When it's good to feel bad: how responses to virtual environments predict real-life sexual risk-reduction

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Content WHEN IT’S GOOD TO FEEL BAD:
HOW RESPONSES TO VIRTUAL ENVIRONMENTS
PREDICT REAL-LIFE SEXUAL RISK-REDUCTION
by
John L. Christensen
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF ARTS
(PSYCHOLOGY)
August 2007
Copyright 2007 John L. Christensen
ii
Acknowledgements
First and foremost, I would like to thank my committee members: Dr. Lynn
Miller, Dr. Stephen Read, and Dr. Antoine Bechara for their time and guidance. Special
acknowledgement also must be made to Dr. Paul Robert Appleby and Dr. Carlos Gustavo
Godoy for their support, encouragement, and inspiration along the way. I would further
like to single out Dr. Brian Lickel and Dr. Norman Miller for their commitment to
holding me to the highest standards throughout my graduate studies thus far. I feel
fortunate to have had the opportunity to be in the company of my family, friends,
colleagues, and fellow graduate students – all of whom never cease to inspire and
challenged me. Also, my enduring gratitude to Jeff Witzke for his positivity and
understanding, and for reminding me to sometimes take my eyes off the goal to look back
at how far I’ve come in its pursuit.
iii
Table of Contents
Acknowledgements ii
List of Tables iv
Abbreviations v
Abstract vi
Introduction 1
Developmental Considerations in Young MSM’s Risky Decision-Making 2
Socially Optimized Learning in Virtual Environments 4
The Role of Negative Affect in Decision-Making 6
Hypotheses Tested 7
Method 8
Eligibility, Sample Characteristics, and Procedures 8
Experimental Conditions 10
Formative Research, Development, and Production of the Interventions 10
Description of the Interactive Video Interventions 12
Measures 15
Results 17
Preliminary Analyses 17
Main Analyses 18
Discussion 19
Summary of the Findings 19
Anticipatory Negative Emotions in Decision-Making and Learning 21
The Intensity of Negative Affect 22
Developmental Factors 23
Virtual Interactive Communication Interventions 23
Limitations 25
Future Directions 27
Conclusion 28
References 29
iv
List of Tables
Table 1 - Sample Characteristics 8
Table 2 – Means and Standard Deviations of Change in UAI Acts 18
Table 3 - ANOVA for the Effects of Affect and Interactivity on UAI Change 19
v
Abbreviations
AIDS = Acquired Immunodeficiency Syndrome
HIV = Human Immunodeficiency Virus
IAV = Interactive Video
MSM = Men who have Sex with Men
SOLVE = Socially Optimized Learning in Virtual Environments
UAI = Unprotected Anal Intercourse
vi
Abstract
We examined relationships between sexual risk-taking and self-conscious
negative affect following exposure to a narrative-based HIV-prevention video. The
intervention, designed for men who have sex with men, simulates the interpersonal,
emotional, and contextual cues of a sexual scenario. One group viewed an interactive
version of the video in which they actively made decisions. A second group passively
viewed a non-interactive version. Subjects reporting higher levels of post-intervention
negative affect experienced greater subsequent risk-reduction, F(1, 96) = 13.1, p < .001.
This effect was qualified by a significant interaction with interactivity, F(1, 96) = 9.62, p
= .003, such that the relationship between higher negative affect and risk-reduction was
much stronger in the interactive condition. The findings suggest that interactivity plays a
critical role in the intervention’s ability to link affect with subsequent behavior. Unlike
traditional approaches, our intervention may result in the automatic encoding of affective
cautionary signals.
1
Introduction
Since its apex in 1992, AIDS diagnoses have decreased and stabilized at about
40,000 new cases annually (CDC, 2006). Nevertheless, HIV, the virus that causes AIDS,
continues to pose a severe health threat to men who have sex with men (MSM) (CDC,
2004). Although only 5% to 7% of adult males in the United States are MSM, this group
accounted for approximately 70% of all estimated HIV infections in 2004 (CDC, 2004).
Among those 18 to 30, younger MSM engage in more risky sexual behaviors (MacKellar,
et al., 2005; Xia, Osmond, Tholandi, Pollack, Zhou, Ruiz, and Catania, 2006). There are
a number of effective HIV risk-reduction interventions. Most of which focus on
promoting more deliberate, rational decision-making. Yet, as Reyna and Farley (2006)
note in a major recent review of adolescent decision-making, such interventions may be
insufficient given that effective decision-making is often based on non-rational “gist” and
“emotional” reactions within the context of risk. This notion is supported by a
compelling line of research on the role of emotion in decision-making that argues that
“non-conscious biases guide behavior before conscious knowledge does” and, “without
the help of such biases, overt knowledge may be insufficient to ensure advantageous
behavior” (Bechara, Damasio, Tranel, & Damasio, 1997, p. 1293). Unfortunately,
younger MSM typically lack the experience within contexts of risk needed to develop
appropriate “gist” and “emotional” reactions that would prevent risky choices. Thus,
existing attempts at HIV prevention may be less effective with younger MSM (Reyna &
Farley, 2006).
Ideally, we would like to provide experience to younger MSM without exposing
them to the HIV risks associated with that experience. Virtual social environments may
2
prove useful for achieving this goal. In the current work
1
, we consider how an
interactive video (IAV) may “contextualize risk,” providing a virtual environment that
facilitates the learning of risk cues and anticipatory negative emotions that might then
reduce unprotected anal intercourse (UAI) in real life. Specifically, we examine whether
the negative emotions generated in an interactive sexual scenario predict reductions in
subsequent risky sexual behavior.
Below, we first consider the decision-making styles our interventions should take
into account for younger MSM and then discuss an intervention, Socially Optimized
Learning in Virtual Environments (SOLVE), which aims to facilitate the learning of
anticipatory emotions that might reduce UAI for young MSM.
Developmental Considerations in Young MSM’s Risky Decision-Making
Developmental factors have a major impact on risky decision-making patterns.
Although young adolescents generally overestimate their risk (e.g., for contracting HIV),
as they become increasingly sexually active without negative consequences (e.g., testing
positive for HIV), their perceptions of vulnerability diminish in late adolescence (Reyna
& Farley, 2006). This is consistent with recent data suggesting that, among young MSM
(15 to 29), 59% of those who tested positive for HIV perceived that they were at low risk
for infection despite engaging in UAI (MacKellar, et al., 2005). Reyna and Farley
suggest that, because of the lack of explicit negative consequences, young men fail to
develop the “gists” and anticipatory emotional reactions that prevent risky choices. This
suggests that an effective intervention should lead men to develop such “gists” and

