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A MedED LECTURE ICA 3: Data Management Jack Tighe BSc (Hons) Disclaimer There are many ways to tackle ICA 3, this is not a definitive guide and my advice may differ from others. Please consult your course lead for any essential queries about the ICAs.Table of Contents 01 What is it? 02 Main Body Abstract Lay Summary 03 0401. What is it?What is it? Writing up the findings from the data you collected in your lab report in the format of an academic paper, with abstract and lay summary. Specifications Word limit: Grade contribution: • Main Body: 1,500 words • Abstract: 350 words • 70% of Module one • 21% of Overall BSc • Lay Summary: 500 words Figures and Tables • ≤7 figures/tables Referencing: • No reference limit 02 Main BodyMain Body How you submit How you write Introduction Results Methods Methods Results Discussion Discussion Introduction Results Quantitative = Measures of value are expressed as numbers Paired = Same population before and after intervention Parametric = Normally distributed Results Step 1: Is your data parametric or non-parametric? How? 1. Visual inspection (Not recommended) 2. Kolmogrov-Smirnov Test (N ≥50) 3. Shapiro-Wilk Test (N <50) e.g. P<0.05 = Data is significantly different from normal distribution Therefore, data is Non-Parametric Step 2: Perform appropriate test according to statistical tree P<0.05 = significant difference between cohorts Parametric data = Mean ±SEM Non-Parametric data = Median ±IQR Results Step 3: Present your data as a graph Parametric data: Bar chart Non-Parametric data: Box and Whisker Plot ALWAYS include variance measure (SEM or IQR) DO NOT exclude outliers Present statistical difference using lines with * denoting P<0.05 Y-Axis must be from 0.0-1.0 if values are a proportion (or 0.0%-100.0%) Axis needs to be labelled with appropriate units Figure legend should allow the graph to be interpreted in ISOLATION Results Can anyone spot any issues with the graph on the right? Why did they use a lower case N? Issues: - Not many, this is a good example - Could have stated what type of graph this is (simple bar chart) - Should have stated what LH stood for in legend Lower case n = data is from the same person/subject Upper case N = data is from multiple people/subjects Results Results Figures: Select which figures clearly demonstrate your results Structure your findings in a logical and clear way Results Text DESCRIBE what is observed within the results ONLY state that something has “increased” or “decreased” if it is statistically significant – otherwise use “rose” or “fell” State exact averages from your data WITH variance measurements Results Statistical Software Packages Available through Imperial Free to use GraphPad Prism SPSS STATA (Free 30 day trial) R Studio Methodolgy Main Sections 1. Subject/Patient/Sample 2. Dependent variables 3. Statistical Analysis Methodolgy (1) Subject/Patient/Sample (2) Dependent Variable Describe your subject: Describe how you measured the effect of your - Relevant PMH and comorbidities (if intervention: applicable) - Describe how you measured changes following - Exclusion/inclusion criteria your intervention - Previous investigations findings - What reagents were used - Independent variable - Are there any known methodological standards? - Post-intervention changes - Magnification? Number of fields? - Equipment used to measure the effect?Methodolgy (4) Statistical Analysis Describe how you performed your analysis: - Normality test - Statistical test used - Alpha value (P-value) used (0.05) - Statistical software used - What did you do with anomalous data Discussion Overall - Put your results into context - Compare your study to wider literature and explain any differences between your results, if any - Explain why the results you have observed may have occurred - Explore how any confounders may have affected the results - Identify any limitations present in your study and how they may be addressed in future studies - Conclusion Discussion Example This study found that sperm morphology improved following weight loss sufficient enough to reduce the patient’s BMI from 36 to 28. Given the deleterious effect reactive oxidative species (ROS) have on spermatogenesis, and the increased levels of ROS in obese males, it is potentially unsurprising sperm parameters improved post-weight loss(ref).This is supported by a prospective cohort study by Beasley et al. which found that in males who lost greater than ten kilograms in one year, experienced a 32%(N=5,678) increase in normal sperm morphology(ref). However, whilst it is promising semen parameters have improved following this inexpensive intervention, future studies should examine the impact weight loss has on live birth rates in couples with male obesity to evaluate its direct impact on fertility outcomes. Introduction Key Points Nothing “new” should be discussed that isn’t already mentioned here You are setting the scene for your narrative – hence why it is important to know how it ends! Probably very reference heavy and difficult to write – this is normal! Introduction 1 Paragraph NB: You want to quote actual - What is the condition or problem? statistics throughout your intro - How much of a problem is it? - Why are we looking at this specific issue? Other paragraphs - Discuss concepts you want to touch upon later in the discussion - Explain potential reasons why this condition or problem may be occurring - Highlight why your intervention may (theoretically) produce a desired change Final Paragraph - Aims - Hypothesis (1 line)Top Tips Think of your “story” Keep your sentences detailed BUT succinct, clear and effective Use your feedback and tips from the previous ICA1 assessment03 Abstract Abstract Intro – Brief background, pathophysiology, aim and hypothesis (include some pertinent stats) Methodology – keep it short and simple – what happened, subject, measurements, statistical analysis Results – Report your findings including averages ± (variance stat) with (P-Value) Discussion – Much shorter, include: - Interpretation - Strengths - Limitations - Conclusion (significance) - Future research04 Lay Summary Lay Summary Overall - Keep it simple – like really simple - Avoid jargon like the plague - Explain any terminology (motility/morphology) or use a more lay-man term - Classic intro, methods etc. structure less relevant here - Want to tell a story which is engaging and succinct - Rough structure: context, strategy, results, discussion, significance - Avoid using numbers - Discussion and significance: What do your findings mean? What could have affected the findings? Implications of the research and future direction - Don’t simplify by overstating your findings – still keep using may, possibly, suggest etc. - Keep it conversational, but still formal (don’t use “but” instead of “however”), imagine you are writing a newspaper article - Get someone with NO medical knowledge to read through your summary and identify any areas of confusionThank You! Do you have any questions? JT5318@ic.ac.uk CREDITS: This presentation template was created by Slidesgo, including icons by Flaticon, infographics & images by Freepik Please keep this slide for attribution