Personalized normative feedback to reduce drinking among college students: a social norms intervention examining gender-based versus standard feedback.
Descriptive norms, which are beliefs about the most commonly exhibited behavior in a group, are commonly used in normative interventions to reduce harmful drinking and perceptions about the extent of drinking among peers. The present study examined if interventions utilizing gender personalized normative would decrease subjects 'misperceptions and individual drinking behavior (frequency and quantity) more than both a no feedback control group, and a group receiving standard normative feedback. The sample consisted of 161 female and 85 male participants with an average age of 21. Results demonstrated that feedback decreased misperceptions of others' alcohol use, however significant differences were not found between gender-specific feedback and gender nonspecific feedback, suggesting that tailoring the feedback by gender may not be particularly beneficial. Also, reductions in drinking among the groups from baseline through 2 month follow-up were not observed. Implications of the results and suggestions for further research that might refine social normative approaches are discussed.
The literature indicates that 80 to 90% of college students drink at least some alcohol (Graham, Tatterson, Roberts, & Johnston, 2004; Wechsler et al., 2003). Binge drinking most often occurs among college-aged individuals between the ages of 18 and 25 years old and is commonly defined as consuming 5 standard drinks for men and 4 standard drinks for women (Tapert, Tate, & Brown, 2001; Wechsler et al., 2003). Approximately 40% of college students who do drink alcohol engaged in binge drinking at least once in the previous two weeks (Kypri & Langley, 2003; Leigh & Neighbors, 2009; Wechsler et al., 2003).
One widespread approach that combats harmful collegiate drinking is the use of social normative interventions. Social normative information has been utilized in an attempt to change students' perceptions of others' drinking behaviors with the goal of decreasing individual drinking behavior. Interventions involving social normative feedback are based on the common finding that college students consistently perceive their peers as holding more permissive attitudes toward drinking and perceive them as drinking more often than the actual norm (Mattern & Neighbors, 2004). For example, Lewis and Neighbors (2004) found that college students overestimated the number of drinks the typical student has per week, as well as the frequency and quantity per occasion. Furthermore, Kypri and Langley (2003) found that perceptions of social drinking norms were established by socially proximal drinking groups. In other words, students' predictions for people the same age and gender were strongly associated with individual drinking levels when compared to predictions made for the typical student. In addition, Lewis and Neighbors (2004) found students overestimated the overall amount of alcohol use on campus. They found that males and females made more accurate predictions of others' drinking for their same gender peers, and that females were more accurate than males. These findings support the idea that gender-specific norms may be more representative and valuable to use when presenting personalized normative feedback.
Prior research demonstrates that there have been several approaches to using social normative information, including marketing strategies, personalized feedback during motivational interviewing, and personalized feedback given via the internet or by mail. Each way of presenting the norms involves different levels of personalization and involvement, ranging from the impersonal mass media marketing approach that requires no active involvement from the participant, to the personalized feedback provided through intense involvement in motivational interviewing or feedback through mail or via the internet.
Researchers have provided normative information through social marketing campaigns which typically convey messages about campus norms through mass media and several other announcement techniques (Wechsler et al., 1996). For example, Clapp et al. (2003) found that a 6-week social marketing campaign reduced misperceptions but not drinking behaviors among college students. In addition, Wechsler et al. (2003) studied the data from colleges that used social norm marketing campaigns and those that did not and found that these campaigns were not associated with any significant decreases in the seven standard measures of alcohol consumption (annual and 30 day use, frequency, usual quantity and volume consumed, heavy episodic use, and drunkenness) when compared to the colleges that did not use social norm marking campaigns. There may be several reasons why social norm marketing campaigns do not typically work. For example, there are some college students who do not binge drink, and there is little research on how nondrinking college students react to social normative information, especially if they drink below the norm or abstain from alcohol. In addition, marketing techniques and the media used to disseminate the message may impact the drinking related outcomes (Wechsler et al., 2003). Therefore, social norm information may be more effective in reducing misperceptions and excessive drinking episodes if it is personalized, rather than presented through mass media or presented over a long period of time. The difference may be related to how relevant the information is to the individual.
