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Breaking it down to make it stronger: examining the role of source credibility and reference group specificity in the influence of personalized normative feedback on perceived alcohol use norms a...
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DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 1
Breaking it Down to Make it Stronger: Examining the Role of Source Credibility and Reference
Group Specificity in the Influence of Personalized Normative Feedback on Perceived Alcohol
Use Norms and Intentions to Drink
Justin F. Hummer
Second Year Project
University of Southern California
Committee:
Chair: Gerald C. Davison, Ph.D., Professor of Psychology and Gerontology, University of
Southern California
Carol Prescott, Ph.D., Professor of Psychology, University of Southern California
Richard John, Ph.D., Associate Professor of Psychology, University of Southern California
Acknowledgment:
I wish to extend my sincere gratitude to the following research assistants who assisted with the
design of intervention materials and data collection: Artemis Zavaliangos-Petropulu; Hannah
McCaleb; Mary Hakimeh
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 2
Table of Contents
Abstract 3
Introduction 5
Social Norms and College Student Drinking 5
Social Norms Alcohol Interventions for College Students 6
Data Source Credibility 8
Reference Group Specificity 10
Addressing Potential Barriers through Experimental Manipulation 11
Current Study and Hypotheses 11
Methods 12
Participants 13
Research Design 13
Procedures 15
Measures 18
Analytic Plan 20
Results 21
Supplementary Analyses 27
Discussion 27
Implications of Significant Findings 29
Interpretations via the Social Norms Theoretical Framework 30
Limitations 31
Conclusions 33
Tables 1-3 35
Figure 1 38
References 39
Appendices
Appendix A: Standard Drink Definition 47
Appendix B: PNF Intervention Script 48
Appendix C: Example Feedback Slides 51
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 3
Abstract
Objective: The present research examines the roles of data source credibility and reference
group specificity in the effectiveness of a simulated personalized normative feedback
intervention to reduce perceived drinking norms of other students and decrease individuals’ own
intentions to drink. Method: Following completion of an online pre-intervention survey and
using a 2x2 between-subjects experimental design, 104 college student drinkers were randomly
assigned to one of four experimental intervention conditions: two source credibility conditions
concerning the validity of the data on which the group norm was based (high credibility, low
credibility) and two specificity conditions (high specificity, low specificity) representing two
different reference groups for which normative feedback was provided (i.e., a typical American
college student or a same-gender/same-class year USC student). Participants then completed a
post-intervention questionnaire to assess for changes in study outcomes. Results: A series of
multiple regression models was used to evaluate condition effects on the three main post-
intervention outcomes of perceived total drinks per week of American college students (Model
1), perceived total drinks per week of USC students (Model 2), and intended drinks per week
(Model 3). For Model 1, a significant main effect was found for the credibility condition (β = -
.27, p = .01). For Model 2, a significant main effect was found for the reference group condition
(β = -.19, p = 04). In Model 3, no condition effects emerged as significant. No significant
condition interaction effects were present in any of the models. Conclusions: The findings
suggest that the credibility of the data source used in the provision of normative feedback is of
importance for decreasing perceived drinking norms of the more distal American college student
reference group, while the specificity of the reference group used in the PNF intervention had a
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 4
stronger impact on reducing perceived drinking norms of students at one’s own university who
are of the same gender and class year as the participant.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 5
Breaking it Down to Make it Stronger: Examining the Role of Source Credibility and Reference
Group Specificity in the Influence of Personalized Normative Feedback on Perceived Alcohol
Use Norms and Intentions to Drink
Problematic drinking by college students is a national health concern with significant
negative consequences for drinkers themselves (e.g., poor grades, disciplinary sanctions,
accidental injury, death) as well as others and the larger community (e.g., fights, sleep/study
disruption, sexual assaults, having to care for an intoxicated student, property damage) (Hingson,
Heeren, Winter, & Wechsler, 2005; Hingson, Zha, & Weitzman, 2009). Almost half of college
students (44.7%) report heavy episodic (i.e., “binge”) drinking in the last month; one in three
(28.9%) reports driving under the influence of alcohol, and in 2005 alone, approximately 1,825
students died due to unintentional, alcohol-related injuries (Hingson et al., 2009). Researchers
and personnel at institutions of higher education (IHE’s) have developed and implemented
numerous individual and group-based interventions to reduce alcohol harm (Larimer & Cronce,
2007). Despite substantial efforts focused on prevention, rates of high-risk drinking among
college students have remained elevated (Borsari, Murphy, & Barnett, 2007; O’Malley &
Johnston, 2002; Wechsler & Nelson, 2008). The current study describes an experimental
examination of factors that may strengthen or weaken the efficacy of a widely used intervention
approach to curb college student drinking.
Social Norms and College Student Drinking
As is the case in other behavioral domains, social influences are consistent predictors of
heavy drinking among college students (Borsari & Carey, 2003; Perkins, 2002), and perceptions
of the prevalence and acceptability of alcohol use among peers (perceived norms) influence
personal decisions about when and how much to drink (Berkowitz, 2004). Perceived norms are
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 6
classified as either descriptive (what people actually do; behavior) or injunctive (what people
feel is correct/level of acceptability or approval of certain behaviors; attitudes) and may function
differently in both the initiation and continuation of drinking (Lee, Geisner, Lewis, Neighbors, &
Larimer, 2007; Rimal & Real, 2003). Students consistently and overwhelmingly overestimate the
drinking norms of other students (how much students in general and more proximal peer groups
drink) (Borsari & Carey, 2003; Larimer et al., 2009; Neighbors, Lee, Lewis, Fossos, & Larimer,
2007; Perkins, Haines, & Rice, 2005). In fact, nationwide data indicate that approximately seven
in ten students overestimate the amount of alcohol consumed by typical students at their college
(Perkins et al., 2005). Perceived descriptive norms account for more variance in alcohol use than
sex, affiliation with Greek letter organizations, alcohol expectancies, or drinking motives
(Neighbors et al., 2007). This strong prognostic factor offers an ideal target for intervention
strategies seeking to reduce problematic drinking.
Social Norms Alcohol Interventions for College Students
Social norms-based interventions have grown popular at IHE’s and have attempted to
correct students’ misperceptions regarding the prevalence of heavy drinking by providing them
with information regarding the actual prevalence of drinking among fellow students (Larimer &
Cronce, 2007). They typically focus on the distinction between actual behavior of others and
perceived norms since (1) perceived rather than actual norms directly influence behavior (Rimal
& Real, 2003; 2005) and predict alcohol-related consequences even after controlling for level of
consumption (LaBrie, Hummer, Neighbors, & Larimer, 2010), and (2) discrepancies between
perceived and actual norms are consistently associated with alcohol use, with larger
discrepancies related to higher rates of alcohol use (Larimer, Turner, Mallett, & Geisner, 2004;
Lewis & Neighbors, 2004; Reis & Riley, 2000). However, while a student may have larger
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 7
discrepancies between perceived and actual behavior of a more distal reference group (e.g., “a
typical college student in general”), misperceptions of behavior for more proximal and
meaningful reference groups (e.g., “a typical female college student at your university”) have
greater influence over one's own behavior (e.g., Borsari & Carey, 2003; Korcuska & Thombs,
2003; Latane, 1981; Neighbors et al., 2010). Interventions aimed at correcting normative
misperceptions have shown promise at reducing drinking and negative consequences among
college students (e.g., LaBrie, Hummer, Neighbors, & Pedersen, 2008; Neighbors, Larimer, &
Lewis, 2004; Walters, 2000). Social norms interventions typically come in one of two forms
which have been more or less effective depending on several factors: social norms marketing
(SNM) or personalized normative feedback (PNF).
