Stephen Hatch and Dr. Scott Braithwaite, Psychology Department
Introduction
Pornography consumption has grown over the past decade with the industry’s leading providers reporting billions of more views with each passing year (Pornhub.com, 2015). The Internet has facilitated the social acceptance and spread of pornographic material, and it is believed that approximately 40 million Americans view pornography regularly. With such a large number of Americans viewing pornography, and providers reporting more video views, it is unsurprising to learn that the pornography industry generates more income than professional basketball, football, and baseball combined (Cooper, 1998; Ropelato, 2006).
The first phase to understanding the effects of pornography is to redefine the way pornography is being measured. Measurement of pornography in the current literature has been problematic for a few reasons. First, several studies only utilize a single-item Likert-style measure, and others only use a single-item measure with a binary response (e.g., “Have you viewed a pornographic film in the prior year? Yes, or no?”). Some may question whether a single-item measure accurately represents the complexities of this construct. Second, these measures appear to only measure a single factor of the overarching pornography consumption construct: frequency, or how often an individual views pornography. It is entirely plausible that an individual that consumes pornography frequently may have different psychological or health outcomes than an individual that consumes pornography for long amounts of time, or an individual that has only been accidentally exposed to pornography. Third, although multiple-item measures have been used in the literature for analysis, these measures often combine duration – or the amount of time an individual views pornography – and frequency, not allowing these two different constructs to be parsed apart and individually studied. Fourth, outcomes related to exposure and arousal to content, or viewing different types of pornography and the intensity of sexual arousal that follows, have been neglected in the current research. Exposure and arousal also may be crucial to understanding how individuals are affected by pornographic material.
Due to the problematic measurement in the pornography consumption literature, the literature studying this broad area has many conflicting results. With that in mind, the current study attempts to examine the factor construct of pornography consumption with an exploratory factor analysis. We hypothesize that by running this statistical test we will be able to identify three distinct factors: exposure and arousal to content, the frequency of consumption, and the duration of consumption. We believe that by doing so, we will be able to accurately understand the psychological outcomes of pornography consumption, and bring the literature in this area to a general consensus.
Methodology
To recruit our participants, we utilized Amazon’s TurkPrime.com – an Internet-based platform. Via TurkPrime.com, we recruited 321 individuals, and as per protocol, participants were asked to complete a 20-minute survey. In exchange for their participation, individuals were compensated $0.50.
Sample Information
Exactly 143 respondents were female and 176 were male, and 2 respondents did not indicate their gender. The average age of participants was 36.48. The average age that individuals in our sample reported first viewing pornography was 12.93 for males and 15.15 for females. A majority of our sample was White American (73.52%); 10.59% reported being Black American; 5.30% Asian American; 5.30% Latino American; 3.43% Biracial American; 1.25% belonged to a race not listed; and 0.62% of participants did not respond. A majority of our sample reported having viewed pornography on purpose (98.12%) with a notably lower proportion of our sample reporting having ever viewed pornography by accident (77.43%). Additionally, most participants reported accessing pornography via the internet (89.10%), followed by 4.98% accessing pornography through DVDs, 1.87% via Pay-Per-View, 1.56% through magazines, and 2.49% of individuals did not respond.
Measurement
Participants were asked a battery of questions that were believed to best represent our three theorized factors: exposure and arousal to content, the frequency of consumption, and the duration of consumption.
Results
We used the statistical software r to run an exploratory factor analysis. Based on our plot, Eigenvalues greater than 1, and by the grouping of the factor loadings, we extracted the three factors that we originally theorized: exposure and arousal to content, the frequency of consumption, and the duration of consumption (see Figures 1 & 2). Additionally, we dropped any items with factor loadings below 0.52, and the internal consistency of the scale was good (Cronbach’s Alpha = 0.87).
Discussion
The current paper sought to add to the literature by redefining the measurement of pornography consumption and examining its factor structure. We confirmed our hypothesis, three unique factors from our data emerged.
One strength of the current study is this is the first psychometric scale, of which we are aware, that measures the hypothetical construct of pornography consumption. Past scales have only measured a single facet, or have only utilized a single item. However, this study was not without weakness. This scale, for example, does not claim to measure all types of pornography consumption (e.g., paraphilic pornography consumption).
Conclusion
Pornography consumption continues to grow, especially through the internet. Because so many individuals view pornographic material regularly, it is important to understand the possible effects pornography may have on consumers. To do this, a new pornography consumption scale must be created. In line with our hypothesis, three unique factors emerged: exposure and arousal to content, the frequency of consumption, and the duration of consumption. We hope this will be utilized to better understand the psychological and health effects of pornography consumption.