Recently, interventions aimed at reducing alcohol misuse on college campuses have been influenced by the harm reduction model. The basic goal of harm reduction is to educate students about how to minimize alcohol related negative consequences (Marlatt et al., 1998). An example of this approach is The Brief Alcohol Screening and Intervention for College Students (BASICS), which was developed for heavy drinking college students who may have already experienced negative consequences from drinking or are considered at high-risk for negative consequences. BASICS is comprised of two 50-minute sessions with a trained counselor familiar with the motivational interviewing approach which is defined as a therapeutic approach that aims to direct clients "past ambivalence toward positive behavior change" (Miller & Rollnick, 2002, p. 38). The first session is for data collection and assessment, and the second session, which occurs about 2 weeks later, is for feedback (Dimeff, Baer, Kivlahan, & Marlatt, 1999). The normative feedback given to each participant during BASICS is personalized in that it takes each student's drinking behavior and compares it to the student's perceived norm for other students' drinking and the actual norm for the typical student at the same school. The feedback is not personalized by gender however, which may be a relevant factor because men typically drink more than women (Marlatt et al., 1998). Research using BASICS has produced promising results, but a review of previous research using this approach is beyond the scope of this article. The interested reader is directed to several studies on the utility of BASICS (e.g., Agostinelli, Brown, & Miller, 1995; Bosari & Carey, 2000; Collins, Carey, & Sliwisnki, 2002; Cunningham, Humphreys & Koski-Jannes, 2000; Kypri et al., 2009; Marlatt et al., 1998; Neighbors, Larimer, & Lewis, 2004; 2000) The time required to present the normative information or the degree of exposure to the normative information, may also be an important factor, but one that has varied greatly from study to study. Clapp, Lange, Russel, Shillington, and Voas (2003) exposed students to a social norms marketing campaign for 6 weeks while Neighbors et al. (2004) shared the normative information directly after the participants completed a brief battery of questionnaires. Williams, Thomas, Buboltz, and McKinney (2002) found that a brief, 15-minute intervention given during a college class can decrease misperceptions about others' alcohol use. In addition, Baer et al. (1992) found that a single session of motivational interviewing, which includes feedback and advice about avoiding the risks of heavy drinking, significantly reduced the frequency and the number of drinks per occasion among student participants as much as 6 weeks of a classroom skills training program. Finally, Schroeder and Prentice (1998) utilized normative information with college students in a 1 hour presentation. Those who received the peer presented normative information reported a significant decrease in drinking when compared to a group that received values clarification. There was, however, no increase in the accuracy of the normative perceptions.
In summary, prior research has shown that a presentation of normative information is adequate to decrease misperceptions about others' drinking, and that students' perceptions of social norms are based on close drinking groups (Kypri & Langley, 2003). In addition, alcohol consumption was accurately predicted by a student of the same gender, especially for women (Lewis & Neighbors, 2004). Finally, results show that personalized normative feedback reduced misperceptions about others' drinking and decreased drinking among college students (Neighbors et al.).
It is still unclear if gender personalization in normative feedback is more effective than generic feedback, as researchers have not directly compared gender-specific feedback to the typical normative feedback method used in most studies. Thus, the purpose of this study was to determine if interventions utilizing normative information could benefit from gender personalization. It was hypothesized that a normative intervention will decrease misperceptions of others' alcohol use and decrease drinking behaviors among heavy drinking college students compared to a control group at follow-up. Heavy consumption was defined as drinking between 2-4 times a month or more. Specifically, it was hypothesized that the gender-specific personalized group will have more dramatic decreases in misperceptions and individual drinking behavior (frequency and quantity) than the nonspecific gender personalized group.
Three hundred and forty-six students enrolled at a midsized public university in the Southeast participated in the study. They were given extra credit and a chance to win prizes at follow-up as an incentive to participate in the two phases of the study. One student who did not wish to participate in the study was able do so without a penalty. All participants were treated according to the guidelines set forth by the American Psychological Association (APA). In addition, the Institutional Review Board (IRB) at the university reviewed and approved the study.
