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ORIGINAL PAPER
‘‘Let My Fingers Do the Talking’’: Sexting
and Infidelity in Cyberspace
Diane Kholos Wysocki
•
Cheryl D. Childers
Published online: 20 March 2011
Springer Science+Business Media, LLC 2011
Abstract This exploratory project investigated the behaviors of sexting and infi-
delity on the internet. The researchers placed a survey on a web site designed for
married people to find sexual partners outside their marriage. Using a sample of
5,187 respondents, the study explored how people use the internet to find partners.
Using both descriptive statistics and binary logistic regression analysis, the
researchers found that the respondents use the internet to find real-life partners, both
for dating and for sex hookups, but many are anxious about being caught. Females
are more likely than males to engage in sexting behaviors, while females and males
are equally as likely to cheat both online and in real life while in a serious real-life
relationship. Older males, however, are more likely than younger males to cheat in
real life. The results suggest that perhaps people who are using dating web sites
do not conform to the ‘‘official’’ standards of dating culture, but that maybe the
standards are changing.
Keywords Sexting Infidelity Cybersex Internet Online dating
Online Survey
Introduction
The ways in which individuals become involved in interpersonal relationships has
changed at a dramatic rate during the last 20 years. Anthony Giddens (1992:4) once
stated that ‘‘…the modes of life brought into being by modernity……have come to
D. K. Wysocki (&)
Sociology Department, University of Nebraska at Kearney, Kearney, NE 68845, USA
e-mail: wysockid@unk.edu
C. D. Childers
Sociology Department, Washburn University, Topeka, KS 66621, USA
e-mail: cheryl.childers@washburn.edu
123
Sexuality & Culture (2011) 15:217–239
DOI 10.1007/s12119-011-9091-4
alter some of the most intimate and personal features of our day-to-day existence.’’
Modernity has given individuals the opportunities to develop interpersonal
relationships with new ways of social interaction (Ackland 2009; Jones 2005;
Lewis and West 2009; Walther et al. 2009; Wysocki 1998).
The increased availability, as well as declining prices, of technological products
such as computers, modems, video cams, and cell phones has had a dramatic effect
on our social life (Charness and Boot 2009; Ono and Tsai 2008). Since 2000, the
number of people who use the internet has increased over 399% around the world
(Internet World Stats 2010). While in the comfort of their home or office, social
networks are increased (Wysocki 2001; Wysocki 1998), new on-line communities
created (Bowker and Tuffin 2004; Frank 2008; Nimrod 2010; Sarmiento and
Shumar 2010), individuals have met their spouses/partners (Castaldo 2009; Epstein
2009; Whitty and Carr 2006), and even fulfilled their deepest sexual fantasies
(Blackstone 1998; Horvath et al. 2008; Jones 2005; Ross et al. 2007; Wysocki and
Thalken 2007; Wysocki 1998).
Love and Sexuality
An essential aspect of the social construction of romance, love, and sexuality has
evolved around an individual’s attempt to go along with the various scripts made
available to them by family, friends, and the mass media (Anderson 1996; Sanders
2008; Simon and Gagnon 1984). Gagnon and Simon (1973) describe scripts as
‘repertoire of acts and statuses that are recognized by social groups, together with
the rules, expectations, and sanctions governing these acts and statuses’. Males and
females learn very different scripts as they grow up (Beasley 2005; Laws and
Schwartz 1977; Simon and Gagnon 1984) and by puberty, societal scripts for both
sexes traditionally have become ‘emphatically heterosexual and oriented towards
marriage’ (Laws and Schwartz 1977, p. 39). These scripts about love and romance
prepare an individual to act within the dominant scripts of society, which is to find
the ideal romantic relationship with the hope of living happily ever after with their
mate (Giddens 1992).
In the past, people met their ‘true love’ and their sexual partner from a pool of
eligible individuals who were in close proximity to one another and who were
involved in the same activities such as church, school, and play; and individuals
tended to pick partners who were very similar to themselves in religion, education,
and within 5 years of their own age (Michael et al. 1994). When people fall in love,
the experience can be ‘‘euphoric…where we go to sleep thinking of one another…are
emotionally obsessed with each other…
and spending time together is like playing in
the anteroom of heaven’’ (Chapman 2010, p. 29). However, when the ‘‘real world of
marriage’’ happens, we find that oftentimes ‘‘heaven’’ is gone because of the reality
of life. For instance, spouses get upset when their partner forgets to put things away,
toilet seats are left up, bills pile up, children need to be taken care of; and then lovers
become enemies who no longer talk to each other or look into each other’s eyes.
Things change; partners become depressed, wonder what happened to that ‘‘in love’’
feeling, and then try to recreate it. Sometimes they recreate it with someone else.
218 D. K. Wysocki, C. D. Childers
123
While there can be similarities between the two people involved in the
relationship, there can be differences as well, especially regarding sexual desires.
Sustaining the romantic relationship or marriage is dependent upon many things, but
especially on what Giddens calls confluent love which
makes the achievement of reciprocal sexual pleasure a key element in whether
the relationship is sustained or dissolved. The cultivation of sexual skills, the
capability of giving and experiencing sexual satisfaction, on the part of both
sexes, become organised reflexively via a multitude of sources of sexual
information, advice, and training (Giddens 1992, p. 63).
Modernity and the advancements made in technology have brought about
dramatic changes in the amount and variety of sexual information or new sexual
scripts that are available once the computer is turned on (Barraket and Henry-
Waring 2008; Berne 2007; Kammeyer 2008; Wysocki and Thalken 2007). As
society has changed, sexual desires and scripts that were once hidden behind closed
doors have become readily available for anybody to experience. However,
according to Michael et al. (1994), while couples in long-term relationships have
talked about many different issues prior to their marriage or partnership, they rarely
have talked about the specific sexual practices they desire in their relationship. For
instance, men were found to be more interested than women were in oral sex, anal
sex, using autoerotic material, and having sex with a stranger, thus widening the
sexual gap between the individuals in the primary relationship.
It is no wonder that the changes in the way individuals think about relationships,
love, and sex, along with the advancement in technology have ‘narrowed the
bandwidth’ (Turkle 1995) where individuals are able to meet in virtual space without
the ability to touch. Meeting in virtual space allows the participants the ability to
‘create extremely detailed images of the absent and invisible body, of human
interaction, and the symbol-generating artifacts which are part of that interaction’
(Stone 1995 p. 93) so they may participate in on-line sexual relationships.
