Underage faculty students who acquire and use false identification (fake ID) are in danger for negative outcomes. Nevertheless, it is at the moment 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 threat factors (e.g., deviant peers, low self-control).


In order to examine whether or not the “fake ID effect” would maintain after accounting for phenotypic threat, we utilized propensity rating matching (PSM) in a cross-sectional sample of n=1,454 students, and a longitudinal replication sample of n=3,720 undergraduates. People with a fake ID have been matched with individuals and not using a fake ID, when it comes to a number of trait-based mostly and social threat factors. These matched teams have been then in contrast on 5 problematic outcomes (i.e., frequent binge consuming, alcohol-associated problems, arrests, marijuana use, and onerous drug use).



Findings showed that “fake ID results” have been considerably—although not fully—diminished following PSM. The “fake ID effect” remained strongest for alcohol-associated arrests. This may increasingly relate to problems with enforcement and students’ willingness to have interaction in deviant conduct with a fake ID, or it could be a perform of combined processes.


Overall, the findings recommend that interventions shouldn’t solely be aimed at reducing fake ID-associated alcohol entry specifically, but also needs to be aimed extra usually in direction of at-threat youths’ entry to alcohol. Future analysis might study whether or not fake IDs have their strongest efficiency as moderators of the effects of risky traits—similar to impulsiveness—on consuming outcomes.

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


Fake IDs, a novel mode of alcohol entry, are more and more wanted as individuals close to the minimum legal consuming age (Martinez et al., 2007; Wagenaar et al., 1996). These types of false identification may be borrowed (or duplicated) from an older peer or sibling (Myers et al., 2001), or they could be a specially crafted document obtained domestically or from an internet vendor (Murray, 2005). Regardless of their source, there appears to be a bidirectional relation between heavy consuming and fake IDs, such that (1) heavy consuming predicts subsequent obtainment of a fake ID, and (2) “possession” (i.e., possession) of a fake ID predicts subsequent frequency of heavy consuming (defined as 5+ drinks per event; Martinez, et al., 2007).

This bidirectional relation not solely illustrates the general public well being risks of this mode of alcohol entry, but begs the question of whether or not 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 or not such harms and outcomes are predominantly pushed by a basic stage of phenotypic threat on the part of the fake ID “proprietor” (e.g., deviant peer associations, low self-control). Though basic alcohol entry theories might help the former speculation almost completely (specifically, fake ID possession increases alcohol entry and subsequent harm; see Gruenewald, 2011), basic criminological theories of phenotypic threat help the latter (specifically, that broad categories of threat—or propensities to have interaction in risky conduct—are the true cause of harm; see Pratt & Cullen, 2000). Certainly, such propensities is likely to be what predicts fake ID obtainment in the first place, and though the energy of the fake ID effect appears to extend over time, it is greatly diminished after controlling for sex, Greek status, and pre-faculty rates of consuming (Martinez et al., 2007). In sum, it is unclear how strong the fake ID effect is likely to be after accounting for people’ ranges of phenotypic or propensity threat—although this question has bearing on prevention and policy initiatives, which can concentrate on both strengthening enforcement of fake ID laws themselves, rising assets for trait-based mostly at-threat youth applications, or a group-pushed combination of each (see Fell, Thomas, Scherer, Fisher & Romano, 2015; Fell, Scherer, Thomas & Voas, 2016; Fell, Scherer & Voas, 2015; Grube, 1997) .

Thus, with a purpose to examine the energy of the fake ID effect, we matched students with and without fake IDs on a number of threat-based mostly covariates using propensity rating matching (PSM) techniques. We first in contrast matched teams’ consuming- and drug-use-associated outcomes in a cross-sectional sample of n=1,454 faculty students at a large Southeastern university. We additionally in contrast matched teams in an extra longitudinal replication sample of n=3,720 undergraduates at a large Midwestern university. We hypothesized that the effects of fake ID possession on outcomes could be greatly diminished by—and therefore largely attributable to—the pre-current trait-based mostly factors on which fake ID house owners and non-house owners could possibly be matched. These comparisons can inform the extent to which the connection between negative outcomes and false identification possession are attributed to selection factors, which again, may have sensible software for intervention and policy.

