Underage school students who acquire and use false identification (fake ID) are at risk for unfavourable outcomes. Nevertheless, it’s presently unclear how uniquely the fake ID itself serves as a car to subsequent harm (i.e., the “fake ID impact”) over and above common and trait-associated threat elements (e.g., deviant friends, low self-management).


As a way to examine whether the “fake ID impact” 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 were matched with individuals and not using a fake ID, by way of quite a few trait-based and social threat factors. These matched groups were then compared on five problematic outcomes (i.e., frequent binge drinking, alcohol-associated issues, arrests, marijuana use, and exhausting drug use).



Findings confirmed that “fake ID effects” were considerably—though not totally—diminished following PSM. The “fake ID impact” remained strongest for alcohol-associated arrests. This may relate to problems with enforcement and students’ willingness to interact in deviant habits with a fake ID, or it could be a function of mixed processes.


Total, the findings counsel that interventions mustn’t only be aimed at decreasing fake ID-associated alcohol access specifically, but should also be aimed extra typically towards at-threat youths’ access to alcohol. Future analysis would possibly look at whether fake IDs have their strongest efficiency as moderators of the results of dangerous traits—resembling impulsiveness—on drinking outcomes.

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


Fake IDs, a unique mode of alcohol access, are more and more wanted as individuals near the minimal authorized drinking age (Martinez et al., 2007; Wagenaar et al., 1996). These types of false identification could also be borrowed (or duplicated) from an older peer or sibling (Myers et al., 2001), or they may be a specifically crafted document obtained locally or from a web based vendor (Murray, 2005). No matter their supply, there appears to be a bidirectional relation between heavy drinking and fake IDs, such that (1) heavy drinking predicts subsequent obtainment of a fake ID, and (2) “ownership” (i.e., possession) of a fake ID predicts subsequent frequency of heavy drinking (outlined as 5+ drinks per occasion; Martinez, et al., 2007).

This bidirectional relation not only illustrates the public health dangers of this mode of alcohol access, but begs the question of whether it’s extra the case that a fake ID itself serves as a car to subsequent harm (i.e., the “fake ID impact”) or whether such harms and outcomes are predominantly pushed by a common stage of phenotypic threat on the part of the fake ID “owner” (e.g., deviant peer associations, low self-management). Though common alcohol access theories would possibly help the previous speculation virtually entirely (specifically, fake ID possession increases alcohol access and subsequent harm; see Gruenewald, 2011), common criminological theories of phenotypic threat help the latter (specifically, that broad classes of threat—or propensities to interact in dangerous habits—are the true cause of harm; see Pratt & Cullen, 2000). Definitely, such propensities might be what predicts fake ID obtainment within the first place, and although the power of the fake ID impact appears to extend over time, it’s tremendously diminished after controlling for intercourse, Greek status, and pre-school rates of drinking (Martinez et al., 2007). In sum, it’s unclear how robust the fake ID impact might be after accounting for people’ levels of phenotypic or propensity threat—though this question has bearing on prevention and policy initiatives, which can deal with both strengthening enforcement of fake ID legal guidelines themselves, increasing sources for trait-based at-threat 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 a view to examine the power of the fake ID impact, we matched students with and without fake IDs on quite a few threat-based covariates utilizing propensity rating matching (PSM) techniques. We first compared matched groups’ drinking- 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 groups in an additional longitudinal replication sample of n=3,720 undergraduates at a big Midwestern university. We hypothesized that the results of fake ID ownership on outcomes could be tremendously diminished by—and subsequently largely attributable to—the pre-current trait-based elements on which fake ID house owners and non-house owners could be matched. These comparisons can inform the extent to which the connection between unfavourable outcomes and false identification ownership are attributed to selection elements, which once more, might have practical software for intervention and policy.