1
The project described was supported by Grant Number 1 R01AI052756-01A1 from the NIAID. Its
contents are solely the responsibility of the author and do not necessarily represent the official views of the
NIAID.
3
anticipatory emotions. They argue that if men’s risk-taking is to decrease, it will be
“not out of any conscious deliberation or choice, but because they intuitively grasp the
gists of risky situations, retrieve appropriate risk-avoidant values, and never proceed
down the slippery slope of actually contemplating tradeoffs between risks and benefits”
(Reyna & Farley, 2006, p. 2).
But, a conscious focus on tradeoffs among risks and benefits is an important
aspect of traditional HIV prevention approaches that focus on more “rational decision
making” or conscious behavioral deliberations in making decisions that enhance the
decision-makers’ perceived probability of achieving their goals (Reyna & Farley, 2006).
Unfortunately, for many individuals, including young adults (Lowenstein & Schkade,
1999), the complex of goals in a given situation is dynamic and, at any point in time,
despite one’s initial intentions, immediate goals in the sexual scenario (e.g., avoiding
rejection, achieving pleasure) leading to risk may conflict with (and have more
immediate consequences than (Herrnstein & Prelec, 1992)) long range goals such as
maintaining one’s health (Miller, Bettencourt, DeBro, & Hoffman, 1993).
Traditional interventions do account for significant variance in the change of risky
behavior; however, the amount of variance accounted for is usually small (for reviews
see, Baron & Brown, 1991; Kirby, 2001; Romer, 2003). That is, this type of intervention
may work with some men (e.g., more rational and conscious behavioral deliberators).
Reyna and Farley (2006) suggest that “novel interventions that discourage deliberate
weighing of risks and benefits” by younger MSM “may ultimately prove more effective
and enduring” (p. 2).
4
Furthermore, Reyna and Farley (2006) argue that new interventions should be
crafted for those whose risks are driven by emotions or contextual factors (“risky
reactors”) or have an insufficiently mature “intuitive (gist-based)” ability to detect cues
that signal and thereby allow them to avoid risks (Reyna & Farley, 2006, p. 33). They
argue that “risk reactors” often give “in to temptation or were not thinking at the time of
the decision [and recognize that they] are worse off for having done so” (p. 35). These
“risk reactors” and “intuitive (gist-based) risk avoiders,” they argue, would be better
served by interventions “that stress automatic (non-conscious) encoding of cautionary
cues in the environment (getting the gist of risky situations) and repeated practice at
retrieving and implementing risk-avoiding values in simulated contexts” (p. 33).
Socially Optimized Learning in Virtual Environments
Over the last decade, Socially Optimized Learning in Virtual Environments
(SOLVE) has taken this tack to HIV prevention by simulating the emotional and
contextual features that provide such cues for decision makers who might be reacting to
risk (e.g., risk reactors, gist-based decision makers). SOLVE has done this while also
incorporating traditional behavior change components (e.g., self-efficacy, social norms,
beliefs, perceptions of risk, perceived control) from approaches that may appeal to
rational decision makers, such as cognitive social learning theory (Bandura, 1994),
cognitive behavior theory (Beck, 1970), and the theory of planned behavior (Ajzen, 1985,
1991; Ajzen & Fishbein, 1980). SOLVE affords the opportunity, within the safety of
virtual social environments, to help young men reframe emotional and contextualized
risky situations and/or evoke emotions (e.g., negative emotions associated with risk) that
5
may guide, in a more automatic and risk-reducing way, subsequent safer “real-life”
decisions (e.g., whether to engage in unprotected anal intercourse).
SOLVE integrates multimedia formats (e.g., video, audio, text) and places the
player in an interactive, virtual world that realistically simulates the emotional,
interpersonal, and contextual narratives of sexual scenarios that lead up to “contexts of
risk,” that is, contexts within which the player can make risky virtual decisions. The
SOLVE approach integrates interactive narrative and responsive counselors that stimulate
and co-create memories of events and stories (i.e., scaffold). Players assume the role of
the main character and are encouraged to become engaged and immersed in the virtual
environment, interacting with other characters and making decisions as if it were reality.
Supportive peer counselors scaffold the player’s decision-making and relearning process
by interrupting the narrative at critical points, offering both solicited and unsolicited
advice.
SOLVE has been demonstrated to be an effective HIV-prevention tool. In a
sample of MSM, participants received either a SOLVE intervention combined with in-
person peer counseling or the peer counseling alone (Read, Miller, Appleby, Nwosu,
Reynaldo, & Lauren, 2006). Compared to those who received peer counseling alone,
those additionally receiving the SOLVE intervention significantly reduced risky anal sex
behaviors and increased protected anal sex behaviors. Indeed, SOLVE challenges the
player’s automatic patterns of risky judgment and decision-making while fostering
situated learning of behavioral and self-regulatory skills. Key to these findings we
suspect is that the program is interactive; the participant makes decisions on which he
receives feedback. In the current work, we examine how emotional responses following
6
an interactive intervention (where MSM can actively make their own choices and view
the consequences those decisions) predict change in UAI over 3 months.
The Role of Negative Affect in Decision-Making
SOLVE’s ability to reduce risk-taking may be partially attributed to the fact that it
addresses the role of negative affect in decision-making. SOLVE attempts to challenge
the automatic emotional responses that are elicited during a sexual scenario. There is
considerable evidence suggesting that healthy behavior change can be evoked by
persuasive messages that arouse negative affect (Witte & Allen, 2000). SOLVE
incorporates appeals that may evoke negative affect via the use of loss-frame messages,
which emphasize what one might lose if the behavioral recommendation is not followed.
There is compelling evidence that loss-frame messages are effective when the message
recipient is risk-seeking (Rothman & Salovey, 1997); a recommendation that is consistent
with Prospect Theory (Tversky & Kahneman, 1981). Although loss-frame messages
have frequently been used in health communication research, these are typically used via
mass media and are not intended to be embedded at critical points during which the
message recipient is given the opportunity to rethink the risky decision and choose
differently. SOLVE accomplishes this by introducing virtual peer guides that suspend
the narrative and interject with loss-frame messages at critical “context of risk” decision
points (when the participant has made a risky decision). Thus, we designed the
intervention such that a loss-frame message would be closely contingent and tied to the
cues leading up to the context of risk – attempting to enhance this association and the
emotions that it might evoke.
7
We argue that, following exposure to the SOLVE intervention, a linkage should
be formed that ties the resultant negative affective response to the situational cues present
in the virtual environment. Such linkages should be reinforced and strengthened over the
course of multiple exposures. We further argue that, when situational cues that were
encountered in the virtual environment are subsequently encountered in reality, they
should evoke the newly associated affective response, which should lead to the desired
behavioral outcome (e.g., reduced UAI). That is, a subsequent reduction in sexual risk-
taking should emerge due to associative learning, in which new affective responses (i.e.,
those leading to advantageous decision-making) have been trained.
Hypotheses Tested
The current study examines the relationship between self-conscious negative
emotions following an interactive HIV prevention intervention (where MSM can actively
make their own choices and view the consequences of those decisions) and subsequent
risk behavior 3 months later. We expect this linkage will be formed when participants
have actually made their own decisions within the interactive video condition (IAV)
rather than merely observing the decisions of another MSM passively in a “Yoked”
condition. Our specific hypotheses are listed below:
H
1
: Those who reported higher negative affect post-intervention will have greater
UAI risk reduction (Post intervention UAI – Pre-intervention UAI, or higher negative
numbers associated with reduced risk-taking). Therefore a significant main effect for
affect is predicted.
8
H
2
: In the interactive condition (but not in the Yoked), higher levels of post-
intervention negative affect will be associated with a greater reduction in sexual risk-
taking (UAI). Thus a significant interaction between condition and affect is predicted.
Method
Eligibility, Sample Characteristics, and Procedures
Eligibility. Because this was an intervention designed for younger MSM at risk
for contracting HIV through unprotected anal intercourse (UAI), those eligible to
participate in the longitudinal study were men who had engaged in receptive or insertive
UAI with another man in the past 90 days, were 18 to 30 years old, HIV-negative, had
never used injection drugs, would be in the Los Angeles area for the next 3 months, and
were either African American, Latino, or Caucasian.
Table 1
Sample Characteristics
Sample
(N = 100)
Ethnicity White/Caucasian
Hispanic/Latino
Black/African-American
47%
38%
15%
Sexual Orientation Gay/Homosexual
Bisexual
Man who has sex with men
84%
14%
2%
Median Annual Income $25,001 - $30,000
Median Education Some College
9
Sample characteristics. Table 1 reports the sample characteristics (N = 100).
Participants ranged from 18 to 30 years of age and approximately half (49%) were age
24 or younger. Of these men, 47% were White/Caucasian, 38% were Hispanic/Latino,
and 15% were Black/African-American. The majority self-identified as gay or
homosexual (84%). Of the rest, 14% were bisexual and 2% chose to define themselves
as “a man who has sex with men.” The median personal annual income category for this
group was “$25,001 to $30,000” and the median level of educational attainment was
“some college.”
Procedures. Eligible potential participants were scheduled immediately
following the screening process by phone if recruited via advertisements or in-person if
recruited at a venue or street intercept. They were asked to choose codenames at this
time in an attempt to ensure confidentiality. Session 1 took place at the University of
Southern California in private offices. Participants were introduced to the researchers
and randomly assigned to condition
2
immediately before the informed consent process.
The components of each condition are described in detail below.
Reports of sexual behavior were collected during session 1 and various measures
(e.g., attitudes, behavioral intentions, affect) were assessed pre- and post-intervention.
These measures were collected once more when participants returned for the second