Process and Contributors

Two samples have been separately investigated following Institutional Assessment Board (IRB) approval: (1) A cross-sectional sample of n=1,454 underage faculty students from a large Southeastern University (IRB Protocol H12032) and (2) a prospective replication sample of n=3,720 undergraduates underneath the minimum legal consuming age from a large Midwestern college (IRB Protocol 01-01-001). Of note, each samples offer distinctive insights into the connection between false identification use and negative outcomes. Extra specifically, the cross-sectional research consists of gadgets that distinguish between the usage of fake IDs in several situations (at bars, at grocery shops, etc.) and the longitudinal research affords insight into the potential results of fake ID possession over time and establishes temporal order.

With regard to the cross-sectional sample, throughout the educational 12 months 2011–2012, members have been recruited from forty randomly selected large (>99 students) and reasonable enrollment (30–99 students) classes. Contributors accomplished a one-page informed consent document in the selected classes before being given a six-page paper survey about faculty life and behaviors to complete with pencil or pen. Contributors were not compensated. All enrolled students have been invited to participate and the response price was excessive at 80.four% (Stogner & Miller, 2013; 2014; Hart et al., 2014). After those above the legal consuming threshold have been removed, the analytic sample was n=1,454 underage individuals. The sample was largely consultant of the college with regard to demographics and was specifically 51.6% female, 68.9% White/non-Hispanic, with a median age of 18.95 (SD=.795). Though this sample is cross-sectional, establishing temporal ordering of the covariates and fake ID possession is essentially inconsequential for the majority of covariates as many are immutable (age, race, gender) or exterior of the person’s control (house 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 throughout the summer time prior to college entrance using paper and pencil after which have been requested to complete online surveys each semester for the following four years (a total of eight semesters). Students provided informed consent and have been compensated $25 in each wave. After excluding the n=35 who have been of age, 88% of the eligible entering class accomplished the survey (n=3,720). The sample was 53.7% female, 90.3% White/non-Hispanic, and averaged 17.9 (SD=.36) years of age (reflecting demographics which might be consultant of the college as a complete [University Registrar, 2013]). Students have been historically aged; by the start of their junior 12 months, just one-third of the sample had reached the minimum legal consuming age, climbing expectedly to 99.7% by the final semester of faculty, Pattern retention was good, ranging from sixty nine% to 87% of baseline respondents participating at each subsequent wave. Retention biases have been low, although individuals have been extra more likely to remain in the sample in the event that they have been females (OR=2.33) and have been much less more 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 ninety% of scholars participated in two or extra evaluation waves and eighty two% participated in three or extra waves. The longitudinal PSM offered throughout the text utilized the primary two years of faculty solely (i.e., the primary four semesters, when the overwhelming majority of members have been underage) and, according to most PSM analysis, solely created matches between individuals in a fashion which is instantly comparable to the evaluation carried out with the cross-sectional sample.1


For the needs of replication, it was important that the measures used in each the cross-sectional and longitudinal studies stayed as similar as possible. For ease of presentation, measures are organized when it comes to their conceptual importance to the general research with cross-sectional and longitudinal measures explained collectively in each section. Timing of the longitudinal measures was thought-about important and is described as is appropriate. Particularly, although the eight-wave longitudinal sample included multiple measurements of many covariates throughout time, the first 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 each Waves 3 and Wave four). The second semester of faculty (Wave 2) was chosen as the singular goal time-point at which fake ID possession (or the “fake ID effect”) was measured, as a result of it is regarded as a peak time of threat for negative consuming-associated outcomes and false ID possession (see Martinez et al., 2008).