Procedure and Members

Two samples were separately investigated following Institutional Assessment Board (IRB) approval: (1) A cross-sectional sample of n=1,454 underage school students from a big Southeastern University (IRB Protocol H12032) and (2) a potential replication sample of n=3,720 undergraduates underneath the minimal authorized drinking age from a big Midwestern college (IRB Protocol 01-01-001). Of observe, both samples provide unique insights into the connection between false identification use and unfavourable outcomes. More specifically, the cross-sectional examine includes gadgets that distinguish between the usage of fake IDs in different conditions (at bars, at grocery shops, etc.) and the longitudinal examine provides perception into the potential effects of fake ID ownership over time and establishes temporal order.

With regard to the cross-sectional sample, in the course of the educational year 2011–2012, participants were recruited from forty randomly chosen massive (>ninety nine students) and average enrollment (30–ninety nine students) classes. Members accomplished a one-web page knowledgeable consent document within the chosen lessons earlier than being given a six-web page paper survey about school life and behaviors to finish with pencil or pen. Members were not compensated. All enrolled students were invited to participate and the response fee was excessive at 80.4% (Stogner & Miller, 2013; 2014; Hart et al., 2014). After these above the authorized drinking threshold were 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 18.95 (SD=.795). Though this sample is cross-sectional, establishing temporal ordering of the covariates and fake ID ownership is essentially inconsequential for almost all of covariates as many are immutable (age, race, gender) or exterior of the individual’s management (dwelling location, parental income, sexual orientation, etc.).

The longitudinal sample additionally utilized a self-report survey methodology. All incoming students in 2002 were recruited to finish an instrument in the course of the summer season prior to school entrance utilizing paper and pencil after which were asked to finish on-line surveys every semester for the subsequent four years (a complete of eight semesters). College students supplied knowledgeable consent and were compensated $25 in every wave. After excluding the n=35 who were of age, 88% of the eligible entering class accomplished the survey (n=3,720). The sample was 53.7% feminine, 90.3% White/non-Hispanic, and averaged 17.9 (SD=.36) years of age (reflecting demographics which might be representative of the college as a whole [University Registrar, 2013]). College students were historically aged; by the beginning of their junior year, just one-third of the sample had reached the minimal authorized drinking age, climbing expectedly to 99.7% by the final semester of faculty, Sample retention was good, ranging from sixty nine% to 87% of baseline respondents taking part at every subsequent wave. Retention biases were low, though individuals were extra more likely to stay within the sample if they were females (OR=2.33) and were much less more likely to stay within the sample if they were frequent binge drinkers (OR=.88; Sher & Rutledge, 2007). By the final time-level, the sample dimension was n=2,250, though ninety% of scholars participated in two or extra assessment waves and eighty two% participated in three or extra waves. The longitudinal PSM offered inside the text utilized the primary two years of faculty only (i.e., the primary four semesters, when the overwhelming majority of participants were underage) and, in step with most PSM analysis, only created matches between individuals in a way which is straight akin to the evaluation performed with the cross-sectional sample.1


For the needs of replication, it was vital that the measures utilized in both the cross-sectional and longitudinal studies stayed as comparable as possible. For ease of presentation, measures are organized by way of their conceptual significance to the overall examine with cross-sectional and longitudinal measures defined collectively in every section. Timing of the longitudinal measures was considered vital and is described as is appropriate. Specifically, though the eight-wave longitudinal sample included multiple measurements of many covariates across time, the primary longitudinal PSM only utilized measurements as they might be expected to happen if observing a “fake ID impact” over a logical development of time (i.e., Trait/propensity measures were measured at Wave 1 and used to foretell fake ID ownership at Wave 2 which in turn assessed as a predictor for outcome measures at both Waves 3 and Wave 4). The second semester of faculty (Wave 2) was chosen because the singular goal time-level at which fake ID ownership (or the “fake ID impact”) was measured, as a result of it’s considered a peak time of threat for unfavourable drinking-associated outcomes and false ID ownership (see Martinez et al., 2008).

