BACKGROUND

Underage school students who acquire and use false identification (fake ID) are at risk for unfavourable outcomes. Nevertheless, it is presently unclear how uniquely the fake ID itself serves as a automobile to subsequent harm (i.e., the “fake ID effect”) over and above basic and trait-associated risk components (e.g., deviant peers, low self-control).

METHODS

In an effort to examine whether the “fake ID effect” would hold after accounting for phenotypic risk, we utilized propensity score matching (PSM) in a cross-sectional sample of n=1,454 students, and a longitudinal replication sample of n=three,720 undergraduates. People with a fake ID have been matched with people with no fake ID, when it comes to quite a few trait-based and social risk factors. These matched teams have been then compared on five problematic outcomes (i.e., frequent binge ingesting, alcohol-associated problems, arrests, marijuana use, and arduous drug use).

RESULTS

Fake-ID-1

Findings confirmed that “fake ID results” have been substantially—although not absolutely—diminished following PSM. The “fake ID effect” remained strongest for alcohol-associated arrests. This may increasingly relate to issues of enforcement and students’ willingness to have interaction in deviant behavior with a fake ID, or it may be a operate of mixed processes.

CONCLUSIONS

General, the findings recommend that interventions shouldn’t solely be geared toward reducing fake ID-associated alcohol entry specifically, however also needs to be aimed extra usually in the direction of at-risk youths’ entry to alcohol. Future analysis might examine whether fake IDs have their strongest efficiency as moderators of the results of dangerous traits—equivalent to impulsiveness—on ingesting outcomes.

Key phrases: False identification, Fake IDs, underage alcohol use, heavy episodic ingesting, binge ingesting

Introduction

Fake IDs, a novel mode of alcohol entry, are increasingly wanted as people near the minimum legal ingesting age (Martinez et al., 2007; Wagenaar et al., 1996). These forms of false identification could also be borrowed (or duplicated) from an older peer or sibling (Myers et al., 2001), or they might be a specifically crafted doc obtained domestically or from a web-based vendor (Murray, 2005). No matter their supply, there appears to be a bidirectional relation between heavy ingesting and fake IDs, such that (1) heavy ingesting predicts subsequent obtainment of a fake ID, and (2) “possession” (i.e., possession) of a fake ID predicts subsequent frequency of heavy ingesting (outlined as 5+ drinks per occasion; Martinez, et al., 2007).

This bidirectional relation not solely illustrates the public well being risks of this mode of alcohol entry, however begs the question of whether it is extra the case that a fake ID itself serves as a automobile to subsequent harm (i.e., the “fake ID effect”) or whether such harms and outcomes are predominantly pushed by a basic stage of phenotypic risk on the a part of the fake ID “proprietor” (e.g., deviant peer associations, low self-control). Though basic alcohol entry theories might assist the former hypothesis almost entirely (namely, fake ID possession increases alcohol entry and subsequent harm; see Gruenewald, 2011), basic criminological theories of phenotypic risk assist the latter (namely, that broad categories of risk—or propensities to have interaction in dangerous behavior—are the true reason behind harm; see Pratt & Cullen, 2000). Certainly, such propensities could be what predicts fake ID obtainment in the first place, and although the strength of the fake ID effect appears to increase over time, it is drastically diminished after controlling for intercourse, Greek standing, and pre-school rates of ingesting (Martinez et al., 2007). In sum, it is unclear how sturdy the fake ID effect could be after accounting for individuals’ ranges of phenotypic or propensity risk—although this question has bearing on prevention and policy initiatives, which can give attention to either strengthening enforcement of fake ID laws themselves, increasing assets for trait-based at-risk youth packages, or a community-pushed mixture of both (see Fell, Thomas, Scherer, Fisher & Romano, 2015; Fell, Scherer, Thomas & Voas, 2016; Fell, Scherer & Voas, 2015; Grube, 1997) .

Thus, with the intention to examine the strength of the fake ID effect, we matched students with and without fake IDs on quite a few risk-based covariates utilizing propensity score matching (PSM) techniques. We first compared matched teams’ ingesting- and drug-use-associated outcomes in a cross-sectional sample of n=1,454 school students at a big Southeastern university. We additionally compared matched teams in an extra longitudinal replication sample of n=three,720 undergraduates at a big Midwestern university. We hypothesized that the results of fake ID possession on outcomes could be drastically diminished by—and subsequently largely attributable to—the pre-present trait-based components on which fake ID homeowners and non-homeowners might be matched. These comparisons can inform the extent to which the relationship between unfavourable outcomes and false identification possession are attributed to selection components, which once more, might have practical software for intervention and policy.