The sample consisted of 65% (n = 161) female and 35% (n = 85) male participants, with an average age of 21.3 years (SD = 5.5). The ages of the participants ranged from 18-50 years, with 56% of the sample being under the age of 21 years old. Most of the participants were freshman (48%), and the other half of the sample were sophomores, juniors, seniors, and other (2.4%, 19%, 29%, 1.6%, respectively). One hundred and twenty participants were recruited from introductory Freshman Year Experience classes (48.8%), and 126 participants were enrolled in upper level psychology courses (52.2%). Most of the participants were White (82%), with Black (7%), Hispanic (5%), Asian (3.3%), and other (3.3%) comprising the rest of the sample.
Of the 246 completers, 7% were employed on campus, 55% off campus, and 2% reported having both on and off campus jobs. Thirty-six percent of the completers were not employed. Of those who were employed, the average work week was 15.5 hours. Finally, 95% of the completers were full-time students at the university.
All questions concerning alcohol consumption will be based on standardized drinks as defined in Lewis and Neighbors (2004). One standard drink consists of 4 ounces of wine, a 10-ounce wine cooler, 12 ounces of beer (8 ounces of Canadian, malt liquor, or "ice beers", or 10 ounces of a microbrew), or 1 cocktail with 1 ounce of 100-proof liquor or 1.25 ounce of 80-proof liquor. The current study also included clarification of the definition of a standard drink not typically found in other research. The researcher obtained information on a typical "specialty drink" (e.g., a martini, Long Island Iced Tea, Absolut Stress, Rum and Coke, Whiskey and Coke) and determined that these drinks typically consist of at least three standard shots of 80-proof liquor per drink. Participants were instructed to consider specialty drinks when reporting their thoughts about others' drinking and their own drinking behaviors.
The measures used in the current study included a consent form, demographic information form, the Drinking Norms Rating Form (DNRF), the Alcohol Use and Disorders Identification Test (AUDIT), and the CAPS-r.
The Drinking Norms Rating Form (DNRF)
The DNRF evaluates individual perceived norms of alcohol use. The modified version used in this study requests the perceived number of drinks per occasion for each participant's best friend and the typical student, for each day of the week, and it has an additional question assessing the participants' perceptions about the number of drinks per occasion for a same-gendered student at the same school for each day of the week. The participant was able to enter any number in a blank space for each day of the week. A question about how often per month each participant thinks the typical student at his or her school consumes alcohol was also included. Each participant was able to choose an answer ranging from never to every day. The final question inquires about each participant's perception of the number of drinks consumed on a given occasion for the typical student, which provided the first dependent variable: perceptions of how many drinks the typical student at the same campus drinks per occasion. Answers for this question ranged between 0-25 or more drinks. In addition, the current study added a question asking about the perception of the number of drinks consumed on a given occasion for a same-gendered student at the same school; answers for this question also ranged between 0-25 or more drinks.
The original version of the DRNF can be found in the BASICS manual (Dimeffet al., 1999). According to Larimer, Turner, Mallet and Geisner (2004), the DNRF highlights how students' perceptions of other students' drinking behaviors are related to their own drinking behaviors. Lewis and Neighbors (2004) have found an internal reliability (Chronbach's alpha) of .76 for the nonspecific gender version used in their study, and .80 for the gender-specific version.
The Alcohol Use and Disorders Identification Test (AUDIT)
The AUDIT (Babor, de la Fuente, Saunders, & Grant, 1992) is a screening instrument developed by the World Health Organization and is used to identify individuals who have harmful drinking habits (Plake, Impara, & Spies, 2003). It consists of 10 questions, 3 of which involve quantitative alcohol consumption, 3 about general drinking behavior, 2 about adverse reactions, and 2 involving alcohol related problems. Of primary interest in this study were the questions about quantitative alcohol consumption and the frequency of alcohol consumption. For example, "How many drinks containing alcohol do you have on a typical day when you are drinking?" and "How often do you have a drink containing alcohol?" These questions provided the information for the second and third dependent variables: the frequency of personal drinking (how often), and the typical number of drinks consumed per drinking episode.