Freed from our burdensome material selves…. we become fluid entities,
overcoming those societal stigmas inscribed on the body-race, gender, age,
size, beauty……. (Campbell 2004): 5
Sex On-line
Researchers have found that the Internet is where the majority of people who are
looking for sex go to find partners (Cooper et al. 2003; Couch and Liamputtong 2008;
Wood 2008). Barak and King (2000) say there are two faces of the internet. One which
allows us to gain all kinds of great information and the other called the ‘‘virtual
monster…which can influence individual’s beliefs and potentially change their
lifestyles (Barak and King 2000 p. 518). For those individuals who have a great sexual
face-to-face relationship, the internet can be used as a way to explore other dimensions
of their sexuality together. However, if the face-to-face relationship already has
Sexting and Infidelity in Cyberspace 219
123
problems, the internet can become a place to explore other sides of sexuality away
from their face-to-face relationship and with other people.
Sex via the computer can develop through the interactive sharing of fantasies,
using real-time cameras, looking at sexually explicit photographs, and/or sharing
similar sexual interests. The amount of people who use the internet for social
network is staggering. ComScore keeps track of various social networks and
blogging platforms, and have found that Bloggers have an estimated 222 million
users in November 2008 (up 44 percent from November, 2007); Facebook has 200
million unique visitors (up 116 percent); MySpace has 126 million unique users;
and WordPress has 114 million (up 68 percent) (Schonfeld 2008). While it is
impossible to tell how many people actually use the internet for sexual-related
communications, we do know that sex on the internet is very easy to find and one of
the most sought-after topics for people (Barak and King 2000; Cohen 2008; Farrell
and Petersen 2010; Wysocki 1998).
Finding people who participate in cybersex is not difficult; and those who do
participate have found to be comfortable telling personal things about themselves
with another human on-line, have on-line sexual encounters, and ‘cheat’ on their
spouses with someone they have met on the internet (Cohen 2008; Jones 2005;
Whitty 2005; Wysocki 1998). In October 1995, the InterCommerce Corporation
created an on-line sexual survey. By June 1997, a total of 20,791 respondents had
participated in the survey and reported that being on-line enhanced their sexual
behaviors (InterCommerce Corporation 2005). The top reasons respondents gave for
participating in sex on-line was that it was ‘a benign outlet for sexual frustration…It
has made me more open-minded…Promotes honest communication … Promotes
safe sex … [and] has improved my sex-life’. Other respondents believed cybersex
helped their marriage and discouraged adultery. While information about the exact
number of people who use the computer for sexual activities and information
changes constantly, it is becoming recognized that if you want sex…it is only a
keyboard away.
Sexting
One fairly new phenomenon that has come out of the influx of new types of media is
‘‘sexting,’’ which refers to the sending and receiving of sexually explicit photos and/
or text using cell phones with digital cameras. While not in the academic literature
as of yet, this term has hit the mass media with a vengeance. Television shows such
as The Trya Banks Show and Oprah, and various news shows such as Good Morning
America and The Today Show, have talked about the problems with sexting and how
common it has become, especially in the younger population (Anonymous 2010).
What has attracted media attention is the fact that the younger population has
included teens. However, sending or receiving naked pictures of someone who is
underage is a criminal offense, which often leads to being required to register as a
sex offender (National Center for Missing and Exploited Children 2009). While
sexting among minors is an important and dangerous issue, for the purposes of this
paper, we are only considering the sexting behavior of adults who are sending their
220 D. K. Wysocki, C. D. Childers
123
photographs to another adult for the purpose of turning them on and increasing the
likelihood of a relationship.
Infidelity
Why do people cheat on their partners? There are a number of books written on the
subject by counselors and family therapists who explain what to do if you have been
cheated on (Glass and Staeheli 2004; Neuman 2009; Pittman 1990; Spring and Spring
1997). In fact, many of the books give signs on how to detect cheating, such as your
partner spending more time away from home, less frequent sex, less physical contact,
your partner criticizing more, beginning to start fights and always mentioning another
‘‘friend’’ in casual conversation (Neuman 2009). While many might think it is only the
male who does the betraying, women are turning to the web more and more to find a
sexual partner. Women know more about their own sexuality than ever before. They
know what they want sexually and if their primary relationship disappoints them, then
women are going to go looking for someone else just like the men (Laws and Schwartz
1977; Wagner 2009; Wysocki and Childers 2009).
Different types of extramarital relations have been defined in the literature
(Bagarozzi 2008). The first is a ‘‘brief encounter,’’ which can be a one-night stand or
a relationship that lasts for a very short time. This type of affair usually involves
drugs or alcohol, which lowers inhibitions, involves strangers, occurs far from the
individual’s home, and has a low probability of discovery. A ‘‘periodic sexual
encounter’’ is more premeditate, persistent and chronic, yet the individual is not
interested in developing a deep, long-term relationship. An ‘‘instrumental and
utilitarian affair’’ is one where the individual enters it for personal gain and in order
to achieve a specific goal. In this type of affair, the sexual act is very important and
is often used as a way to get out of, or deal with, an unhappy marriage.
The internet has made the act of infidelity much easier. While the internet does not
cause the person to cheat, if someone is unhappy in his/her relationship, if ‘‘heaven’’
is gone, s/he is more likely to go to the internet to look for someone with which to
explore relations. Whitty (2005) found that online infidelity included not only sexual
infidelity, but also emotional infidelity and the use of pornography. A study of 123
university students who completed an Internet-Based Experience and Relationship
Survey found the following to be considered unfaithful online behavior (Henline
et al. 2007): Sexual chat which includes masturbation while having cybersex,
emotional involvement which includes deep self-disclosure with another person,
meeting or planning to meet someone in person, talking dirty or flirting, watching or
looking for online pornography, and betraying the confidence of a partner.