Foremost Outcomes Five outcomes associated to substance use were explored. First, a measure of frequent binge drinking was created in both samples. A six-choice ordinal merchandise asked respondents how many days within the last month did they consume five or extra alcoholic drinks. A intercourse-specific binge drinking measure was not available. These deciding on both of the two highest frequency choices (10–19 days and 20+ days) were categorised as frequent binge drinkers whereas all others were not. This dichotomous merchandise represents binge drinking greater than ten days within the last month. Second, we utilized an instrument created by Maney, Higham-Gardill, and Mahoney (2002) to characterize alcohol-associated issues within the cross-sectional sample. This ten-merchandise scale assesses the degree to which the individual feels that alcohol use has created relationship, family, health, behavioral, and professional/college issues within the last year and exhibits ample reliability (α=.822). In the longitudinal sample, this scale was approximated from ten gadgets taken from the Younger Grownup Alcohol Problems Screening Check (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 inside both samples utilizing gadgets that asked respondents if that they had ever been arrested or cited for driving underneath the affect, underage drinking, public disorder (because of alcohol), being drunk in public, or an open container violation within the last year. The final two outcomes were both dichotomous and measured equally in every sample; marijuana use and exhausting drug use characterize whether the respondent self-reported any use of marijuana and cocaine, heroin, and/or methamphetamine, respectively, within the last year.

False Identification Current fake ID “ownership” was assessed dichotomously in both samples (0=No, 1=Sure). The cross-sectional examine additionally included extra gadgets that asked respondents whether or not they had used the fake ID in a bar or club and whether or not they had used it in a retailer to purchase alcohol.

Trait and threat issue (matching) covariates Fifteen variables were utilized in propensity rating matching within the cross-sectional sample and fourteen were used within the longitudinal sample. Variables were chosen because of their inclusion in both datasets and previous analysis suggesting that they may be associated to the propensity to own a fake ID and experience one of the five outcomes. These matching variables are: (1) age, (2) age of alcohol use onset, (3) employment status, (4) exposure to substance use, (5) family income, (6) gender, (7) GPA, (eight) Greek membership, (9) health, (10) low self-management, (11) peer substance use, (12) race, (13) rural dwelling location (only measured within the cross-sectional examine), (14) sexual orientation (1=LGBT), and (15) subjective distress.

Eight of the fifteen variables were measured identically and a ninth was measured nearly identically. Amongst these identically measured were age, age of first alcohol use, employment status (0= not employed; 1=employed), gender (0=feminine; 1=male), self-reported grade level average (GPA), membership in a campus Greek group (0=non-member; 1=member), race (0=white, 1=non-white), and sexual orientation (0=heterosexual; 1=lesbian, gay, bisexual, or other). Self-reported health was measured with an merchandise that asked respondents to fee their very own health—the cross-sectional examine offered responses ranging from 1 (poor) to 4 (glorious) whereas the longitudinal examine choices ranged from 1 (poor) to 5 (glorious).

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

Each studies included a single-merchandise family socioeconomic status measure. In the cross-sectional examine a measure of family income was used. Members chose between choices ranging from underneath $10,000 per year (coded 1) to over $a hundred seventy five,000 per year (coded 9). An merchandise assessing whether or not students were the primary in their family to attend school (0=No, 1=Sure) was utilized within the longitudinal study.

Rural dwelling location was used within the cross-sectional examine, but no comparable measure was available within the longitudinal data. This variable was vital to include regardless of creating differing matching criteria as a result of traits of the examine area. The cross-sectional sample was drawn from an area that may be very rural apart from one main city; thus, a dichotomous merchandise representing whether the scholar grew up in an urban / suburban area (coded 0) 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 draws students from two massive neighboring cities and its own reasonably massive population.


