cluster randomized trial
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Food Policy ◽  
2022 ◽  
Vol 107 ◽  
pp. 102211
Author(s):  
Sharna Si Ying Seah ◽  
Rob M. van Dam ◽  
Bee Choo Tai ◽  
Zoey Tay ◽  
May C. Wang ◽  
...  

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Gloria D. Sclar ◽  
Valerie Bauza ◽  
Hans-Joachim Mosler ◽  
Alokananda Bisoyi ◽  
Howard H. Chang ◽  
...  

Abstract Background Poor child feces management (CFM) is believed to be an important source of exposure to enteric pathogens that contribute to a large disease burden in low-income settings. While access to sanitation facilities is improving, national surveys indicate that even households with latrines often do not safely dispose of their child’s feces. Working with caregivers in rural Odisha, India, we co-developed an intervention aimed at improving safe disposal of child feces and encouraging child latrine use at an earlier age. We describe the rationale for the intervention and summarize the protocol for a cluster randomized trial (CRT) to evaluate its effectiveness at changing CFM practices. Methods The intervention consists of six behavior change strategies together with hardware provision: wash basin and bucket with lid to aid safe management of soiled nappies and a novel latrine training mat to aid safe disposal and latrine training. The intervention will be offered at the village level to interested caregivers of children < 5 years of age by a community-based organization. Following a baseline survey, 74 villages were randomly allocated to either intervention or control arm. The primary outcome is caregiver reported safe disposal of child feces after last defecation, either by the caregiver disposing of the child’s feces into the latrine or the child using the latrine, measured approximately four to six months following intervention delivery. Secondary outcomes include fecal contamination of household drinking water and the childs’ hands. A process evaluation will also be conducted to assess intervention fidelity and reach, and explore implementer and participant feedback. Discussion This study addresses a crucial knowledge gap in sanitation by developing a scalable intervention to improve safe management of child feces. The behavior change strategies were designed following the Risks, Attitudes, Norms, Abilities and Self-Regulation (RANAS) approach, which has shown to be effective for other environmental behavior change interventions in low-income settings. The latrine training mat hardware is a novel design developed cooperatively and manufactured locally. The evaluation follows a rigorous CRT study design assessing the impact of the intervention on CFM behavior change, as well as fecal contamination of two sources of potential exposure. Trial registration This trial is registered at ISRCTN: ISRCTN15831099.


Science ◽  
2022 ◽  
Vol 375 (6577) ◽  
Author(s):  
Jason Abaluck ◽  
Laura H. Kwong ◽  
Ashley Styczynski ◽  
Ashraful Haque ◽  
Md. Alamgir Kabir ◽  
...  

Persuading people to mask Even in places where it is obligatory, people tend to optimistically overstate their compliance for mask wearing. How then can we persuade more of the population at large to act for the greater good? Abaluck et al . undertook a large, cluster-randomized trial in Bangladesh involving hundreds of thousands of people (although mostly men) over a 2-month period. Colored masks of various construction were handed out free of charge, accompanied by a range of mask-wearing promotional activities inspired by marketing research. Using a grassroots network of volunteers to help conduct the study and gather data, the authors discovered that mask wearing averaged 13.3% in villages where no interventions took place but increased to 42.3% in villages where in-person interventions were introduced. Villages where in-person reinforcement of mask wearing occurred also showed a reduction in reporting COVID-like illness, particularly in high-risk individuals. —CA


Trials ◽  
2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Krithika Suresh ◽  
Jodi Summers Holtrop ◽  
L. Miriam Dickinson ◽  
Emileigh Willems ◽  
Peter C. Smith ◽  
...  

Abstract Background Despite the overwhelming prevalence and health implications of obesity, it is rarely adequately addressed in a health care setting. PATHWEIGH is a pragmatic approach to weight management that uses tools built into the electronic medical record to overcome barriers and guide care. Implementation strategies are employed to facilitate adoption and use of the PATHWEIGH tools and processes. The current study will compare the effectiveness of PATHWEIGH versus standard of care (SOC) on patient weight loss in primary care and explore factors for its successful implementation. Methods A stepped wedge cluster randomized trial design will be used within an effectiveness-implementation hybrid study. Adult patient weight loss and weight loss maintenance will be compared in PATHWEIGH versus SOC in 57 family and internal medicine clinics in a large health system in Colorado, USA. Effectiveness will be evaluated using generalized linear mixed models to determine statistical differences in weight loss and weight loss maintenance at 6, 12, and 18 months. Patient-, provider-, and clinic-level predictors will be identified using mediator and moderator analyses. Conceptually guided by the Practical, Robust, Implementation and Sustainability Model (PRISM), a mixed methods approach including quantitative (practice surveys, use tracking) and qualitative (interviews, observations) data collection will be used to determine factors impeding and facilitating adoption, implementation, and maintenance of PATHWEIGH and evaluate specified implementation strategies. A cost analysis of the practice and system costs and resources required by PATHWEIGH relative to the reimbursement collected will be performed. Discussion The effectiveness and implementation of PATHWEIGH, and their interrelatedness, for patient weight loss are collectively the focus of the current trial. Findings from this study are expected to serve as a blueprint for available and effective weight management in primary care medical practice. Trial registration ClinicalTrials.govNCT04678752. Registered on December 21, 2020.