2
These two conditions are part of a larger study in which participants were randomly assigned into one of
four conditions. In addition to the IAV and Yoked conditions discussed here, there was also a control
condition (in which participants did not receive an intervention) and a one-on-one condition in which
participants interacted with a real-life HIV-prevention counselor. Since we are arguing that interactive
decision-making in the context of risk is critical to the effects of interest, it is important to note in neither
the control condition nor the one-on-one condition did participants either actively make decisions or merely
observe a participant making decisions in the emotional “context of risk.”
10
session 3 months later. During the 12-week period between sessions 1 and 2,
participants completed weekly phone-in (or email) sexual behavioral assessments.
Participants received $50.00 for each of the two sessions and $5.00 for each
weekly phone-in completed. $10.00 was given for each eligible participant they referred
to the study, with a maximum of three referrals. Thus, participants completing all phases
of the study received a total of $190.00 in cash.
Experimental Conditions
Overview of the experimental conditions. Two conditions are relevant to the
current work (1) an interactive video condition (IAV) and (2) a Yoked (non-interactive)
condition. In the IAV condition, participants were exposed to the interactive version of
our video intervention. In the Yoked condition, participants were exposed to a factually
equivalent video intervention but, rather than making choices, participants passively
watched a scenario that corresponded to the choices made by a participant in the IAV
condition. That is, these conditions were similar in that decisions were being made in the
“context of risk” but only in one (IAV) did the participant make the decisions for his
character that we have argued are necessary to link emotion to subsequent behavior
change. Below we describe formative research that informed the development of our
intervention. We then briefly describe the intervention content before discussing
dependent measures relevant to the current analyses.
Formative Research, Development, and Production of the Video Interventions
Background and formative research. We produced three separate, but factually
equivalent, versions of the “Virtual Sex Project” HIV prevention video. Each was
tailored to a specific ethnicity: African American, Latino, or Caucasian. We first
11
conducted pilot research to identify the narrative structures of typical MSM sexual
scenarios. This research also allowed us to identify key features of typical sexual
scenarios that might lead up to or precipitate risky behavior (e.g., drug use and UAI).
One-on-one interviews informed the content of the intervention (e.g., setting, characters,
language use, and storyline). These data revealed that sexual encounters and the
narratives that precede them are quite similar for African American, Latino, and
Caucasian MSM in Los Angeles. For example, the two most frequently reported ways in
which men in this sample met a sexual partner were through the Internet and at a bar/club
and, moreover, this was true regardless of participant ethnicity. In addition to preferred
personality and physical features of sexual partners, the data also revealed the most
frequently reported sexual acts (e.g., oral sex, anal sex, and mutual masturbation) and the
most frequently reported ways to bring up the topic of safe sex (e.g., directly, sexual
history, and HIV status). This research served as the foundation for the 3 culturally
tailored scripts.
Development and production. In an attempt to create interventions that would
speak to their intended audiences, the narrative portion of each script was written by an
ethnically matched professional MSM screenwriter. Our research team then wrote and
integrated content that was informed by relevant social science literatures.
Community Advisory Boards (CAB) reviewed the scripts and provided feedback
regarding the realism of the intervention and its sensitivity to the MSM community.
There were two types of boards: leadership CABs (i.e., representatives from community-
based organizations, the entertainment industry, and local businesses frequented by
MSM) and youth CABs (i.e., young MSM, all of whom met the study’s eligibility
12
criteria). During production, the director, producers, and many other key personnel
were members of the MSM community and represented diverse ethnic and racial
backgrounds, continuing to address realism and cultural sensitivity issues.
Description of the Interactive Video Interventions
Traditional intervention components incorporated. SOLVE incorporates
traditional behavior change components (e.g., self-efficacy, social norms, beliefs,
perceptions of risk, perceived control) by employing peer guide characters that speak
directly to the participant in an authoritative yet accepting and caring manner. They
verbalize the risks of engaging in unprotected sex while fostering self-efficacy by
educating the participant about successful HIV prevention practices. Furthermore,
SOLVE affords the opportunity for participants to vicariously observe the behavior of
these peer counselors and other characters (e.g., how to refuse alcohol, drugs, and sex
with partners who resist condom use and how to skillfully initiate and negotiate safer sex
practices). See Appleby et al. (in press), Miller & Read (2005), and Read et al. (2005)
for more detailed explanations of how these theoretical components were implemented.
Intervention messages embedded in the “context of risk.” Unlike in traditional
interventions, guide characters in the IAV can interrupt the participant’s decision-making
process by pausing the action and interjecting at points when the participant is making a
risky decision. During standard interventions, an interventionist (in a one-on-one
session) might role-play a partner during a sexual scenario. But, the action does not
approach the interpersonal and emotional realism of a sexual interaction in real life.
Furthermore, participants neither have the option of actually getting caught up in the
13
ongoing sexual scenario (and a chance to “feel” similar emotions in the context of risk)
nor can they choose to make a risky decision (that could be interrupted).
Loss-frame messages. At such “context of risk” decision points (when the
participant has made a risky decision), the guides provide unsolicited advice in the form
of a loss-frame message. For example, one such message delivered by the SOLVE guide
characters warns, “Some people think Tina, meaning crystal meth, makes sex better but it
really doesn’t because it can keep you and your partner from getting or staying hard.”
We then later review the choices participants made throughout the scenario and offer
advice regarding how things could have gone differently in an attempt to stay safe. This
was done to better link elements in the scenario involving cues before risk, thoughts
during risk, and effects of the decision regarding risk with the goal of making it clear,
although via story, how alternative reactions might produce different effects (and implicit
emotions).
Script and experience of participants. Before the narrative begins, two guide
characters appear on-screen and introduce themselves. Both are knowledgeable about
HIV prevention practices, however, one guide is older and more authoritative than the
other. The younger guide provides a humorous approach to the content. After giving
brief instructions on how to use the video, the guides encourage the player to become
immersed in the virtual environment and assume the role of the main character,
interacting with other men and making decisions as if they were in a real-world scenario.
The guides remind the player that they “will be there when it counts,” offering obligatory
and non-obligatory advice at critical context of risk decision points throughout the
narrative.
14
As the story begins, the player is asked to choose where he would like to meet a
potential sexual partner: at a bar/dance club or via the Internet. The two characters meet
and engage in flirtatious banter as they get to know each other better. Soon it becomes
obvious that both are attracted to each other and are interested in pursuing a sexual
encounter.
Their conversation is interrupted as a peripheral character approaches and offers
the player drugs (i.e., crystal methamphetamine). Three options are available to the
player at this decision point: accept the drugs, decline the drugs, or ask for advice. If the
player accepts the drugs, the guide characters pop-up and provide a mandatory loss-frame
intervention in which they warn of the risks associated with crystal methamphetamine
use, particularly in a sexual context. If the player decides to decline the drugs, the
narrative continues and successful refusal skills are modeled. If the player chooses to ask
for advice, the guide characters appear and offer guidance before encouraging the player
to rethink the decision and make a choice.
The main character agrees to go to his partner’s apartment and is offered an
alcoholic beverage. Three options are available: accept the drink, decline the drink, or
ask for advice. After making this decision, they continue to flirt and get know each other
better. The guide characters then encourage the player to initiate a conversation about
safer sex “before things get too hot and heavy.” The player must decide how he would
like to bring up the topic of safe sex; by discussing it directly, by talking about HIV
status, or by talking about their past relationships/sexual history. If either of the latter
two options are chosen, the player views the appropriate scene and is additionally obliged
15
to view the “direct” discussion of safer sex in an attempt to reiterate the value of such a
frank dialogue.
The characters agree to have safe sex before they proceed to the bedroom. The
player must now choose among sexual activities (i.e., mutual masturbation, oral sex, anal
sex) and, if anal sex is chosen, he must decide whether he would prefer to be the insertive
or receptive partner and whether or not a condom will be used. The guides again interject
with a loss-frame message if a risky decision has been made. As the sexual scenario
proceeds, a player encounters resistance by his partner in terms of the decision the player
has just made (i.e., to use a condom or not). That is, MSM choosing to engage in safe sex
must react to a partner that has changed his mind and now wants to forego condom use.
On the other hand, MSM choosing to engage in unsafe sex must react to a partner that
wishes to follow through with their initial intentions to use a condom. The video closes
following a review of choices made throughout the scenario and suggestions about what
the player could have done to avoid risk-taking.
Measures
Unprotected anal intercourse. Because patterns of unprotected anal intercourse
are different for primary partners (defined in the current study as a man with whom an
MSM is in a relationship for at least 3 months and with whom he shares a special
emotional bond) and non-primary partners (Elford, Bolding, Maguire, & Sherr, 1999),
participants were asked to report the frequency with which they engaged in various anal
sex behaviors with non-primary male partners during the prior 3-months. Individual
measures assessed whether the acts were receptive or insertive and whether they engaged
in protected (i.e., used a condom) or unprotected (i.e., did not use a condom) anal
16
intercourse. Change in UAI for non-primary partners from baseline (assessed before
the intervention) to 3 months after the intervention constitute the primary dependent
measure
3
. Details regarding this measure are provided in the preliminary analyses
section of the results.
Negative affect. We measured affect immediately following the intervention
using Watson and Clark’s (1994) Positive and Negative Affect Schedule Expanded
Version (PANAS-X). The reliability and validity of the PANAS-X is well established
(Watson & Clark, 1994). The 60-item measure consists of words and phrases describing
different emotions and feelings. Participants were instructed to indicate to what extent
they felt this way at the present moment. The 5-point scale was labeled as follows: very
slightly or not at all, a little, moderately, quite a bit, and extremely. Higher values
indicate greater emotional intensity.
A principal components factor analysis with varimax rotation was performed on
the PANAS-X items collected immediately following the intervention. The analysis
resulted in 5 interpretable factors that accounted for 52.2% of the variance. Of these
factors, the one accounting for the most variance (23.3%) was interpreted as relating to
positive affect and had an eigenvalue of 14.2. A second factor was identified as the
“guilt” subscale of the PANAS-X and accounted for the next largest amount of variance
(13.4%) and had an eigenvalue of 8.17. This latter factor is relevant to the current work
and comprised the following items: dissatisfied with self, angry at self, disgusted with
self, guilty, blameworthy, and ashamed. Details regarding the alpha associated with this