The current study modified the AUDIT to better conform to the time frame of a college semester. The AUDIT also provided inclusion and exclusion criteria for the current study. Participants who indicated that they "never" drink, or drink "monthly or less" were excluded from the main analyses due to the focus of the intervention, which was to assess the changes that occurred among college students who reported more significant use of alcohol, sometimes excessively. Researchers have found satisfactory test-retest reliability and internal consistency (Fleming, Barry, & MacDonald, 1991; the Mental Measurements Yearbook, 2003) and significant convergent validity (r = .88 for women and men) with the Michigan Alcohol Screening Test (MAST), another test commonly used to assess alcohol abuse (Bohn, Babor, & Kranzler, 1995).
College Alcohol Problem Scale-revised (CAPS-r)
O'Hare (1997) developed the College Alcohol Problem Scale (CAPS) to assess alcohol related problems among college students. Later, Maddok, Laforge, Rossi, and O'Hare (2001) refined the CAPS into the CAPS-r, an 8 item scale focusing on the personal and social problems of college students resulting from alcohol use. More specifically, the CAPS-r includes questions about the frequency of depressed or anxious feelings, self-esteem problems, appetite and sleeping problems, having unprotected or unplanned sexual activity, risk taking and other illegal activities. With the refinement, it was found that the CAPS-r had concurrent validity with the Young Adult Alcohol Problem Screening Test (YYAPST), r = .78. The format of the CAPS-r was modified in the current study to correspond with a college semester.
Random assignment to each of the three different feedback groups, the gender-specific, nonspecific gender, and control groups, was completed for each class rather than on an individual basis, because normative feedback was presented in a group format. Each participant received a pretest questionnaire packet with two copies of the consent form and measures of demographic variables, the DNRF, the AUDIT, and the CAPS-r. Of the 346 participants who completed the pretest questionnaire, 242 participants completed the posttest approximately three months later. Several attempts were made to contact those participants who did not complete the posttest, resulting in an additional 4 completed questionnaires; thus a total of 246 participants (71%) completed both pretest and posttest measures
Immediately after completion of the questionnaires at the pretest, those in the experimental classes were given a form prompting each participant to indicate how many drinks they have when they go out and drink (similar to the AUDIT); Normative feedback was provided in all class sections by the first author. All alcohol related information and feedback was derived from intracampus statistics using the American College Health Association-National College Health Assessment (ACHA-NCHA) which was collected at the same university. The normative feedback was either gender specific or nonspecific gender.. The control group received no feedback. Participants in the experimental conditions received a detailed representation of college drinking norms and their misperceptions. For example, in the gender-specific personalized normative feedback group, the participants reported the average number of drinks they have when they do drink and their perceived norms for college students of the same gender at the same campus. The researcher then instructed the participants to write in the norms for the students of the same gender at the same campus. This resulted in a comparison of the participants' drinking behaviors, their thoughts about others' drinking behaviors, and the actual drinking behaviors of other college students of the same gender on the same campus.
Also modeled from part of the feedback participants can receive during BASICS (Dimeff et al., 1999), participants in the current study received their percentile rank, depending upon the number of drinks they typically have in one sitting. They were also given additional normative information about the use of alcohol among their peers. The students were given no further instruction on the additional information other than they were free to view it at their leisure.
The posttest included the same measures as the pretest, although they were modified to reflect the participants' thoughts and behaviors since the beginning of the semester. The posttest also included questions assessing participation in an online tool for measuring alcohol use and any participation in activities related to a campus-wide Alcohol Awareness Week that focused on education and prevention of alcohol abuse. These questions were added to detect the presence of potential confounds in the study, given the study's intervention focus.
DESIGN AND STATISTICAL ANALYSES
The current study utilized a 3 (feedback condition) x 2 (sex of participant) x 2 (pretest and posttest) repeated measures mixed design. Data was analyzed using SPSS. Also, three separate 3 x 2 (feedback type x sex) analyses of covariance (ANCOVA) were conducted to determine if exposure to the different norms caused significantly different decreases in the misperceptions or overgeneralizations participants make for others' alcohol use (as measured by specific questions on the DNRF) and the mean drinking levels (as measured by specific questions on the AUDIT) among each group. Pretest misperceptions and drinking levels served as covariates to control for potential baseline differences. The main analyses also involved only those participants who reported drinking 2-4 times or more a month.