SNM approaches rely on mass communication methods for educating students regarding
actual drinking behaviors utilizing national or campus-specific drinking statistics. As early as
2000, they were being implemented at nearly 25% of IHE’s as a primary technique designed to
address heavy drinking (Wechsler, Lee, Kuo, & Lee, 2000). The evidence for the effectiveness
of this approach has been mixed (e.g., Perkins & Craig, 2006; Wechsler et al., 2003) with more
recent research calling attention to factors necessary to be in place if there is to be an expectation
for intervention efficacy (DeJong et al., 2006; DeJong et al., 2009; Perkins, LinkenBach, Lewis,
& Neighbors, 2010). For example, in order for a SNM campaign to have any chance at changing
behavior, the messages presented as part of the campaign must be viewed by the target audience
with sufficient dosage to ensure viewers actively process the information, especially considering
the prevalence of competing messages (popular media glorifying alcohol use, peer influence,
etc.). Moreover, changing perceived norms is a prerequisite for social norms interventions to
impact behavior, yet previous research studies that found no support for SNM have often not
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 8
evaluated the extent to which the intervention was implemented effectively, whether the intended
audience actually viewed the message, and whether failure to achieve desired outcomes was
related to a failure to reduce normative perceptions.
By contrast, PNF is one-time individually delivered information designed to correct
normative misperceptions. Typical PNF contains the individual’s own drinking behavior, his or
her perceptions of others’ drinking behavior, and others’ actual drinking behavior (Lewis &
Neighbors, 2006). Individual PNF appears more effective than social norms marketing
campaigns (Lewis & Neighbors, 2006), and to date, several intervention trials support the
efficacy of stand-alone PNF interventions to reduce normative misperceptions and alcohol use
(for review, see Zisserson, Palfai, & Saitz, 2007). In light of the early success of PNF
interventions and the potential for this approach to replace traditional SNM approaches,
continued research seeking to better understand and enhance PNF is important.
Data Source Credibility
Efforts to better identify and resolve shortcomings of social norms intervention
approaches could result in a more effective intervention strategy. First, the effectiveness may be
diminished if participants question the validity or source of the normative feedback presented or
if the information is confusing (Fabiano, 1999; Granfield, 2002; Thombs, Dotterer, Olds, Sharp,
& Raub, 2004). Source credibility, which refers to a message source’s perceived expertise and
trustworthiness (e.g., Kelman & Hovland, 1953), has a rich history in persuasion research. A
recent review on the empirical evidence of the effect of credibility of the message source on
persuasion over the span of 5 decades suggests that a high credibility source is more persuasive
than is a low credibility source in both changing attitudes and achieving behavioral compliance
(Pornpitakpan, 2004).
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 9
Social norms theorists and practitioners generally accept that students experience varying
degrees of skepticism related to the normative information included in these interventions
(Berkowitz, 2004). Many normative feedback interventions present norms from a vague source
(a survey of some number of “typical students” conducted at some past point, often several years
prior), the validity of which students cannot determine or may be unfamiliar, leading some
participants to discredit the information presented. Discounting the credibility of normative
feedback may allow for students to continue their level of drinking without experiencing the
sense of conflict elicited by the knowledge that they are deviating from the prevailing norm. That
is, students perceived norms are reliably higher than what students actually drink. Thus, if a
student does not believe the normative data that he or she receives, then a presumed active
mechanism of change (modifying one’s own behavior to conform to the lower, more modest
actual norm) cannot occur.
For example, in one study that reported null findings for the impact of a SNM
intervention to change perceptions and reduce alcohol use (Granfield, 2002), it was found that
the majority of students were skeptical of the marketed social norms information. This
skepticism was correlated with the variables of age, alcohol use, and the perception of heavy use
on campus, but was not evaluated in the context of the study’s main effects. Based on their
findings, the authors called for future efforts to assess measures of believability and credibility in
order to “assist in identifying and responding to the barriers that may impede successful
outcomes (Granfield, p. 28).” The current study directly addresses this call to action by
evaluating the extent to which source credibility/believability impacts intervention efficacy.
A similar study by Thombs et al. (2004) explored factors that might help explain a failed
social norms intervention. They too noted that most participants in a post-intervention sample did
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 10
not believe the norms messages and higher levels of drinking were associated with lower levels
of perceived credibility. However, limitations associated with study design precluded a valid
evaluation of the role that credibility issues may have played in the intervention’s null effects
(i.e., effect of feedback on perceived norms). Despite the seemingly critical role of source
credibility in the design and success of social norms interventions, studies have not
comprehensively explored this important factor, and no studies to our knowledge have evaluated
source credibility in the context of PNF, a seemingly more efficacious intervention than SNM
campaigns.
Reference Group Specificity
A second shortcoming of most PNF and SNM interventions is that the content consists of
general student norms (i.e., typical college students), which may not be as effective as more
specific reference group norms since they might not be perceived as relevant or meaningful. This
is consistent with theoretical perspectives that suggest that individuals look to those around them
to make decisions about the appropriateness of behavior, and that more socially proximal and
important, as compared to more distal and less important social reference groups, have a greater
impact on an individual’s behavioral decisions (e.g., Social Comparison Theory, Festinger, 1954;
Social Impact Theory, Latane, 1981). Indeed, research suggests that misperceptions of more
proximal and salient reference groups are more likely to influence drinking behavior than
misperceptions of more distal and less salient reference groups (Borsari & Carey, 2003;
Korcuska & Thombs, 2003; Larimer et al., 2009; Lewis & Neighbors, 2006; Neighbors et al.,
2010). Perceptions of more specific reference groups may be more likely to influence drinking
behavior, but it is not known if feedback about more specific reference groups interacts with
source credibility in any meaningful way to impact the efficacy of PNF interventions.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 11
Addressing Potential Barriers through Experimental Manipulation
In sum, normative feedback information presented to students during social norms
interventions ought to be highly believable, specific and from a credible source in order to
maximize the probability of changing behavior. By using an experimental manipulation of the
source of the normative feedback being delivered in the intervention (i.e., credibility) as well as
the reference group implicated in the normative feedback (i.e., specificity), it was expected that
there would be variability in the extent to which the intervention would result in reductions in
students’ normative perceptions and behavioral intentions to drink, which are considered the
final pathway to behavior. Because of limited resources (e.g., time and finances) available to the
investigators, it was not possible within the confines of this study to obtain what would be
necessary to create a “highly credible” data source. Therefore, in addition to the manipulations
described above as part of the experimental design, the ‘actual norm’ used in the normative
feedback was created by the investigators. In concert with findings reported in the literature
using large sample sizes and multiple different reference groups (e.g., Larimer et al., 2011;
Neighbors et al., 2010), the ‘actual norm’ presented to each participant was approximately half
of that individual’s perceived group norm. Although the limited size and location of the sample
used in this study precludes a formal test of whether the same degree of discrepancy between
perceived and actual drinking norms is present, we will derive a proxy test by comparing
perceived norms to the actual drinking rates of the selected sample. It is hypothesized that a
similar degree of discrepancy will be present as in previous research.
Current Study and Hypotheses
As already mentioned, college students consistently overestimate the amount of alcohol
use among their peers and these misperceptions influence their own drinking. A considerable
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 12
amount of effort has been expended to reduce risky drinking by correcting these misperceptions.
Despite considerable promise, social norms feedback interventions have yielded mixed results at
decreasing problematic drinking (for reviews see Lewis & Neighbors, 2006; Miller et al., 2012;
Walters & Neighbors, 2005). Consequently, a substantial proportion of students who receive
interventions continue to drink heavily and experience negative consequences. Thus, additional
research is needed to more fully identify the limitations and active mechanisms of social norms
interventions, which overall appear promising.
The primary objectives of this research were to examine the main effects and interactions
for each experimental condition of a simulated PNF intervention in reducing perceived alcohol
use norms of a typical American college student, perceived alcohol use norms of a typical same-
sex, same-class year student from one’s university, and intentions to drink among college
students who reported drinking on a weekly basis. First, we hypothesized that there would be an
overall reduction in each of the three main outcomes from pre-intervention to post-intervention.
