Underage college students who receive and use false identification (fake ID) are in danger for unfavourable outcomes. Nonetheless, it is at present unclear how uniquely the fake ID itself serves as a automobile to subsequent harm (i.e., the “fake ID impact”) over and above general and trait-associated danger factors (e.g., deviant peers, low self-control).
In an effort to investigate whether or not the “fake ID impact” would maintain after accounting for phenotypic danger, 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 with no fake ID, in terms of plenty of trait-primarily based and social danger factors. These matched groups have been then compared on 5 problematic outcomes (i.e., frequent binge drinking, alcohol-associated problems, arrests, marijuana use, and exhausting drug use).
Findings confirmed that “fake ID results” have been substantially—although not absolutely—diminished following PSM. The “fake ID impact” remained strongest for alcohol-associated arrests. This may relate to issues of enforcement and students’ willingness to engage in deviant habits with a fake ID, or it might be a operate of mixed processes.
Total, the findings recommend that interventions shouldn’t solely be geared toward lowering fake ID-associated alcohol entry particularly, but must also be aimed extra typically in the direction of at-danger youths’ entry to alcohol. Future analysis would possibly examine whether or not fake IDs have their strongest efficiency as moderators of the results of dangerous traits—equivalent to impulsiveness—on drinking outcomes.
Key phrases: False identification, Fake IDs, underage alcohol use, heavy episodic drinking, binge drinking
Fake IDs, a singular mode of alcohol entry, 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 may 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 source, there seems 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) “possession” (i.e., possession) of a fake ID predicts subsequent frequency of heavy drinking (outlined as 5+ drinks per event; Martinez, et al., 2007).
This bidirectional relation not solely illustrates the public well being dangers of this mode of alcohol entry, but begs the query 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 impact”) or whether or not such harms and outcomes are predominantly pushed by a general stage of phenotypic danger on the a part of the fake ID “proprietor” (e.g., deviant peer associations, low self-control). Though general alcohol entry theories would possibly help the previous speculation nearly completely (specifically, fake ID possession increases alcohol entry and subsequent harm; see Gruenewald, 2011), general criminological theories of phenotypic danger help the latter (specifically, that broad categories of danger—or propensities to engage in dangerous habits—are the true cause of harm; see Pratt & Cullen, 2000). Certainly, such propensities is perhaps what predicts fake ID obtainment within the first place, and although the energy of the fake ID impact seems to increase over time, it is vastly diminished after controlling for intercourse, Greek status, and pre-college charges of drinking (Martinez et al., 2007). In sum, it is unclear how robust the fake ID impact is perhaps after accounting for individuals’ ranges of phenotypic or propensity danger—although this query has bearing on prevention and coverage initiatives, which may give attention to both strengthening enforcement of fake ID legal guidelines themselves, growing sources for trait-primarily based at-danger youth packages, 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, to be able to investigate the energy of the fake ID impact, we matched students with and with out fake IDs on plenty of danger-primarily 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 college students at a big Southeastern university. We additionally compared matched groups in an extra longitudinal replication sample of n=3,720 undergraduates at a big Midwestern university. We hypothesized that the results of fake ID possession on outcomes could be vastly diminished by—and subsequently largely attributable to—the pre-present trait-primarily based factors on which fake ID homeowners and non-homeowners might be matched. These comparisons can inform the extent to which the connection between unfavourable outcomes and false identification possession are attributed to selection factors, which once more, could have practical software for intervention and policy.
Procedure and Contributors
Two samples have been separately investigated following Institutional Assessment Board (IRB) approval: (1) A cross-sectional sample of n=1,454 underage college students from a big Southeastern University (IRB Protocol H12032) and (2) a prospective replication sample of n=3,720 undergraduates beneath the minimal authorized drinking age from a big Midwestern college (IRB Protocol 01-01-001). Of observe, each samples provide distinctive insights into the connection between false identification use and unfavourable outcomes. More particularly, the cross-sectional examine contains objects that distinguish between the use of fake IDs in several conditions (at bars, at grocery stores, etc.) and the longitudinal examine gives insight into the potential results of fake ID possession over time and establishes temporal order.