2022 ◽  
pp. 174077452110634
Author(s):  
Philip M Westgate ◽  
Debbie M Cheng ◽  
Daniel J Feaster ◽  
Soledad Fernández ◽  
Abigail B Shoben ◽  
...  

Background/aims This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression. Methods Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective. Results The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression. Conclusion Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare.


2022 ◽  
pp. 174077452110634
Author(s):  
David M Murray

Background. 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. Methods. 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. Results. 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. Conclusions. 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.


Author(s):  
Ruth Mächler ◽  
Noemi Sturm ◽  
Eckhard Frick ◽  
Friederike Schalhorn ◽  
Regina Stolz ◽  
...  

Background: The “Holistic Care Program for Elderly Patients to Integrate Spiritual Needs, Social Activity and Self-Care into Disease Management in Primary Care” (HoPES3) examines the implementation of a spiritual history (SH) as part of a multifaceted intervention in German general practices. While the effectiveness of the interventions was evaluated in a cluster-randomized trial, this article investigates the patients’ views concerning the acceptability of the SH and its effects. Methods: A mixed-methods study was conducted in which 133 patients of the intervention group filled in a standardized questionnaire after the intervention. Later, 29 of these patients took part in qualitative semi-standardized interviews. Results: According to the survey, 63% (n = 77) of patients found the SH helpful. In the interviews, however, many indicated that they either kept the conversation brief or declined the offer to talk about spirituality. Contents of longer conversations referred to difficult life events, personal sources of strength, and experiences with religious institutions. Many patients who had a longer conversation about spirituality reported that their relationship with their general practitioner (GP) had improved. Almost all patients recommended integrating a personal conversation of this kind into primary care. Conclusions: The SH seems to be a possible ‘door opener’ for a trusting doctor-patient relationship, which can then be built upon.


2022 ◽  
Author(s):  
Chao-Han Lai ◽  
Kai-Wen Li ◽  
Fang-Wen Hu ◽  
Pei-Fang Su ◽  
I-Lin Hsu ◽  
...  

BACKGROUND Multidisciplinary rounds (MDRs) are scheduled, patient-focused communication mechanisms among multidisciplinary providers in the intensive care unit (ICU). OBJECTIVE i-Dashboard is a custom-developed visualization dashboard that supports 1) key information retrieval and reorganization, 2) time-series data and 3) display on large touchscreens during MDRs. The present study aimed to evaluate the performance, including the efficiency of pre-rounding data gathering, communication accuracy and information exchange, and clinical satisfaction of integrating i-Dashboard as a platform to facilitate MDRs. METHODS A cluster randomized trial was performed in two surgical ICUs at a university hospital. Study participants included all multidisciplinary care team members. The performances and clinical satisfaction of i-Dashboard during MDRs were compared with those of the established electronic medical record (EMR) through direct observation and questionnaire survey. RESULTS Between April 26, 2021, and July 18, 2021, 78 and 91 MDRs were performed with the established EMR and i-Dashboard, respectively. For pre-rounding data gathering, the median (interquartile range [IQR]) time was 10.4 (9.1-11.8) and 4.6 (3.5-5.8) minutes using the established EMR and i-Dashboard (P<.001), respectively. During MDRs, data misrepresentations were significantly less frequent with i-Dashboard (median [IQR]: 0 [0-0]) than with the established EMR (4 [3-5]; P<.001). Also, effective recommendations were significantly more frequent with i-Dashboard than with the established EMR (P<.001). The questionnaire results revealed that participants favored using i-Dashboard in association with the enhancement of care plan development and team participation during MDRs. CONCLUSIONS i-Dashboard increases the efficiency in data gathering. Displaying i-Dashboard on large touchscreens in MDRs may enhance communication accuracy, information exchange and clinical satisfaction. The design concepts of i-Dashboard may help develop visualization dashboards that are more applicable for ICU MDRs. CLINICALTRIAL ClinicalTrials.gov NCT04845698; https://clinicaltrials.gov/ct2/show/NCT04845698


2022 ◽  
Vol 226 (1) ◽  
pp. S777
Author(s):  
Kjersti M. Aagaard ◽  
Gregory C. Valentine ◽  
Kathleen M. Antony ◽  
Haleh Sangi-Haghpeykar ◽  
Rose Chirwa ◽  
...  

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