Major Outcomes 5 outcomes associated to substance use have been explored. First, a measure of frequent binge consuming was created in each samples. A six-choice ordinal merchandise requested respondents what number of days in the last month did they eat 5 or extra alcoholic drinks. A sex-particular binge consuming measure was not available. These selecting both of the 2 highest frequency choices (10–19 days and 20+ days) have been labeled as frequent binge drinkers whereas all others have been not. This dichotomous merchandise represents binge consuming greater than ten days in the last month. Second, we utilized an instrument created by Maney, Higham-Gardill, and Mahoney (2002) to symbolize alcohol-associated problems in the cross-sectional sample. This ten-merchandise scale assesses the degree to which the person feels that alcohol use has created relationship, family, well being, behavioral, and professional/college problems in the last 12 months and shows enough reliability (α=.822). Within the longitudinal sample, this scale was approximated from ten gadgets taken from the Young Grownup Alcohol Problems Screening Test (YAAPST; Hurlbut & Sher, 1992) with enough reliability (α=.848 in second-12 months fall and α=.846 in second-12 months spring). A dichotomous alcohol-associated arrest/citation measure was created inside each samples using gadgets that requested respondents if that they had ever been arrested or cited for driving underneath the influence, underage consuming, public dysfunction (due to alcohol), being drunk in public, or an open container violation in the last year. The ultimate two outcomes have been each dichotomous and measured equally in each sample; marijuana use and onerous drug use symbolize whether or not 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 each samples (zero=No, 1=Yes). The cross-sectional research additionally included additional gadgets 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 store to purchase alcohol.

Trait and threat issue (matching) covariates Fifteen variables have been used in propensity rating matching in the cross-sectional sample and fourteen have been used in the longitudinal sample. Variables have been selected due to their inclusion in each datasets and former analysis suggesting that they could be associated to the propensity to own a fake ID and experience one of the 5 outcomes. These matching variables are: (1) age, (2) age of alcohol use onset, (3) employment status, (four) exposure to substance use, (5) family earnings, (6) gender, (7) GPA, (8) Greek membership, (9) well being, (10) low self-control, (11) peer substance use, (12) race, (13) rural house location (solely measured in the cross-sectional research), (14) sexual orientation (1=LGBT), and (15) subjective distress.

Eight of the fifteen variables have been measured identically and a ninth was measured nearly identically. Amongst those identically measured have been age, age of first alcohol use, employment status (zero= not employed; 1=employed), gender (zero=female; 1=male), self-reported grade point average (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 different). Self-reported well being was measured with an merchandise that requested respondents to price their own well being—the cross-sectional research provided responses ranging from 1 (poor) to four (wonderful) whereas the longitudinal research choices ranged from 1 (poor) to five (wonderful).

The cross sectional research utilized four-merchandise measures tailored from Lee, Akers, and Borg (2004) to symbolize exposure to substance use (α=.786) and peer substance use (α=.801). Because the longitudinal data did not embrace similarmeasures, each of these constructs was represented by a single merchandise slightly than a four-merchandise scale. The primary (exposure) was measured dichotomously whereas the second (peer substance use) was measured on a six-choice ordinal scale. Low self-control was operationalized using the 24-merchandise Grasmick et al. (1993) scale (α=.889) in the cross-sectional research and the NEO 5 Issue Inventory conscientiousness scale (reverse-coded) in the longitudinal sample (α=.844; Costa & McCrae, 1992). Subjective distress was measured using Cohen and Williamson’s (1988) ten-merchandise perceived scholar stress scale (α=.814) in the cross-sectional research and the International Severity Index from the Temporary Symptom Inventory-18 in the longitudinal sample (Derogatis, 2000). Higher values on these scales symbolize extra exposure to substance use, a larger portion of peers that use substances, lower self-control, and extra subjective distress, respectively.

Both studies included a single-merchandise family socioeconomic status measure. Within the cross-sectional research a measure of family earnings was used. Contributors chose between choices ranging from underneath $10,000 per 12 months (coded 1) to over $a hundred seventy five,000 per 12 months (coded 9). An merchandise assessing whether or not or not students have been the primary of their family to attend faculty (zero=No, 1=Yes) was utilized in the longitudinal study.

Rural house location was used in the cross-sectional research, but no similar measure was out there in the longitudinal data. This variable was important to incorporate despite creating differing matching standards due to the traits of the research area. The cross-sectional sample was drawn from an space that is very rural with the exception of one main city; thus, a dichotomous merchandise representing whether or not the student grew up in an urban / suburban space (coded zero) or a rural one (coded 1) was included. By comparison, this was not a particular consideration for the longitudinal sample, which originated from a college of 35,000 that draws students from two large neighboring cities and its own reasonably large population.