Conducting Sexual Research Online
The internet has become a good place to conduct research (Farrell and Petersen
2010). Studies have been done on gay chat rooms (Campbell 2004; Jones 2005), neo
nazi groups (Hughey 2008; Mitra and Watts 2002; Mitra 1996) finding mail order
Sexting and Infidelity in Cyberspace 221
123
brides (Johnson 2007), S & M (Wysocki and Thalken 2007), and even those who
have developed an asexual identity (Scherrer 2008). In fact, researchers have now
started to understand the rapidly growing importance of the internet as a way to
access factors that influence human behavior (Farrell and Petersen 2010). They have
found that using the Internet provides study participants with both convenience and
privacy, which is an asset in the studies of special populations. While it is being
used more and more often, there are some things to consider with internet research.
For instance, it is a self-selection of respondents. This research does not reach out to
all people who are cheating on their spouse on the internet, but rather only includes
those people on one web site who decided to participate in the project. Another
problem is the lack of control for honesty of the respondent. However, that is a
problem with any type of survey that is given.
The purpose of this paper is threefold: (1) to gain demographic information from
respondents who participate on a specific website geared toward infidelity; (2) to
find out why individuals go to a website to cheat on their spouses; and (3) to explore
the phenomena of ‘‘sexting.’’
Research Questions
To understand the behaviour of our respondents, this study asks several research
questions:
Q
1
: In what activities are respondents engaged on this specific website?
Q
2
: How are respondents engaged in sexting?
Q
3
: Are respondents cheating with people they find on the internet while in a
serious real-life relationship?
To understand whether the findings for Questions #1–3 vary by other factors, we
ask these additional questions:
Q
4
: What are the predictors for sexting by sex?
Q
6
: What are the predictors for infidelity by sex?
Methods
The Web Site
AshleyMadison.com was launched on February 14, 2002 by Noel Biderman and
Darren Morgenstern. Biderman, who is married with two children, and Morgenstern
set out to create a singles dating service. However, after doing some preliminary
research, they discovered that 30% of people using the various singles dating
services were actually people who were married or in a relationship and who were
lying about their status (Personal phone call between Diane and Noel 2008; personal
experiences of Diane while using dating sites). As a result, they decided to create
AshleyMadison.com for married people and provided them a place where they
222 D. K. Wysocki, C. D. Childers
123
could be open and honest about their situation and connect with other people who
were looking for the exact same thing. Because they wanted to further the position
that the service was a discreet type of dating service, they named it Ashley
Madison.com, which were the two most popular baby names that year for girls.
Since its inception, AshleyMadison.com has grown in terms of users and
popularity. As of May 30, 2010, AshleyMadison.com, whose tag line is ‘‘Life is
short…Have an Affair,’’ states it has 6,095,000 members. After learning about
AshleyMadison.com on the radio in 2008, Diane decided to contact Mr. Biderman,
tell him about her past work on sex online (Wysocki 1998; Wysocki and Thalken
2007; Wysocki 1999), and see if she could put a survey on the AshleyMadison.com
website. Because Mr. Biderman didn’t have any demographic information on his
users, which he wanted to further market his site, they agreed to partner and came
up with a survey that would get not only the demographic information
Mr. Biderman needed for marketing, but the data that we wanted about sex on
the internet.
The Survey
The survey is comprised of 68 questions. There are 20 questions about internet use,
33 questions about sexual behaviours and/or feelings about sexual behaviours on the
internet, and 15 questions asking for demographic information. After obtaining IRB
approval, Diane placed the survey on Qualtrics on the University of Nebraska at
Kearney server. Qualtrics checks IP addresses, which enabled us, to the best of our
ability, to make sure that each person answered the survey only once. A link to the
survey was placed on the last page that individuals saw as they were logging off
AshleyMadison.com. This page asked the users if they would be interested in
answering a sex survey, housed at UNK, and were told that all answers were
anonymous. Respondents also had to confirm that they were 19 years of age or
older. The survey was active from March 19, 2009 through June 5, 2009.
Self-Selection
It is common for sociologists to find interesting groups of people to study. For
instance, research has been done on couples who engage in swinging sexual activity
(de Visser and McDonald 2007). The couples were recruited from advertisements
on swingers’ websites, club newsletters, and through snowball sampling. In another
study of individuals who used a sexual chat room called Pleasure Pit, an email was
sent to all users, and only those who were interested in participating in the study
responded (Wysocki 1998), and another study online investigated the sexual risk
taking of men who have sex with men (Horvath et al. 2008).
What our study has in common with the above studies is that the respondents are
self-selected and not random. This means that we cannot generalize to the entire
population of people, but only to those who happened to be on the particular sites to
see the ads for the survey. According to Farrell and Petersen (2010), the internet can
produce representative data. Dillman (2000) found that representativeness is the
Sexting and Infidelity in Cyberspace 223
123
degree to which there is a match between the target population and the sampling
frame population and, therefore, web surveys have been found to have only very
minor coverage problems.
In the past, using the telephone was a way to obtain a random sample of
respondents. Today, however, because many people have only cell phones, or are
not home, or are not willing to answer questions, especially about sexual practices,
the telephone is no longer a good way to obtain respondents. Hence, the Internet is
proving to be an excellent way to obtain data from specific groups of people
(Dillman et al. 2009).
Variables
Dependent Variables
This study uses three dependent variables: Sexting, Cheating Online, and Cheating
in Real Life.
Sexting is defined as sending sexually explicit text messages and/or photographs
through e-mail or cell phone. It is operationally defined as the answer to the
questions ‘‘Have you ever had sex via texting?’’ and ‘‘Have you ever sent a nude or
nearly nude photo of yourself via email or from your cell phone?’’ Each question
was coded as ‘‘0 = No’’ and ‘‘1 = Yes.’’ The scores on the two variables were
added together, with a range of scores possible from 0 to 2. However, since a
respondent could score a 1 if s/he had either had sex via texting or sent a nude photo
through phone or email, we recoded the score for sending a nude photo to
‘‘ 2 = Yes.’’ Consequently, the range of scores is 0–3. Respondents score 0 if they
have neither had sex via texting nor sent a nude photo through phone or email; a
score of 1 means they have had sex via texting but had not sent a nude photo. A
score of 2 means they have not had sex via texting but have sent a nude photo, while
a score of 3 means they have done both.
Four new dummy variables were created using the total scores: Scores of 0 were
coded as ‘‘Neither Text nor Photos.’’ Scores of 1 were coded as ‘‘Text Only’’; scores
of 2 were coded as ‘‘Photos Only,’’ and scores of 3 were coded as ‘‘Text and
Photos.’’ Each variable was coded as ‘‘0 = No’’ and ‘‘1 = Yes.’’ Since each is a
dichotomous variable, we used binary logistic regression to understand their
relationship to selected influencing factors.