The CAPS-r was also included in the current study for secondary analysis. The researchers were interested in the relationship between the individual items and total score on the CAPS-r, and the number of drinks the participant typically drank per episode for all drinkers. In addition, a 3 x 2 (feedback x gender) mixed design repeated measures analysis of variance (ANOVA) was used to determine if there were any main effects or interactions for changes on the total score from the CAPS-r. No formal hypotheses were made in this regard.
To determine if there were any differences between those participants who completed just the pretest (i.e., noncompleters) and those who completed the pretest and the posttest (i.e., completers), a series of chi-square and independent samples t tests were used. Chi square tests showed no significant differences between completers and noncompleters, by sex and race/ethnicity, [chi square] (1) = .61, p > .05; [chi square] (4) = 2.13 ,p > .05, respectively. Significant differences were found between younger students (i.e., freshmen and sophomores) and upper level students (i.e., juniors, seniors, and others), [chi square] (1) = 6.11, p < .05 and type of feedback received, [chi square] (2) = 8.85, p < .05. Results indicated that more upper level students missed the posttest and the nonspecific feedback condition was the least represented at pretest. At posttest, the least represented feedback condition was the control group.
A series of t-tests were conducted to assess possible differences between the completers and noncompleters on the three dependent variables. There was a significant difference between completers and noncompleters on drinks per occasion. Completers drank significantly fewer drinks per occasion than noncompleters, t (343) = -2.38,p < .05, and had an average score of .88 (SD = 1.05)compared to 1.2 (SD = 1.35). The t-tests showed no significant differences between the completers and noncompleters with respect to perceptions of the number of drinks others drink per occasion and the frequency of participants' drinking, t (344) = -.530, p >.05 and t (343) = -.390, p >.05, respectively.
The covariate used for the perception of number of drinks consumed by others per episode was 5.89 drinks. The covariates for the behavioral dependent variables were 2.67 (associated with drinking 2-4 times a month), and 1.38 (associated with consuming 3-4 drinks per episode) for the frequency of personal drinking and number of drinks per episode, respectively. Analyses for the three drinking related dependent variables included only those participants who completed both the pretest and posttest and reported drinking at least 2-4 times a month.
Changes in Perceptions of Others' Drinking
ANCOVA analysis demonstrated a significant main effect for the type of normative feedback for the perceptions of others' drinking, F (2, 129) = 6.55, p < 0.05, [[eta].sup.2] = 0.90. This variable measured the number of drinks participants thought other students drank per episode. The adjusted mean and standard error for each group were: gender-specific feedback, 4.21 (.25); nonspecific gender feedback, 4.56 (.34); and control, 5.5 (.26). Tukey HSD found significant differences between the adjusted means comparing the gender-specific feedback group and the control group, as well as between the nonspecific feedback group and control group. Differences between treatment conditions were not significant. The main effect for gender was not significant, or was the feedback by gender interaction for the perceptions of others' drinking, F(1,129) = 0.67,p > 0.05, [[eta].sup.2] = 0.13; and F (2, 129) = 0.36,p > 0.05, [[eta].sup.2] = 0.10, respectively.
The ANCOVA showed no significant main effects for feedback or gender, and the feedback x gender interaction was also not significant for the frequency ofpersonal drinking, F (1,129) = 0.46, p > 0.05, [[eta].sup.2] = 0.10; F (2, 129) = 0.12, p > 0.05, [[eta].sup.2] = 0.07; F (2, 129) = 0.01, p > 0.05, [[eta].sup.2] = 0,05, respectively. The final ANCOVA showed no significant main effects for feedback or gender, and the feedback x gender interaction was also not significant for the quantity per episode of personal drinking, F (1, 129) = 2.69,p > 0.05, [[eta].sup.2] = 0.37; F(2, 129) = 0.25,p > 0.05, [[eta].sup.2] = 0.09; F (2, 129) = 0.97, p > 0.05, [[eta].sup.2] = .22, respectively.