3
We also collected data for primary partners (i.e., a partner with whom a subject had been in a relationship
for at least 3 months and shared a special emotional bond) but those data are not reported here.
17
composite for the current sample can be found in the preliminary analyses section of
the results.
Results
Preliminary Analyses
Recruitment and retention. 62% of the sample was recruited in-person at Los
Angeles County venues or street intercepts and 28% responded to online or print
advertisements. Study participants referred the remaining 10%. Retention was 73% and
no significant differences in baseline measures were found between those who completed
and those who chose not to complete one or more components of the study. Similarly,
there were no differences in attrition explained by demographics or condition.
Change score for unprotected anal intercourse. To create a measure of change in
unprotected anal intercourse, we first created a composite of insertive and receptive UAI
for the 3-month period preceding the first session. We created a similar composite for
the 3-month period preceding the second session. We calculated the difference between
UAI at times 1 and 2 by subtracting time 1 scores from time 2 scores. Negative values
indicate reduced risk-taking (the desired health-prevention outcome) and positive values
indicate increased risk-taking. A value of 0 indicates no change in UAI.
Emotion measure: reliability, nature of the variable, and analyses required. In
the current sample, Cronbach’s alpha for the negative affect scale was high (α = .86). As
a whole, our sample reported low to moderate levels of negative affect. Because the
variable was significantly skewed, and remained so even after applying various
transformations, these data violated assumptions of parametric tests. Due to the non-
parametric nature, we dichotomized using a median split. In the resulting variable, we
18
consider “low negative affect” participants to be those reporting little or no negative
affect (i.e., values of 0 or 1 on the PANAS-X scale) and “high affect participants” to be
those reporting all other values.
Table 2
Means and Standard Deviations of Change in UAI Acts (Time 2 – Time 1)
Low Negative Affect High Negative Affect
Interactivity M SD M SD
IAV -.216 3.3 -4.13 2.7
Yoked -1.59 2.2 -1.89 2.1
Note. N = 100.
Main Analyses
We conducted a two-way analysis of variance (ANOVA) for post-intervention
negative affect (low vs. high) and intervention type (IAV vs. yoked) on UAI change (see
table 3). This analysis did not reveal a significant main effect of intervention type on
UAI change F(1, 96) = .555, p = .458. However, in line with H
1
, there was a significant
main effect for negative affect, F(1, 96) = 13.1, p < .001, with high negative affect
participants experiencing greater reduction (time 2-time 1) in UAI (M = -3.01) than low
negative affect participants (M = -.903). See Table 2 for means and standard deviations.
This effect was qualified by a significant interaction with interactivity, F(1, 96) = 9.62, p
= .003 (see Figure 1).
We interpreted the interaction between negative affect and interactivity on UAI
change by performing simple effects analyses. Greater UAI reduction among the high
19
negative affect participants compared to the low negative affect participants was
significant in the IAV condition, t(35) = 4.46, p < .001, but non-significant in the Yoked
condition, t(38) = .477, p = .636. Moreover, there was a significant difference in UAI
change between IAV and Yoked participants who reported low negative affect, t(62) =
2.01, p = .049, as well as a significant difference between IAV and yoked participants
who reported high negative affect, t(28) = -2.67, p = .012.
Table 3
Two-way ANOVA for the Effects of Affect and Interactivity on UAI Change
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model
174.007(a) 3 58.002 7.703 < .001
Intercept
340.237 1 340.237 45.187 < .001
Negative Affect
98.774 1 98.774 13.118 < .001
Interactivity
4.178 1 4.178 .555 .458
Affect * Interactivity
72.419 1 72.419 9.618 .003
Error
722.833 96 7.530
Total
1134.00 100
Corrected Total
896.840 99
a. R Squared = .194 (Adjusted R Squared = .169)
Discussion
Summary of Findings
As predicted, self-conscious negative affect was significantly associated with
changes in post-intervention sexual risk-taking for MSM who actively made choices in
the IAV intervention. In particular, higher levels of negative affect following exposure to
the interactive intervention were associated with a greater reduction in subsequent UAI.
20
Lower levels of post-intervention negative affect were also associated with a decrease
in risk-taking, although this reduction in risk-taking was small. Our findings suggest that
giving participants the opportunity to engage in active decision-making plays a key role
in the current intervention’s ability to foster connections between negative affect and
sexual risk-taking.
Figure 1
The Interaction Between Negative Affect and Interactivity on UAI Change
-4.5
-4
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
IAV Yoked
UAI Change
Low Negative
Affect
High Negative
Affect
Note. Higher negative numbers indicate greater UAI risk reduction; the desired behavioral outcome).
Below, we consider anticipatory negative emotions in the contexts of decision-
making and learning. We relate the current study to dominant perspectives in this
domain and discuss the role of negative affect, particularly fear. We then discuss the role
21
of developmental factors and interactivity before addressing limitations of the current
study and possible future directions.
Anticipatory Negative Emotions in Decision-Making and Learning
Compelling evidence suggests that affect plays a critical role in judgment and
decision-making processes (Damasio, 2000; Panksepp, 1998; Rolls, 1999). A dominant
perspective is the somatic marker hypothesis, which posits that emotions and feelings are
types of somatic responses that mark a situation as good or bad (Bechara, Damasio, &
Damasio, 2000; Damasio, 2000; Damasio, Everitt, & Bishop, 1996). When the situation
recurs, these affective markers assist decision-making under circumstances of conflict or
uncertainty and may operate either consciously or non-consciously. That is, anticipatory
emotions serve a socially adaptive function insofar as they may automatically elicit
advantageous behavioral responses in social situations (Frijda, 1986; Keltner & Gross,
1999; Levenson, 1994; Oatley & Johnson-Laird, 1996; Plutchik, 1979).
There is also evidence suggesting an association between emotional learning and
the brain reward system (for a review, see Milner, 1991). Dopamine drives the system
and serves as a powerful reinforcement for learning both positive and negative behaviors.
Although emotional cues associated with rewards such as social acceptance and praise
reliably activate the system, affect caused by sexual arousal elicits a much stronger effect
(Thompson & Madigan, 2005). SOLVE takes into consideration these and other
processes that may foster chronic sexual risk-taking in some men if risky behaviors and
their associated affective responses remain unchallenged.
22
The Intensity of Negative Affect
