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Abstract

A number of college presidents have endorsed the Amethyst Initiative, a call to consider lowering the minimum legal drinking age (MLDA). Our objective is to forecast the effect of the Amethyst Initiative on college drinking. A system model of college drinking simulates MLDA changes through (i) a decrease in heavy episodic drinking (HED) because of the lower likelihood of students drinking in unsupervised settings where they model irresponsible drinking (misperception), and (ii) an increase in overall drinking among currently underage students because of increased social availability of alcohol (wetness). For the proportion of HEDs on campus, effects of large decreases in misperception of responsible drinking behavior were more than offset by modest increases in wetness. For the effect of lowering the MLDA, it appears that increases in social availability of alcohol have a stronger impact on drinking behavior than decreases in misperceptions.
Author Copy
Fitzpatrick, BG, R Scribner, AS Ackleh, J Rasul, GM Jacquez, N Simonsen, R Rommel. 2012.
Forecasting the Effect of the Amethyst Initiative on College Drinking. Alcoholism Clinical
and Experimental Research (impact factor: 3.34). 03/2012; 36(9):1608-13. DOI:10.1111/j.1530-
0277.2012.01765.x 5
Title: Forecasting the Effect of the Amethyst Initiative on College Drinking
10
Authors: Ben G. Fitzpatrick PhD1,2 , Richard Scribner MD, MPH3 , Azmy S. Ackleh PhD4,
Jawaid Rasul, PhD5, Geoffrey Jacquez PhD5,6 Neal Simonsen PhD3, Robert Rommel PhD5
1Loyola Marymount University, 1 LMU Drive, Los Angeles, CA 90045
2Tempest Technologies, 8939 S. Sepulveda Blvd, Suite 506, Los Angeles, CA 90045 15
3Louisiana State University School of Public Health, 1615 Poydras St., Room 1535, New
Orleans, LA 70112
4University of Louisiana at Lafayette, P.O. Box 41010, Lafayette, LA 70504-1010
5Biomedware Incorporated, 3526 W. Liberty, Suite 100, Ann Arbor, MI 48103
6The University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 20
48109-2029
Corresponding Author : Ben G. Fitzpatrick PhD, Loyola Marymount University, 1 LMU
Drive, Los Angeles, CA 90045, 310.338.7892 (voice), 310.338.3768 (fax), bfitzpatrick@lmu.edu
Support : This research was supported by National Institute on Alcohol Abuse and Alcoholism 25 grant RO1 AA015573.
Abstract
Background: A number of college presidents have endorsed the Amethyst Initiative, a call to
consider lowering the minimum legal drinking age (MLDA). Our objective is to forecast the 30
effect of the Amethyst Initiative on college drinking.
Methods: A system model of college drinking simulates MLDA changes through (1) a decrease
in heavy episodic drinking (HED) due to the lower likelihood of students drinking in
unsupervised settings where they model irresponsible drinking (misperception), and (2) an
increase in overall drinking among currently underage students due to increased social 35
availability of alcohol (wetness).
Results: For the proportion of HEDs on campus, effects of large decreases in misperception of
responsible drinking behavior were more than offset by modest increases in wetness.
Conclusions: For the effect of lowering the MLDA, it appears that increases in social
availability of alcohol have a stronger impact on drinking behavior than decreases in 40
misperceptions.
Keywords: Amethyst Initiative, Modeling, College, Heavy Episodic Drinking, Misperception
Introduction
College drinking is one of the most significant and complex public health problems 45
today. Heavy drinking among college students remains a pervasive problem that places students
at considerable risk for a variety of negative outcomes, including date rape, academic problems,
traffic accidents, and health problems ( Hingson, Heeren, Winter, and Wechsler, 2005; Wechsler
and Nelson, 2008). Alcohol use is embedded in the college lifestyle, resulting in enormous
social, economic, and health consequences among some of the nation’s finest students (Task 50
Force on College Drinking, 2002). Heavy episodic drinking is generally conducted in private,
among peers, and college students engage in the behavior in much higher proportions than do
other young adults (Schulenberg, et al., 2001; Carey, Scott-Sheldon, Carey, and DeMartini,
2007; Substance Abuse and Mental Health Services Administration, 2006; Timberlake, et al.,
2007). 55
Interventions to reduce the negative outcomes associated with college drinking have
been mixed. For example, reeducation programs targeting misperception of drinking norms
remain a popular intervention. Social norms researchers have found that college students
routinely misperceive the level of alcohol use among their peers (Baer, Stacy, and Larimer,
1991; Perkins, Haines, and Rice, 1991) and liberal perceptions of social norms for peer 60
drinking are consistently shown to be strong predictors of alcohol use among college
students (Baer, Stacy, and Larimer, 1991; Perkins, Haines, and Rice, 1991; Reis and Riley,
2000; Baer and Carney, 1993, Perkins, et al., 1999; Babor, Aguirre-Molina, Marlatt, and
Clayton, 1999; Thombs, Wolcott, and Farkash, 1997). Rather than address the population level
factors that lead to misperception of social norms in the first place, Social Norms Marketing 65
(SNM) interventions attempt to reeducate students by correcting their misperceptions of their
peers’ behavior in hopes of changing individual behavior. The results of these interventions
have been equivocal (Thombs, Wolcott, and Farkash, 1997; Haines and Spear, 1996; Werch, et
al., 2000; Wechsler, et al., 2003; Toomey, Lenk, and Wagenaar, 2007; DeJong, et al., 2006).