With regard to the cross-sectional sample, in the course of the educational yr 2011–2012, contributors have been recruited from forty randomly chosen large (>99 students) and average enrollment (30–99 students) classes. Contributors accomplished a one-page informed consent doc within the chosen classes before being given a six-page paper survey about college life and behaviors to complete with pencil or pen. Contributors weren’t compensated. All enrolled students have been invited to take part and the response rate was high at 80.4% (Stogner & Miller, 2013; 2014; Hart et al., 2014). After those above the authorized drinking threshold have been eliminated, the analytic sample was n=1,454 underage individuals. The sample was largely representative of the college with regard to demographics and was particularly 51.6% feminine, 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 basically inconsequential for the majority of covariates as many are immutable (age, race, gender) or exterior of the individual’s control (dwelling location, parental income, 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 in the course of the summer prior to university entrance utilizing paper and pencil and then have been requested to complete online surveys every semester for the subsequent four years (a total of eight semesters). College students provided informed consent and have been compensated $25 in every 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% feminine, 90.3% White/non-Hispanic, and averaged 17.9 (SD=.36) years of age (reflecting demographics which can be representative of the college as a whole [University Registrar, 2013]). College students have been traditionally aged; by the start of their junior yr, just one-third of the sample had reached the minimal authorized drinking age, climbing expectedly to 99.7% by the ultimate semester of college, Pattern retention was good, ranging from sixty nine% to 87% of baseline respondents collaborating at every subsequent wave. Retention biases have been low, although individuals have been extra more likely to remain within the sample if they have been females (OR=2.33) and have been less more likely to remain within the sample if they have been frequent binge drinkers (OR=.88; Sher & Rutledge, 2007). By the ultimate time-point, the sample size was n=2,250, although ninety% of students participated in or extra evaluation waves and 82% participated in three or extra waves. The longitudinal PSM introduced inside the textual content utilized the primary years of college solely (i.e., the primary four semesters, when the overwhelming majority of contributors have been underage) and, consistent with most PSM analysis, solely created matches between individuals in a way which is directly comparable to the analysis carried out with the cross-sectional sample.1
For the needs of replication, it was necessary that the measures utilized in each the cross-sectional and longitudinal studies stayed as comparable as possible. For ease of presentation, measures are organized in terms of their conceptual importance to the overall examine with cross-sectional and longitudinal measures explained together in every section. Timing of the longitudinal measures was considered necessary and is described as is appropriate. Particularly, although the eight-wave longitudinal sample included multiple measurements of many covariates throughout time, the primary longitudinal PSM solely utilized measurements as they might be expected to occur if observing a “fake ID impact” over a logical progression of time (i.e., Trait/propensity measures have been measured at Wave 1 and used to predict fake ID possession at Wave 2 which in turn assessed as a predictor for outcome measures at each Waves 3 and Wave 4). The second semester of college (Wave 2) was chosen as the singular target time-point at which fake ID possession (or the “fake ID impact”) was measured, because it is considered a peak time of danger for unfavourable drinking-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 drinking was created in each samples. A six-option ordinal merchandise requested respondents what number of days within the final month did they eat 5 or extra alcoholic drinks. A intercourse-particular binge drinking measure was not available. These selecting both of the 2 highest frequency choices (10–19 days and 20+ days) have been categorized as frequent binge drinkers while all others have been not. This dichotomous merchandise represents binge drinking greater than ten days within the final month. Second, we utilized an instrument created by Maney, Higham-Gardill, and Mahoney (2002) to signify alcohol-associated problems within the cross-sectional sample. This ten-merchandise scale assesses the diploma to which the individual feels that alcohol use has created relationship, family, well being, behavioral, and professional/school problems within the final yr and shows adequate reliability (α=.822). In the longitudinal sample, this scale was approximated from ten objects taken from the Younger Adult Alcohol Problems Screening Test (YAAPST; Hurlbut & Sher, 1992) with adequate reliability (α=.848 in second-yr fall and α=.846 in second-yr spring). A dichotomous alcohol-associated arrest/citation measure was created within each samples utilizing objects that requested respondents if they’d ever been arrested or cited for driving beneath the influence, underage drinking, public dysfunction (on account of alcohol), being drunk in public, or an open container violation within the final year. The ultimate outcomes have been each dichotomous and measured equally in every sample; marijuana use and exhausting drug use signify whether or not the respondent self-reported any use of marijuana and cocaine, heroin, and/or methamphetamine, respectively, within the final year.
False Identification Present fake ID “possession” was assessed dichotomously in each samples (zero=No, 1=Yes). The cross-sectional examine additionally included further objects that requested respondents whether they had used the fake ID in a bar or membership and whether they had used it in a retailer to purchase alcohol.