Second, it was anticipated that participants in the high credibility condition would demonstrate
greater reductions relative to participants in the low credibility condition. We also expected a
main effect of reference group specificity on intervention efficacy such that participants in the
high specificity condition would demonstrate greater reductions relative to participants in the low
specificity condition. Finally, we hypothesized an interaction between the two experimental
conditions on the efficacy of the intervention such that participants in the high credibility/high
specificity condition would evidence stronger intervention effects than participants in the low
credibility/low specificity condition.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 13
Method
Participants
Recruitment and data collection occurred at the University of Southern California (USC),
which is a large private U.S. west-coast university. A local institutional review board approved
the current study. Male and female undergraduate college students ranging in age from 18 to 22
were recruited from the psychology subject pool to participate in this study. Subject pool credit
was offered to aid in the recruitment and retention of participants. In total, 104 students met the
inclusion criterion (consuming at least one alcoholic drink during a typical week; see below for
details on study procedures) and consented to participate in all aspects of the study.
Participants ranged in age from 18 to 22 years (M [SD] = 19.91 [1.11]). Ethnic
composition of the sample 20.2% Hispanic/Latino(a) and 79.8% non-Hispanic/Latino(a). Self-
reported racial background was as follows: 56.4% White/Caucasian, 23.8% Asian, 2.0%
Black/African American, 12.9% Multiracial, and 5.0% described their racial background as
‘Other’. Participants were also asked whether their birth sex was male or female and whether
they were currently a member of a fraternity or sorority (i.e., Greek-affiliation). The sample was
revealed to be primarily female (82.7%) and of non-Greek letter affiliation (61.5%). With the
exception of first-year students, class standing was fairly evenly distributed: 7.7% of the sample
reported first-year status, 31.7% sophomore, 28.8% junior, and 31.7% senior. The majority of
participants (69.2%) reported living off-campus with roommates, 17.3% lived in on-campus
housing, 8.7% lived in off-campus Fraternity/Sorority housing, 2.9% lived in an off-campus
residence with their parent(s)/guardian(s), and 1.9% reported living alone in an off-campus
residence.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 14
Research Design
The current experiment used a combination of the dismantling and parametric treatment
package strategies to evaluate specific aspects of PNF intervention efficacy. The dismantling
strategy consists of analyzing specific components of a treatment package. The parametric-
treatment strategy refers to altering specific aspects of treatment to determine how to maximize
change. In the current study, we isolated credibility and specificity components of the PNF
intervention approach. Thus, this study employed a pre/post 2X2 between-subjects experimental
design (see Figure 1).
Reference group specificity conditions. Two reference group specificity conditions
were used in the assessment of perceived norms and simulated normative feedback intervention.
They were operationalized as a typical American college student (low specificity) and a typical
USC student of the same gender and class year as the individual participant (high specificity;
e.g., a typical female USC sophomore).
Credibility conditions. Two conditions with varying credibility were employed in the
normative feedback. In the low credibility condition, data for the ‘actual’ group norm were
designed to reflect a questionable and perhaps unreliable source. For the low specificity
reference group norm (i.e., a typical American college student), participants were told that the
data came from a 2002 telephone interview survey of college parents in which parents were
asked how much alcohol their son or daughter drank on average. For the high specificity
reference group norm (i.e., gender-and class-specific USC student), participants were told that
the data came from a 2002 telephone interview survey of college parents from the university that
the student attended, in which parents were asked how much alcohol their son or daughter drank
on average.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 15
In the high credibility condition, data for the ‘actual’ group norm was designed to reflect
a source of outstanding credibility. For the low specificity reference group norm (i.e., a typical
American college student), participants were told that the data came from a 2010 study of over 1
million college students published by the American Medical Journal (this journal name was
created for the purposes of this study). For the high specificity reference group norm (i.e.,
gender-and class-specific USC student), participants were told that the data came from a 2010
study of over 4,700 undergraduates from the university and that the study was published by the
American Medical Journal.
Procedures
During the fall 2013 semester, students deciding to participate in the current study signed
up via the psychology subject pool Sona system on a rolling basis. Surveys were sent out and
administered using Qualtrics online data collection software. The email that was sent to the
student through Qualtrics contained a study description and a link to an informed consent form
documenting the research protocol and confidentiality of responses. Participant confidentiality
was fully ensured and identifying information was never associated with the data at any time.
Participants were assigned a personalized identification number (PIN) that was used to link the
data collected from the baseline survey and lab-based portion of the study.
Upon submitting their consent, participants were directed to an online survey that served
as the baseline assessment and asked about participants’ demographic information, drinking
behaviors, and perceived drinking norms. The student survey took approximately 15-20 minutes
to complete. Before answering questions related to drinking behavior, a standard drink was
defined as a drink containing one-half ounce of ethyl alcohol — one 12 oz. beer, one 4 oz. glass
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 16
of wine, or one 1.25 oz. shot of 80 Proof liquor. Pictures of standard drinks accompanied these
descriptions (see Appendix A).
Participants were eligible to participate in the study if they reported consuming at least
one alcoholic beverage during a typical week. If the inclusion criterion was met, a page appeared
at the end of the survey that asked students to sign up for a day and time to complete the lab-
based PNF intervention and assessment portion of the study. Available timeslots were within one
to three weeks of when the participant completed the baseline assessment. Groups of 5-12
participants then attended the intervention portion of the study in a computer lab at a location on
the university’s campus. At the end of the intervention and while still in the laboratory,
participants completed a brief online post-intervention assessment of their normative
perceptions, drinking intentions, and ratings of the credibility of the normative feedback.
While interventions seeking to reduce college student drinking typically conduct post-
intervention assessments ranging from several months to years after the intervention in order to
know the extent and durability of intervention effects, this was not possible in the current study
for several reasons. First, participation in the subject pool is time-limited in that it must be
completed within a semester. Thus, the rolling recruitment method used to enroll enough
participants was not conducive to even short-term follow-up assessments. More importantly,
however, the procedures of the study involved the use of deception and it was therefore
necessary to debrief participants prior to their exit from the laboratory. Due to these reasons,
drinking intentions served as the main outcome rather than actual alcohol use, as intentions could
be assessed immediately after the intervention. Following the post-intervention assessment,
participants were informed of the study’s aims and told that the actual norm and data source were
part of an experimental manipulation and therefore not real data.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 17
Lab-based PNF intervention protocol. Participants were randomly assigned to one of
the four experimental conditions using a random number generator. Final sample sizes following
random assignment to condition were as follows: High Credibility / Low Specificity (N = 24),
High Credibility / High Specificity (N = 29), Low Credibility / Low Specificity (N = 21), and
Low Credibility / High Specificity (N = 30). Once in the lab, each participant was seated at a
computer, provided with a set of headphones, and asked to wait to begin until all participants
were ready. Then, the instruction was given to begin the PowerPoint presentation slide show.
The presentation began with an example feedback slide to introduce the types of information that
would subsequently be shown. The slide was built for the participant, one piece at a time, and a
pre-recorded audiotape was synced with the presentation to verbally guide the participant with an
explanation about what each component of the slide represents (see Appendix B for intervention
scripts). The audio accompanied visual objects and arrows pointing at each part of the feedback
graph, as it was introduced, until it formed the complete feedback slide. Participants were asked
to attend to the differences between their perceived group norms and their own individual
behavior, the difference between their perceived group norms and the actual group norms, and
the source of the ‘actual’ group data.
In contrast to PNF administrations in previous research, the feedback was divided and
presented in “chunks” per the Articulated Thoughts in Simulated Situations paradigm (ATSS;
Davison, Robins, & Johnson, 1983). This was the chosen procedure because the current
experimental study is also laying the foundation for a future study in which, per the ATSS
paradigm, participants will be instructed to think-aloud after each of several segments or chunks
of presentation material in order to assess their active cognitions and emotions related to the
feedback in a more immediate, on-line fashion than is possible in conventional communications.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 18
The data used in constructing the electronic normative feedback graphs were derived
from two sources. An individual’s perceived group norms and individual alcohol use were
collected from responses on the baseline survey. The ‘actual’ group norm was experimentally
manipulated to be approximately half of the individual’s perceived group norm, which is
consistent with regularly observed differences detailed in the literature (e.g., Larimer et al., 2011;
Neighbors et al., 2010). After viewing the example feedback slide, they were given an
opportunity to ask any questions about the graphical feedback display.