First, we estimated the proportions of fake ID ownership in both the cross-sectional and longitudinal samples. In addition to possession of a fake ID, the cross-sectional sample additionally documented participants’ utilizing of the fake ID in bars/golf equipment 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 raised determine the power of the “fake ID impact” after accounting for trait measures, propensity rating matching (PSM) was used for both samples. PSM provides a clearer image of the connection between two variables than bivariate analyses which can yield spurious outcomes (Guo & Fraser 2009) and has been used to evaluate points associated to substance use (Miller et al., 2011). Also of observe, PSM is preferable to multivariate regression models in situations resembling this where the variable of interest is probably not independently connected to the dependent variable, but is probably going correlated with these which might be and likewise occurs extra proximally. The propensity matching techniques developed by Rosenbaum and Rubin (1983, 1985) can be used to create a sample with two groups which might be comparable in all related variables except for the “treatment” (i.e., fake ID possession). While their techniques do lead to a discount in dimension of analytic sample (typically main PSM to be referred to as resampling), they’re effective at creating a scenario whereby the impact of “treatment” might be estimated as the typical distinction between these uncovered to the treatment and “counterfactuals,” outlined because the anticipated outcomes were it not for exposure to the treatment (Guo & Fraser 2009). On this case, the PSM method creates analytic groups whereby differences apart from false identification use are minimalized.

As instructed by Rosenbaum and Rubin (1983, 1985), we utilized logistic regression to estimate a propensity rating for every participant in every analytic sample. Fake ID possession was regressed on 15 covariates within the cross-sectional sample (age, age of firsts alcohol use, employment status, exposure to substance use, family income, gender, grade level average, membership in a campus Greek group, self-assessed health, low self-management, peer substance use, race, dimension of dwelling community, sexual orientation, and subjective misery) and 14 comparable variables (dimension of dwelling community excluded, as defined above) in the principle longitudinal PSM evaluation (i.e. fake ID possession measured on the second semester and outcomes evaluated within the third and fourth semesters). Utilizing these models, every participant’s propensity rating was then calculated as their conditional likelihood of getting a fake ID. Following an assessment of areas of frequent help, we created comparability groups inside 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 within the cross-sectional sample and .0426 within the longitudinal sample. This matching approach led to the expected lower in sample dimension (n=817 and n=518, respectively) but a enough number of circumstances were retained for statistical comparisons.

Charges of fake ID ownership

Charges of fake ID ownership were fairly excessive, notably within the cross-sectional sample. That is, of the 1,454 underage alcohol shoppers within 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.eight%) have used the ID to purchase alcohol at a store. Prevalence rates of false ID use within the Midwestern sample modified over time. Fake ID ownership among students underneath 21 peaked in the course of the third year of faculty (pre-school=12.5%, first-year fall=17.1%, first-year spring=21.4%, second-year fall=28.1%, second-year spring=32.2%, third-year fall=34.9%, third-year spring=39.0%, fourth-year fall=38.1%, fourth-year spring= fewer than ten students were beneath the minimal authorized drinking age).2

The “fake ID impact” prior to matching

Table 1 presents mean scores for five substance use outcomes for fake ID house owners and non-house owners in both samples (outcomes at both Wave 3 and 4 are reported for the longitudinal sample). Common scores for every outcome (frequent binge drinking [10 or extra days within the last month], self-reported alcohol associated issues, alcohol-associated arrests, marijuana use, and exhausting drug use) are offered for those that have and have not owned a fake ID, used a fake ID at a bar/club (cross-sectional sample only), and used a fake ID at a retailer (cross-sectional sample only). Independent samples t-tests were performed to determine whether, on average, differences exist between fake ID customers and non-users. Each of the tests reached significance. No matter whether the main target was ownership of a fake ID or utilizing it at a particular sort of outlet, the outcomes were consistent. At the bivariate stage, extra individuals with false identification engage in frequent binge drinking, have been arrested/cited for an alcohol violation, engage in marijuana use, and use exhausting drugs. People with fake identification additionally, on average, report extra alcohol-associated problems. These outcomes would point out that fake IDs are a car of risk. Nevertheless, it’s attainable that fake ID ownership (and associated dangers) are extra a function of underlying dangerous traits.