Process and Contributors

Two samples have been individually investigated following Institutional Evaluation Board (IRB) approval: (1) A cross-sectional sample of n=1,454 underage school students from a big Southeastern College (IRB Protocol H12032) and (2) a prospective replication sample of n=three,720 undergraduates below the minimum legal ingesting age from a big Midwestern college (IRB Protocol 01-01-001). Of note, both samples supply unique insights into the relationship between false identification use and unfavourable outcomes. Extra specifically, the cross-sectional examine includes items that distinguish between the use of fake IDs in several conditions (at bars, at grocery stores, etc.) and the longitudinal examine affords perception into the potential results of fake ID possession over time and establishes temporal order.

With regard to the cross-sectional sample, during the educational year 2011–2012, members have been recruited from forty randomly chosen massive (>ninety nine students) and moderate enrollment (30–ninety nine students) classes. Contributors accomplished a one-web page knowledgeable consent doc in the chosen classes earlier than being given a six-web page paper survey about school life and behaviors to complete with pencil or pen. Contributors weren’t compensated. All enrolled students have been invited to participate and the response fee was high at 80.four% (Stogner & Miller, 2013; 2014; Hart et al., 2014). After these above the legal ingesting threshold have been removed, the analytic sample was n=1,454 underage individuals. The sample was largely representative of the college with regard to demographics and was specifically 51.6% feminine, 68.9% White/non-Hispanic, with an average age of 18.ninety five (SD=.795). Though this sample is cross-sectional, establishing temporal ordering of the covariates and fake ID possession is basically inconsequential for almost all of covariates as many are immutable (age, race, gender) or outdoors of the individual’s control (dwelling location, parental earnings, sexual orientation, etc.).

The longitudinal sample additionally utilized a self-report survey methodology. All incoming students in 2002 have been recruited to complete an instrument during the summer season prior to school entrance utilizing paper and pencil and then have been requested to complete on-line surveys every semester for the following 4 years (a total of eight semesters). Students provided knowledgeable consent and have been compensated $25 in every wave. After excluding the n=35 who have been of age, 88% of the eligible coming into class accomplished the survey (n=three,720). The sample was 53.7% feminine, 90.three% White/non-Hispanic, and averaged 17.9 (SD=.36) years of age (reflecting demographics which can be representative of the college as an entire [University Registrar, 2013]). Students have been historically aged; by the start of their junior year, only one-third of the sample had reached the minimum legal ingesting age, climbing expectedly to 99.7% by the final semester of school, Pattern retention was good, ranging from 69% to 87% of baseline respondents participating at every subsequent wave. Retention biases have been low, although people have been extra likely to remain in the sample in the event that they have been females (OR=2.33) and have been less likely to remain in the sample in the event that they have been frequent binge drinkers (OR=.88; Sher & Rutledge, 2007). By the final time-point, the sample measurement was n=2,250, although 90% of students participated in two or extra evaluation waves and eighty two% participated in three or extra waves. The longitudinal PSM offered inside the text utilized the first two years of school solely (i.e., the first 4 semesters, when the overwhelming majority of members have been underage) and, according to most PSM analysis, solely created matches between people in a manner which is straight akin to the evaluation carried out with the cross-sectional sample.1

Measures

For the purposes of replication, it was important that the measures utilized in both the cross-sectional and longitudinal research stayed as similar as possible. For ease of presentation, measures are organized when it comes to their conceptual significance to the general examine with cross-sectional and longitudinal measures explained together in every section. Timing of the longitudinal measures was considered important and is described as is appropriate. Specifically, although the eight-wave longitudinal sample included a number of measurements of many covariates across time, the primary longitudinal PSM solely utilized measurements as they would be expected to occur if observing a “fake ID effect” over a logical progression of time (i.e., Trait/propensity measures have been measured at Wave 1 and used to foretell fake ID possession at Wave 2 which in turn assessed as a predictor for final result measures at both Waves three and Wave four). The second semester of school (Wave 2) was chosen because the singular target time-point at which fake ID possession (or the “fake ID effect”) was measured, as a result of it is thought to be a peak time of risk for unfavourable ingesting-associated outcomes and false ID possession (see Martinez et al., 2008).

