NOTE: This study is not safe for work, and may not be appropriate for people of a certain age– all of this however is at your discretion. With that said, this study examines a topic most people consider taboo: masturbation. We’ll take a look at it from several angles in hopes that we may be
NOTE: This study is not safe for work, and may not be appropriate for people of a certain age– all of this however is at your discretion. With that said, this study examines a topic most people consider taboo: masturbation. We’ll take a look at it from several angles in hopes that we may be able to support already completed studies or find novel results.
Before I continue, I will take the time to explain several terms that may be unfamiliar to you. Throughout this study, I will refer to masturbation as “wanking”. Wank is simply the slang version of masturbation. I do this to alleviate any discomfort one may feel from the word “masturbation”. Another term is “edging”. Edging is a tactic people employ to increase the intensity of an orgasm. Just as individuals are about to climax, they will purposefully stop. Then they will try to reach the brink of climax, stop, and repeat this process until they feel ready to release. In other words, it is a monumental demonstration of self-control.
In this first study, we look at the frequency of wanking per week as a function of several variables. We will see if gender, relationship status, edging time, recency, location, current age, or age of first wank may explain the frequency of wanking.
Alex Barwell surveyed individuals and collected all the data. I, in no way, played a role in data collection. He collected responses from 487 different individuals between January 27 and January 30, 2015. The data collected came exclusively from Reddit.
Okay, so this table looks intimidating, but let’s break it down. From this table we know there’s a pretty heavy gender skew; there is a 4:1 male-female ratio. There also seems to be a heavy location skew with most people going-at-it in the bathroom– it’s a 10:5:1 bathroom-bedroom-other ratio. The skew is not as heavy for relationships where its a 3:2 yes-no ratio. The least skewed of the categorical variables is the recency of the last wank — “this month” can be considered an outlier. So what does all this skew mean? It simply means that our data may favor one variable over another (aka bias). That’s okay, because we can address it in future studies.
Here’s a visual representation of gender (above).
This one is for prime wanking location (above).
Here’s one for relationship status (above).
And the recency of the last wank (above).
We’ve covered all the categorical variables. Now we’ll look at quantitative variables through graphs — most of us cannot imagine a distribution from descriptive statistics. But if you can, more power to you.
The graph above tells us that the people surveyed are most likely to be from the 16-26 age range. From the table (way above), we know the average age is about 22. We don’t have the greatest sample size for people over 30, but it’s expected since Reddit is used mostly by the 18-34 age group–the skew will probably show in our results.
We can see the average age of when people first began to wank was around 12. Now this is an ideal distribution. It is approximately normal: most of the people fall around the mean, and less do as we move further away from it. The lack of a skew allows for more accurate results.From our table and histogram, we can see that most people go at it between 5-6 times a week. That’s almost once a day. But dang, look at our friends who can wank 25-30 times a week–they must have a lot of time on their hands (along with something else if you get my drift).
So this graph is a fun one. Our table tells use that most people can edge from 13 to 18 min. You may be wondering how edging was measured. We asked individuals to time themselves from the moment of the first intentional stop to the orgasm. There’s a notable amount of people who can edge for an hour. Before I cleaned the data, we had someone who could go for 3 hours (but they were a huge outlier so we had to remove them). Now that’s intense.
You’ve gotten a taste of the data, so now we’ll get to see some how our variables affect the frequency of wanking.
For our stat geeks out there, we mostly used linear models and multivariate regression to look for significance. The table below again will look really scary but again we will break it down.
From our linear models we can see that Gender, Relationship and the Age of First Wank yield significant results. Males–on average–wank twice as much than their female counterparts. Those in relationships wank less on a weekly basis, and the earlier people start wanking, the more often they wank. Our linear models also indicated that people wank more frequently in the bathroom than they do in any other setting however this difference is not significant. Also, as one ages (past 23 or so), the frequency of wanking decreases– but this result is also not significant. Lastly, higher edging times also increase frequency of wanking, but the difference is so low, it’s better to simply say it does not really have an impact whatsoever.
We had some pretty solid results in terms of simple linear models, but now we want to explain the relationship a little more. Many of the relationships we tested were duds, but we found some new and unexpected relationships. While we could spend ages explaining every single result we found on this table, we’ll focus on the ones that stand out.
Looking at Edging and Age of First Wank, we see the p value has massively decreased (which is really good). Our data indicates that when accounting for Age of the First Wank , the effect Edging has on Frequency is significant. As edging time increase and the earlier someone begins wanking, their frequency of wanking increases. Another example of where a p value has decreased with Relationship Status and Age of First Wank. We would think that people in relationships who began wanking early would probably wank less. But our data tells us that people in relationships who begun wanking early –actually– wank more frequently than those who aren’t in a relationship.
Now the relationships that follow are not significant, they might be in future data that is more representative. Those who are in a relationship, and wank in the bedroom wank more than any of those in or not in relationships, in other locations . This has some interesting implications that we will address later.
While our study is revealing, there are many things we can improve to find more representative results.
The first problem we need to address is the massive skews present in this study. If we are able to obtain more normal data as we found in the Age of First Wank, then we might have more reliable results overall. For categorical variables, we need a more even ratio to avoid any large skews. For example, our study indicates that women do engage in wanking just as men do. There is a huge difference between genders in this study, but this may be a consequent of the heavy gender skew. Another issue that would alleviate biases is samples from more varied locations– for example, Reddit caters to mostly males, so that can explain the large gender difference.
Our R squared value with any given relationship never exceeded .12. Even when we accounted for every variable for one large model, the R squared never surpassed .12. That means that the differences we found may very well be due to chance. Consequently, the correlations are pretty weak.
Reliability was about .03 for every variable. This means our study would be hard to replicate. But our effect size for certain variables– gender and relationship status–provided high effect sizes (.80, and .60 respectively).
We also overlooked a pretty huge variable that may have better explained our data: sexual orientation. Because non-heterosexual couples may engage in sexual activity more than just penetrative acts, it may have manifested itself as a confound in our study.
One thing we cannot explain is that even though they were skewed, pretty much every variable met the conditions for a linear model to work.
So now we ask the important question, why is all of this even relevant?
Looking at relationships and locations and their effect on frequency: this relationship indicates that wanking with a partner is just as relevant as wanking in no relationship. This may uncouth a nuance in the definition of sexual intercourse especially for non-heterosexual couples. The current misconception is that, for example anal sex is the only form of sex in male-male couples. Our study, debunks this concept but not even remotely conclusive– it is more of a reason for us to include sexual intercourse. Accounting for sexual orientation is crucial to progress our comprehension of sex norms beyond heterosexuality.
Back in the 1940’s and 1950’s, Kinsey challenged the culture of abstinence and purity by elucidating sexual norms in America. This was one of the first attempts to normalize sexual activities, and it was highly successful. We–as a nation– initiated the process of achieving sex positivity. In the modern era, we have a new problem. We oversexualize everything, especially women. There is still the lingering Victorian ideal that women are these pure creatures that transcend the realm of carnal pleasure.
From our overexposure, the media distorts our perceptions of sex. Related, the number of sexual activities someone engages assigns a label that can be not only unrealistic but also toxic. For example, females who engage in more sexual activities are labelled as “sluts” or “skanks” whereas males are praised as “players”. Our study is a step– albeit a tiny one– towards destigmatizing concepts and challenges our unrealistic standards of sex.