scholarly journals Randomized Control Trials with Schools: Handling Real-World Practicalities and Problems

2022 ◽  
Author(s):  
Tanya Maria Paes ◽  
Michelle Renee Ellefson

There is a need for more evidence-based research in education and research involving the use of randomized control trials (RCTs) to examine the efficacy of interventions. However, the difficulty of conducting interventional research in educational settings is often less acknowledged. This article provides practical examples of the issues encountered when implementing a cognitive science informed intervention and the solutions that were successfully implemented. This article will also highlight the importance of designing a multifaceted intervention while considering the cost of the intervention itself, especially when working with hard-to-reach families. It is helpful to make use of existing classroom resources in the intervention to lower costs. Additionally, being consistent and attentive to the developmental stage of the children and supporting parental engagement are two aspects that are crucial to the implementation of the intervention. Researchers would benefit from conducting workshops and public engagement events and can use these opportunities to provide practical strategies about how to support the development of children’s skills in the home environment. In-person interactions are key as parents can ask any questions that they may have, and it can help to dispel any mistrust that they may have with the research process. The article also provides suggestions for building the researcher-practitioner relationship from study onset, including being flexible and accommodating towards the changes in the school context and communicating effectively with teachers. Lastly, the article outlines the benefit of using scaffolding, positive reinforcement, and play-based learning over the course of the intervention to support child outcomes.

2008 ◽  
Vol 28 (3_suppl) ◽  
pp. 76-80
Author(s):  
Wai Kei Lo

The target of renal anemia correction with erythropoietin stimulating agents (ESAs) has been traditionally set at a hemoglobin (Hb) level of 11 – 12 g/dL. However, a trend has arisen of progressively increasing the Hb level to beyond 12 g/dL. Recent randomized control trials (RCTs) on correction of renal anemia in chronic kidney disease patients found that normalization of anemia to above 13 g/dL was associated with negative outcome parameters, echoing a previous RCT that showed increased death and myocardial infarction risk after normalization of hemoglobin level in hemodialysis patients. The latest consensus is to limit Hb to a level not exceeding 13 g/dL during renal anemia correction with ESAs. Currently, there are three ESAs available commercially. The choice of ESA should consider safety of subcutaneous administration, cost-effectiveness, and dosing frequency, all of which may affect compliance with ESA administration. Early identification of, and an early search for the causes of hyporesponsiveness to, ESAs is needed to avoid unnecessary escalation in the dose of ESAs. These approaches will help to improve the cost-effectiveness of ESA therapy and permit early detection of hidden problems. The current definitions of hyporesponsiveness are far too stringent and should be reviewed.


2021 ◽  
pp. 174749302110132
Author(s):  
Ahmed Mohamed ◽  
Nida Fatima ◽  
Ashfaq Shuaib ◽  
Maher Saqqur

Introduction There is controversy if direct to comprehensive center “mothership” (MS) or stopping at primary center for thrombolysis before transfer to comprehensive center “drip-and- ship” (DS) are best models of treatment of acute stroke. In this study, we compare MS and DS models to evaluate the best option of functional outcome. Methods Studies between 1990 and 2020 were extracted from online electronic databases. We compared the clinical outcomes, critical time measurements, functional independence and mortality were then compared. Results A total of 7,824 patients’ data were retrieved from 13 publications (3 randomized control trials and 10 retrospective ones). 4,639 (59.3%) patients were treated under MS model and 3,185 (40.7%) followed the DS model with mean age of 70.01±3.58 vs. 69.03±3.36; p< 0 .001, respectively. The National Institute Health Stroke Scale was 15.57±3.83 for the MS and 15.72±2.99 for the DS model (p=<0.001). The mean symptoms onset-to-puncture time was significantly shorter in the MS group compared to the DS (159.69 min vs. 223.89 min; p=<0.001, respectively). Moreover, the collected data indicated no significant difference between symptom’s onset to intravenous (IV) thrombolysis time and stroke onset-to-successful recanalization time (p=0.205 and p=<0.001, respectively). Patients had significantly worse functional outcome [modified rankin score (mRS)] (3-6) at 90-days in the DS model [Odds Ratio (OR): 1.47, 95% Confidence Interval (CI): 1.13-1.92, p<0.004] and 1.49-folds higher likelihood of symptomatic intracerebral hemorrhage (OR: 1.49, 95%CI: 1.22-1.81, p<0.0001) compared to MS. However, there were no statistically significant difference in terms of mortality (OR: 1.16, 95%CI: 0.87-1.55, p=0.32) and successful recanalization (OR: 1.12, 95%CI: 0.76-1.65, p=0.56) between the two models of care. Conclusion Patients in the MS model have significantly improved functional independence and recovery. Further studies are needed as the data from prospectively randomized studies is not of sufficient quality to make definite recommendations.


2015 ◽  
Vol 130 (3) ◽  
pp. 1117-1165 ◽  
Author(s):  
Hunt Allcott

Abstract “Site selection bias” can occur when the probability that a program is adopted or evaluated is correlated with its impacts. I test for site selection bias in the context of the Opower energy conservation programs, using 111 randomized control trials involving 8.6 million households across the United States. Predictions based on rich microdata from the first 10 replications substantially overstate efficacy in the next 101 sites. Several mechanisms caused this positive selection. For example, utilities in more environmentalist areas are more likely to adopt the program, and their customers are more responsive to the treatment. Also, because utilities initially target treatment at higher-usage consumer subpopulations, efficacy drops as the program is later expanded. The results illustrate how program evaluations can still give systematically biased out-of-sample predictions, even after many replications.


Sign in / Sign up

Export Citation Format

Share Document