Trait and danger factor (matching) covariates Fifteen variables have been utilized in propensity rating matching within the cross-sectional sample and fourteen have been used within the longitudinal sample. Variables have been chosen on account of their inclusion in each datasets and previous analysis suggesting that they might 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, (4) exposure to substance use, (5) family income, (6) gender, (7) GPA, (8) Greek membership, (9) well being, (10) low self-control, (11) peer substance use, (12) race, (13) rural dwelling location (solely measured within 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 practically identically. Among those identically measured have been age, age of first alcohol use, employment status (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, gay, bisexual, or different). Self-reported well being was measured with an merchandise that requested respondents to rate their own well being—the cross-sectional examine offered responses ranging from 1 (poor) to 4 (glorious) whereas the longitudinal examine choices ranged from 1 (poor) to five (glorious).
The cross sectional examine utilized four-merchandise measures tailored from Lee, Akers, and Borg (2004) to signify exposure to substance use (α=.786) and peer substance use (α=.801). Because the longitudinal data didn’t embrace similarmeasures, every of those constructs was represented by a single merchandise quite than a four-merchandise scale. The primary (exposure) was measured dichotomously while the second (peer substance use) was measured on a six-option ordinal scale. Low self-control was operationalized utilizing the 24-merchandise Grasmick et al. (1993) scale (α=.889) within the cross-sectional examine and the NEO Five Factor Stock conscientiousness scale (reverse-coded) within the longitudinal sample (α=.844; Costa & McCrae, 1992). Subjective distress was measured utilizing Cohen and Williamson’s (1988) ten-merchandise perceived student stress scale (α=.814) within the cross-sectional examine and the World Severity Index from the Temporary Symptom Stock-18 within the longitudinal sample (Derogatis, 2000). Larger values on these scales signify 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. In the cross-sectional examine a measure of family income was used. Contributors selected between choices ranging from beneath $10,000 per yr (coded 1) to over $one hundred seventy five,000 per yr (coded 9). An merchandise assessing whether or not or not students have been the primary in their family to attend college (zero=No, 1=Yes) was utilized within the longitudinal study.
Rural dwelling location was used within the cross-sectional examine, but no comparable measure was accessible within the longitudinal data. This variable was necessary to include regardless of creating differing matching standards due to the traits of the examine area. The cross-sectional sample was drawn from an area that is very rural excluding one major city; thus, a dichotomous merchandise representing whether or not the student grew up in an urban / suburban area (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 pulls students from 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. Along with possession of a fake ID, the cross-sectional sample additionally documented contributors’ utilizing of the fake ID in bars/clubs 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.”
Subsequent, to raised decide the energy of the “fake ID impact” after accounting for trait measures, propensity rating matching (PSM) was used for each samples. PSM gives a clearer image of the connection between variables than bivariate analyses which may yield spurious outcomes (Guo & Fraser 2009) and has been used to evaluate issues associated to substance use (Miller et al., 2011). Additionally of observe, PSM is preferable to multivariate regression models in cases equivalent to this the place the variable of interest might not be independently related to the dependent variable, but is probably going correlated with those which can be and likewise happens extra proximally. The propensity matching methods developed by Rosenbaum and Rubin (1983, 1985) can be utilized to create a sample with groups which can be comparable in all related variables except for the “therapy” (i.e., fake ID possession). While their methods do result in a reduction in size of analytic sample (usually main PSM to be known as resampling), they’re efficient at making a situation whereby the impact of “therapy” might be estimated as the typical distinction between those exposed to the therapy and “counterfactuals,” outlined as the anticipated outcomes have been it not for exposure to the therapy (Guo & Fraser 2009). In this case, the PSM technique creates analytic groups whereby variations aside from false identification use are minimalized.
As steered 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 point common, membership in a campus Greek group, self-assessed well being, low self-control, peer substance use, race, size of dwelling group, sexual orientation, and subjective distress) and 14 comparable variables (size of dwelling group excluded, as explained above) in the main longitudinal PSM analysis (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 probability of getting a fake ID. Following an evaluation of regions of common help, we created comparison groups within every sample utilizing a -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 technique led to the expected decrease in sample size (n=817 and n=518, respectively) but a sufficient variety of cases have been retained for statistical comparisons.