Propensity rating matching (PSM)

Because of the consistency within the findings so far regardless of false identification measure (ownership, bar use, and/or retailer use), the additional analyses with every sample makes use of just one false identification measure, possession of a false ID. We carried out PSM analyses in both samples, to examine whether individuals with and without fake IDs continue to differ on these outcomes after being matched on substantively vital traits. Table 2 exhibits that individuals with and without fake IDs certainly differed from one another on these trait propensity variables, suggesting that it’s these variables which can finally be driving the fake ID effect. Table 2 additionally exhibits that the PSM approach worked properly in both samples, consistently decreasing bias associated with the statistically vital differences between these with and without fake IDs by greater than 50% on all but one variable. Although three vital differences nonetheless remained within the cross-sectional sample (age of alcohol use onset, Greek affiliation, and having been raised in a rural area), the magnitude of the differences in age of onset and Greek affiliation were minor in comparison with pre-matching. On this, matching was equally, if not more, profitable within the longitudinal sample. It ought to be noted that matching did yield a discount in sample size. Total, nonetheless, in both samples matching appears to have created treatment and comparability groups which might be extra equivalent and extra applicable for comparability than the unequalled data.

The propensity scores that were calculated for every case are graphically displayed in Determine 1. As might be seen within the determine, a area of frequent help exists, but very few with low propensity scores had a fake ID and very few with excessive propensity scores did not.

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

Cross-sectional sample After matching, false identification house owners and non-house owners were compared on every of the five substance use associated outcomes. While significantly extra of these with fake IDs within the cross-sectional sample were frequent binge drinkers prior to matching (t=9.eighty one, df=815), the groups were now not significantly different after matching (t=1.eighty one, df=815) and the typical treatment impact (ATE; e.g., differences in group means), as displayed in Table 3, was decreased by 59.2%. Similarly, prior to matching, fake ID house owners had significantly greater scores on the alcohol associated issues scale than non-house owners (t=9.83, df=815), but the groups were now not significantly different after matching (t=1.31, df=815) and the ATE was decreased by 63.4%. Nevertheless, by way of alcohol-associated arrests, the two groups were nonetheless significantly different and the ATE successfully remained unchanged. As was the case for the primary two outcomes, fake ID possession was associated with marijuana use prior to matching (t=9.36), but not after (t=1.52; ATE decreased by 60.4%). Finally, exhausting 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 38.4%.

Longitudinal sample As was the case within the cross-sectional sample, propensity rating matching led to a considerable lower within the ATE for four of the five outcomes (Table 3, columns 3–6). Nevertheless, in contrast to the cross-sectional sample, ATEs remained vital for alcohol associated issues (t=4.00 wave 3; t=4.17, wave 4, df=516) and marijuana use (t=4.13, wave 3; t=2.fifty eight, wave 4, df=516) after propensity rating matching. The ATE additionally remained vital for frequent binge drinking (t=3.26, df=516, wave 3) and exhausting drug use (t=2.06, df=516, wave 4) at one wave but not the other. Once more, these effects sizes were considerably decreased, but within the aforementioned circumstances, not eliminated. As was the case within the cross-sectional sample, propensity rating matching had little affect on the ATE on alcohol-associated arrests.3


This examine’s preliminary outcomes are in step with previous analysis—a considerable number of underage students have fake IDs and are at greater threat for binge drinking, alcohol-associated issues, 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, it seems that what initially might have gave the impression to be a “fake ID impact” is essentially the result of elements that influenced both the acquisition of the false ID and the outcome. The numerous relationship between fake ID use and other substance use outcomes typically remained after PSM, but the magnitude of these relationships were considerably diminished, most by over 40%. Alcohol-associated arrests were an exception as the connection was unaffected by PSM (i.e., after matching, these with a fake ID were nonetheless at equally excessive levels of threat for alcohol-associated arrests [DUIs, open container, etc.]). The rationale this outcome is distinct from the others will not be readily clear; perhaps legislation enforcement officers usually tend to difficulty citations or arrests for other substance-associated offenses when a person can be discovered with a fake ID. If this is the case, the “impact” wouldn’t appear smaller in propensity rating models because the distinction could be pushed by officers’ reactions to the fake ID moderately than individuals’ underlying propensity.