Reviews of the health communication literature reveal that, compared to messages
eliciting low or moderate levels of negative affect, those that elicit a more intense
emotional experience tend to be more persuasive (Witte & Allen, 2000; Boster &
Mongeau, 1984; Sutton, 1982; Hale & Dillard, 1995). They do warn of a curvilinear
relationship, however, in which low-level affective appeals are likely to be ineffective
because they fail to evoke enough affect and appeals eliciting high levels of affect are
likely to backfire, resulting in “maladaptive fear control actions such as defensive
avoidance or reactance” (Witte & Allen, 2000). Negative affect, as measured by
PANAS-X subscales, was largely in the moderate range for MSM in the current study
and so it remains unclear if higher levels of intervention-induced negative affect would
enhance or inhibit our effects. After reviewing the literature, it also remains unclear how
message recipients differ in terms of their emotional responses to loss-frame messages
and, consequently, we plan to systematically examine how the nature of our manipulation
impacts perceived emotion.
Perceptions of self-efficacy. It has been argued that, for strong affective appeals
to be persuasive, they must also elicit perceptions of self-efficacy in the message
recipient (Witte & Allen, 2000; Boster & Mongeau, 1984; Sutton, 1982; Hale & Dillard,
1995). We do provide such training in the current intervention, however, we have not yet
examined how participants’ perceptions of self-efficacy before, or as a result of the
intervention, are associated with behavior change.
Perceived affect between conditions. We found no differences between
participants in the IAV and Yoked conditions in a comparison of post-intervention
23
negative affect. Consequently, the link between negative affect and subsequent
reductions in risk-taking (for younger MSM) cannot be explained by such differences.
Active decision-making in the “context of risk,” rather than simply viewing the same
interactive video with someone else’s choices, apparently served to create a linkage
between affect and subsequent behavior.
Developmental Factors
Under optimal conditions, adolescents are capable of engaging in rational
decision-making, however, “in the heat of passion, on the spur of the moment, in
unfamiliar situations, when trading off risks and benefits favors bad long-term outcomes,
and when behavioral inhibition is required for good outcomes, adolescents are likely to
reason more poorly than adults” (Reyna & Farley, 2006, p. 12). For these reasons,
interventions designed to emphasize conscious beliefs, deliberate tradeoffs, and
behavioral intentions might be effective only for more mature audiences and should be
augmented if they are to be successful for those who have not yet developed the self-
regulatory abilities to avoid risk via rational deliberation. We plan to further examine
how our intervention is impacted by developmental factors that influence sexual risk-
taking and rational decision-making by MSM in contexts of risk.
Virtual Interactive Communication Interventions
From the virtual to the real. SOLVE differs from traditional interventions by
incorporating interactive narratives that allow the player to directly influence the story’s
outcome by actively making choices for the main character. It is clear that interactivity
plays a vital role in SOLVE’s ability to foster associative learning. Perhaps this is
because a truly engaging interactive environment may serve to blur the boundaries
24
between what is virtual and what is real. Taking a more agentic role in the virtual
decision-making process may intensify the player’s feeling of being immersed in the
environment and, with this heightened sense of immersion, the player may be more likely
to attend to and feel responsible for the outcomes resulting from the choices he has made.
The current work supports this notion by suggesting that individuals’ reactions in
virtual environments can have an impact on real-life decision-making. These findings are
supported by a recent study providing evidence of “parallel play” in virtual environments
(Godoy, Appleby, Christensen, Miller, & Read, 2006). That is, behavioral choices made
by individuals in these environments were strongly associated with their prior and
subsequent real-life behaviors. They are also consistent with Gilbert’s (1991) argument
that, “when absorbed in health simulations, people can forget that the outcomes are
defined by the interventions because their minds are so busy processing other aspects of
the experience their natural inclination is to assume the simulation is accurate.”
It is important to note that some individuals may respond more favorably to non-
interactive narratives rather than those requiring active decision-making. Research
suggests that “individuals with lesser cognitive capacity feel more entertained, that is,
they feel more empathic toward the protagonist, feel more suspense, and evaluate the
movie more positively when they watch it without any interactivity, in the traditional
passive manner” (Vorderer, Knobloch, and Schramm, 2001). In contrast, individuals
with higher cognitive capacities react more positively to interactive narratives in which
they are able to directly influence the plot (Vorderer, Knobloch, and Schramm, 2001).
The SOLVE approach affords the opportunity to take these findings into consideration
when tailoring future interventions to specific audiences.
25
Incorporating elements from earlier “rational” approaches. In addition to
incorporating elements from traditional HIV prevention interventions (e.g., self-efficacy,
behavioral intentions, social norms, beliefs, perceptions of risk, perceived control, refusal
skills, and negotiation skills), SOLVE also incorporates effective elements that are not
found in standard approaches. SOLVE allows individuals to actively make decisions in
environments that simulate the emotional and situational features of real-world social
scenarios. Moreover, SOLVE guides strategically interrupt participants’ risky decisions
with messages mapping onto their specific choices. The guides then review these choices
at the end of the intervention and model alternative behaviors when appropriate. It
remains unclear to what extend the current findings go beyond what might have been
found within a traditional intervention condition. We have included a standard control as
well as a one-on-one intervention control condition for this reason. Although we have
just begun to examine these conditions in our comparisons, initial analyses suggest that
affect is not significantly associated with subsequent sexual risk-taking for younger or
older MSM in either of these conditions, both of which lack interactive components.
Limitations
Scenario and venue limitations. Budgetary constraints limited the number of
scenarios we could simulate in the virtual environment. Formative research revealed the
numerous ways in which MSM meet sexual partners; however, we could only include the
two most frequently reported venues. The narrative depicted in the intervention is
consequently one in which the main character must choose to meet a sexual partner in