Two survey questions specifically addressed infidelity—one question asked about
cheating online, and the other asked about cheating in real-life. We did not combine
these questions, as with the sexting questions, because we were interested in
whether people distinguish online vs. real-life cheating (Millner 2008; Whitty
2005). Cheating Online was measured using the question ‘‘Have you ever cheated
online while in a serious relationship with someone in real life?’’ Cheating in Real
Life was measured with the question ‘‘Have you ever cheated in real life while in a
serious relationship?’’ Each variable was coded as ‘‘0 = No’’ and ‘‘1 = Yes.’’ As
dichotomous variables, we used binary logistic regression to explore them.
224 D. K. Wysocki, C. D. Childers
123
Independent Variables
We used several independent variables in our analysis. Age was measured in raw
years and was re-coded into age groups (18–24, 25–29, 30–39, 40–49, and
50? years). Each category was also dummy coded where ‘‘0 = No’’ and ‘‘1 =
Yes,’’ with ‘‘18–24 years.’’ as the reference category.
Income and Education were both coded at the ordinal level. Income was measured
using the categories ‘‘Less than $25,000,’’ ‘‘$25,000–50,000,’’ ‘‘$50,001–100,000,’’
and ‘‘More than $100,000.’’ Education was coded ‘‘HS/Equivalent,’’ ‘‘A.A. degree or
Some College,’’ BA level Degree,’’ and ‘‘Post-BA Degree.’’
Race/Ethnicity was measured using categories ‘‘White,’’ ‘‘Black,’’ ‘‘Hispanic,’’
and ‘‘Other Races/Ethnicities,’’ and was dummy coded where ‘‘0 = No’’ and ‘‘1 =
Yes,’’ with ‘‘Other Races/Ethnicities’’ as the reference category.
Martial Status was collected using the categories ‘‘Single, Never Married,’’
Married,’’ ‘‘Divorced but Never Remarried,’’ ‘‘Divorced and Remarried,’’ ‘‘Wid-
owed,’’ and ‘‘Separated.’’ We collapsed the responses ‘‘Married’’ ‘‘Separated,’’ and
‘‘Divorced and Remarried’’ into ‘‘Married,’’ with all the other categories collapsed
into the category ‘‘Not Married.’’ Each category was dummy coded as ‘‘0 = No’’
and ‘‘1 = Yes,’’ with ‘‘Not Married’’ as the reference category.
Sexual Orientation was measured with the question: ‘‘What is Your Sexual
Preference?—Heterosexual, Homosexual, Bisexual, Transgender?’’. Because of
small numbers in the values of Homosexual, Bisexual, and Transgender, we recoded
all three into LGBT, with Heterosexual as the reference category.
The survey gave respondents the opportunity to specify religious affiliations. We
collapsed the responses into ‘‘Protestant,’’ ‘‘Catholic,’’ ‘‘Other Religions,’’ and ‘‘No
Religion.’’ ‘‘Protestant’’ includes religions and/or denominations usually accepted in
the U.S. as being labelled Protestant. These include such answers as Baptist,
Methodist, Presbyterian, Episcopal, Lutheran, all Evangelical denominations whose
members identify themselves as Christian, etc. ‘‘Catholic’’ includes respondents
who specifically state that they are affiliated as ‘‘Catholic.’’ The category ‘‘Other
Religions’’ includes other Christian religions other than Catholics and those whose
members do not usually identify themselves as Protestant; and non-Christian
religions. These include such answers as Judaism, Islam, Buddhist, Quakers, LDS,
Wicca, Scientology, Pagan, etc. The category ‘‘No Religion’’ includes all
respondents who specifically stated they held no religious affiliation, or who gave
answers such as Atheist, Agnostic, Spiritual but not Religious, etc. Each category
was dummy coded as ‘‘0 = No’’ and ‘‘1 = Yes,’’ with ‘‘Other Religions’’ as the
reference category.
Work Status was measured using the question ‘‘What is your Work Status? ‘Not
Working’, ‘Working Part-Time’, or ‘Working Full-Time’.’’ Each category was
dummy coded as ‘‘0 = No’’ and ‘‘1 = Yes,’’ with ‘‘Working Part-time’’ as the
reference category.
Had Cybersex is defined as having had sex online with someone the respondent
met on the internet, and was coded as ‘‘0 = No’’ and ‘‘1 = Yes,’’ with ‘‘No’’ being
the reference category.
Sexting and Infidelity in Cyberspace 225
123
Statistical Analysis
We analyzed the first three research questions using Chi-Square. Because the level
of significance can become inflated through multiple tests, we employed the Holm-
Bonferroni method to correct the level of significance. We used binary logistic
regression to explore predictors for females and males on the behaviors as asked in
the last two research questions.
Sample
During the time the survey was online, it was accessed 8,801 times, with 8,678
people actually beginning the survey. However, we had to eliminate 3,365 surveys
because the respondents answered only the questions about sexual behaviour and
did not complete any of the demographic questions. We refined it further using only
those respondents who had the most complete demographic information (defined as
those completing at least 75% of the demographic questions), which left us with
5,187 as a final sample size.
As Table 1 below shows, our sample reflects what researchers are beginning to
understand about sex samples. Similar to other sex surveys, this study was comprised
of respondents who are more highly educated, with higher household incomes, and are
a bit older than the general population (Farrell and Petersen 2010; Wysocki and
Childers 2009). For example, over 60% of our sample is older than 40 years of age,
while less than 50% of the general population is over 40 years old. Similarly, almost
20% of our sample holds an advanced college degree, compared to only 10.6% of the
general population (U.S. Census Bureau 2010). Our sample is a bit more likely to be
White (82.6%) than the general population (76.2%), and has a median household
income approximately 170% of the general population. Certainly, our sample does not
reflect the general population. However, we could ask the question: does our survey
represent the population of people who frequent internet sites geared toward finding
real-life and/or sex partners. Swedish researchers Cooper, et al. (2003) have found
evidence that a convenience sample of a specific internet site might approximate a
representative sample of that site. Even if this is true, we have to acknowledge that
people who frequent particular internet sites are still a self-selected population.
