029: How to Read a Science Paper

Mastering Nutrition Episode 29

Mar 11, 2017

∙ Paid

Introduction

In this episode, I explain how to come up with a good question, obtain the background information you need, find research, obtain full texts, organize them, read the different sections of a paper to get the right kind of value out of it, and critically analyze the study design. If you’re a beginner, this is really designed for you. If you’re more advanced, you’ll enjoy the specific examples I give of problems interpreting research studies.

Show Notes

In this episode, you will find all of the following and more:

0:06:15 How to develop a good question
0:06:17 How to use Pubmed and Google Scholar
0:08:44 Why and how to use MeSH terms (medical subject headings)
0:13:46 5 ways to get full-texts for free that are totally legal
0:21:31 How Sci-Hub will facilitate the technological evolution of research distribution and the Spotify-ication of the science publication industry
0:29:39 How to organize science papers to prevent wasted time and frustration later
0:31:34 Reference management software
0:33:29 The anatomy of a science paper; how you should approach each section and what you can learn from it
0:43:41 Peer review makes discussions within papers more objective; how a scathing peer review from six years ago continues to influence how I teach hormesis today
0:52:27 Acquiring background information with textbooks
0:54:19 Specific textbook recommendations
1:01:51 What you need to do before developing your own point of view
1:07:26 Strengths and limitations of different study designs
1:10:42 Observational versus experimental studies and the tradeoffs of context, size, and duration with strength of cause-and-effect inferences
1:13:47 The central role of randomization in experimental studies
1:16:16 Randomization needs a high sample size to be effective
1:17:48 Example: Finnish Mental Hospital Study
1:19:44 Example: LA Veterans Administration Hospital Study
11:22:44 Regression to the mean; how a study can show something to be true when it’s completely false; change-from-baseline data versus differences-between-groups data
1:32:29 The need for a control group: Atkins and methylglyoxal study as an example
1:34:33 Compared to what? Picking the right control group
1:38:40 The generalizability tradeoff: in vitro and in vivo, animal and human, sex, race, and other population differences
1:43:44 Contextual patterns determine outc
1:44:43 Thailand zinc/vitamin A study as an example of nutrient interactions.
1:53:15 Do your homework, assume good faith, ask questions