The relationship between age and drinking perceptions and behaviors were evaluated using a Pearson r correlation. For all participants who completed the pretest, age was significantly correlated with pretest measures of the participants' perceptions of others' drinking (r = -.16, p < .001) and the number of drinks the participants drank per episode (r = -. 16, p < .01). According to these correlations, age was negatively correlated with perceptions of others' drinking and personal drinking behaviors. The older the participants, the less they thought other students' drank per episode and the less they drank per episode. For all participants who completed the posttest, correlations were present for the same variables, r = -.15,p < .05 and r = -.17,p < .01, respectively, with the same trend in responses.
CAPS-r analyses. Finally, the analysis of the relationship between alcohol related problems and the number of drinks the participant typically consumes are presented for both the pre- and post-test data in Table 1 and include all completers who reported to drink (less than monthly or more). The researchers also used a 3 x 2 (feedback x gender) mixed design repeated measures ANOVA and determined that there were no significant gender or normative feedback main effects or a feedback x gender interaction for differences in alcohol related problems on the CAPS-r total score from pretest to posttest for completers who reported drinking at least once monthly, F (1,198) = 0.15, p > 0.05; F (2, 198) = 0.31,p > 0.05; F (2, 198) = 0.26,p > 0.05, respectively. Table 2 shows the means and standard deviations of the CAPS-r total score for the two experimental groups and control group at posttest. Differences between groups were not significant, F (2, 205) = 0.574,p > 0.05.
Personalized normative feedback has been used to reduce binge and otherwise harmful levels of drinking among collegians and to decrease overestimations students make about alcohol use. In an attempt to refine specific parameters within the social norms approach (i.e., gender), the current study assessed both cognitions and self-reported drinking behaviors before and after the group presentation of personalized normative feedback that was either tailored to participants' gender or presented for the "typical" student.
The current research did not replicate the behavioral changes found in other studies (e.g., Baer et al., 1992; Barnett, Far, Mauss, & Miller, 1996; Borsari & Carey, 2000; Collins et al., 2002; Neighbors et al., 2004; Schroeder & Prentice, 1998). However, the normative feedback was effective in reducing the misperceptions participants had about other students' alcohol use. Regardless, the presentation of gender-based feedback (i.e., providing males and females with their respective drinking norms) did not significantly change the misperceptions more than feedback for the typical student. Overall, there were no significant differences in the reported frequency of drinking and quantity of drinks per drinking episode between males and females and among normative feedback groups which questions the overall usefulness of feedback used as an intervention without additional components (e.g., motivational interviewing, social skills training, drink refusal skills, cognitive behavioral therapy, environmental approaches, etc.). This is consistent with the latest recommendations from NIAAA.
Participants 'Perceptions and Drinking Behaviors
According to pretest measurements, 84% of the completers in the current study have used alcohol at least once in the past year, which is consistent with previous research (Wechsler et al., 2003). Thirty-eight percent of male completers participated in heavy episodic drinking in the past year defined as 5-6 drinks per episode. Forty-seven percent of female completers reported consuming 3-4 drinks per episode, which is consistent with previous research at other universities (i.e., Haines & Spear, 1996; Kypri & Langley, 2003) and is also consistent with campus norms. The data from the norms came from the ACHA-NCHA assessment at the same university and found that 50% of females and 37% of males drank 3-4 or 5-6 drinks per episode, respectively.
Previous research has found that college students generally perceive their peers engage in drinking more than the norm (Mattern & Neighbors, 2004). The current study replicated earlier findings of social normative research and found that female participants made more accurate predictions for a student of the same gender than for a typical student. On the other hand, male participants made more accurate predictions for the typical student than for students of the same gender. Of the completers, male participants in the current study reported the belief that other male students drank 7.12 (SD = 4.18) drinks per episode, while the typical student drank 5.93 (SD = 3.68). On the other hand, female participants were more accurate for the same gendered student and reported the belief that the same gendered student drinks 4.17 (SD = 2.18) drinks per episode, whereas the 'typical' student drinks an average of 5.25 (SD = 2.8) drinks per occasion.
The overall average for all completers in the current study was 3-4 drinks per episode, according to the mean score on the AUDIT, and for females, this is less than the norm found for other females at the same campus. According to AUDIT mean scores, male completers drank an average of 3-4 drinks per occasion, while female completers drank an average of 1-2 drinks per occasion. The fact that females in the current study drank fewer drinks per episode than the campus norm may have impacted results, even though the inclusion criteria of drinking at least 2 to 4 times a week was included in the main analyses to capture heavier drinkers.