First, we estimated the proportions of fake ID possession in each the cross-sectional and longitudinal samples. In addition to possession of a fake ID, the cross-sectional sample additionally documented members’ using of the fake ID in bars/golf equipment and stores. We estimated the bivariate associations of fake IDs with the 5 specified substance use outcomes in each samples—a rudimentary “fake ID effect.”

Next, to raised determine the energy of the “fake ID effect” after accounting for trait measures, propensity rating matching (PSM) was used for each samples. PSM affords a clearer image of the connection between two variables than bivariate analyses which can yield spurious results (Guo & Fraser 2009) and has been used to assess points associated to substance use (Miller et al., 2011). Additionally of note, PSM is preferable to multivariate regression fashions in instances similar to this the place the variable of interest may not be independently related to the dependent variable, but is likely correlated with those which might be and likewise happens extra proximally. The propensity matching methods developed by Rosenbaum and Rubin (1983, 1985) can be used to create a sample with two teams which might be similar in all related variables aside from the “therapy” (i.e., fake ID possession). While their methods do lead to a reduction in measurement of analytic sample (typically leading PSM to be referred to as resampling), they are effective at creating a situation whereby the effect of “therapy” could be estimated as the common distinction between those exposed to the therapy and “counterfactuals,” defined as the anticipated outcomes have been it not for exposure to the therapy (Guo & Fraser 2009). On this case, the PSM methodology creates analytic teams whereby differences aside from false identification use are minimalized.

As prompt by Rosenbaum and Rubin (1983, 1985), we utilized logistic regression to estimate a propensity rating for each participant in each analytic sample. Fake ID possession was regressed on 15 covariates in the cross-sectional sample (age, age of firsts alcohol use, employment status, exposure to substance use, family earnings, gender, grade point average, membership in a campus Greek group, self-assessed well being, low self-control, peer substance use, race, measurement of house group, sexual orientation, and subjective distress) and 14 similar variables (measurement of house group 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, each participant’s propensity rating was then calculated as their conditional likelihood of having a fake ID. Following an evaluation of areas of frequent help, we created comparison teams inside each sample using 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 lower in sample measurement (n=817 and n=518, respectively) but a enough number of instances have been retained for statistical comparisons.

Charges of fake ID possession

Charges of fake ID possession have been quite excessive, notably in the cross-sectional sample. That is, of the 1,454 underage alcohol customers in the cross-sectional sample, 583 or 40.1% own 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 purchase alcohol at a store. Prevalence rates of false ID use in the Midwestern sample modified over time. Fake ID possession amongst students underneath 21 peaked throughout the third 12 months of faculty (pre-faculty=12.5%, first-12 months fall=17.1%, first-12 months spring=21.four%, second-12 months fall=28.1%, second-12 months spring=32.2%, third-12 months fall=34.9%, third-12 months, fourth-12 months fall=38.1%, fourth-12 months spring= fewer than ten students have been under the minimum legal consuming age).2

The “fake ID effect” previous to matching

Table 1 presents mean scores for 5 substance use outcomes for fake ID house owners and non-house owners in each samples (outcomes at each Wave 3 and four are reported for the longitudinal sample). Average scores for each final result (frequent binge consuming [10 or extra days in the last month], self-reported alcohol associated problems, alcohol-associated arrests, marijuana use, and onerous drug use) are offered for those who 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 store (cross-sectional sample solely). Impartial samples t-tests have been carried out to determine whether or not, on average, differences exist between fake ID customers and non-users. Each of the tests reached significance. Regardless of whether or not the main target was possession of a fake ID or using it at a selected type of outlet, the results have been consistent. At the bivariate stage, extra individuals with false identification have interaction in frequent binge consuming, have been arrested/cited for an alcohol violation, have interaction in marijuana use, and use onerous drugs. People with fake identification additionally, on average, report extra alcohol-associated problems. These results would point out that fake IDs are a automobile of risk. Nevertheless, it is doable that fake ID possession (and associated risks) are extra a perform of underlying risky traits.