Rates of fake ID possession
Rates of fake ID possession have been quite high, particularly within the cross-sectional sample. That’s, of the 1,454 underage alcohol customers 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 (27.8%) have used the ID to purchase alcohol at a store. Prevalence charges of false ID use within the Midwestern sample changed over time. Fake ID possession among students beneath 21 peaked in the course of the third yr of college (pre-college=12.5%, first-yr fall=17.1%, first-yr spring=21.4%, second-yr fall=28.1%, second-yr spring=32.2%, third-yr fall=34.9%, third-yr spring=39.zero%, fourth-yr fall=38.1%, fourth-yr spring= fewer than ten students have been under the minimal authorized drinking age).2
The “fake ID impact” previous to matching
Desk 1 presents mean scores for 5 substance use outcomes for fake ID homeowners and non-homeowners in each samples (outcomes at each Wave 3 and 4 are reported for the longitudinal sample). Average scores for every outcome (frequent binge drinking [10 or extra days within the final month], self-reported alcohol associated problems, alcohol-associated arrests, marijuana use, and exhausting drug use) are introduced 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 conducted to determine whether or not, on common, variations exist between fake ID customers and non-users. Every of the assessments reached significance. No matter whether or not the main target was possession of a fake ID or utilizing it at a specific type of outlet, the outcomes have been consistent. At the bivariate stage, extra individuals with false identification have interaction in frequent binge drinking, have been arrested/cited for an alcohol violation, have interaction in marijuana use, and use exhausting drugs. People with fake identification additionally, on common, report extra alcohol-associated problems. These outcomes would point out that fake IDs are a automobile of risk. Nonetheless, it is attainable that fake ID possession (and associated dangers) are extra a operate of underlying dangerous traits.
Propensity rating matching (PSM)
As a result of consistency within the findings thus far regardless of false identification measure (possession, bar use, and/or retailer use), the extra analyses with every sample makes use of just one false identification measure, possession of a false ID. We carried out PSM analyses in each samples, to examine whether or not individuals with and with out fake IDs continue to differ on these outcomes after being matched on substantively necessary traits. Desk 2 shows that individuals with and with out fake IDs certainly differed from each other on these trait propensity variables, suggesting that it is these variables which may ultimately be driving the fake ID effect. Desk 2 additionally shows that the PSM technique labored nicely in each samples, consistently lowering bias related to the statistically vital variations between those with and with out fake IDs by greater than 50% on all but one variable. Though three vital variations 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 variations in age of onset and Greek affiliation have been minor compared to pre-matching. In this, matching was equally, if not more, successful within the longitudinal sample. It should be noted that matching did yield a reduction in sample size. Total, nevertheless, in each samples matching seems to have created therapy and comparison groups which can be extra equal and extra acceptable for comparison than the unrivaled data.
The propensity scores that have been calculated for every case are graphically displayed in Determine 1. As might be seen within the determine, a region of common help exists, but only a few with low propensity scores had a fake ID and only a 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 5 substance use associated outcomes. While considerably extra of those with fake IDs within the cross-sectional sample have been frequent binge drinkers previous to matching (t=9.eighty one, df=815), the groups have been now not considerably totally different after matching (t=1.eighty one, df=815) and the typical therapy impact (ATE; e.g., variations in group means), as displayed in Desk 3, was decreased by 59.2%. Equally, previous to matching, fake ID homeowners had considerably greater scores on the alcohol associated problems scale than non-homeowners (t=9.83, df=815), but the groups have been now not considerably totally different after matching (t=1.31, df=815) and the ATE was decreased by 63.4%. Nonetheless, in terms of alcohol-associated arrests, the 2 groups have been nonetheless considerably totally different and the ATE effectively remained unchanged. As was the case for the primary outcomes, fake ID possession was related to marijuana use previous to matching (t=9.36), but not after (t=1.52; ATE decreased by 60.4%). Lastly, exhausting drug use was related to fake ID possession each before (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 substantial decrease within the ATE for four of the 5 outcomes (Desk 3, columns 3–6). Nonetheless, in contrast to the cross-sectional sample, ATEs remained vital for alcohol associated problems (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. Again, these results sizes have been substantially decreased, but within the aforementioned cases, not eliminated. As was the case within the cross-sectional sample, propensity rating matching had little influence on the ATE on alcohol-associated arrests.3
This examine’s initial outcomes are consistent with previous analysis—a substantial variety of underage students have fake IDs and are at greater danger for binge drinking, alcohol-associated problems, alcohol associated arrests, and different 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 gave the impression to be a “fake ID impact” is basically the results of factors that influenced each the acquisition of the false ID and the outcome. The significant relationship between fake ID use and different substance use outcomes usually remained after PSM, but the magnitude of those relationships have been substantially diminished, most by over forty%. 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 high ranges of danger for alcohol-associated arrests [DUIs, open container, etc.]). The rationale this outcome is distinct from the others just isn’t readily clear; perhaps regulation enforcement officers are more likely to issue citations or arrests for different substance-associated offenses when a person can also be found with a fake ID. If so, the “impact” wouldn’t appear smaller in propensity rating models as the distinction could be pushed by officers’ reactions to the fake ID quite than individuals’ underlying propensity.