The slide show then progressed through the normative feedback designated by each
participant’s assigned condition (see Appendix C for example feedback slides). Each feedback
condition contained three individually-tailored slides referring to a different drinking behavior
reported by the participant. The first slide presented feedback pertaining to the average number
of drinks consumed per drinking occasion. The second slide presented feedback pertaining to the
total number of drinks consumed during a typical week in the prior month. The third slide
provided information about the maximum amount of drinks consumed at any one time in the
prior month.
Post-intervention assessment. Immediately following completion of the PNF
intervention, participants were asked to complete a brief online survey that was sent via email
while participants were engaged in the intervention presentation. To determine the ability of the
simulated intervention to immediately change normative perceptions and drinking intentions,
participants completed several of the same measures assessed during the baseline assessment. In
order to perform a manipulation check, participants answered questions pertaining to the
credibility of the feedback they received.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 19
Measures
Demographic information. Questions pertaining to participant demographics included
age, gender, ethnicity, racial background, class year, residence location, and fraternity/sorority
affiliation.
Alcohol Consumption. Participants completed the Daily Drinking Questionnaire (DDQ:
Collins, Parks, & Marlatt, 1985; Kivlahan, Marlatt, Fromme, Coppel, & Williams, 1990), which
is designed to assess daily alcohol consumption during a typical week in the past month. The
respondent is asked to report how many drinks he or she consumes on each day of a typical
week, Monday through Sunday. The resulting data were used to compute two of the drinking
variables used in the normative feedback: the average number of drinks consumed during a
typical occasion and total number of drinks consumed during a typical week. The DDQ has been
commonly used in alcohol intervention studies, and has been shown to be a reliable and valid
measure of college student drinking (e.g., Larimer et al., 2001; Marlatt et al., 1998). It has
demonstrated good convergent validity (e.g., r = .50; Collins, Parks, & Marlatt,1985) and test-
retest reliability (e.g., r = .87; Neighbors, Dillard, Lewis, Bergstrom, & Neil, 2006).
The DDQ was also used to assess participant’s intended drinking behaviors. Summed
composite variables for intended total drinks per week at pre- and post-intervention were used as
outcomes to assess intervention efficacy.
The Quantity/Frequency/Peak Alcohol Use Index (Marlatt, Baer, & Larimer, 1995) was
also used to assess drinking behavior in the past month. Participants indicated their frequency of
drinking, quantity per drinking occasion, and the maximum amount of drinks consumed during
one episode (the latter was the third drinking variable used in the normative feedback).
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 20
Descriptive norms. The Drinking Norms Rating Form (DNRF: Baer et al., 1991)
assessed descriptive norms, or perceptions of others’ drinking behavior. The format of the DNRF
mirrors that of the DDQ, except that participants provide estimates of alcohol use for a particular
reference group. All participants completed this measure twice at both pre- and post-
intervention: once for perceptions of a typical American college student and again for
perceptions of a typical student of their same gender and class year at their university. Responses
for the seven days were summed to create a perceived total drinks per week variable for each
reference group and at each time point. The DNRF and modifications thereof have been used in
numerous studies related to social norms and college student drinking. It has consistently
demonstrated good predictive and concurrent validity and has good test-retest reliability (e.g.,
Neighbors et al., 2006).
Credibility of normative feedback. Participants’ ratings of the credibility of the data
source used in the normative feedback were measured via an adapted assessment modeled after
research by Cacioppo, Petty, Kao, & Rodriguez (1986). The items assessed the extent to which
participants found the feedback meaningful, trustworthy, believable, and credible. Participants
rated the following statements on a Likert-type scale of 1 (strongly disagree) to 7 (strongly
agree): (a) The source of the feedback was trustworthy, (b) The feedback came from an expert
source, (c) I found the graphical feedback about my peers believable, (d) I found the graphical
feedback compelling, (e) The source of the graphical feedback was credible, and (f) I found the
graphical feedback meaningful. The six items were averaged to form a credibility composite
variable (α = .95).
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 21
Analytic Plan
To assess for baseline differences at Time 1 following randomization to condition, a one-
way between subjects ANOVA was implemented. Next, a correlation matrix was computed to
examine bivariate relationships between all study variables. Paired samples t-tests were
conducted to determine the discrepancy between the samples’ perceived norms of different
reference groups relative to the samples’ own self-reported alcohol use behavior. A series of
paired samples t-tests was also used to examine overall changes from pre-intervention (Time 1)
to post-intervention (Time 2) on the following three main outcomes: (a) perceived total drinks
per week consumed by a typical American college student, (b) perceived total drinks per week
consumed by a typical same-sex, same-class-year USC student, (c) and intended total drinks per
week. Effect sizes (d) for paired samples t-tests were calculated as the mean difference divided
by the standard deviation of the difference, with small effects .2, medium effects .5, and large
effects .8 or higher (Cohen, 1988). Skewness and kurtosis for all study variables were adequate
(Kline, 1998).
A series of multiple regression models was first conducted to assess for interactions
between Time 1 levels of the Time 2 outcome variables and experimental condition. A second
series of multiple regression models was used to evaluate condition effects of the simulated PNF
intervention on the same three main Time 2 outcomes described above. Participants’ gender and
race, as well as Time 1 levels of the three outcomes, respectively, served as covariates to
statistically rule out these variables as rival effects of intervention efficacy. For both
experimental conditions, participant status was dummy-coded as 0 (low) and 1 (high). Gender
was dummy-coded as 0 (female) and 1 (male). Race was dummy-coded as 0 (non-White) and 1
(White). Consistent with recommended procedures for estimating and interpreting interactions in
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 22
multiple regression (Aiken & West, 1991; Cohen, Cohen, West & Aiken, 2003), all predictors
were standardized prior to computing interaction terms. Multicollinearity problems were not
encountered as all variance inflation factor (VIF) values were below 1.1 (Tabachnick & Fidell,
2007).
Results
Randomization Check
To test whether any Time 1 differences existed between groups following randomization
to condition, a one-way between subjects ANOVA was implemented to estimate and compare
means on important Time 1 variables as a function of condition assignment: (a) High Credibility
/ Low Specificity, (b) High Credibility / High specificity, (c) Low Credibility / Low specificity,
(d) Low Credibility / High Specificity. As presented in Table 1, there were no significant
differences on baseline measures as a function of condition status (all ps > .05).
Manipulation Check
As indicated earlier, immediately following completion of the PNF intervention,
participants answered questions pertaining to the credibility of the feedback they had received, as
a manipulation check for the credibility condition. Participants in the high credibility condition
indeed rated the overall credibility of their feedback significantly higher (M = 5.49, SD = 1.07)
than the low credibility condition (M = 3.20, SD = 1.62), t(102) = -8.49, p < .001, d = 1.67.
Bivariate Associations
A correlation matrix of study variables, along with their means and standard deviations,
is presented in Table 2. Student Time 1 drinks per week was associated with Time 1 intended
drinks per week, r(103) = .73, p < .001, Time 2 intended drinks per week, r(103) = .73, p < .001,
Time 2 perceived American drinks per week, r(103) = .22, p = .02, and Time 2 perceived
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 23
University drinks per week, r(103) = .42, p < .001. Student Time 1 intended drinks per week was
associated with Time 2 intended drinks per week, r(103) = .75, p < .001, Time 2 perceived
American drinks per week, r(103) = .27, p = .006, and Time 2 perceived University drinks per
week, r(103) = .37, p < .001. Student Time 1 perceived American drinks per week was
significantly correlated with Time 1 perceived University drinks per week, r(103) = .71, p <
.001, Time 2 perceived American drinks per week, r(103) = .46 p < .001, and Time 2 perceived
University drinks per week, r(103) = .34, p < .001. Time 1 perceived University drinks per week
was positively related to Time 2 perceived American drinks per week, r(103) = .41 p < .001, and
Time 2 perceived University drinks per week, r(103) = .37, p < .001. There was a significant
correlation between Time 2 intended drinks per week and Time 2 perceived University drinks
per week, r(103) = .37, p < .001. Lastly, Time 2 perceived American drinks per week was
associated with Time 2 perceived University drinks per week, r(103) = .67, p < .001, and
credibility ratings, r(103) = -.24, p = .02.