Because of the documented problems associated with excessive drinking such as driving while intoxicated, motor vehicle accidents, potential mental health problems, and other high risk behaviors (e.g., NIAAA, 2002; Pullen, 1994), we also examined the relationship between individual items on the CAPS-r, the CAPS-r total, and alcohol consumption. Our findings here clearly demonstrate why research involving harm reduction messages should continue. For example, the current study found moderately strong correlations between drinking and unplanned/unprotected sexual activity, driving under the influence, and participation in other illegal activities. Also, social normative feedback does not appear, at least in the present study, to effect negative alcohol related problems as evidenced by non-significant differences on the CAPS-r total score between the experimental groups and the control group from pretest to posttest.
The differences between the completers and non-completers may have impacted results. Analyses showed that completers drank significantly fewer drinks per episode than non-completers at baseline; thus, the heavier drinking students were not included in the analysis due to missing the posttest measurement. In addition, the information provided based on gender was not all inclusive and could have included other behavioral or even biological factors that may differentially impact men and women's perceptions and drinking behavior (e.g., alcohol decreases testosterone, may increase weight and speeds aging process). Finally, because the study was implemented within a mid-sized university in the south with female participants (65%), generalizations of the findings to other samples should be made cautiously.
Replication and expansion of the current study would be beneficial to determine the effects of gender personalization with a sample that consistently consumes more alcohol than the participants in the current study. Perhaps, using a larger sample with more stringent inclusion criteria, such as elevated total scores on the AUDIT or the CAPS-r, would be useful in detecting differences between gender-specific and nonspecific feedback, as previous researchers have detected, i.e., Neighbors et al. (2004). Also, Larimer, Turner, Mallet and Geisner (2004) argue that the inclusion of injunctive norms (i.e. the acceptability of drinking behaviors among peer groups) in prevention and intervention strategies based on social norms may be beneficial. In fact, a comparison of descriptive and injunctive norms may help to determine how normative feedback could or should be presented to college students to attain the greatest reduction in harmful drinking.
Results demonstrated that feedback decreased misperceptions of others' alcohol use more than not receiving feedback. No significant differences were found between the gender-specific normative feedback and nonspecific feedback conditions, suggesting that tailoring the feedback by gender may not provide additional benefits, at least based on the gender-specific drinking norms utilized here. As with other findings from the literature, the relative absence of behavioral changes (i.e., reduction in drinking) after the presentation of the personalized normative feedback in the present study is not surprising. This supports the notion that norm-based interventions need to occur within the context of a more comprehensive campus and community-wide harm reduction strategy (NIAAA, 2007).
Correspondence concerning this article should be addressed to: Rob J. Rotunda, Department of Psychology, University of West Florida, Pensacola, FL 32514; Phone: (850) 474-2294; Email: email@example.com.
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Renee Lojewski, Rob J. Rotunda and James E. Arruda
University of West Florida
TABLE 1 Correlations Between Number of Drinks per Episode and Questions on CAPS-r for AU Drinkers. Pretest Posttest Pearson Pearson Correlation Correlation CAPS-r question (n = 283) (n = 283) Feel sad .15 * ns Feel nervous .21 ** .19 ** Appetite/Sleep problems .28 ** .40 ** Unplanned sexual activity .35 ** .29 * Drove under the influence .43 ** .32 ** No protection during sex .17 ** .15 Illegal activities .35 ** .31 CAPS-r total score .44 ** .36 ** Note. ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). TABLE 2 Means and Standard Deviations for Posttest CAPS-r Total Score by Normative Feedback Group. Type of feedback Mean SD N Gender-Specific 3.68 (5.14) 80 Nonspecific 3.96 (4.55) 53 Control 4.6 (6.24) 73 ** Note: Calculated for completers who reported drinking at least once per month at pretest.
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|Author:||Lojewski, Renee; Rotunda, Rob J.; Arruda, James E.|
|Publication:||Journal of Alcohol & Drug Education|
|Date:||Dec 1, 2010|
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