Avicenna Medical & Research Initiative’s Post

🧩 Harnessing Qualitative Research with Implementation Science Combining qualitative research with implementation science frameworks like CFIR and RE-AIM enhances our ability to create impactful, contextually relevant health interventions. This synergy drives meaningful change in public health related research by bridging the gap between research and practice. And it can be use to open for evaluations in especially in health economics, nutrition and allied health sciences. This paper was very useful for me as a PhD student to open my eyes and thinking about implementing my research project. #QualitativeResearch #ImplementationScience #PublicHealth #CFIR #RE_AIM

I wanted to share an overview of Clinical research study designs, highlighting their importance in evaluating interventions and health outcomes. These designs are play crucial role in interpreting research findings and making informed decisions. The Randomized Controlled Trial (RCT) is the gold standard, where participants are randomly assigned to treatment or control groups. Cohort Studies observe groups over time to study exposure effects. Case-Control Studies compare individuals with a condition to those without, identifying potential risk factors. Cross-Sectional Studies provide a snapshot of a population at one point, showing associations but not causality. Not but not least systematic reviews and meta-analysis combine data from multiple studies to draw broader conclusions. Choosing the right design depends on the research question and objectives, each offering unique insights into clinical questions. Thank you for joining me in my journey of Learning, Growing, Sharing. #Studydesigns #Clinicalresearch #RCT #Cohortstudy #Goldstandardstudy #Metanalysis

What is patient-centered outcomes research? How does the research process work? How can I be an effective partner on a research study? Explore PCORI's online and on-demand training, Research Fundamentals, to answer these questions and more. https://pcori.me/30VD4rn

The Grading of Recommendations, Assessment, Development, and Evaluation (#GRADE) is a systematic approach to assess the #quality of #evidence and strength of recommendations in #healthcare #research. GRADE focuses on five key considerations: study design, risk of bias, inconsistency, indirectness, and imprecision. These factors collectively contribute to the overall quality of evidence for a specific outcome. ➡️Study design: GRADE assigns higher confidence to well-designed #randomized controlled trials (RCTs) and lowers confidence for observational studies. Recognizing the #hierarchy of evidence aids in the critical appraisal of studies. ➡️Risk of bias: Rigorous evaluation of study quality is fundamental. GRADE assesses the risk of bias in individual studies, considering factors such as randomization, blinding, and allocation concealment. High-risk studies may downgrade the overall evidence quality. ➡️Inconsistency: Consistency across study results enhances confidence. GRADE evaluates the consistency of findings among studies. If substantial heterogeneity exists, confidence in the evidence may be downgraded. In summary, GRADE offers a robust framework for systematically assessing evidence quality and making transparent recommendations. By using GRADE, you can enhance the reliability of clinical decision-making, ultimately supporting evidence-based practice. Comment here if you have already used GRADE in any work! ♻️ Repost this to help others! Join in waitlist: https://lnkd.in/d8xn9UNG

📌 Exploring the Power of Cluster Randomized Trials (CRTs) in clinical research design 📍 Cluster randomized trials (CRTs) are a design that randomizes clusters, rather than individuals, to intervention arms. 📍 The design is used because the intervention is at the cluster level, such as behavioral group therapy, or due to potential contamination between participants, or because of ethical or logistic considerations. 📍 Clusters may be households, clinics, schools or towns, and individuals within clusters are usually correlated, thereby violating the independence assumption of common statistical methods. 📍 The data from each of the clusters is summarized by a single value, such as the mean (thereby removing the issue of intra-cluster correlation). 📍 For a small number of clusters (< 40 total) the recommendation is to use a cluster-level analysis, particularly if unweighted generalized estimating equations are used, as type I error can be severely inflated otherwise. 📍 The intracluster correlation (ICC), defined as the ratio of the between-cluster variance to the total variance, is the measure of this non-independence. 📍 CRTs are increasingly being used as they are a good design for comparative effectiveness research and pragmatic trials. 📍 As CRTs continue to shape the future of research, understanding their design and analysis is crucial for accurate and reliable results. 📍 Are you using CRTs in your research? Share your experiences below! Thank you for taking the time to read the post.   If you like it, please share, repost, and follow for more insightful posts. #Clinicaltrials #Researchdesign #Data #Healthcare #Results #Analysis #Design #Clusters #Intervention #Participants #Research #Trail

