Seventy-four male participants between the age of 18 and 47 (
Mage
=

20.79,
SD
=

3.55) from a university in California participated in this study. They were randomly assigned to play either a sexually-explicit video game with female “objectification” content (
N
=

24), a control game with non-sexual social interactions (
N = 25), or a second non-sexual and non-social control game (N

=

25) on a Sony PlayStation 2
® (PS2) game console for 25 minutes. A check of the randomization confirmed that participants in each condition had similar age (
F(2, 74)
=

1.516,
p
=

.226) and video game playing experience (
F(2, 74)
=

.872,
p
=

.423). After game play, they performed a lexical decision task and completed the Likelihood to Sexually Harass (LSH) scale (Pryor
1987; Rudman and Borgida
1995). The lexical decision task included sexual words and neutral words to measure the accessibility of sex-related thoughts. This task also included sexually objectifying and neutral descriptions of women. All words used in this study were scrambled into meaningless letter strings to control for lengths of each word. The LSH scale was used to measure a participant’s self-report behavioral tendency (i.e., susceptibility) to sexually harass.
Stimulus Materials
The sexually oriented game used in this study was Leisure Suit Larry: Magna cum LaudeTM (Leisure Suit Larry). This game is rated “M” for “mature” by the Electronic Software Rating Board (ESRB). In this game, players assume the identity of Larry, a funny-looking and socially-awkward college student who tries to enter a televised dating show. To achieve this goal, Larry must gain affection from various female characters. Players would explore 17 different locations on and around a college campus to interact with these female characters. Such interactions include playing mini-games (e.g., drinking games, trampoline, and wet T-shirt contests) and engaging in humorous and sexually-suggestive conversations. In addition to its sexually-charged narrative and game objective, Leisure Suit Larry also contains computer-animated nudity as well as photographs of human female models dressed in sexy outfits.
As part of the introduction and training sequence, the beginning of Leisure Suit Larry requires players to go through a series of relatively simple tasks such as navigating the campus, flirting with a female character, and trying to impress her with cocktail mixing and dancing skills. After successfully getting her drunk enough, Larry would have an opportunity to invite her back to his dorm room. This introduction and training sequence would take about 15 to 30 minutes to complete.
In order to provide adequate control for both the sexual content and the simulated social interactions in Leisure Suit Larry, two control conditions were included in the present study.
The first control game employed was the PS2 version of the Sims. Sims is one of the most popular game series developed for the PC platform. It is a simulation game in which players can freely engage in normal daily activities such as finding a job, earning money, reading books, playing pool, etc. Similar to Leisure Suit Larry, The Sims II allows for social interactions among computer-generated characters, it does not contain any explicit sexual imagery or sexually charged narrative. It is rated “T” for “Teen” by ESRB. Although the PC version of the Sims II is quite different from Leisure Suit Larry, a number of key modifications were made specifically for the PS2 version of this game, making it a suitable control in the present study. First, the animated characters in this game are similar to those found in Leisure Suit Larry. Second, the control of the character in this game was modified to better suit the PS2 controller that is also used to play Leisure Suit Larry. Third, when the players first start to play the PS2 version of the Sims II, they only have access the limited “get a life” single-player mode. This mode serves as a tutorial and offers a fairly challenging set of seven different missions that will take several hours to complete. In this mode, the players are required to complete several goals, such as making new friends or improving a player’s home. However, they are prevented from completing more interesting objectives such as winning the affection of female characters or getting married because they are restricted by the fact that they have to spend a great deal of time performing mandatory activities like going to work or refilling its motives. This modification effectively reduced the likelihood of participants engaging in sexually motivated activities (e.g., seeking a mate) and making it a suitable control in our study.
A second control game, PacMan II, was used in the present study. This game served as a true control for the sexual condition because this game does not have any human character, social interaction, or sexual imagery. Players of the PacMan II game simply control a circular-shaped smiley-face that eats various objects (e.g., white dots, fruits, coins, etc.) in two-dimensional mazes while being chased by enemies.
The Lexical Decision Task
The lexical decision task (Meyer and Schvaneveldt
1971;
1976) is widely used in cognitive psychology experimentations as a measure of semantic memory structure or the organization of general world knowledge. This technique has also been used in studies that examine sex-related cognitive structures (Geer and Bellard
1996; Geer and Melton
1997; Spiering et al.
2002). In a typical lexical decision task, participants are presented with a mixture of words and nonwords. Participants are asked to determine as quickly as possible whether a letter string is or is not a word by pressing a button.
In the present study, two groups of lexical decision stimuli were administered; each group contains two sets of words .The first group of stimuli was designed to compare participants’ reaction time to either sexual words or neutral words. The second group of lexical decision stimuli included words that described women either as sex objects or non-objectifying descriptions of women. Each word used in the study was scrambled to create a pseduword of equal length. The purpose of scrambling each word used in the study rather than using random letter strings is to ensure that the length and letter combination of each nonword is consistent with the target word.
Sexual and neutral words. Sixteen sexual words (e.g., sex, penis, etc.) and 16 neutral words (e.g., door, bank, etc.) frequently used in past research on sexual priming (Geer and Bellard
1996; Geer and Melton
1997; Spiering et al.
2002) were selected to be the lexical decision stimuli. These words are frequently used in colloquial English and have similar number of letters and syllables.
Sexually objectifying and neutral descriptions of females. In a pilot study, 34 male and 48 female students enrolled in an upper division communication course generated a list of sexually objectifying or neutral words describing women. Participants were asked to free-associate for 90 seconds to the two counterbalanced categories. Words independently generated by more than 33% of the sample were chosen as examples of that category (Gilbert and Hixon
1991; Rudman and Borgida
1995). Overall, 10 sexually objectifying references of females (e.g. slut, whore, bitch, etc.) and 10 neutral descriptions (e.g. sister, nurturer, caregiver, niece, etc.) were selected to represent each category. Words in each category had similar number of letters and number of syllables. They are also scrambled into meaningless letter strings to be used as control.
The final version of lexical decision task included 104 letter strings divided into eight types of stimuli: 16 words with sexual connotation, 16 non-sexual words, 10 sexually-objectifying descriptions of women, 10 neutral (i.e., non-sexual and non-objectifying) references to females, and a corresponding number of scrambled nonwords for each of these categories.
Likelihood to Sexually Harass (LSH) Scale
The Likelihood to Sexually Harass (LSH) scale (Pryor
1987) contains 10 scenarios depicting sexually-exploitive opportunities (e.g., granting the female subordinate’s request in exchange for a sexual favor). Respondents were asked to indicate on a 7-point scale (1 being not at all likely and 7 being extremely likely) whether they would take advantage of the depicted situation and sexually exploit the female described in each vignette. There were a total of 29 possible responses to 10 different scenarios. A summation of scores from the 10 scenarios was calculated with a possible total score range from 29 to 203 to measure participants’ self-reported tendency to sexually harass. The higher the score, the more likely an individual is to engage in sexually-exploitive behavior in these situations. A check of data revealed no missing scores. The internal reliability of 10-items LSH was high (Cronbach
α
=

