Posts

Showing posts with the label Study design

New year, new experiences

Image
I started the year teaching... I had never taught part of an online workshop before. I attended many and may even have thought about it, but I wasn't sure I had anything new to say. It turns out, I kind of did.  I focused on how to best write the methods section of a research paper in the life sciences. To some people, this is the easiest section to write because it does not involve much “story”, it is instead a description of all the steps taken that led to the study’s findings.  A clear methods section impacts editorial evaluation and readers’ understanding. Transparency creates trust and is the key to ensuring the credibility of the research. Reproducibility relies on detail, so never  methods should never be summarized or abbreviate d without giving full details in a discoverable supplemental section. I learned a lot in the last 3 years. Regarding writing, publishing, and science communication. But there are concepts that researchers still have not fully adopted, eit...

Sex influences the heart 💜

Image
Literally, I'm not being romantic or lyrical here. Patients' gender-related characteristics may partly explain traditional sex differences in risk factors for cardiovascular disease (such as for acute coronary syndrome ). The graph below shows that sex and gender are partly independent (which means, not totally separate but also not the same thing). Additionally, individuals with high feminine gender scores were twice as likely to be re-admitted to hospital and to experience worse prognoses following discharge after heart attack. Adapted from Pelletier, Roxanne PhD; Ditto, Blaine PhD; Pilote, Louise MD, MPH, PhD.  A Composite Measure of Gender and Its Association With Risk Factors in Patients With Premature Acute Coronary Syndrome. Psychosomatic Medicine 77(5):p 517-526, June 2015. DOI: 10.1097/PSY.0000000000000186 Now, I'm not saying that men act all tough in the presence of male doctors... but they do. Nor am I saying that birthing mothers feel more at ease to scre...

Reusable methods for Open Science

Image
It's Peer Review Week 2023! This is the second post of this week, so we're discussing how reporting of methodology came to be regarded as an asset to the reproducibility initiative. Stick around and follow daily! If you want to read why the scientific method was developed, check it here . If you want to know why you should care, read on.   Promoting Reusable and Open Methods and Protocols ( PRO-MaP ) is a set of recommendations aimed at improving the reporting of protocols in the life sciences.    I first heard of this initiative through my work at Bio-protocol . This is an online peer-reviewed protocol journal that curates and hosts high quality, free access, step-by-step protocols across the life sciences. Although relatively recent, it's by no means unique . The expansion of protocol sharing led to the establishment of detailed guidelines for preprints, and validation sections were introduced in protocol articles. The detailed features of these protocols, structur...

Living under the ROC

Image
To diagnose a condition, physicians often resort to different tests. The performance of each of these diagnostic methods can be measured using different characteristics: Predictive value is the probability of correctly identifying a subject's condition given the test result. ✅ Youden's J is the likelihood of a positive test result in subjects with the condition versus those without the condition — probability of an informed decision . 👀 Sensitivity is the proportion of people who actually have a target disease that are tested positive ( true positive or detection rate ).📍 A negative result in a test with high sensitivity can be useful for ruling out disease, because it has a lower type II error rate. Specificity is the proportion of people who do not have a target disease that are tested negative ( true negative rate ). The false positive rate (1 − specificity) is the probability of false alarm . 🚫 A positive result in a test with high specificity can be useful...

Reliability

Image
Reliability is the characteristic of a test or method that produces consistent results, which means the test instrument is unlikely to be influenced by external factors. Validity and reliability are used to assess the rigour of research. A study's quality relies on its ability to produce results that are easily interpreted — as such, several researchers conducting the same experiment using the same test on the same group of participants should be able to produce similar results.   How is this evaluated? Internal consistency : a measure of correlation, not causality . The extent to which all the items on a scale measure one construct or the same latent variable. Depending on the type of test, internal consistency may be measured through Cronbach's alpha , Average Inter-Item , Split-Half , or Kuder-Richardson test .   Example: Visual Analog Scales and Likert Scales. This VAS for pain is presented to participants without the numerical scale (see here ).       ...

Biases and bathing suits

Image
It's summer in the northern hemisphere, and I put on a bathing suit today... 😒 How can we tell if we are measuring what we think we are measuring?   From the 1970s , the Body Mass Index (BMI) was adopted by medics as a measure of obesity, but several issues have come to light regarding the use of this tool . As more knowledge has been amassed, the clinical definition of obesity has changed.    Nowadays, the WHO still imparts some face validity to assessing the BMI —because it “looks like” or “appears to” measure what it is intended to measure , although scientists are aware that body fat proportion is a better predictor for the risk of diabetes . 🍕🍎🍔🍓   Correlation between BMI and Body Fat Percentage for Men (NHANES, 1994) For the original study where this graph came from, see here . So, construct validity determines if something “really” measures the construct (in this case, of obesity ), and content validity measures the tool's overall value (in this c...

Validity

Image
The aim of scientific research is to produce generalizable knowledge about the real world. An experiment's validity is established in reference to a specific purpose —the test or technique used may not be valid for different purposes. However, scientists are human and fallible. The  illusion of validity describes our tendency to be overconfident in the accuracy of our judgements, specifically in our interpretations and predictions regarding a given data set.   Temporal validity tests the plausibility of research findings over a given time frame. When conducting the same experiment at key points over a period of time, historical events may affect results.  The most recent example of this is the rise in cancer deaths due to untreated or undiagnosed cancers during the COVID-19 mandatory lockdown.   Population validity evaluates whether the chosen sample or cohort represents the entire population, and also whether the sampling method is acceptable. In evide...

The scientific method: dull, dry, and dead?

Image
I have nightmares about the scientific method… 😵 When it was first taught to me, it seemed dull, dry, and dead. But then, I heard we could blow stuff up … wait… back up… What? I love these toys!   Why are we told that the methodology section in a research paper is the "easiest" to write? If you have done the experiments, and repeated them, you know how to do them. But would you be able to teach them? 😯 Explain them to your colleague in the lab? 😔 The methodology section of the research paper is the first that peer reviewers will prod and test. For them, it's the most important. 😧 Why?   If the design of a study is not sound,  then you can not trust the results,  discussion, or conclusions.     So, the main characteristics of adequate methodology are: Validity   Make sure your technique enables you to measure what you intend to measure. This seems trivial... but how many times did you run a Western blot without a loading control when you were first...