Propensity rating matching (PSM)

As a result of consistency in the findings to this point regardless of false identification measure (possession, bar use, and/or store use), the extra analyses with each sample makes use of just one false identification measure, possession of a false ID. We carried out PSM analyses in each samples, to look at whether or not individuals with and without fake IDs continue to vary on these outcomes after being matched on substantively important traits. Table 2 shows that individuals with and without fake IDs certainly differed from one another on these trait propensity variables, suggesting that it is these variables which can finally be driving the fake ID effect. Table 2 additionally shows that the PSM approach labored nicely in each samples, persistently reducing bias related to the statistically important differences between those with and without fake IDs by greater than 50% on all but one variable. Although three important differences nonetheless 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. On this, matching was equally, if no more, profitable in the longitudinal sample. It should be famous that matching did yield a reduction in sample size. Overall, nevertheless, in each samples matching appears to have created therapy and comparison teams which might be extra equal and extra applicable for comparison than the unmatched data.

The propensity scores that have been calculated for each case are graphically displayed in Figure 1. As could be seen in the figure, a region of frequent help exists, but very few with low propensity scores had a fake ID and very few with excessive propensity scores did not.

Comparing fake ID house owners and non-house owners after PSM

Cross-sectional sample After matching, false identification house owners and non-house owners have been in contrast on each of the 5 substance use associated outcomes. While significantly extra of those 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 significantly different after matching (t=1.81, df=815) and the common therapy effect (ATE; e.g., differences in group means), as displayed in Table 3, was diminished by 59.2%. Similarly, previous to matching, fake ID house owners had significantly higher scores on the alcohol associated problems scale than non-house owners (t=9.eighty three, df=815), however the teams have been no longer significantly different after matching (t=1.31, df=815) and the ATE was diminished by 63.four%. Nevertheless, when it comes to alcohol-associated arrests, the 2 teams have been nonetheless significantly different and the ATE successfully remained unchanged. As was the case for the primary two outcomes, fake ID possession was related to marijuana use previous to matching (t=9.36), but not after (t=1.fifty two; ATE diminished by 60.four%). Lastly, onerous drug use was related to fake ID possession each before (t=7.26, df=815) and after matching (t=2.29, df=815), however the ATE was diminished by 38.four%.

Longitudinal sample As was the case in the cross-sectional sample, propensity rating matching led to a substantial lower in the ATE for four of the 5 outcomes (Table 3, columns 3–6). Nevertheless, not like the cross-sectional sample, ATEs remained important for alcohol associated problems (t=4.00 wave 3; t=4.17, wave four, df=516) and marijuana use (t=4.13, wave 3; t=2.fifty eight, wave four, df=516) after propensity rating matching. The ATE additionally remained important for frequent binge consuming (t=3.26, df=516, wave 3) and onerous drug use (t=2.06, df=516, wave four) at one wave but not the other. Again, these results sizes have been considerably diminished, but in the aforementioned instances, not eliminated. As was the case in the cross-sectional sample, propensity rating matching had little influence on the ATE on alcohol-associated arrests.3


This research’s preliminary results are according to previous analysis—a substantial number of underage students have fake IDs and are at higher threat for binge consuming, alcohol-associated problems, alcohol associated arrests, and different substance use (see Arria et al., 2014; Martinez & Sher, 2010; Nguyen et al., 2011). Yet our work additionally showed that for some outcomes, plainly what initially might need seemed to be a “fake ID effect” is essentially the result of factors that influenced each the acquisition of the false ID and the outcome. The numerous relationship between fake ID use and different substance use outcomes typically remained after PSM, however the magnitude of these relationships have been considerably diminished, most by over 40%. Alcohol-associated arrests have been an exception as the connection was unaffected by PSM (i.e., after matching, those with a fake ID have been nonetheless at equally excessive ranges of threat for alcohol-associated arrests [DUIs, open container, etc.]). The rationale this final result is distinct from the others is not readily clear; maybe regulation enforcement officers usually tend to challenge citations or arrests for different substance-associated offenses when an individual is also found with a fake ID. If this is the case, the “effect” wouldn’t seem smaller in propensity rating fashions as the distinction could be pushed by officers’ reactions to the fake ID slightly than individuals’ underlying propensity.