Table 2 below shows the demographics of our sample by sex. Similar to other
research of internet sites (Attwood 2009; Ross et al. 2004), males comprised the
majority of respondents (61%). Over 66% of males were married, compared to
59% of females and were more likely to cohabit with romantic partners (73.3%)
than females (67.4%), whether married or not. The mean age of our sample
was 44.35 years (SD = 9.90) for males and 40.35 years (SD = 9.51) for women
(t =-13.60, p \ .01). Females were over twice as likely (23.5%) as males (10.1%)
to not be working, while males were almost 1.4 times as likely (85.5%) as females
(60.1%) to be working full-time. Over half of the females who are not working
report that they are homemakers. While both females and males were most likely to
log onto the internet at home, males working full-time (53.6%) were more likely
than females working full-time (46.4%) to log onto the internet at work.
226 D. K. Wysocki, C. D. Childers
123
Results
Our first research question was: ‘‘In what activities are respondents engaged on this
specific website?’’ Table 3 shows the results.
Over 66% of all respondents reported that they had met someone in real life after
first meeting them online. Females, however, were more likely (82.8%) than males
(66.7%) to engage in this behavior. While approximately 66% of all respondents
reported using the internet to find real-life dates, clearly most were looking for
sexual partners. Approximately 75% reported finding real-life sex partners, and over
66% reported finding people for purely real-life sexual hook-ups, both with no
significant differences between females and males. Our respondents were also more
Table 1 Demographics
of sample
a
Michael et al. (1994)
US Population—
2008
(N = 304,059,724)
Sex in
America
a
(N = 3,159)
Ashley
Madison
(N = 5,187)
Sex
Male 49.3% 44.6% 61%
Female 50.7% 55.4% 39%
Age
18–24 years 9.8% 15.9% 3.5%
25–29 years 6.9% 14.5% 6.5%
30–39 years 13.5% 31.3% 27.1%
40–49 years 14.9% 22.9% 37.5%
50? years 30.4% 15.3% 25.3%
Education
Less than
high school
19.8% 13.9% 0
High school
or GED
34.9% 62.2% 10%
Any college 41.4% 16.6% 70.3%
Advanced
degree
9.0% 7.3% 19.7%
Marital status
Currently
married
50.2% 53.3% 63.8%
Race
White 76.2% 76.5% 82.6%
Black 12.1% 1% 5.4%
Hispanic 9.7% 7.5% 5.3%
Other 2% 3.3% 6%
Sexual preference
Heterosexual 90.4%
LGBT 9.6%
Median
Income
$50,233 $85,918
Sexting and Infidelity in Cyberspace 227
123
interested in finding real-life partners than online-only partners. Given that this web
site is specifically advertised as a place to find people with whom to have an affair,
these high percentages would be expected. Women respondents were more likely
than men to report finding real-life dates on the internet, while men were more likely
than women to report finding online-only sex partners.
Interestingly, males were more likely than females to be anxious about being
caught looking at sexually explicit material. We can make no assumptions about the
reasons for their anxiousness. Our results show that almost 50% of the male
respondents were reluctant for their partners to find out what they are doing on the
Table 2 Characteristics of sample by sex
Females (N = 2,021)
(%)
Males (N = 3,166)
(%)
Sig.
Age
Mean (SD) 40.35 (9.51) 44.35 (9.90) t =-13.60, p \.01
Median 41.0 45.0
Heterosexual 85.4% 93.5% X
2
= 93.29, p \.01
Marital status
Married 59.0% 66.8% X
2
= 32.40, p \.01
Cohabiting in a relationship 67.4% 73.3% X
2
= 20.55, p \.01
Race/ethnicity
White 78.9% 84.9% X
2
= 29.86, p \.01
Black 7.0% 4.5% X
2
= 14.62, p \.01
Hispanic/Latino 6.1% 4.9% X
2
= 3.56, n.s.
Other 8.0% 5.6% X
2
= 11.21, p \.05
Education
HS/equivalent 11.2% 9.3% X
2
= 4.54, p \.05
A.A. degree/some college 44.3% 34.0% X
2
= 54.75, p \.01
BA degree 30.0% 33.7% X
2
= 7.90, p \.05
Post-BA degree 14.5% 23.0% X
2
= 54.45, p \.01
Religious affiliation
Protestant 30.5% 29.1% X
2
= 1.11, n.s.
Catholic 22.1% 22.8% X
2
= .284, n.s.
Other 14.7% 22.3% X
2
= 6.78, p \.05
None 32.6% 35.8% X
2
= 5.422, p \.05
Work status
Not working 23.5% 10.1% X
2
= 169.88, p \.01
Working part-time 16.4% 4.3% X
2
= 42.62, p \.01
Working full-time 60.1% 85.5% X
2
= 289.42, p \.01
Where they usually logon to internet
At home 93.0% 86.6% X
2
= 50.97, p \.01
At work 31.6% 47.5% X
2
= 127.92, p \.01
At internet cafe
´
2.6% 3.1% X
2
= .98, n.s.
At other places 6.9% 7.2% X
2
= .343, n.s.
228 D. K. Wysocki, C. D. Childers
123
internet. Males were also more likely than females to remove their cyber-trail. One
possible reason for this might be that men may be more aware of how to remove a
cyber-trail than are women. However, one 40ish female seems to have worked this
out in detail. She covers her tracks in the following ways; disposable email address,
an alias when corresponding with dates, a disposable cell phone that is turned on
only when she is using it and all history is erased at day’s end, a computer tech
comes in once a month to check her home computer for spy programs, hiding her
information on Zabasearch.com which is a skip trace search engine that lists
address, DOB, phone, other people living in the house with you. She requires every
partner to have a 9-panel STD test via tstd.org, uses airport hotels/suites and always
uses ‘‘CASH.’’
The second research question is: ‘‘How are the respondents engaging in
sexting?’’ Table 4 begins our exploration.
Clearly, almost 60% of our respondents have participated in one or both of the
behaviours comprising sexting, and just over one-fifth (21.9%) have participated in
both behaviours. Further analysis showed that when broken down into who had
participated in one but not the other behaviour comprising sexting, respondents were
over 4 times more likely to have sent a nude photo of themselves through email or on
cell phone (29.1%) than to have had sex via texting (7.1%). One possible reason for
this finding could be that email technology has been in existence longer than texting
capability. It is possible that as people become more comfortable with texting
technology, the percentages will equalize. It appears that the younger generation has
mastered texting on their cell phones; however, more and more of us who are older
Table 3 Selected activities by sex
Females
(N = 2,021)
(%)
Males
(N = 3,166)
(%)
Sig.
