problems subscales, and on the AAQ-II. Patients who received the ACT intervention were more likely to achieve a ≥5% weight loss from baseline to follow-up and to maintain the weight loss after discharge. The ACT intervention was thus effective in maintaining weight loss over time.

1503O Clinical and scientific impact of National Cancer Institute: Sponsored clinical trial network group treatment trials

In the U.S., the NCI National Cancer Clinical Trials Network (NCTN) groups have conducted publicly funded cancer research for more than 50 years. A major aim of the groups is to identify effective new treatments for patients with cancer. The impact of all adult network group trials has never been systematically examined.

A group-based mental health intervention for young people living with HIV in Tanzania: results of a pilot individually randomized group treatment trial

BackgroundIncreasing numbers of young people living with HIV (YPLWH) have unaddressed mental health challenges. Such challenges are associated with poor antiretroviral therapy (ART) adherence and high mortality. Few evidence-based mental health interventions exist to improve HIV outcomes among YPLWH.MethodsThis pilot group treatment trial individually randomized YPLWH from two clinical sites in Tanzania, evaluated acceptability, feasibility, and preliminary effectiveness of a mental health intervention, Sauti ya Vijana (SYV; The Voice of Youth), was compared to the local standard-of-care (SOC) for improving ART adherence and virologic suppression. Enrolled YPLWH were 12–24 years of age and responded to mental health and stigma questionnaires, self-reported adherence, objective adherence measures (ART concentration in hair), and HIV RNA at baseline and 6-months (post-intervention). Feasibility and acceptability were evaluated, and potential effectiveness was assessed by comparing outcomes between arms using mixed effects modeling.ResultsBetween June 2016 and July 2017, 128 YPLWH enrolled; 105 were randomized and 93 (55 in SYV) followed-up at 6-months and were thereby included in this analysis. Mean age was 18.1 years; 51% were female; and 84% were HIV-infected perinatally. Attendance to intervention sessions was 86%; 6-month follow-up was 88%, and fidelity to the protocol approached 100%. Exploratory analyses of effectiveness demonstrated self-reported adherence improved by 7.3 percentage points (95% CI: 2.2, 12.3); and the pooled standard deviation for all ART concentration values increased by 0.17 units (95% CI: − 0.52, 0.85) in the SYV arm compared to SOC. Virologic suppression rates (HIV RNA < 400 copies/mL) at baseline were 65% in both arms but increased to 75% in the SYV arm while staying the same in the SOC arm (RR 1.13; 95% CI: 0.94, 1.36).ConclusionsYPLWH often have poor HIV outcomes, making interventions to improve outcomes in this population critical. This pilot trial of the Tanzania-based SYV intervention demonstrated trends towards improvement in ART adherence and virologic outcomes among YPLWH, supporting efforts to scale the intervention into a fully-powered effectiveness trial.Trial registrationClinicalTrials.gov Identifier: NCT02888288. Registered August 9, 2016. Retrospectively registered as first participant enrolled June 16, 2016.

Improving Insomnia in Primary Care Patients a Randomized Controlled Trial of Nurse-Led Group Treatment: A Literature Review

Introduction: Insomnia is generally defined as complaints of poor or unsatisfactory sleep, which can include difficulty initiating sleep, awakening after sleep onset, poor sleep quality, early morning awakenings, short sleep times, short total sleep times and daytime consequences. Chronic insomnia is a common problem in primary health care, affecting 10 - 19% of those seeking primary care.&#x0D; Method: Patient is a randomly selected sample of 165 people and divided into 2 groups, namely 90 treatment groups and 75 control groups in seven routine primary health care in Stockholm County, Sweden between August 2011 and June 2014. The intervention to be given was in the treatment group given the intervention consisting of a group treatment program for insomnia based on the CBT-I technique while the control group was free to undergo insomnia treatment as usual.&#x0D; Result: The formulation of the research problem is to compare how the effect of nurse-led group treatment with the effect of treatment as usual in routine primary health care in Stockholm County, Sweden. In this study, the researcher determined a sample of 165 people who met the research requirements, and divided respondents randomly (single-blinded) consisting of 90 treatment groups and 75 control groups.&#x0D; Conclusion: There was a significant difference between the treatment of insomnia with cognitive therapy and the treatment of insomnia with drugs. So that we can reduce the long-term effects of using drugs to treat insomnia.

Essential Ingredients and Innovations in the Design and Analysis of Group-Randomized Trials.

This article reviews the essential ingredients and innovations in the design and analysis of group-randomized trials. The methods literature for these trials has grown steadily since they were introduced to the biomedical research community in the late 1970s, and we summarize those developments. We review, in addition to the group-randomized trial, methods for two closely related designs, the individually randomized group treatment trial and the stepped-wedge group-randomized trial. After describing the essential ingredients for these designs, we review the most important developments in the evolution of their methods using a new bibliometric tool developed at the National Institutes of Health. We then discuss the questions to be considered when selecting from among these designs or selecting the traditional randomized controlled trial. We close with a review of current methods for the analysis of data from these designs, a case study to illustrate each design, and a brief summary.