either a bar/club atmosphere or online. Those who typically meet sexual partners in other
26
ways (e.g., through friends, bathhouses, sex clubs, or community activities) may be
less invested in the narrative as a result.
The current work is further limited insofar as there was only sufficient time
during the intervention for men to view a single scenario. It is unclear if risk reduction
could be enhanced via multiple exposures to either the same scenario or to different
scenarios. Perhaps risk reduction could be enhanced if men had more exposure to a
greater number of intervention components within a variety of scenarios and venue
contexts. It also remains unclear whether the intervention is more effective when men
are exposed to scenarios and venues in the intervention that closely map onto subsequent
real-life encounters. We plan to take into account how the choices men make in the
intervention relate to subsequent real-life choices. That is, we will assess outcomes
(UAI) for men who met sex partners in ways that were more similar or less similar to
those depicted in our intervention.
Limited partner interaction types. In the current intervention, we chose to depict
a scenario in which MSM interacted with a new sexual partner. We did not have the
resources to also create scenarios that depicted sexual risk taking with long-term partners.
Hence, the story may not ring true with men who are currently in romantic relationships
or with men who have repeated encounters with familiar non-primary partners.
Game limitations in customizing preferences. The current SOLVE intervention
was limited insofar as there were no opportunities for the player to customize preferences
and features of the environment or characters. Such customization might enhance
immersion via perceived realism of the intervention. We plan to address this limitation
by creating future SOLVE interventions that are based in video game-like virtual
27
environments. This new approach would utilize customizable virtual agents rather
than filmed human actors, which are used in the current DVD format. The use of virtual
agent technology is advantageous because it allows researchers (or the players
themselves) to modify the environment with relative ease. The narrative can be
personalized based on characteristics of the target audience (e.g., age, class, relationship
status). Men should be more likely to identify with and assume the role of a character
that is similar in terms of physical features (e.g., ethnicity, hair color, and body type).
Moreover, engagement and sexual arousal are likely to be increased if the player is able
to “design” his ideal partner by choosing preferred physical and personality
characteristics. Personalization such as this is important in that it increases the likelihood
of immersion in the virtual environment, which may, in turn, be associated with
attenuated risk-taking.
Generalizations to other populations. In the current work, we produced three
factually equivalent video interventions and each was tailored to a different ethnicity:
African-American, Latino, and Caucasian. The impact of ethnic differences in our
effects remains unclear at present because the study is in progress and we currently lack
the sample size needed to make such comparisons. When a sufficient sample size has
been obtained, we plan to assess the extent to which ethnicity influences subsequent
reductions in UAI.
Future Directions
As a health communication tool, the use of virtual environments is valuable
because it provides social scientists with the opportunity to create SOLVE interventions
that might speak to a wider range of audiences. This approach is doubly valuable as a
28
research tool insofar as it allows investigators to strategically manipulate experimental
variables in controlled social environments. Future studies might use these SOLVE
environments to address research questions arising from the current study. One such
study might further investigate the role of interactivity in SOLVE’s ability to reduce risk-
taking. Are there individual difference variables that might predict for whom active
decision-making is better suited? Under what circumstances might one benefit from
passively watching a narrative rather than actively taking a first person perspective?
Another set of questions serves to shed light upon the role of affect in the decision-
making process. How exactly does emotion operate in this context? Is there an ideal
amount of negative affect that should be evoked and how might this differ across
individuals? Do other types of affect (e.g., positive, sexual arousal) interfere with or
inhibit the effects of negative emotions, thereby reducing the intervention’s
effectiveness? If so, how might this concern impact the design of future interventions?
Conclusion
In sum, the limited success of conventional health interventions may be due to the
fact that they have traditionally ignored the emotional and developmental factors that
influence some men’s risk-taking behaviors. SOLVE builds upon prior HIV prevention
efforts by incorporating, not only elements from traditional approaches, but also those
that may challenge and train the automatic encoding of contextual cautionary signals.
Thus, the current approach may serve to benefit a previously overlooked group of
individuals who engage in risk-taking, not as a result of conscious or rational decision-
making, but because they have not yet learned to intuitively perceive and avoid risks in
social situations.
29
References
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl &
J. Beckmann (Eds.), Action-control: From cognition to behavior (pp. 11-39).
Heidelberg, Germany: Springer.
Ajzen, I. (1991). The theory of planned behavior. [Special Issue: Theories of cognitive
self-regulation]. Organizational Behavior and Human Decision Processes, 50,
179-211.
Appleby, P. R., Godoy, C., Miller, L. C., & & Read, S. J. (In press). Reducing Risky Sex
Through the Use of Interactive Video Technology. In T. Edgar, S. M. Noar & V.
S. Freimuth (Eds.), Communication perspectives for HIV/AIDS in the 21st
century. Mahwah, NJ: Lawrence Erlbaum Associates.
Appleby, P. R., Miller, L. C., & Ayala, A. (2003). Why methamphetamine contributes to
risky sex for MSM. (Tech. Rep.). Los Angeles, California: University of Southern
California, Annenberg School for Communication.
Appleby, P. R., Miller, L. C., & Rothspan, S. (1999). The paradox of trust for male
couples: When risking is a part of loving. Personal Relationships, 6, 81-93.
Azjen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior.
Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A. (1994). Social cognitive theory and the exercise of control over HIV
infection. In R. J. DiClemente & J. L. Peterson (Eds.), Preventing AIDS: Theories
and methods of behavioral interventions (pp. 25-59). New York: Plenum Press.
Baron, J., & Brown, R. V. (1991). Teaching decision making to adolescents. Hillside, NJ:
Erlbaum.
Bechara, A., Damasio, H., & Damasio, A. R. (2000). Emotion, Decision Making and the
Orbitofrontal Cortex. Cerebral Cortex, 10(3), 295-307.
Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding
advantageously before knowing the advantageous strategy. Science, 275(5304),
1293-1294.
