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Peer reviewed
Direct linkAndrija Babic; Ognjen Barcot; Tomislav Viskovic; Frano Šaric; Aleksandar Kirkovski; Ivana Barun; Zvonimir Križanac; Roshan Arjun Ananda; Yuli Viviana Fuentes Barreiro; Narges Malih; Daiana Anne-Marie Dimcea; Josipa Ordulj; Ishanka Weerasekara; Matteo Spezia; Marija Franka Žuljevic; Jelena Šuto; Luca Tancredi; Andela Pijuk; Susanna Sammali; Veronica Iascone; Thilo Groote; Tina Poklepovic Pericic; Livia Puljak – Research Synthesis Methods, 2024
Risk of bias (RoB) assessment is essential to the systematic review methodology. The new version of the Cochrane RoB tool for randomized trials (RoB 2) was published in 2019 to address limitations identified since the first version of the tool was published in 2008 and to increase the reliability of assessments. This study analyzed the frequency…
Descriptors: Risk, Bias, Use Studies, Meta Analysis
Charlotte Z. Mann; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2025
Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…
Descriptors: Causal Models, Statistical Analysis, Privacy, Risk
Yuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
Konstantina Chalkou; Tasnim Hamza; Pascal Benkert; Jens Kuhle; Chiara Zecca; Gabrielle Simoneau; Fabio Pellegrini; Andrea Manca; Matthias Egger; Georgia Salanti – Research Synthesis Methods, 2024
Some patients benefit from a treatment while others may do so less or do not benefit at all. We have previously developed a two-stage network meta-regression prediction model that synthesized randomized trials and evaluates how treatment effects vary across patient characteristics. In this article, we extended this model to combine different…
Descriptors: Medical Research, Outcomes of Treatment, Risk, Randomized Controlled Trials
Brenda Jones Harden; Tiffany L. Martoccio; Lisa J. Berlin – Prevention Science, 2025
Although there is robust evidence of the benefits of attachment-based parenting interventions, limited research has examined their impact on dyadic mutuality and toddler behavior problems. Given the central question in prevention research of what works for whom, and the documented relation of maternal psychological risk to parenting and…
Descriptors: Mothers, Psychological Patterns, Risk, Attachment Behavior
Charles Weijer – Research Ethics, 2024
The COVID-19 pandemic touched off an unprecedented search for vaccines and treatments. Without question, the development of vaccines to prevent COVID-19 was an enormous scientific accomplishment. Further, the RECOVERY and Solidarity trials identified effective treatments for COVID-19. But all was not success. The urgent need for COVID-19…
Descriptors: COVID-19, Pandemics, Immunization Programs, Research and Development
Joseph Murray; Rafaela Costa Martins; Melanie Greenland; Suélen Cruz; Elisa Altafim; Adriane Xavier Arteche; Peter J. Cooper; Marlos Rodrigues Domingues; Andrea Gonzalez; Adriana Kramer Fiala Machado; Lynne Murray; Isabel Oliveira; Iná Santos; Tâmara Biolo Soares; Luciana Tovo-Rodrigues; Merryn Voysey – Prevention Science, 2024
Violence is a major public health problem globally, with the highest rates in low- and middle-income countries (LMICs) in the Americas and southern Africa. Parenting programmes in high-income countries can diminish risk for violence, by reducing risk factors such as child aggression and harsh parenting, and increasing protective factors such as…
Descriptors: Outcomes of Education, Program Effectiveness, Parent Education, Child Behavior
Yao, Minghong; Wang, Yuning; Ren, Yan; Jia, Yulong; Zou, Kang; Li, Ling; Sun, Xin – Research Synthesis Methods, 2023
Rare events meta-analyses of randomized controlled trials (RCTs) are often underpowered because the outcomes are infrequent. Real-world evidence (RWE) from non-randomized studies may provide valuable complementary evidence about the effects of rare events, and there is growing interest in including such evidence in the decision-making process.…
Descriptors: Evidence, Meta Analysis, Randomized Controlled Trials, Decision Making
Download full textUK Department for Education, 2022
At every stage since the start of the pandemic, decisions across education and childcare have been informed by the scientific and medical evidence -- both on the risks of coronavirus (COVID-19) infection, transmission and illness, and on the known risks to children and young people not attending education settings -- balancing public health and…
Descriptors: Evidence, COVID-19, Pandemics, Foreign Countries
Nejstgaard, Camilla Hansen; Lundh, Andreas; Abdi, Suhayb; Clayton, Gemma; Gelle, Mustafe Hassan Adan; Laursen, David Ruben Teindl; Olorisade, Babatunde Kazeem; Savovic, Jelena; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2022
Randomised trials are often funded by commercial companies and methodological studies support a widely held suspicion that commercial funding may influence trial results and conclusions. However, these studies often have a risk of confounding and reporting bias. The risk of confounding is markedly reduced in meta-epidemiological studies that…
Descriptors: Medical Research, Randomized Controlled Trials, Corporations, Financial Support
Held, Leonhard; Matthews, Robert; Ott, Manuela; Pawel, Samuel – Research Synthesis Methods, 2022
It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects…
Descriptors: Bayesian Statistics, Statistical Inference, Hypothesis Testing, Credibility
Kiani Asiabar, Azita; Amin Shokravi, Farkhondeh; Hajifaraji, Majid; Zayeri, Farid – Health Education Research, 2018
Gaining weight above the Institute of Medicine recommended range contributes to the development of obesity, which increases risk for diseases. We evaluated the effectiveness of an educational program with the spouse's participation on the optimal gestational weight gain (GWG) in pregnancy. We conducted a randomized controlled trial on 128…
Descriptors: Foreign Countries, Experimental Groups, Control Groups, Intervention
Burke, Kylie; Dittman, Cassandra K.; Forbes, Elana J.; Eggins, Elizabeth – Campbell Systematic Reviews, 2021
The primary objective of the proposed systematic review is to answer the following research question: do parenting programmes for parents of adolescents impact adolescent mental health outcomes, positive development and the parent-adolescent relationship? This will be achieved by systematically searching for and synthesising the extant evaluation…
Descriptors: Randomized Controlled Trials, Evidence Based Practice, Parent Education, Parenting Skills
Hasegawa, Raiden B.; Deshpande, Sameer K.; Small, Dylan S.; Rosenbaum, Paul R. – Journal of Educational and Behavioral Statistics, 2020
Causal effects are commonly defined as comparisons of the potential outcomes under treatment and control, but this definition is threatened by the possibility that either the treatment or the control condition is not well defined, existing instead in more than one version. This is often a real possibility in nonexperimental or observational…
Descriptors: Causal Models, Inferences, Randomized Controlled Trials, Experimental Groups
Armijo-Olivo, Susan; Craig, Rodger; Campbell, Sandy – Research Synthesis Methods, 2020
Background: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can decrease the time and burden by automating the process, but evidence validating such software is…
Descriptors: Comparative Analysis, Computer Software, Decision Making, Randomized Controlled Trials