Foremost Outcomes Five outcomes associated to substance use have been explored. First, a measure of frequent binge ingesting was created in both samples. A six-choice ordinal item requested respondents how many days in the last month did they devour five or extra alcoholic drinks. A intercourse-particular binge ingesting measure was not available. Those deciding on either of the two highest frequency options (10–19 days and 20+ days) have been categorized as frequent binge drinkers whereas all others have been not. This dichotomous item represents binge ingesting more than ten days in the last month. Second, we utilized an instrument created by Maney, Higham-Gardill, and Mahoney (2002) to represent alcohol-associated problems in the cross-sectional sample. This ten-item scale assesses the diploma to which the individual feels that alcohol use has created relationship, family, well being, behavioral, and professional/college problems in the last year and shows ample reliability (α=.822). Within the longitudinal sample, this scale was approximated from ten items taken from the Young Grownup Alcohol Problems Screening Take a look at (YAAPST; Hurlbut & Sher, 1992) with ample reliability (α=.848 in second-year fall and α=.846 in second-year spring). A dichotomous alcohol-associated arrest/quotation measure was created within both samples utilizing items that requested respondents if they’d ever been arrested or cited for driving below the affect, underage ingesting, public disorder (attributable to alcohol), being drunk in public, or an open container violation in the last year. The final two outcomes have been both dichotomous and measured equally in every sample; marijuana use and arduous drug use represent whether the respondent self-reported any use of marijuana and cocaine, heroin, and/or methamphetamine, respectively, in the last year.

False Identification Present fake ID “possession” was assessed dichotomously in both samples (zero=No, 1=Sure). The cross-sectional examine additionally included additional items that requested respondents whether or not they had used the fake ID in a bar or membership and whether or not they had used it in a retailer to buy alcohol.

Trait and risk factor (matching) covariates Fifteen variables have been utilized in propensity score matching in the cross-sectional sample and fourteen have been used in the longitudinal sample. Variables have been chosen attributable to their inclusion in both datasets and former analysis suggesting that they might be associated to the propensity to personal a fake ID and experience one of many five outcomes. These matching variables are: (1) age, (2) age of alcohol use onset, (three) employment standing, (four) publicity to substance use, (5) family earnings, (6) gender, (7) GPA, (8) Greek membership, (9) well being, (10) low self-control, (eleven) peer substance use, (12) race, (thirteen) rural dwelling location (solely measured in the cross-sectional examine), (14) sexual orientation (1=LGBT), and (15) subjective distress.

Eight of the fifteen variables have been measured identically and a ninth was measured almost identically. Among these identically measured have been age, age of first alcohol use, employment standing (zero= not employed; 1=employed), gender (zero=feminine; 1=male), self-reported grade point common (GPA), membership in a campus Greek group (zero=non-member; 1=member), race (zero=white, 1=non-white), and sexual orientation (zero=heterosexual; 1=lesbian, homosexual, bisexual, or other). Self-reported well being was measured with an item that requested respondents to fee their own well being—the cross-sectional examine provided responses ranging from 1 (poor) to four (glorious) whereas the longitudinal examine options ranged from 1 (poor) to five (glorious).

The cross sectional examine utilized 4-item measures adapted from Lee, Akers, and Borg (2004) to represent publicity to substance use (α=.786) and peer substance use (α=.801). Because the longitudinal information did not embrace similarmeasures, every of these constructs was represented by a single item moderately than a 4-item scale. The first (publicity) was measured dichotomously whereas the second (peer substance use) was measured on a six-choice ordinal scale. Low self-control was operationalized utilizing the 24-item Grasmick et al. (1993) scale (α=.889) in the cross-sectional examine and the NEO Five Factor Stock conscientiousness scale (reverse-coded) in the longitudinal sample (α=.844; Costa & McCrae, 1992). Subjective misery was measured utilizing Cohen and Williamson’s (1988) ten-item perceived scholar stress scale (α=.814) in the cross-sectional examine and the World Severity Index from the Brief Symptom Stock-18 in the longitudinal sample (Derogatis, 2000). Larger values on these scales represent extra publicity to substance use, a larger portion of peers that use substances, decrease self-control, and extra subjective misery, respectively.

Each research included a single-item family socioeconomic standing measure. Within the cross-sectional examine a measure of family earnings was used. Contributors chose between options ranging from below $10,000 per year (coded 1) to over $175,000 per year (coded 9). An item assessing whether or not students have been the first of their family to attend school (zero=No, 1=Sure) was utilized in the longitudinal study.