Beck, A. T. (1970). Cognitive therapy: Nature and relation to behavior therapy. Behavior
Therapy, 1(2), 184-200.
Blascovich, J., Loomis, J., Beall, A., Swinth, K., Hoyt, C., & Bailenson, J. (2002).
Immersive virtual environment technology as a research tool for social
psychology. Psychological Inquiry, 13, 103-125.
30
Boster, F. J., & Mongeau, P. (1984). Fear-arousing persuasive messages. In R. N.
Bostrom & B. H. Westley (Eds.), Communication Yearbook 8 (pp. 330-375).
Beverly Hills, CA: Sage.
CDC. HIV/AIDS among Men Who Have Sex with Men [fact sheet]. Retrieved 102006,
from http://www.cdc.gov/hiv/resources/factsheets.
CDC. Methamphetamine and HIV risk among men who have sex with men [fact sheet].
Retrieved 102006, from http://www.cdc.gov/hiv/resources/factsheets.
CDC. (2003). Increases in HIV diagnoses–29 states, 1999-2002. MMWR, 52, 1145-1148.
CDC. (2005). HIV/AIDS Surveillance Report, 2004 (Tech. Rep. No. 16, pp. 1-46).
Atlanta: US Department of Health and Human Services, CDC.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple
regression/correlation analysis for the behavioral sciences (3rd. ed.). Mahwah,
NJ: Erlbaum.
Cronbach, L. J., & Furby, L. (1970). How we should measure "change": Or should we?
Psychological Bulletin, 74(1), 68-80.
Damasio, A. R. (2000). The feeling of what happens: Body and emotion in the making of
consciousness. New York: Harcourt.
Damasio, A. R., Everitt, B. J., & Bishop, D. (1996). The Somatic Marker Hypothesis and
the Possible Functions of the Prefrontal Cortex [and Discussion]. Philosophical
Transactions: Biological Sciences, 351, 1413-1420.
Elford, J., Bolding, G., Maguire, M., & Sherr, L. (1999). Sexual risk behaviour among
gay men in a relationship. AIDS, 13, 1407-1411.
Frijda, N. H. (1986). The emotions. Cambridge, England: Cambridge University Press.
Gilbert, D. T. (1991). How mental systems believe. American Psychologist, 46(2), 107-
109.
Godoy, C., Appleby, P. R., Christensen, J. L., Miller, L. C., & Read, S. J. (in
preparation). Using Virtual Environments to Unobtrusively Measure Real Life
Risk Taking: Findings and implications for health communication interventions.
Hale, J. L., & Dillard, J. P. (1995). Fear appeals in health promotion campaigns: Too
much, too little, or just right? In E. Maibach & R. L. Parrott (Eds.), Designing
Health Messages (pp. 65-80). Thousand Oaks, CA: Sage.
31
Hebb, D. O. (1949). The organization of behavior: A neuropsychological theory. New
York: Wiley.
Herrnstein, R. J., & Prelec, D. (1992). A theory of addiction. In G. Loewenstein & J.
Elster (Eds.), Choice over time (pp. 331-360). New York: Russell Sage
Foundation.
Keltner, D., & Gross, J. J. (1999). Functional accounts of emotion. Cognition and
Emotion, 13, 467-480.
Kirby, D. (2001). Understanding what works and what doesn't in reducing adolescent
risk-taking. Family Planning Perspectives, 33, 276-281.
Leeper, R. W. (1948). A motivational theory of emotion to replace 'emotion as
disorganized response. Psychological Review, 55(1), 5-21.
Levenson, R. (1994). Human emotion: A functional view. In P. Ekman & R. J. Davidson
(Eds.), The Nature of Emotion: Fundamental Questions (pp. 123-126). New York:
Oxford University Press.
Lowenstein, G., & Schkade, D. A. (1999). Wouldn't It Be Nice? Predicting Tastes and
Feelings. In D. Kahneman, E. Diener & N. Schwartz (Eds.), Well Being: The
Foundations of Hedonic Psychology. Russell Sage Foundation.
MacKellar, D. A., Valleroy, L. A., Secura, G. M., Behel, S., Bingham, T., Celentano, D.
et al. (2005). Unrecognized HIV Infection, Risk Behaviors, and Perceptions of
Risk Among Young Men Who Have Sex With Men: Opportunities for Advancing
HIV Prevention in the Third Decade of HIV/AIDS. Journal of Acquired Immune
Deficiency Syndrome, 38(5), 603-614.
Mansergh, G., Colfax, G. N., Marks, G., & et al. (2001). The Circuit Party Men’s Health
Survey: Findings and implications for gay and bisexual men. American Journal of
Public Health, 91, 953-958.
Miller, L. C., Bettencourt, B. A., DeBro, S. C., & Hoffman, V. (1993). Negotiating safer
sex: Interpersonal dynamics. In J. B. Pryor & G. D. Reeder (Eds.), The social
psychology of HIV infection (pp. 85-123). Hillsdale, NJ: Lawrence Erlbaum
Associates, Inc.
Miller, L. C., & Read, S. J. (2005). Virtual Sex: Creating Environments for Reducing
Risky Sex. In S. Cohen, K. Portnoy, D. Rehberger & C. Thorsen (Eds.), Virtual
Decisions: Digital Simulations for Teaching Reasoning in the Social Sciences and
Humanities. Mahway, NJ: Lawrence Erlbaum.
32
Milner, P. M. (1991). Brain-stimulation reward: A review. Canadian Journal of
Psychology, 45, 1-36.
Oatley, K., & Johnson-Laird, P. N. (1996). The communicative theory of emotions:
Empirical tests, mental models, and implication for social interaction. In L. L.
Martin & A. Tesser (Eds.), Striving and Feeling: Interactions among goals, affect,
and self-regulation (pp. 363-393). Mahwah, NJ: Lawrence Erlbaum Associates.
Panksepp, J. (1998). Affective Neuroscience. New York: Oxford University Press.
Plutchik, R. (1979). A Psychoevolutionary Synthesis. New York: Addison-Wesley.
Read, S. J., Miller, L. C., Appleby, P. R., Nwosu, M. E., Reynaldo, S., Lauren, A. et al.
(2006). Socially Optimized Learning in a Virtual Environment: Reducing Risky
Sexual Behavior Among Men Who Have Sex With Men. Human Communication
Research, 32(1), 1-34.
Reyna, V. F., & Farley, F. (2006). Risk and Rationality in Adolescent Decision Making.
Psychological Science in the Public Interest, 7(2), 1-44.
Rolls, E. T. (1999). Brain and Emotion. Oxford: Oxford University Press.
Romer, D. (2003). Reducing adolescent risk: Toward an integrated approach. Thousand
Oaks, CA: Sage Publications.
Rothman, A. J., & Salovey, P. (1997). Shaping perceptions to motivate healthy behavior:
The role of message framing. Psychological Bulletin, 121(1), 3-19.
Sutton, S. R. (1982). Fear-arousing communication: A critical examination of theory and
research. In Eiser J. R. (Ed.), Social Psychology and Behavioral Medicine (pp.
303-337). London: Wiley.
Thompson, R. F., & Madigan, S. A. (2005). Memory: The Key to Consciousness.
Washington, DC: Joseph Henry Press.
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of
choice. Science, 211(4481), 453-458.
Vorderer, P., Knobloch, S., & Schramm, H. (2001, vol 3, part 4). Does Entertainment
Suffer From Interactivity? The Impact of Watching an Interactive TV Movie on
Viewers' Experience of Entertainment. In Media Psychology (pp. 343-364).
Lawrence Erlbaum Associates.
Watson, D., & Clark, L. A. (1994). The PANAS-X: Manual for the Positive and Negative
Affect Schedule - Expanded Form., University of Iowa, Iowa City, IA.
33
Witte, K., & Allen, M. (2000). A Meta-Analysis of Fear Appeals: Implications for
Effective Public Health Campaigns. Health Education & Behavior, 27(5), 591-
615.
Wolitski, R. J., Valdiserri. (2001). Are we headed for a resurgence of the HIV epidemic
among men who have sex with men? American Journal of Public Health, 91,
883-888.
Xia, Q., Osmond, D. H., Tholandi, M., Pollack, L. M., Zhou, W., Ruiz, J. D. et al. (2006).
HIV Prevalence and Sexual Risk Behaviors Among Men Who Have Sex With
Men: Results From a Statewide Population-Based Survey in California. Journal
of Acquired Immune Deficiency Syndromes, 41(2), 238-245.