The significant relationships described above are consistent with previous research and
are expected, given the conceptual overlap. For example, it is no surprise that intentions to drink
and self-reported drinking behavior are strongly associated, nor is it unexpected to observe
stability of the constructs over time given their robust nature and test-retest reliability, even with
an intervention in between assessments. However, it is surprising that no significant relationship
was found between Time 1 drinks per week and Time 1 perceived University drinks per week,
r(103) = .14, p = .17, nor between Time 1 drinks per week and Time 1 perceived American
drinks per week, r(103) = .06 p = .52. These important null findings are explored further in the
Supplemental Analyses section and interpreted in the Discussion section.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 24
Perceived Group Drinking Norms Compared to Sample’s Alcohol Use
Although a formal label of “overestimation” cannot be made due to the simulated nature
of the ‘actual’ group drinking norms displayed to participants during the feedback, paired
samples t-tests were conducted to determine the relative discrepancy between students’
perceived drinking norms of each reference group and the samples’ own overall typical drinking
behavior. Results indicate that participants’ perceived total drinks per week consumed by a
typical American college student (M = 16.74, SD = 9.81) were significantly higher than, and
approximately double, the sample’s own reports of number of drinks consumed during a typical
week (M = 7.26, SD = 5.66), paired t(103) = 8.78, p < .001, d = .86. In addition, participants’
perceived total drinks per week consumed by a typical same-sex, same-class-year USC student
(M = 14.41, SD = 6.71) were also significantly higher than, by a near perfect factor of two, the
sample’s own reports of number of drinks consumed during a typical week (M = 7.26, SD =
5.66), paired t(103) = 8.93, p < .001, d = .88. These differences reinforce the decision to
construct the ‘actual’ group norms to be approximately 50% of individual participant’s perceived
norms and confirm the decision to provide feedback based on simulated norms.
Pre- to Post-Intervention Changes in Main Outcomes among Overall Sample
Overall, there was a significant reduction from Time 1 (M = 16.74, SD = 9.81) to Time 2
(M = 9.63, SD = 5.77) on the first main outcome of perceived total drinks per week consumed by
a typical American college student, paired t(103) = 8.21, p < .001, d = .81. Similarly, on the
second main outcome of perceived total drinks per week consumed by a typical same-sex, same-
class-year USC student, there was a significant reduction from Time 1 (M = 14.41, SD = 6.71) to
Time 2 (M = 9.36, SD = 5.45), t(103) = 7.45, p < .001, d = .73. However, no significant
differences emerged between Time 1 (M = 5.38, SD = 4.61) and Time 2 (M = 4.90, SD = 4.25)
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 25
intended drinks per week, t(103) = 1.56, p = .12. Thus, overall participants evidenced
considerable change in their perceived norms from pre- to post-intervention, but did not appear
to reduce their intentions to drink.
Models Testing Interactions between Condition and Time 1 Outcomes
Prior to computing the main regression analyses and including Time 1 levels of the
outcomes as covariates for the respective final models, three separate multiple regression models
were estimated to test for the presence of any significant interactions between experimental
conditions and Time 1 outcomes. Main effects are not presented as they are reported in the final
models below and regression coefficients are not presented for the sake of parsimony.
The dependent variable for the first model was perceived American student drinks per
week at Time 2. Time 1 perceived American student drinks per week, credibility condition, and
reference group specificity condition were entered on Step 1. All possible two-way interactions
were entered on Step 2. No significant interactions emerged (all ps > .05).
The dependent variable for the second model was perceived University student drinks per
week at Time 2. Time 1 perceived University student drinks per week, credibility condition, and
reference group specificity condition were entered on Step 1. All possible two-way interactions
were entered on Step 2. No significant interactions emerged (all ps > .05).
The dependent variable for the third model was intended drink per week at Time 2. Time
1 intended drinks per week, credibility condition, and reference group specificity condition were
entered on Step 1. All possible two-way interactions were entered on Step 2. No significant
interactions emerged (all ps > .05).
The lack of any interactions between Time 1 outcomes and experimental conditions
supports the analytic plan to control for Time 1 levels of the outcomes and examine condition
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 26
effects in the main regression models by reducing the likelihood that any subsequent effects are
due to pre-existing differences between groups.
Models Predicting Post-Intervention Outcomes
Three multiple regression models (Table 3) assessed the contribution of predictors in
explaining Time 2 outcomes of perceived total drinks per week of American college students
(Model 1), perceived total drinks per week of University college students (Model 2), and
intended drinks per week (Model 3). At Step 1, respondent sex, race, and Time 1 levels of each
dependent variable (for the respective model) served as covariates. Main effects for the
credibility condition and reference group specificity condition were entered at Step 2. Specified
in Step 3 was the two-way interaction involving the credibility condition and reference group
specificity condition.
Model 1. At Step 1, the covariate of Time 1 perceived American drinks per week
emerged as significant (β = .46, p < .001). At Step 2, a significant main effect was found for the
credibility condition (β = -.27, p = .01). Step 3 revealed no significant interaction between
conditions. The final model accounted for a total of 27% of the variance of Time 2 perceived
American drinks per week, F(6, 97) = 25.80, p < .001. The findings of this regression model
indicate a greater reduction in perceived norms for those in the high credibility condition than
those in the low credibility condition.
Model 2. At Step 1, Time 1 perceived University drinks per week significantly predicted
higher Time 2 perceived University norms for drinks per week (β = .37, p < 001). On Step 2,
Reference group condition was significantly associated with lower Time 2 perceived university
drinks per week (β = -.19, p = 04). Again, there was no significant interaction between
conditions on Step 3. The final model accounted for a total of 21% of the variance of Time 2
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 27
perceived University drinks per week, F(6, 97) = 25.08, p = .001. The significant main effect for
reference group in this model signals a stronger intervention effect on perceived university
norms for those in the high specificity condition, relative to those in the low specificity
condition.
Model 3. At Step 1, Time 1 intended drinks per week evidenced a strong significant
relationship with Time 2 intended drinks per week (β = .73, p < 001). No other main effects
emerged in this model on either Step 2 or Step 3. The final model accounted for a total of 59% of
the variance of Time 2 intended drinks per week, F(6, 97) = 23.14, p < .001. The lack of
significant predictor variables suggests that the intervention was unable to produce a change in
intended drinking behavior after accounting for Time 1 intentions to drink.
Supplementary Analyses
Additional analyses were conducted to explore potential explanations for the
unanticipated null relationship between Time 1 drinking and perceived norms. One such possible
explanation is that the association between the two constructs was present for specific groups of
students but not others. Thus, measured demographic variables were separated in analyses and
correlations between Time 1 weekly drinking and perceived weekly drinking norms of each
reference group were re-run. Correlations were conducted separately for males (n = 18) and
females (n = 86), Greek (n = 40) and non-Greek (n = 64) affiliated students, and White students
(n = 57) and non-White students (n = 47). As with the prior analyses, no significant correlations
were present in any group between Time 1 drinks per week and Time 1 perceived American
drinks per week, or Time 1 perceived University drinks per week.
A second possible explanation is that the relationships were present only among heavier
drinking students. First, participants reporting two or fewer drinks per week (n = 20) were
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 28
excluded and the correlations were conducted. As before, no significant correlations emerged.
Next, participants reporting four or fewer drinks per week (n = 37) were excluded and the same
pattern of non-significant correlations was present. Finally, separate analyses were conducted for
binge drinkers (n = 47) and non-binge drinkers (n = 39). Neither group showed a significant
correlation between any of the three variables.
Discussion
The current study evaluated a simulated PNF intervention, which was designed to address
deficiencies in current social norms-based intervention approaches and research. A novel
experimental manipulation was used to control the source credibility and reference group
specificity of the normative feedback data displayed in the intervention. And, unlike print
displays used in previous PNF interventions, the feedback was divided and presented in
“chunks” using both visual and audio aides per the ATSS paradigm (ATSS; Davison et al.,
1983). Isolating the credibility and specificity factors allowed for a more thorough understanding
of how they can impact the effectiveness of a simulated PNF intervention to reduce perceived
descriptive norms and decrease intentions to drink, which is imperative for the evolution of
norms-based intervention strategies.