Rural dwelling location was used in the cross-sectional examine, however no similar measure was accessible in the longitudinal data. This variable was important to include despite creating differing matching standards because of the traits of the examine area. The cross-sectional sample was drawn from an space that may be very rural excluding one main city; thus, a dichotomous item representing whether the scholar grew up in an city / suburban space (coded zero) or a rural one (coded 1) was included. By comparability, this was not a special consideration for the longitudinal sample, which originated from a college of 35,000 that pulls students from two massive neighboring cities and its personal moderately massive population.

Analysis

First, we estimated the proportions of fake ID possession in both the cross-sectional and longitudinal samples. In addition to possession of a fake ID, the cross-sectional sample additionally documented members’ utilizing of the fake ID in bars/clubs and stores. We estimated the bivariate associations of fake IDs with the five specified substance use outcomes in both samples—a rudimentary “fake ID effect.”

Next, to higher determine the strength of the “fake ID effect” after accounting for trait measures, propensity score matching (PSM) was used for both samples. PSM affords a clearer image of the relationship between two variables than bivariate analyses which can yield spurious outcomes (Guo & Fraser 2009) and has been used to evaluate issues associated to substance use (Miller et al., 2011). Also of note, PSM is preferable to multivariate regression fashions in instances equivalent to this the place the variable of interest will not be independently connected to the dependent variable, however is probably going correlated with these which can be and also occurs extra proximally. The propensity matching strategies developed by Rosenbaum and Rubin (1983, 1985) can be used to create a sample with two teams which can be similar in all related variables except for the “therapy” (i.e., fake ID possession). While their strategies do result in a discount in measurement of analytic sample (usually leading PSM to be known as resampling), they’re effective at making a scenario whereby the effect of “therapy” will be estimated as the typical difference between these uncovered to the therapy and “counterfactuals,” outlined because the anticipated outcomes have been it not for publicity to the therapy (Guo & Fraser 2009). In this case, the PSM technique creates analytic teams whereby differences other than false identification use are minimalized.

As prompt by Rosenbaum and Rubin (1983, 1985), we utilized logistic regression to estimate a propensity score for every participant in every analytic sample. Fake ID possession was regressed on 15 covariates in the cross-sectional sample (age, age of firsts alcohol use, employment standing, publicity to substance use, family earnings, gender, grade point common, membership in a campus Greek group, self-assessed well being, low self-control, peer substance use, race, measurement of dwelling community, sexual orientation, and subjective misery) and 14 similar variables (measurement of dwelling community excluded, as explained above) in the main longitudinal PSM evaluation (i.e. fake ID possession measured at the second semester and outcomes evaluated in the third and fourth semesters). Utilizing these fashions, every participant’s propensity score was then calculated as their conditional chance of getting a fake ID. Following an evaluation of regions of frequent assist, we created comparability teams within every sample utilizing a two-to-one nearest neighbor matching algorithm with a caliper calculated as .25σ of the propensity scores (see Guo & Fraser 2009). This caliper was .0725 in the cross-sectional sample and .0426 in the longitudinal sample. This matching approach led to the expected decrease in sample measurement (n=817 and n=518, respectively) however a adequate number of circumstances have been retained for statistical comparisons.

Rates of fake ID possession

Rates of fake ID possession have been quite high, notably in the cross-sectional sample. That’s, of the 1,454 underage alcohol consumers in the cross-sectional sample, 583 or 40.1% personal or have owned a fake ID, 560 (38.5%) have used a fake ID at a bar, and 460 (27.8%) have used the ID to buy alcohol at a store. Prevalence rates of false ID use in the Midwestern sample changed over time. Fake ID possession amongst students below 21 peaked during the third year of school (pre-school=12.5%, first-year fall=17.1%, first-year spring=21.four%, second-year fall=28.1%, second-year spring=32.2%, third-year fall=34.9%, third-year spring=39.zero%, fourth-year fall=38.1%, fourth-year spring= fewer than ten students have been under the minimum legal ingesting age).2

The “fake ID effect” previous to matching

Desk 1 presents imply scores for five substance use outcomes for fake ID homeowners and non-homeowners in both samples (outcomes at both Wave three and four are reported for the longitudinal sample). Common scores for every final result (frequent binge ingesting [10 or extra days in the last month], self-reported alcohol associated problems, alcohol-associated arrests, marijuana use, and arduous drug use) are offered for those that have and haven’t owned a fake ID, used a fake ID at a bar/membership (cross-sectional sample solely), and used a fake ID at a retailer (cross-sectional sample solely). Unbiased samples t-assessments have been performed to find out whether, on common, differences exist between fake ID users and non-users. Every of the assessments reached significance. No matter whether the focus was possession of a fake ID or utilizing it at a specific kind of outlet, the outcomes have been consistent. At the bivariate stage, extra people with false identification interact in frequent binge ingesting, have been arrested/cited for an alcohol violation, interact in marijuana use, and use arduous drugs. People with fake identification additionally, on common, report extra alcohol-associated problems. These outcomes would indicate that fake IDs are a automobile of risk. Nevertheless, it is possible that fake ID possession (and related risks) are extra a operate of underlying dangerous traits.