The sample that emerges from Table 3 appears to indicate that non-matched samples might have overestimated the impact of false identification use on unfavourable outcomes, but that fake ID ownership has an impact that extends beyond shared causal factors. This specific remaining “fake ID impact” might certainly help the idea that the fake ID itself serves as a type of threshold into other types of deviant habits, where those that are willing to acquire fake IDs become more and more willing to violate other legal guidelines (see Ruedy et al., 2013; Winograd et al., 2014). But in gentle of the opposite findings, it’s extra probably that fake IDs extra typically average the results of dangerous traits on behavior. For instance, fake IDs might have the highest efficiency of impact through providing impulsive individuals with extra means and opportunity for problematic behaviors that they might not otherwise have engaged in. Certainly, underlying trait dangers are often incorporated into opportunity-concept-associated examinations of crime (Grasmick et al., 1993; Lagrange & Silverman, 1999).

As such, these findings have practical implications. Although elevated server training, fake ID manufacturing/provider legal guidelines, and liability legal guidelines are an vital technique of addressing the dangers of fake IDs as a form of alcohol access (Fell, Scherer, Thomas & Voas, 2014; Yörük, 2014), pretend-ID associated outcomes might also partly be a function of trait dangers that may moreover be addressed with intervention. One technique to start addressing this mixture of things could also be through motivational, normative feedback-based, or abilities interventions which might be specifically aimed at lowering the chance that at-threat students acquire a fake ID (see Fromme & Orrick, 2004; Larimer & Cronce, 2007). Furthermore, a fake ID obtainment-aimed intervention would possibly probably be broadly incorporated into interventions which might be especially tailored toward addressing both individuals’ dangerous traits and their ensuing behaviors (see Conrod et al., 2006).

Though an incredible power of this examine rests in the similar findings discovered with two unique school populations, these findings is probably not generalizable to non-school attending populations. Additionally, fake ID insurance policies, enforcement, and worry of sanctions might differ considerably in different localities (Erickson, Lenk, Toomey, Nelson & Jones-Webb, 2016). For instance, some drinking institutions could also be lenient in their carding insurance policies, deliberately accept false identification, and/or not be subject to rigorous regulatory enforcement (Murray, 2005). Also, penalties for possessing and/or utilizing a fake ID to purchase alcohol varies considerably from state to state together with the type of offense, quantity of positive, suspension of driver’s license, and the opportunity of probation or jail time. Future analysis ought to evaluate the influence of fake ID relative to differential insurance policies and enforcement of the minimal authorized drinking age, together with community efforts (Grube, 1997). Further, whereas fifteen distinct traits were included within the matching course of, there remains the likelihood that extra elements not measured in our information would affect both the willingness to access a fake ID and the outcome measures. If this is the case, the “fake ID impact” could also be even smaller than our matching models suggested.

In concluding that the “fake ID impact” is principally a function of phenotypic threat, fake ID ownership might serve as an indicator of heightened threat for extra extreme drinking associated problems. Though most penalties for fake ID ownership are punitive (fines, probation/jail, and/or loss of driver’s license), policy-makers, college officials, and practitioners ought to goal fake ID house owners for intervention strategies aimed at decreasing excessive-threat drinking behaviors (and other problematic behaviors linked to phenotypic threat). Though elevated penalties and enforcement of the minimal authorized drinking age has the potential to reduce fake ID ownership, we caution policy-makers to judge and think about the unfavourable consequences of shifting school drinking away from regulated institutions where safety and emergency companies are extra readily available (see Baldwin et al., 2012; 2014). Though our findings discovered that fake ID possession (regardless of individual threat traits) elevated the risk for alcohol associated arrests, drug use, and alcohol associated issues (Midwest sample only), we did not assess victimization and other harms associated with excessive alcohol consumption that would increase in areas not subject to regulatory controls (Miller, Levy, Spicer & Taylor, 2006). Future analysis is required to judge the influence that fake ID enforcement might have on problematic drinking both in regulated and unregulated spaces.