.927). This is consistent with previous research (Pryor and Meyers
2000). The mean score of the LSH is 93.48,
SD
=

26.07. The distribution did not significantly deviate from normal (
Skewness
=

.684,
SE
=

.274,
Kurtosis
=

.233,
SE
=

.541).
Procedure
Upon arrival to the lab, participants first completed a questionnaire containing general demographic items. They were then led to one of the three small cubicles each equipped with a computer, a TV monitor and a Sony Playstation 2 game console. Based on the outcome of random assignment (drawing a number from a box), participants played
Leisure Suit Larry (
n
=

24),
the Sims II (
n = 25), or
PacMan II (
n = 25) for 25 minutes. Prior to game playing, participants were given a brief instruction on how to use the controller. Instructions of the game and a diagram of the control pad were also posted on the walls in each cubicle.
After 25 minutes, participants were instructed to stop playing the game and turn on the computer monitor on a nearby desk in the same cubicle to complete the lexical decision task. The lexical decision task was conducted through the SuperLab Pro® experimentation program. The participants first went through a computerized instruction of the task and 10 practice trials of using words that are unrelated to the present study (e.g., colors). Then the experimenter left the cubicle while the participants completed 104 experimental trials. Each trial consists of a randomly-selected letter string appearing in the middle of the computer screen. The task is to quickly and accurately identify the string as a word or a non-word by pressing predetermined keys. The computer measured accuracy of response and participants’ reaction times to the nearest millisecond.
After completing the lexical decision task, the experimenter returned to the cubicle and loaded the computer-based LSH questionnaire administered using SuperLab Pro®. Participants were instructed to answer these questions truthfully. Upon completing the LSH scale, participants were debriefed and thanked before they left the lab.
Error Responses and Data Preparation
Several steps were taken to ensure data accuracy. First, we checked whether the error responses in lexical decision tasks (i.e., recognizing a scrambled words as meaningful or vice-versa) were distributed randomly and equally across the conditions. Participant made an average of 7.24 errors out of the 104 trials (
SD
=

7.51). There was no significant difference in the error responses for different word types. Next, a series Kruskal-Wallis non-parametric test of median differences revealed no significant differences in error responses between the three experimental groups across all word type (
p values of the Chi-squared statistics ranged from .20 to .928). Given the relatively low error response rate and the fact that the error response were randomly and equally distributed across word types and the three conditions, the error trials were kept in the overall reaction time calculation.
To conduct the reaction time analyses, harmonic means were calculated for each set of words and nonwords (neutral, sexual, sexually objectifying, etc.). A harmonic mean is more desirable than an algebraic mean (i.e., simple average) in reaction time analyses because it takes the skewed nature of reaction time data into consideration while gives the hypothesis testing more power (Ratcliff
1993).