Propensity score matching (PSM)

As a result of consistency in the findings so far no matter false identification measure (possession, bar use, and/or retailer use), the extra analyses with every sample utilizes only one false identification measure, possession of a false ID. We carried out PSM analyses in both samples, to examine whether people with and without fake IDs continue to differ on these outcomes after being matched on substantively important traits. Desk 2 shows that people with and without fake IDs certainly differed from each other on these trait propensity variables, suggesting that it is these variables which can finally be driving the fake ID effect. Desk 2 additionally shows that the PSM approach worked nicely in both samples, persistently reducing bias associated with the statistically significant differences between these with and without fake IDs by more than 50% on all however one variable. Although three significant differences still remained in the cross-sectional sample (age of alcohol use onset, Greek affiliation, and having been raised in a rural space), the magnitude of the differences in age of onset and Greek affiliation have been minor in comparison with pre-matching. In this, matching was equally, if no more, profitable in the longitudinal sample. It needs to be famous that matching did yield a discount in sample size. General, nonetheless, in both samples matching appears to have created therapy and comparability teams which can be extra equivalent and extra applicable for comparability than the unmatched data.

The propensity scores that have been calculated for every case are graphically displayed in Determine 1. As will be seen in the figure, a region of frequent assist exists, however very few with low propensity scores had a fake ID and very few with high propensity scores did not.

Evaluating fake ID homeowners and non-homeowners after PSM

Cross-sectional sample After matching, false identification homeowners and non-homeowners have been compared on every of the five substance use associated outcomes. While considerably extra of these with fake IDs in the cross-sectional sample have been frequent binge drinkers previous to matching (t=9.81, df=815), the teams have been no longer considerably different after matching (t=1.81, df=815) and the typical therapy effect (ATE; e.g., differences in group means), as displayed in Desk three, was decreased by 59.2%. Equally, previous to matching, fake ID homeowners had considerably increased scores on the alcohol associated problems scale than non-homeowners (t=9.83, df=815), but the teams have been no longer considerably different after matching (t=1.31, df=815) and the ATE was decreased by 63.four%. Nevertheless, when it comes to alcohol-associated arrests, the two teams have been still considerably different and the ATE effectively remained unchanged. As was the case for the first two outcomes, fake ID possession was associated with marijuana use previous to matching (t=9.36), however not after (t=1.fifty two; ATE decreased by 60.four%). Finally, arduous drug use was associated with fake ID possession both earlier than (t=7.26, df=815) and after matching (t=2.29, df=815), but the ATE was decreased by 38.four%.

Longitudinal sample As was the case in the cross-sectional sample, propensity score matching led to a substantial decrease in the ATE for 4 of the five outcomes (Desk three, columns three–6). Nevertheless, unlike the cross-sectional sample, ATEs remained significant for alcohol associated problems (t=4.00 wave three; t=4.17, wave four, df=516) and marijuana use (t=4.thirteen, wave three; t=2.58, wave four, df=516) after propensity score matching. The ATE additionally remained significant for frequent binge ingesting (t=3.26, df=516, wave three) and arduous drug use (t=2.06, df=516, wave four) at one wave however not the other. Once more, these results sizes have been substantially decreased, however in the aforementioned circumstances, not eliminated. As was the case in the cross-sectional sample, propensity score matching had little affect on the ATE on alcohol-associated arrests.three

Conclusions

This examine’s initial outcomes are according to earlier analysis—a substantial number of underage students have fake IDs and are at increased risk for binge ingesting, alcohol-associated problems, alcohol associated arrests, and other substance use (see Arria et al., 2014; Martinez & Sher, 2010; Nguyen et al., 2011). But our work additionally confirmed that for some outcomes, plainly what initially may need seemed to be a “fake ID effect” is basically the result of components that influenced both the acquisition of the false ID and the outcome. The numerous relationship between fake ID use and other substance use outcomes usually remained after PSM, but the magnitude of these relationships have been substantially diminished, most by over forty%. Alcohol-associated arrests have been an exception as the relationship was unaffected by PSM (i.e., after matching, these with a fake ID have been still at equally high ranges of risk for alcohol-associated arrests [DUIs, open container, etc.]). The rationale this final result is distinct from the others isn’t readily clear; perhaps legislation enforcement officers usually tend to subject citations or arrests for other substance-associated offenses when an individual can also be found with a fake ID. If this is the case, the “effect” wouldn’t appear smaller in propensity score fashions because the difference could be pushed by officers’ reactions to the fake ID moderately than people’ underlying propensity.