Met someone in person who they first met on-line 82.8 66.7 X
2
= 161.49,
p \ .01
Use of internet
To find real-life dates 70.3 63.6 X
2
= 231.52,
p \ .01
To find real-life sex partners 74.9 77.2 X
2
= 3.48,
n.s.
To find online-only sex partners 39.3 48.2 X
2
= 35.35,
p \ .05
To find purely sexual real-life hookup 67.1 69.3 X
2
= 2.86,
n.s.
Had cybersex 60.9 53.5 X
2
= 27.09,
p \ .05
Anxiousness
Anxious about being caught after viewing sexually
explicit materials on the internet
34.0 46.5 X
2
= 77.34,
p \ .05
Clears out cache to remove cyber-trail after viewing
sexually explicit materials on the internet
55.4 68.0 X
2
= 82.41,
p \ .05
Sexting and Infidelity in Cyberspace 229
123
are finding it is a great way to reach friends and family and that we will all get better
at it in the future.
Males (52.2%) were approximately 1.5 times less likely than females (67.5%) to
have participated in either of the behaviors associated with sexting, while females
(27.5%) were approximately 1.5 times more likely than males (18.4%) to have
participated in both behaviors. Over 60% of women reported that they had sent nude
photos of themselves through email or on cell phone. While less than 40% of all
respondents had sex via texting, females (35.0%) were about 1.4 times as likely as
men (25.2%) to report having done so. Females were also about 1.3 times more
likely to send nude photos of themselves through email or cell phone than were
men.
When looking at respondents who did one or the other of the behaviors, both
males and females were about 4 times as likely to send a nude photo through email
or cell phone than they were to send explicit text. A 20-year-old female, for
example, states that she sends naked pictures of herself via her cell phone as a
‘‘tease of what they [the men] could have or what they should have.’’ Taking the
pictures of herself nude doesn’t turn her on at all, but she likes knowing that it is
turning on the guys she sends the pictures to. She admits that it helps that she is very
secure in her body image, but knows she has no control over the pictures which
could end up anywhere on the internet.
Mainstream media portrays the sending of nude photos through email or cell
phone as a younger person’s behavior. This could be because the older one is the
more self conscious they are about her/his body. To further explore this idea, we
Table 4 Sexting and cheating
Have respondents …? Total
(N = 5,187)
(%)
Females
(N = 2,021)
(%)
Males
(N = 3,166)
(%)
Sig.
Neither had sex via texting nor sent nude
photos of self through email or on cell
phone?
41.9 32.5 47.8 X
2
= 104.39,
p \ .01
Had sex via texting? 29.0 35.0* 25.2* X
2
= 57.25,
p \ .01
Sent nude photos of self through email or
on cell phone?
51.1 60.0* 45.4* X
2
= 105.42,
p \ .01
Had sex via texting and sent nude photos of
self through email or on cell phone?
21.9 27.5 18.4 X
2
= 59.41,
p \ .01
Texting only 7.1 7.5 6.8 n.s.
Photos only 29.1 32.5 27.0 X
2
= 129.30,
p \ .01
Cheated online while in a serious
relationship with someone in real life?
63.6 67.6 61.0 n.s.
Cheated in real life while in a serious
relationship?
73.7 74.9 72.9 n.s.
Percentages do not add up to 100%. While the category of participating in neither behavior and the
category of participating in both behaviors are mutually exclusive, respondents can be in both categories
marked by the *
230 D. K. Wysocki, C. D. Childers
123
examined various age groups by sex. Table 5 shows the behavior of our
respondents.
In general, as age increased, the incidence of sending nude photos through email
or on cell phone decreased, with one exception. Females aged 25–29 years of age
had the highest incidence (77%) of all groups. While females younger than 40 years
of age were the most likely to send nude photos of themselves through email or on
cell phone, middle-aged and older women were also engaged in this behavior. When
we compared females and males, females were significantly more likely to send
nude photos through email or on cell phone than were males, with the exception of
the youngest age group. The difference between 19- and 24-year-old males and
females was not significant. A 33-year-old female states, ‘‘I love to engage in sexual
activities with people I do not know. Phone sex is the biggest thing for me. To know
that I can be whoever I want to be and make someone aroused and satisfy
themselves [sic] does make me feel beautiful.’’
Question #3 asked ‘‘Are respondents cheating with people they find on the
internet while in a serious real-life relationship?’’ Table 4 shows the results. Over
63% of our respondents reported that they had cheated online, and almost three-
fourths (73.7%) reported cheating in real life while in a serious relationship. Again,
given the nature of this specific internet site, the percentages are not unexpected.
When we explored a bit further, we found that over 25% of our respondents reported
that their cybersex relationships had either a positive impact (29.5%), or no impact
(32.4%), on their off-line relationships. Only 13.0% reported a negative impact, and
the remaining 25.0% reported they were not sure of the impact.
Table 4 also shows the results of our exploration of whether these results vary by
sex. There is no significant difference in whether males or females are more likely to
cheat both online and in real life while in a serious relationship. Research has found
that people actually believe that if their partner finds someone online, it is cheating
and then they become jealous (de Visser and McDonald 2007; Whitty 2005). Our
respondents had various reasons for cheating. One 66-year-old male states that his
wife had a stroke thus ‘‘leaving me alone with no sex. I have met a woman locally
who accepts me as a frequent fuck buddy, so there is a pot of gold at the end of the
online rainbow.’’ A 65-year-old male states that his ‘‘cybersexual relationships have
helped to become a better lover to my real life partner.’’
What we do not yet know is why people are looking for partners online while still
in a real-life relationship. A 61-year-old female has not actually had sex with
anyone she has met, but states that she ‘‘has never had more fun just talking to
people on the internet dating sites and having men come onto her and flirt with her.’’
It makes her feel good and feel wanted.
Table 5 Sending nude photos by sex by age
19–24 years 25–29 years** 30–39 years** 40–49 years** 50? years*
F (%) M (%) F (%) M (%) F (%) M (%) F (%) M (%) F (%) M (%)
Yes 74 61 77 60 65 54 59 48 43 36
* p \ .05; ** p \ .01
Sexting and Infidelity in Cyberspace 231
123
Does cheating vary by age? Table 6 presents the results.