Overall, partial support was found for each of the hypotheses in the study. First, as
expected, the sample reported drinking approximately half of what they perceived other groups
of college students consume during a typical week. Although this is not an actual test of
‘overestimated’ norms due to the reference groups being utilized, it does offer support of the
decision to make the ‘actual’ norm in the feedback approximately half of what each participant
perceived to be the norm. Next, we hypothesized that there would be an overall reduction in each
of the three main outcomes from Time 1 to Time 2. Results revealed large effect sizes for the
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 29
reduction of perceived weekly drinking norms of both a typical American college student and a
typical same-sex, same-class year student from one’s university. However, there was no
significant change in participants’ intentions to drink from Time 1 to Time 2.
Regression analyses were conducted to further qualify the patterns of intervention effects
after controlling for respondent sex, race, and Time 1 levels of each respective dependent
variable. It was anticipated that participants in the high credibility condition would demonstrate
greater reductions in the primary outcomes relative to participants in the low credibility
condition. Being in the high credibility condition was indeed associated with a greater reduction
in perceived weekly drinking norms of an American college student, but no main effects for this
factor was found for either of the other outcomes. Similarly, participants in the high specificity
condition evidenced greater reductions in perceived university-specific weekly drinking norms
than participants in the low specificity condition, although no main effect was found for either of
the other two outcomes. Thus, contrary to hypotheses, there were no condition effects on
intentions to drink and no interactions were present between conditions on any of the three
outcomes.
Implications of Significant Findings
The findings described above offer important incremental extensions of previous
research. Understanding the degree to which data source credibility and reference group
specificity impact intervention efficacy has implications for the design and conservation of
resources associated with the PNF intervention approach. Receiving feedback from a highly
credible data source was found to enhance the intervention’s ability to reduce perceived
American student drinking norms. Thus, although such a distal reference group may not typically
be considered desirable for providing normative feedback, perhaps because of the assumption
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 30
that it is not relevant to students, the current findings suggest that such feedback can indeed lead
to a reduction of normative perceptions provided there is an emphasis on how reliable or credible
the data actually are. This is good news considering the enormous resources the federal
government (e.g., National Institutes of Health, Center for Disease Control) and others use to
document trends in alcohol use behavior among college students. Rather than simply identifying
health-risk behaviors in need of focused intervention and prevention initiatives, those types of
population-level data can actually be used in social norms interventions programs that have the
potential to ultimately impact the very behavior they describe. To our knowledge, there are no
empirical evaluations of PNF trials that use the typical American college student as the reference
group to reduce problematic drinking among college students.
Furthermore, the lack of a credibility condition effect within the more proximal student
reference group concerning same-sex, same-class students from one’s own university, suggests
that practitioners at the university/college level may not need to spend as much of their limited
resources (e.g., time, staff, and financial incentives) surveying large numbers of students to
create a representative and very credible ‘actual norm’. Rather, for those seeking to reduce
perceptions of campus-wide norms, the current findings suggest that a focus on greater
specificity of the normative reference group may be a more effective strategy.
Interpretations via the Social Norms Theoretical Framework
While the PNF delivered to students had the intended effect of reducing normative
perceptions of peer drinking rates, a rather substantial question is why these reductions did not
lead to reductions in intentions to drink. There are several potential explanations for this null
finding. First, we will begin with a brief review of the theoretical rationale of the underlying
mechanisms of social norms interventions.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 31
As mentioned previously, numerous studies have demonstrated the strong prognostic
power of perceived descriptive norms on alcohol use behavior among college students (e.g.,
Neighbors et al., 2007; for reviews and meta-analyses see Berkowitz, 2004, Borsari & Carey,
2003; Perkins, 2002). Nationwide data from over 76,000 students from 130 colleges and
universities show that the large majority of college students overestimate the level of drinking
behavior norms of other students and those perceptions were found to be the strongest predictor
of individual drinking (Perkins et al., 2005). PNF approaches are designed to correct normative
misperceptions by showing discrepancies between actual norms and students’ perceptions and
behaviors, that is, by informing participants that others like them drink less than what they
believe them to drink. Correcting normative misperceptions, the theory suggests, then motivates
behavior change (Rice, 2007). Consistent with this proposed mechanism, reductions in perceived
descriptive norms typically partially mediate the efficacy of PNF interventions (e.g., Doumas,
Workman, Smith & Navarro, 2011; Walters, Vader & Harris, 2007). Thus, despite revealing no
effect on drinking intentions, a close look at the pattern of results observed in this study reveals
that they are actually quite consistent with the social norms theoretical framework and
intervention approach.
The premise that the reduction of perceived peer drinking norms can lead to a reduction
in alcohol use rests on the presence of a strong positive relationship between perceived norms
and individual use. This fundamental association was notably absent at baseline in the current
study, both for perceived American student norms and drinking (r = .06, ns), as well as perceived
university-specific norms and drinking (r = .14, ns). One of the assumptions underlying the
potential for PNF to produce behavioral changes is the principle of conformity; college students
want to think and act in ways that are consistent with the attitudes and behavior of their larger
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 32
peer group (other college students). By receiving personalized normative feedback, students in
the sample did indeed learn that their perceptions were inaccurate and they modified them
accordingly. However, for reasons that are unclear, there was no association between perceived
norms and individual drinking behavior at baseline, suggesting that students in the current
sample were not swayed by their perceived norms of their peers’ drinking when making their
own behavioral decisions about when and how much to drink. Therefore, it makes conceptual
sense that the observed reduction in perceived norms did not coincide with changes in their
intentions to drink.
Limitations
The current findings are tempered by several limitations, several of which suggest
meaningful directions for future research. First, the use of self-reported alcohol use may be a
concern as students may not accurately report on their drinking. However, confidentiality of
participants’ responses was assured and information about standard drink content was provided
to help anchor responses. Research suggests that self-reports of drinking behavior are generally
accurate under these conditions (Babor, Steinberg, Anton, & Del Boca, 2000; Chermack, Singer,
& Beresford, 1998). Second, the study lacked a control group, so inferences about intervention
effects must be interpreted with caution. Designs of similar studies in the future would benefit
from a control condition in which students are presented normative feedback about non- alcohol-
related behaviors (e.g., video game playing, sleeping behavior, frequency of doing one’s laundry,
etc.). Third, the simulated nature of the data to which participants’ perceptions were compared is
a limitation of this research.
Next, the study is limited by its use of a convenience sample comprised of psychology
students from a single university. Although somewhat speculative and without concrete data to
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 33
support the claim, something associated with the demographics of the current sample likely
contributed to the lack of a baseline relationship between perceived norms and individual
drinking behavior. Potential explanations were tested with supplementary analyses in which
correlations were separately conducted for males and females, Greek-affiliated and non-Greek
affiliated students, White students and non-White students, as well as several different groups of
students who varied in their self-reported drinking behavior. None of these isolated factors led to
a significant correlation between perceived norms and drinking at Time 1. This pattern suggests
that an unmeasured third variable accounts for the null finding, as the robust relationship
between perceived norms and alcohol use behavior of college students has been demonstrated in
a remarkably large number of studies. Larger and more diverse samples from multiple sites
would strengthen the external validity of future studies and provide a better test of the relative
influence of credibility and specificity on behavioral outcomes following a PNF intervention.