The pattern that emerges from Desk three seems to indicate that non-matched samples might have overestimated the effect of false identification use on unfavourable outcomes, however that fake ID possession has an effect that extends past shared causal factors. This particular remaining “fake ID effect” could certainly assist the concept that the fake ID itself serves as a type of threshold into other forms of deviant behavior, the place those who are willing to amass fake IDs become increasingly willing to violate other laws (see Ruedy et al., 2013; Winograd et al., 2014). But in mild of the other findings, it is extra possible that fake IDs extra usually moderate the results of dangerous traits on behavior. For example, fake IDs might have the highest efficiency of effect through offering impulsive people with additional means and alternative for problematic behaviors that they would not otherwise have engaged in. Indeed, underlying trait risks are sometimes incorporated into alternative-idea-associated examinations of crime (Grasmick et al., 1993; Lagrange & Silverman, 1999).

As such, these findings have practical implications. Although elevated server training, fake ID production/provider laws, and liability laws are an important means of addressing the risks of fake IDs as a form of alcohol entry (Fell, Scherer, Thomas & Voas, 2014; Yörük, 2014), faux-ID associated outcomes may also partly be a operate of trait risks that may moreover be addressed with intervention. One approach to start addressing this mix of things could also be through motivational, normative feedback-based, or abilities interventions which can be specifically geared toward reducing the likelihood that at-risk students acquire a fake ID (see Fromme & Orrick, 2004; Larimer & Cronce, 2007). Moreover, a fake ID obtainment-aimed intervention might possibly be broadly incorporated into interventions which can be particularly tailored towards addressing both people’ dangerous traits and their ensuing behaviors (see Conrod et al., 2006).

Though a fantastic strength of this examine rests in the same findings found with two unique school populations, these findings will not be generalizable to non-school attending populations. Moreover, fake ID policies, enforcement, and concern of sanctions might fluctuate substantially in several localities (Erickson, Lenk, Toomey, Nelson & Jones-Webb, 2016). For example, some ingesting establishments could also be lenient of their carding policies, deliberately accept false identification, and/or not be topic to rigorous regulatory enforcement (Murray, 2005). Also, penalties for possessing and/or utilizing a fake ID to buy alcohol varies substantially from state to state including the kind of offense, amount of advantageous, suspension of driver’s license, and the potential for probation or jail time. Future analysis ought to evaluate the impact of fake ID relative to differential policies and enforcement of the minimum legal ingesting age, including community efforts (Grube, 1997). Further, whereas fifteen distinct traits have been included in the matching course of, there stays the likelihood that additional components not measured in our information would affect both the willingness to entry a fake ID and the end result measures. If this is the case, the “fake ID effect” could also be even smaller than our matching fashions suggested.

In concluding that the “fake ID effect” is mainly a operate of phenotypic risk, fake ID possession might function an indicator of heightened risk for extra severe ingesting associated problems. Though most penalties for fake ID possession are punitive (fines, probation/jail, and/or loss of driver’s license), policy-makers, college officers, and practitioners ought to target fake ID homeowners for intervention methods geared toward reducing high-risk ingesting behaviors (and other problematic behaviors linked to phenotypic risk). Though elevated penalties and enforcement of the minimum legal ingesting age has the potential to reduce fake ID possession, we caution policy-makers to evaluate and contemplate the unfavourable penalties of transferring school ingesting away from regulated establishments the place security and emergency providers are extra available (see Baldwin et al., 2012; 2014). Though our findings found that fake ID possession (no matter particular person risk traits) elevated the chance for alcohol associated arrests, drug use, and alcohol associated problems (Midwest sample solely), we did not assess victimization and other harms associated with excessive alcohol consumption that would enhance in spaces not topic to regulatory controls (Miller, Levy, Spicer & Taylor, 2006). Future analysis is required to evaluate the impact that fake ID enforcement might have on problematic ingesting both in regulated and unregulated spaces.