Unlike sending nude photos through email or on cell phone, cheating does not
decrease by age. In fact, cheating in real-life appears to generally increase with age,
especially for males. Cheating in real-life also increases for females, but only
through the 30s, then begins to decrease a bit. For respondents aged 25–49 years of
age, females have a higher percentage cheating in real-life, but the only significant
difference is in the 30–39 year age group.
For all age groups, our respondents were more likely to cheat in real-life than
online. A 22-year-old female in an open relationship with her partner states that ‘‘he
doesn’t mind if I mess around with girls or flirt with girls in order to have a
threesome with us. He doesn’t even mind if I hook up with girls when he isn’t
around, but has a problem if I hook up with guys.’’ Another female who is 28
believes that Ashley Madison is a great site because ‘‘you meet others in your same
situation that are not looking to leave the person they are with but just are missing
something in their relationship.’’
Females were a bit more likely than males to cheat online, but the only significant
differences were found in the age groups 30–49 years. A number of women
mentioned the fact that they had found their husbands/partners cheating and went
online as a way to get what they felt they were missing. A 36-year-old female states
that after she found her husband cheating, ‘‘online became an outlet and if he can do
it, so can I. It made me feel desired by others when I had been so hurt and betrayed
by my husband.’’ A 42-year-old woman, who had found her husband was cheating
on her, went online and ‘‘at first enjoyed the compliments, then began to talk to a
man. Finally after about 2 months of talking we agreed to meet and have been
seeing each other for 3 months now.’’
While we have explored the issues of sexting and cheating by sex and age, what
other factors affect these behaviors? Question #4 stated ‘‘What are the predictors for
sexting by sex?’’ Because females are significantly more likely than males to be
involved in sexting behavior, we focused our exploration on women. Table 7
presents the results for each sexting behavior for females.
Being unmarried, younger than 40 years of age, being LGBT, or having had
cybersex were the best predictors for sending explicit texts over the cell phone. The
best predictors for sending nude photos through email or cell phone were lower
education, being white, having no religious affiliation, being younger than 50 years
of age, being LGBT, or working at least part time. Being younger than 40 years of
age, working at least part time, or being LGBT were the predictors for both
behaviors. Having had cybersex, however, quintupled the odds for females to send
Table 6 Cheating while in a serious real-life relationship by sex by age
19–24 years 25–29 years 30–39 years 40–49 years 50? years
F (%) M (%) F (%) M (%) F (%) M (%) F (%) M (%) F (%) M (%)
Online 53 40 65 61 70** 60** 71* 66* 53 41
In real-life 59 59 76 67 79* 74* 78 75 73 75
* p \ .05; ** p \ .01
232 D. K. Wysocki, C. D. Childers
123
explicit texts or nude photos over their cell phones or through email, as well as
being involved in both sexting behaviors. One explanation for this may be that sex
on the internet has been in existence for 15 or so years now, and our respondents
may be familiar with the practice of having cybersex. As sexting emerged, and
especially as it is a more portable behavior, our respondents may have shifted their
focus to sexually explicit behavior on cell phones as well as the internet. Being aged
25–29 years or being LBGT almost doubled the odds of females sending nude
photos of themselves through email or on cell phones.
Question #5 asks ‘‘What are the predictors for infidelity by sex?’’. Table 8
presents the findings for females.
For females, higher household incomes, engaging in both sexting behaviors, being
married, and having had cybersex were the best predictors of infidelity, whether
online or in real life. Lower education levels was also a predictor of cheating in real-
life, but not for cheating online. Again, having had cybersex increased the odds the
Table 7 Binary logistic
regression and odds ratios of
sexting behaviors for females
with selected independent
variables
Females B SE Sig. Exp (B)
Sex via texting
Married (1) -.292 .109 .007 .746
Age 40–49 (1) -.357 .116 .002 .700
Age 50? (1) -1.110 .185 .000 .330
LGBT (1) .318 .148 .032 1.374
Had cybersex (1) 1.584 .123 .000 4.877
Constant -1.251 .132 .000 .286
Model correctly predicted 67%/R
2
= .190
Sent nude photos
Education -.127 .062 .040 .881
Age 25–29 (1) .664 .216 .002 1.947
Age 50? (1) -.741 .150 .000 .470
Being white (1) .296 .129 .021 1.345
LGBT (1) .615 .164 .000 1.851
No religious affiliation (1) .259 .113 .022 1.296
Had cybersex (1) 1.138 .106 .000 3.121
Not working (1) -.453 .127 .000 .836
Constant -.134 .209 .522 .875
Model correctly predicted 67%/R
2
= .159
Both behaviors
Age 40–49 (1) -.431 .123 .000 .630
Age 50? (1) -1.180 .208 .000 .307
Had cybersex (1) 1.668 .140 .000 5.301
LGBT (1) .405 .152 .007 1.500
Not working (1) -.390 .143 .006 .677
Constant -1.791 .138 .000 .167
Model correctly predicted 72%/R
2
= ,217
Sexting and Infidelity in Cyberspace 233
123
greatest for each behavior, tripling the odds for cheating online and more than
doubling the odds for cheating in real life. This may be due to the fact that those with
higher education and household incomes are less likely to go to the neighborhood bar
to find someone to sleep with. They may be more careful and more particular about
who they pick to have an affair.
Table 9 presents the findings for infidelity behavior for males. Similar to the
results for females, the best predictor for males cheating online was having had
cybersex, which quintupled the odds, but less than doubled the odds of males
cheating in real life. Being black and being married doubled the odds for males
cheating online. Males with higher education levels, higher incomes, who were
black and/or not white, were more likely to cheat online. Males with lower income
levels, and who were black or Hispanic, and were older than 30 years of age were
more likely to cheat in real life.