Understanding time series study in social and socio-environmental disciplines is of essence in contemporary research. Hereunder, a summary is provided on longitudinal study. LONGITUDINAL STUDY Longitudinal studies are based on research methods where data are collected from the same or different subjects or groups over a period of time. They allow researchers to observe changes or developments in the respondents or participants (subjects of investigation) about their lives, behaviours and/or conditions. These studies are valuable for understanding how phenomena evolve over time and for identifying causal relationships. Types of Longitudinal Study based on Participants Recruitment 1. Panel longitudinal study: The same group of individuals is repeatedly studied over time. Researchers collect data from the same individuals at multiple points in time to track changes or developments. 2. Cohort longitudinal study: Different groups of individuals who share a common characteristic or experience, such as being born in the same year or having the same condition. Each cohort is followed over time to observe how they change or develop. Types of Longitudinal Study based on Time Frame 1. Retrospective longitudinal study: Looks back in time to examine data or events that have already occurred. Researchers collect data from past records or participants' memories to reconstruct the events and behaviours that happened over time. Researchers look back at past exposures (such as environmental factors, lifestyle choices, or medical treatments) and outcomes (such as disease incidence, health status, or behavioral changes) to identify potential associations or causal relationships. 2. Prospective longitudinal study: Starts in the present and follows participants into the future. Researchers collect data over time as events unfold, allowing them to observe changes or developments as they happen. Researchers follow participants forward in time, collecting data on exposures and tracking outcomes as they occur. This allows for a more direct examination of the relationship between exposures and outcomes as they unfold over time. Image Source: https://lnkd.in/g3Ck2Fwn

You don't have to be a scientist with an MD or PhD to shape and guide health research studies. Anyone can become empowered to engage in research through Research Fundamentals, a free, online, easy-to-use resource offered by Patient-Centered Outcomes Research Institute (PCORI). Check it out! #ClinicalResearch #HealthResearch #CER #PatientCentered

I am thrilled to announce that our new article “PQR cascade: A system proposed for research prioritization in applied sciences” has been published in Journal of Education and Health Promotion. Considering the management problems and the limitation of research resources to deal with health problems in developing countries, in this article we proposed a method that helps to allocate limited resources in an effective way and reduce the burden of these countries’ problems by emphasizing and identifying problems as priority. The outcome was a method we named as PQR model: P stands for Problem; Q for Question; and R for Research. https://lnkd.in/dyQY_Mxv

▪️Let’s be real—research moves fast, and to stay ahead, you need both efficient practices and strong evidence to back your work. That’s where clinical patient databases (both national patient repositories and institutional data bases) come in. ▪️Clinical patient databases provide real-world data to test ideas, validate results, and build credibility, which is one of the determining aspects when applying for grants/ funding and even to land into a competitive position such as a research position, a postdoc or a #PhD. ▪️If you don’t have a few strong research papers, practically it’s difficult to achieve these goals, though exceptions exist. ▪️From my own experience, cohort studies and clinical trials are great for reliability—but they take forever. Retrospective studies, on the other hand, are much efficient, equally trusted by peers and great for generating hypothesis, as long as you’re using reliable data sources. ▪️I’ve put together a list of reliable U.S. databases that are great for getting started with clinical research. ▪️Share this list with others who might find it useful and follow for more useful insights. Thanks 😊 #Research #ClinicalData #Funding #Innovation

👌 As clinical researchers, we are constantly striving to make meaningful discoveries that can transform patient care. But how can we ensure that our studies are designed to truly capture the insights we seek? The answer lies in pre-study power analysis; a pivotal step in the research design process that is often overlooked. 👉 Why is power analysis indispensable? Power analysis allows us to determine the minimum sample size required to detect a specified effect size with a given level of confidence. This is not just a statistical nicety it's a cornerstone of robust research methodology. ✅ Here's why: ➡️ Efficiency: It ensures that resources are used judiciously, avoiding the pitfalls of under or over-recruitment. ➡️ Ethical Considerations: It respects participant contribution by ensuring their involvement has the potential to contribute to significant findings. ➡️ Validity: It enhances the likelihood that your study will yield conclusive results, bolstering the credibility and impact of your work. 🌟 Follow our FAQ to learn more about how power analysis can be the difference between a study that fades into obscurity and one that stands out in the field of medical science. 🤝 Join the conversation and share your thoughts on the importance of power analysis in clinical research. #clinicalresearch #poweranalysis #samplesize #researchmethodology #MARS #biostatistics #MARS_Global