The pattern that emerges from Desk 3 seems to point that non-matched samples could have overestimated the impact of false identification use on unfavourable outcomes, but that fake ID possession has an impact that extends past shared causal factors. This particular remaining “fake ID impact” may certainly help the concept the fake ID itself serves as a kind of threshold into different types of deviant habits, the place those who are prepared to amass fake IDs develop into more and more prepared to violate different legal guidelines (see Ruedy et al., 2013; Winograd et al., 2014). However in gentle of the opposite findings, it is extra seemingly that fake IDs extra typically average the results of dangerous traits on behavior. For example, fake IDs could have the highest efficiency of impact through offering impulsive individuals with further means and alternative for problematic behaviors that they might not in any other case have engaged in. Indeed, underlying trait dangers are sometimes incorporated into alternative-theory-associated examinations of crime (Grasmick et al., 1993; Lagrange & Silverman, 1999).
As such, these findings have practical implications. Though increased server coaching, fake ID production/provider legal guidelines, and legal responsibility legal guidelines are an necessary means of addressing the dangers of fake IDs as a form of alcohol entry (Fell, Scherer, Thomas & Voas, 2014; Yörük, 2014), faux-ID associated outcomes may additionally partly be a operate of trait dangers that can moreover be addressed with intervention. One way to begin addressing this mixture of things may be through motivational, normative suggestions-primarily based, or abilities interventions which can be particularly geared toward decreasing the probability that at-danger students receive 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 can be particularly tailor-made toward addressing each individuals’ dangerous traits and their ensuing behaviors (see Conrod et al., 2006).
Though an incredible energy of this examine rests in the similar findings found with distinctive college populations, these findings might not be generalizable to non-college attending populations. Moreover, fake ID policies, enforcement, and worry of sanctions could differ substantially in several localities (Erickson, Lenk, Toomey, Nelson & Jones-Webb, 2016). For example, some drinking institutions may be lenient in their carding policies, intentionally settle for false identification, and/or not be topic to rigorous regulatory enforcement (Murray, 2005). Additionally, penalties for possessing and/or utilizing a fake ID to purchase alcohol varies substantially from state to state together with the type of offense, amount of high-quality, suspension of driver’s license, and the possibility of probation or jail time. Future analysis ought to evaluate the affect of fake ID relative to differential policies and enforcement of the minimal authorized drinking age, together with group efforts (Grube, 1997). Further, while fifteen distinct traits have been included within the matching course of, there stays the possibility that further 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 so, the “fake ID impact” may be even smaller than our matching models suggested.
In concluding that the “fake ID impact” is especially a operate of phenotypic danger, fake ID possession could function an indicator of heightened danger for extra extreme drinking associated problems. Though most penalties for fake ID possession are punitive (fines, probation/jail, and/or lack of driver’s license), coverage-makers, college officers, and practitioners ought to target fake ID homeowners for intervention strategies geared toward lowering high-danger drinking behaviors (and different problematic behaviors linked to phenotypic danger). Though increased penalties and enforcement of the minimal authorized drinking age has the potential to cut back fake ID possession, we caution coverage-makers to evaluate and take into account the unfavourable consequences of transferring college drinking away from regulated institutions the place security and emergency services are extra readily available (see Baldwin et al., 2012; 2014). Though our findings found that fake ID possession (regardless of particular person danger traits) increased the chance for alcohol associated arrests, drug use, and alcohol associated problems (Midwest sample solely), we didn’t assess victimization and different harms related to excessive alcohol consumption that might increase in spaces not topic to regulatory controls (Miller, Levy, Spicer & Taylor, 2006). Future analysis is needed to evaluate the affect that fake ID enforcement could have on problematic drinking each in regulated and unregulated spaces.