Discussion
This project investigated two behaviors commonly associated in today’s society
with the internet: sexting and infidelity. All of our respondents answered an ad on a
website geared towards married people who wanted to find sexual partners outside
of their marriage. Clearly, not all of our respondents were married; approximately
33% of males were unmarried and over 40% of the females were unmarried. Not
everyone was looking for a partner outside of marriage. It appears that some single
people were also exploring the option of finding real-life and/or online sex partners,
possibly with married partners for ‘‘uncomplicated’’ relationships. These findings
support some of the earliest research about sex on the internet (Wysocki 1998),
which found that due to the many time constraints in their lives, people are too busy
Table 8 Binary logistic
regression and odds ratios of
infidelity behaviors for females
with selected independent
variables
B SE Sig. Exp (B)
Cheating online
Income .186 .060 .002 1.205
Married (1) 1.248 .123 .000 3.483
Had cybersex (1) 1.139 .122 .000 3.123
Both sexting behaviors (1) .277 .051 .000 1.319
Constant -1.463 .202 .000 .232
Model correctly predicted 72%/R
2
= .232
Cheating in real life
Education -.208 .018 .004 .812
Income .195 .066 .003 1.215
Married (1) .823 .125 .000 2.277
Both sexting behaviors (1) .316 .049 .000 1.371
Constant .193 .221 .382 1.213
Model correctly predicted 76%/R
2
= .118
234 D. K. Wysocki, C. D. Childers
123
to sexual contacts on a face-to-face basis. It is even more difficult to find someone
face-to-face with very specific sexual ideas and desires.
We were surprised that approximately 75% of our respondents reported a specific
religious affiliation. Catholicism, as well as most Protestant denominations and
many other religions, have strong beliefs and tenets about sex, especially infidelity.
Sexual scripts people have are part of an ‘‘ideal’’ culture which says ‘‘thou shalt not
commit adultery,’’ yet our research shows that in ‘‘real’’ culture, this activity is
occurring by people who state they subscribe to religious beliefs.
Females were much more likely than males to have met someone in person that
they first met online. Given that our female respondents were much less likely to be
married than were males, females may see the internet as an unthreatening way to
find potential real-life partners. They may feel that the internet gives them a chance
to ‘‘get to know’’ someone before meeting in person, and to ‘‘weed out’’ the
undesirables. They may also see the internet as a place to try to recapture the
‘‘euphoria’’ that being in love can produce before the reality of life infringes on that
feeling.
Our analysis showed that respondents were more interested in finding real-life
partners rather than online-only partners. Part of the reason may be that, as
sociologists proclaim, humans are social creatures and, as such, need face-to-face,
physical contact. Both males and females, however, were more likely to want to find
Table 9 Binary logistic
regression and odds ratios of
infidelity behaviors for males
with selected independent
variables
B SE Sig. Exp (B)
Cheating online
Education .150 .054 .005 1.161
Income .359 .055 .000 1.432
Married (1) .957 .100 .000 2.605
Had cybersex (1) 1.373 .297 .000 5.546
LGBT (1) .486 .208 .025 1.842
Protestant (1) -.228 .100 .023 .796
White (1) -.332 .145 .023 1.394
Black (1) .754 .252 .003 2.127
Constant -.2.672 .242 .000 .069
Model correctly predicted 72%/R
2
= .280
Cheating in real life
Income -.315 .050 .000 1.358
Married (1) .643 .096 .000 1.875
Had cybersex (1) .654 .090 .000 1.903
Black (1) 1.091 .314 .001 2.976
Hispanic (1) .586 .282 .044 1.762
Age 30–39 (1) .367 .157 .011 1.488
Age 50? (1) .375 .153 .015 1.454
Constant -1.280 .365 .000 .284
Model correctly predicted 75%/R
2
= .106
Sexting and Infidelity in Cyberspace 235
123
face-to-face sex partners rather than face-to-face dates. Women though were more
likely than males to find real-life dates. Female respondents reported being ‘‘hit on’’
frequently by lots of men who only wanted a cybersex partner. Therefore it appears
it is much easier for women to find real-life dates because they have so many men
from which to choose. A 41-year-old woman stated ‘‘I have found that on this
website a huge disparity in male/female expectations. Most men that respond to my
ad write as if I had hung out a sign that said FREE! Live glory hole!’’
Almost 40% of our respondents were anxious about being caught viewing
sexually explicit materials on the internet, and over 50% removed their cyber-trails.
Many respondents did not want their partners/spouses to find out what they were
doing. Another possible reason that our respondents were likely to remove their
cyber-trail is that roughly 50% of them who work full-time log onto the internet at
work for non-work activities and are afraid of being caught and perhaps fired.
Almost 60% of our respondents have participated in sexting. Just over half of
them have sent a nude photo of themselves through e-mail or by cell phone. Females
were almost 1.5 times as likely as males to do so. While we may expect that this
behavior occurs primarily in younger women, our analysis showed that, while a
smaller percentage of older women did send nude photos, over 50% of women aged
40–49 years did so, and over 40% of women older than 50 years of age did so. As
the technology of social networking changes, females may be using nude photos as
a way to replace the behavior of ‘‘flirting’’ that used to occur in bars between
potential sex partners. However, regardless of their age, they might not realize that
once they hit ‘‘send,’’ they have lost complete control over their photos and
messages which could end up anywhere and accessible to anyone.
Our binary logistic regression analysis showed that having had cybersex
significantly increased the odds for females in both sexting behaviors. From our
analysis, it appears that previously engaging in cybersex might be the first foray into
sex activities on the internet. Age slightly decreased the odds of females engaging in
both behaviors, while homosexuality slightly increased the odds for both behaviors.
Over 2/3 of our respondents have cheated online while in a serious relationships,
and over 3/4 have cheated in real life. While not unexpected given the nature of the
web site, we were surprised by some of the predictors of both behaviors. From our
analysis, previously engaging in cybersex tripled the odds of females cheating
online and quintupled the odds for males who cheated online. Cybersex doubled the
odds for males cheating in real life, but did not show as significant for females
cheating in real life. Similarly, age increased the odds for cheating in real life, but
only for males. Men aged 30–39 years or older than 49 years of age were more
likely to cheat in real life than other age groups. Does this support a ‘‘mid-life’’
crisis? We need further research to explore this possibility.
Ultimately, our research suggests the possibility that as technology changes, the
way that people find each other and the way they attract a potential partner also
changes. Social networking sites, such as AshleyMadison, are increasingly being
used for social contact. However, our analysis also shows that our respondents are
more interested in real-life partners, rather than online-only partners. It seems that,
at some point in a ‘‘relationship,’’ people need the physical, face-to-face contact.
236 D. K. Wysocki, C. D. Childers
123
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