Finally, due to the use of deception in the current study and the need to debrief
participants immediately after receiving the normative feedback, the decision was made to use
drinking intentions as a proxy for alcohol use behavior. The bivariate relationship between
baseline drinking and intentions among the current sample was r = .73, which indicates a strong,
but not perfect overlap. It is not possible to know whether there would have been a different
pattern of results had actual drinking behavior been collected, but this would be an important
consideration for future research. A second aspect of this limitation is that intentions to drink
were collected immediately after the intervention. It is possible that an intervention effect on
behavior may have emerged if students had been allowed more time to process the feedback and
actually adjust the level of alcohol intake during subsequent drinking episodes. Only one study to
our knowledge has examined and documented the ability of a social norms intervention to
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 34
produce immediate reductions in perceived group-specific drinking norms across three different
high-risk groups of college students (LaBrie, Hummer, Grant, & Lac, 2010). The study did not
report on subsequent relationships with drinking behavior as a result of these immediate
reductions, but earlier articles from the same intervention studies showed that longitudinal
reductions in misperceptions via the social norms feedback intervention mediated actual changes
in drinking up to two months post-intervention (LaBrie et al., 2008; LaBrie, Hummer, Huchting,
& Neighbors, 2009). Therefore, it is not unreasonable to suspect that the PNF intervention from
the current study may have produced changes in drinking behavior over time.
Conclusions
The present research extends previous implementation of social norms-based
interventions for drinking in several ways. It offers a novel methodological approach for testing
factors that may impact intervention efficacy, while not actually requiring the resources typically
needed to conduct true randomized clinical trials. Although the results did not support
intervention effects on intentions to drink alcohol, they did shed light on how designs of future
PNF interventions might benefit from selectively focusing on issues of data source credibility
and reference group specificity to reduce misperceptions of college student drinking, depending
on the goals of those implementing such programs and the scope of their intended reach. More
generally, the results of this study highlight the importance of continuing to focus on ways in
which PNF interventions can be optimized and under what conditions to achieve good outcomes.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 35
Mean Differences in important study variables at Time 1 as a function of condition status
Measure Mean SD Mean SD Mean SD Mean SD F -test
Time 1 drinks per week 8.21 7.03 6.66 4.37 8.52 7.14 6.20 4.21 1.03
Time 1 intended drinks per week 6.50 5.16 4.28 3.69 6.05 5.17 5.10 4.49 1.22
Time 1 perceived American drinks per week 16.08 11.58 17.38 7.06 16.48 7.49 16.83 12.15 0.08
Time 1 perceived University drinks per week 14.63 6.29 14.48 5.55 15.29 5.61 13.57 8.72 0.28
Note. "Time 1" refers to pre-intervention. "American" refers to a typical American college student. "University" refers to a typical same-gender,
same-class-year student.
Table 1
High Credibility /
Low Specificity
High Credibility /
High Specificity
Low Credibility /
Low Specificity
Low Credibility /
Low Specificity
N = 24 N = 30 N = 29 N = 21
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 36
Table 2
Correlation Matrix of Variables
Measure M (SD ) 1 2 3 4 5 6 7 8
1. Time 1 drinks per week
7.26 5.66 --
2. Time 1 intended drinks per week
5.38 4.61 .73*** --
3. Time 1 perceived American drinks per week
16.74 9.81 .06 .08 --
4. Time 1 perceived University drinks per week
14.41 6.71 .14 .15 .71*** --
5. Time 2 intended drinks per week
4.9 4.25 .73*** .75*** -.06 -.01 --
6. Time 2 perceived American drinks per week
9.63 5.77 .22* .27** .46*** .41*** .15 --
7. Time 2 perceived University drinks per week
9.36 5.45 .42*** .37*** .34*** .37*** .37*** .67*** --
8. Time 2 credibility composite
4.34 1.78 -.07 .04 -.02 -.06 .03 -.24* -.12 --
Note. "Time 1" and "Time 2" refer to pre-intervention and post-intervention, respectively. "American" refers to a typical American
college student. "University" refers to a typical same-gender, same-class-year student.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 37
Table 3
Multiple Regression Models Predicting Time 2 Outcomes (Ns = 104)
R
2
∆ B SE β
Model DV: Time 2 perceived American drinks per week
Step 1: .21***
Sex
a
0.28 0.52 .05
Race
b
-.37 0.52 -.06
Time 1 perceived American drinks per week 2.64 0.52 .46***
Step 2: 0.05*
Credibility condition
c
-1.31 0.50 -.27*
Reference group condition
c
-.28 0.51 -.05
Step 3: 0.001
Credibility condition x Reference group condition 0.20 0.51 .03
Model F (6, 97) = 25.80***, Total R
2
= .27
Model DV: Time 2 perceived University drinks per week
Step 1: .15**
Sex
a
0.58 0.50 .11
Race
b
-.05 0.50 -.01
Time 1 perceived University drinks per week 2.00 0.50 .37***
Step 2: 0.05
Credibility condition
c
-.67 0.50 -.12
Reference group condition
c
-1.06 0.50 -.19*
Step 3: 0.01
Credibility condition x Reference group condition 0.56 0.50 .10
Model F (6, 97) = 25.08**, Total R
2
= .21
Model DV: Time 2 intended drinks per week
Step 1: .58***
Sex
a
0.21 0.29 .05
Race
b
0.49 0.28 .11
Time 1 intended drinks per week 3.10 0.29 .73***
Step 2: 0.009
Credibility condition
c
-.21 0.28 -.05
Reference group condition
c
-.36 0.28 -.09
Step 3: 0.001
Credibility condition x Reference group condition 0.11 0.28 .03
Model F (6, 97) = 23.14***, Total R
2
= .59
a
Gender (0 = female, 1 = male).
b
Race (0 = non-White, 1 = White).
c
Condition (0 = low, 1 = high)
Note . Coefficients are based on standardizing all predictors prior to computing interaction terms.
*p < .05. **p < .01. ***p < .001.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 38
Figure 1. Experimental conditions in the 2x2 between-subjects design.
REFERENCE GROUP SPECIFICITY (IV)
CREDIBILITY (IV)
Low Specificity
Reference Group
High Specificity
Reference Group
Low Credible Data Source
Low Credible Data Source
(2002 telephone survey of college parents)
+
Low Specificity Reference Group
(Typical American College Student)
Low Credible Data Source
(2002 telephone survey of USC parents)
+
High Specificity Reference Group
(Typical same-gender, same-class USC student)
High Credible Data Source
High Credible Data Source
(2010 study of over 1 million college students
published in American Medical Journal)
+
Low Specificity Reference Group
(Typical American College Student)
High Credible Data Source
(2010 study of over 4700 undergraduate USC students,
published in American Medical Journal)
+
High Specificity Reference Group
(Typical same-gender, same-class USC student)
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 39
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DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 47
APPENDIX A: Standard Drink Definition
Before answering questions related to drinking behavior, students were presented with the
following definition and examples of what constitutes one standard alcoholic drink.
For the following questions regarding # of drinks, one drink equals:
• 12 oz. beer (8 oz. Canadian beer, malt liquor, or ice beers or 10 oz. of
microbrew)
• 10 oz. of wine cooler
• 4 oz. of wine
• 1 oz. of 100 proof or 1 1/4 oz. of 80 proof liquor (one shot)
• 1 cocktail with 1 oz. of 100 proof or 1 1/4 oz. of 80 proof liquor
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 48
APPENDIX B: PNF Intervention Script
Introduction and Example Feedback Slide:
Audio:
Recently, you completed an online survey that asked about your own alcohol use, as well as your
estimates of other college students’ drinking behavior. We have compiled your responses into
graphical feedback that you will be viewing. In addition, we will provide you with feedback
about the actual drinking behavior of college students.
Please take a moment to follow along with an example feedback slide. This slide will describe
how to interpret all the following slides.
First, the top of the slide will provide you with information about how your responses on the
earlier online survey compare to a specific group of college students. Next, notice the top of the
graph. Here you will see the drinking behavior that the graph is referring to. This will be one of
three drinking behaviors: the average number of drinks consumed on a typical drinking
occasion, the total number of drinks consumed per week, or the maximum amount of drinks
consumed at any one time in the past month.
Then, you will see two bars appear in the graphs. The first bar is your own drinking behavior,
exactly as you reported it on the recent online survey. The second bar represents your estimate
of a typical member of that group, also exactly as you reported it on the survey.
Next, you will see a third bar that represents the actual drinking behavior of a typical college
student. At the bottom of the slide, you will see a note that informs you of the source of the data
for the actual group norm. As you are viewing the complete feedback slide, please pay attention
to how your own alcohol use, and your perceptions, is similar to or different from the average
behavior of other college students. Consider whether your estimates were too high or too low
and how your own alcohol use compares to the average use of a typical college student. Think
carefully about how the source of the data pertains to your thoughts about the graphs.”