The pattern that emerges from Table 3 appears to point that non-matched samples may have overestimated the effect of false identification use on negative outcomes, but that fake ID possession has an effect that extends beyond shared causal factors. This particular remaining “fake ID effect” might certainly help the concept the fake ID itself serves as a kind of threshold into different types of deviant conduct, the place those who are willing to accumulate fake IDs turn out to be more and more willing to violate different laws (see Ruedy et al., 2013; Winograd et al., 2014). But in light of the opposite findings, it is extra probably that fake IDs extra usually reasonable the effects of risky traits on behavior. For example, fake IDs may have the very best efficiency of effect via providing impulsive individuals with additional means and alternative for problematic behaviors that they would not in any other case have engaged in. Indeed, underlying trait risks are often integrated into alternative-principle-associated examinations of crime (Grasmick et al., 1993; Lagrange & Silverman, 1999).

As such, these findings have sensible implications. Although elevated server coaching, fake ID manufacturing/provider laws, and legal responsibility laws are an important technique of addressing the risks of fake IDs as a form of alcohol entry (Fell, Scherer, Thomas & Voas, 2014; Yörük, 2014), pretend-ID associated outcomes may additionally partly be a perform of trait risks that can moreover be addressed with intervention. One way to begin addressing this mixture of things may be via motivational, normative feedback-based mostly, or skills interventions which might be specifically aimed at decreasing the probability that at-threat students acquire a fake ID (see Fromme & Orrick, 2004; Larimer & Cronce, 2007). Furthermore, a fake ID obtainment-aimed intervention might possibly be broadly integrated into interventions which might be particularly tailor-made towards addressing each individuals’ risky traits and their resulting behaviors (see Conrod et al., 2006).

Though a great energy of this research rests in the same findings found with two distinctive faculty populations, these findings may not be generalizable to non-faculty attending populations. Moreover, fake ID policies, enforcement, and worry of sanctions may range considerably in several localities (Erickson, Lenk, Toomey, Nelson & Jones-Webb, 2016). For example, some consuming institutions may be lenient of their carding policies, deliberately accept false identification, and/or not be subject to rigorous regulatory enforcement (Murray, 2005). Additionally, penalties for possessing and/or using a fake ID to purchase alcohol varies considerably from state to state together with the type of offense, amount of high quality, suspension of driver’s license, and the potential for probation or jail time. Future analysis should evaluate the impression of fake ID relative to differential policies and enforcement of the minimum legal consuming age, together with group efforts (Grube, 1997). Further, whereas fifteen distinct traits have been included in the matching process, there stays the possibility that additional factors not measured in our data would have an effect on each the willingness to entry a fake ID and the end result measures. If this is the case, the “fake ID effect” may be even smaller than our matching fashions suggested.

In concluding that the “fake ID effect” is especially a perform of phenotypic threat, fake ID possession may serve as an indicator of heightened threat for extra severe consuming associated problems. Though most penalties for fake ID possession are punitive (fines, probation/jail, and/or lack of driver’s license), policy-makers, college officers, and practitioners should goal fake ID house owners for intervention methods aimed at reducing excessive-threat consuming behaviors (and different problematic behaviors linked to phenotypic threat). Though elevated penalties and enforcement of the minimum legal consuming age has the potential to scale back fake ID possession, we warning policy-makers to guage and take into account the negative penalties of shifting faculty consuming away from regulated institutions the place safety and emergency providers are extra available (see Baldwin et al., 2012; 2014). Though our findings found that fake ID possession (regardless of individual threat traits) elevated the chance for alcohol associated arrests, drug use, and alcohol associated problems (Midwest sample solely), we did not assess victimization and different harms related to extreme alcohol consumption that could enhance in spaces not subject to regulatory controls (Miller, Levy, Spicer & Taylor, 2006). Future analysis is required to guage the impression that fake ID enforcement may have on problematic consuming each in regulated and unregulated spaces.