Abstract (if available)

Abstract We examined relationships between sexual risk-taking and self-conscious negative affect following exposure to a narrative-based HIV-prevention video. The intervention, designed for men who have sex with men, simulates the interpersonal, emotional, and contextual cues of a sexual scenario. One group viewed an interactive version of the video in which they actively made decisions. A second group passively viewed a non-interactive version. Subjects reporting higher levels of post-intervention negative affect experienced greater subsequent risk-reduction, F(1, 96) = 13.1, p < .001. This effect was qualified by a significant interaction with interactivity, F(1, 96) = 9.62, p = .003, such that the relationship between higher negative affect and risk-reduction was much stronger in the interactive condition. The findings suggest that interactivity plays a critical role in the intervention's ability to link affect with subsequent behavior. Unlike traditional approaches, our intervention may result in the automatic encoding of affective cautionary signals.

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Using virtual environments to unobtrusively measure real-life risk-taking: findings and implications for health communication interventions

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Creator Christensen, John L. (author)

Core Title When it's good to feel bad: how responses to virtual environments predict real-life sexual risk-reduction

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 07/25/2007

Defense Date 07/02/2007

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag anticipatory emotion,condom,Decision making,Gay,HIV,interactivity,intervention,MSM,negative affect,OAI-PMH Harvest,risk taking,Sex,somatic,Video,virtual

Language English

Advisor Miller, Lynn Carol (committee chair), Bechara, Antoine (committee member), Read, Stephen J. (committee member)

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