Relationship Study Issues Example 2

Recently we shared a story of how researchers drew an obviously incorrect conclusion from a correlation, and how that information essentially became "fact" in the mainstream media despite clear issues with what the research really meant. The issue in that article was incorrect conclusions. Yet sometimes the research is flawed before it even reaches a conclusion, and yet despite these flaws, the conclusions are still considered fact.

The most obvious example comes from a study from Ohio State University that measured how often students thought about sex on any given day, comparing males to females. The results were supposedly groundbreaking, because while men thought about sex more often than women, the two numbers were much closer than research and society traditionally believe. In fact, they gave it specific numbers .

They found that men think about sex an average of 19 times per day, while women think about sex an average of 18 times per day. Men still think about sex more often, but women are not as far behind as people would have you believe. It's a pretty interesting conclusion, and one that may be true.

Unfortunately, it's also one that has severe methodological problems – problems that the researchers themselves even acknowledge, but then inexplicably decide aren't big enough issues to prevent releasing the data.

Having specific numbers is fairly interesting. Indeed, if men really think about sex 19 times a day compared to women at 18, one can ask all sorts of questions, such as "why only once more?" But then this brings up its own questions – how did they come up with these numbers? It's certainly not the type of data that one can collect against a person's knowledge, nor is it something that could be collected without the study participant's own admissions.

To collect this data, they had each student carry a counter around with them. Every time they thought about sex, or anything related to sex, they were told to click on the counter. Then every day they logged the number and this number was then averaged out to get the 19 and 18 found in the study.

Perhaps you can see the problem with this type of data collection already. This method of data collection introduced a potential problem that blatantly affects the accuracy of the data. We'll look at this problem in the next article.