You will now be viewing feedback slides using real data from yourself and other college
students.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 49
Four Experimental Conditions (Audio Script):
Low Specificity/High Credibility Condition:
The statistics you are about to view were collected from very large representative samples of college
students who completed surveys during 2010. They were assured that their responses would be
anonymous and never associated with their names. Thus, the statistics are extremely accurate and
reliable. The following three slides provide you with information about how you compare to a typical
American college student. These data were collected from a random sample of over 1 million college
students from around the country during 2010, and published in the leading scientific journal, the
“American Medical Journal.” After viewing the first slide, please continue to view the second and
third slides that refer to a different drinking behavior of a typical American college student.
High Specificity/High Credibility Condition:
The statistics you are about to view were collected from a very large representative sample of USC
students who completed surveys during 2010. They were ensured that their responses would be
anonymous and never associated with their names. Thus, the statistics are extremely accurate and
reliable. The following three slides provide you with information about how you compare to a typical
USC student of your same gender and class year. These data were collected from a random sample of
over 4700 USC undergraduate students. The data were reported in a study published in the leading
scientific journal, “American Medical Journal.” After viewing the first slide, please continue to view
the second and third slides that refer to different drinking behaviors of a typical USC student of your
same gender and class year.
Low Specificity/Low Credibility Condition:
The following three slides provide you with information about how you compare to a typical American
college student. These data were collected from a 2002 telephone interview survey of college parents
in which parents were asked how much alcohol their son or daughter drank on average. After viewing
the first slide, please continue to view the second and third slides that refer to different drinking
behaviors of a typical American college student.
High Specificity/Low Credibility Condition:
The following three slides provide you with information about how you compare to a typical USC
student of your same gender and class year. These data were collected from a 2002 telephone
interview survey of USC parents in which they were asked how much alcohol their son or daughter
drank on average. After viewing the first slide, please continue to view the second and third slides that
refer to different drinking behaviors of a typical USC student of your same gender and class year.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 50
Three Alcohol Use Variables Used in Feedback (Audio Script):
PNF Slide Number of Drinks per Occasion:
As in the example, the top of the slide will provide you with information about how your responses on
the earlier online survey compare to a specific group of college students. First, notice the top of the
graph. This slide will display your feedback regarding the number of drinks consumed during a typical
drinking occasion in the past month. The first bar is your own drinking behavior, exactly as you
reported it on the recent online survey. The second bar represents your estimate of a typical member of
that group, also exactly as you reported it on the survey. How does your estimate compare to your own
alcohol use? Next, the third bar represents the actual drinking behavior of that group of students. At
the bottom left of the slide, the note informs you of the source of the data for the actual group norm.
Now that you are viewing the complete feedback slide, please take a moment to consider how your
own alcohol use, and your perceptions, are similar to or different from the average behavior of other
college students.
PNF Slide Number of Drinks Per Week:
The top of the slide will provide you with information about how your responses on the earlier online
survey compare to a specific group of college students. First, notice the top of the graph. This slide
will display your feedback regarding the total number of drinks consumed during a typical week in the
past month. The first bar is your own drinking behavior, exactly as you reported it on the recent online
survey. The second bar represents your estimate of a typical member of that group, also exactly as you
reported it on the survey. How does your estimate compare to your own alcohol use? Next, the third
bar represents the actual drinking behavior of that group of students. At the bottom left of the slide, the
note informs you of the source of the data for the actual group norm. Now that you are viewing the
complete feedback slide, please take a moment to consider how your own alcohol use, and your
perceptions, are similar to or different from the average behavior of other college students.
PNF Slide Max Drinks During One Occasion:
The top of the slide will provide you with information about how your responses on the earlier online
survey compare to a specific group of college students. First, notice the top of the graph. This slide
will display your feedback regarding the maximum number of drinks consumed at any one time in the
past month. The first bar is your own drinking behavior, exactly as you reported it on the recent online
survey. The second bar represents your estimate of a typical member of that group, also exactly as you
reported it on the survey. How does your estimate compare to your own alcohol use? Next, the third
bar represents the actual drinking behavior of that group of students. At the bottom left of the slide, the
note informs you of the source of the data for the actual group norm. Now that you are viewing the
complete feedback slide, please take a moment to consider how your own alcohol use, and your
perceptions, are similar to or different from the average behavior of other college students.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 51
APPENDIX C: Example Feedback Slides
1) The feedback presented below uses fictitious values to illustrate an example presentation, but the
actual values of each student were customized according to their self-reported perceptions and
behavior at baseline (always with actual norm approximately half of the perceived norm as in the slides
below).
2) The example feedback slides below display one example slide for each of the three drinking
variables used in the presentation and provides these sets for two of the four conditions (High
Credibility / High Specificity and Low Credibility / Low Specificity). This is represented by the
reference group being referred to in the text and the asterisk at the bottom of the slide describing the
source from where the data originated.
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 52
HIGH CREDIBILITY / HIGH SPECIFICITY
Total Number Of Drinks Per Week
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 53
HIGH CREDIBILITY / HIGH SPECIFICITY
Average Number Of Drinks Per Occasion
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
HIGH CREDIBILITY / HIGH SPECIFICITY
Maximum Number Of Drinks In One Occasion
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
HIGH CREDIBILITY / HIGH SPECIFICITY
Maximum Number Of Drinks In One Occasion
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 54
HIGH CREDIBILITY / HIGH SPECIFICITY
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
LOW CREDIBILITY / LOW SPECIFICITY
Total Number Of Drinks Per Week
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
LOW CREDIBILITY / LOW SPECIFICITY
Total Number Of Drinks Per Week
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 55
LOW CREDIBILITY / LOW SPECIFICITY
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
LOW CREDIBILITY /
Average Number Of Drinks Per Occasion
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
LOW CREDIBILITY / LOW SPECIFICITY
Average Number Of Drinks Per Occasion
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 56
LOW SPECIFICITY
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
LOW CREDIBILITY / LOW SPECIFICITY
Maximum Number Of Drinks In One Occasion
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION
LOW CREDIBILITY / LOW SPECIFICITY
Maximum Number Of Drinks In One Occasion
DECONSTRUCTING ELEMENTS OF A PNF INTERVENTION 57
LOW CREDIBILITY / LOW SPECIFICITY
Abstract (if available)
Abstract
Objective: The present research examines the roles of data source credibility and reference group specificity in the effectiveness of a simulated personalized normative feedback intervention to reduce perceived drinking norms of other students and decrease individuals’ own intentions to drink. Method: Following completion of an online pre‐intervention survey and using a 2x2 between‐subjects experimental design, 104 college student drinkers were randomly assigned to one of four experimental intervention conditions: two source credibility conditions concerning the validity of the data on which the group norm was based (high credibility, low credibility) and two specificity conditions (high specificity, low specificity) representing two different reference groups for which normative feedback was provided (i.e., a typical American college student or a same‐gender/same‐class year USC student). Participants then completed a post‐intervention questionnaire to assess for changes in study outcomes. Results: A series of multiple regression models was used to evaluate condition effects on the three main post‐intervention outcomes of perceived total drinks per week of American college students (Model 1), perceived total drinks per week of USC students (Model 2), and intended drinks per week (Model 3). For Model 1, a significant main effect was found for the credibility condition (β = -.27, p = .01). For Model 2, a significant main effect was found for the reference group condition (β = -.19, p = 04). In Model 3, no condition effects emerged as significant. No significant condition interaction effects were present in any of the models. Conclusions: The findings suggest that the credibility of the data source used in the provision of normative feedback is of importance for decreasing perceived drinking norms of the more distal American college student reference group, while the specificity of the reference group used in the PNF intervention had a stronger impact on reducing perceived drinking norms of students at one’s own university who are of the same gender and class year as the participant.
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Breaking it down to make it stronger: examining the role of source credibility and reference group specificity in the influence of personalized normative feedback on perceived alcohol use norms a...
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