The limited effectiveness of college drinking interventions has led to calls to 70
reexamine the MLDA. One of these, called the Amethyst Initiative, asks chancellors and
presidents of universities and colleges across the country to sign on to a call asking elected
officials to revisit the 21 year old drinking age. So far over 100 chancellors and presidents
have signed on. The Amethyst Initiative statement argues that the 21 year old drinking
age is not working. Underage students are legally prohibited from purchasing and 75
possessing alcohol and the majority continue to drink. In addition, the statement argues the
rampant flaunting of the drinking laws by students has led to a “culture of dangerous binge
drinking” on many campuses. John McCardell, the original author of the initiative, has
described the mechanism by which this culture has evolved. He argues that because of the
21 MLDA underage students are precluded from drinking in supervised settings (e.g., bars, 80
school sponsored parties). As a result, they are more likely to drink in unsupervised settings
(e.g., off campus parties) where there are fewer constraints on excessive drinking. He
concludes that in these settings underage students who are new to drinking develop
misperceptions of the normal drinking behavior and binge drinking tends to be viewed as
normal (McCardell, 2008). This argument is consistent with literature that demonstrates 85
misperception of drinking norms predicts individual drinking (Baer, Stacy, and Larimar,
1991; Perkins, Haines, and Rice, 2005). Social norms theory argues that the effect of
misperceptions is rooted in a psychological attribution process in which the individual tends
to perceive the drinking actions of others as reflective of their individual drinking
temperament and align their behavior accordingly (Perkins, 1997; Prentice and Miller, 1993), 90
proponents suggest that the MLDA of 21 years of age is the problem. Critics of the
Amethyst Initiative argue that lowering the MLDA will increase the availability of alcohol
for both social and home consumption, and therefore increase drinking among the entire
population with disastrous results (Babor, 2008).
Lowering the current MLDA represents an enormous social experiment with potentially 95
major consequences. While there is considerable evidence indicating the harms associated with
lowering the MLDA with regard to the general population (Wagenaar and Toomey, 2002), there
is little in the way of observational evidence (Kypri, et al., 2006) to either support or oppose the
specific hypotheses regarding student drinking behaviors embedded in the Amethyst initiative.
A systems approach is one method of providing a forecast for the effects of a policy change prior 100
to carrying out interventions based on that policy. Public health researchers are beginning to see
the opportunities of moving from a purely inferential approach of experimental design and data
analysis to a more mechanistic, systems approach (Homer and Hirsch, 2006). In particular, the
social and economic cost of suboptimal policy decisions can potentially be mitigated by an
increased understanding of the potential consequences that a systems model can provide. 105
Materials and Methods
We have developed a systems model, referred to as SimHED (Ackleh, et al., 2009;
Scribner, et al., 2009), to simulate a college campus student population structured by drinking 110
behavior and drinking age. The model, a continuous dynamical systems compartmental model
derived using epidemiological reasoning, is provided in detail in the Appendix. The
compartmental structure involves two levels of structure in age, namely underage (U) and legal
age (L), as well as four drinking styles associated with college drinking, namely abstainers (1)
social drinkers (2), problem drinkers (3), and heavy episodic drinkers or HEDs (4). Abstainers 115
are defined as individuals who do not drink. Social drinkers are individuals who drink more
frequently than abstainers but do not belong to the other two compartments. Problem drinkers
are those who report at least two out of four indicators of problem drinking based on the CAGE
instrument (Mayfield, McLeod, and Hall, 1974), regardless of the amount or frequency of their
drinking. Heavy episodic drinkers are individuals who consume more than five drinks in a single 120
sitting on at least one occasion in the past two weeks. In this manner, the state of the system at
any given time is defined by 8 numbers,
43214321 ,,,,,,, LLLLUUUU
, which are the number of
individuals in each of the four drinking style compartments for the underage drinkers
(
4321 ,,, UUUU
) followed by the corresponding numbers for the legal age drinkers
(
4321 ,,, LLLL
). 125
Individuals move from underage to legal age purely by aging. We assume that the aging
process itself does not directly change the drinking style of the individual, so that transition from
the underage to legal age compartments preserves the drinking style. The drinking style
transition model includes three types of parameters that control transfers between the four
drinking style compartments: individual risk (Wechsler, Dowdall, Davenport, and Castillo, 1995, 130
Presley, Meilman, and Leichliter, 2002), social interactions (Reifman, Watson, and McCourt,
2002; McCabe, et al., 2005), and social norm misperception (Perkins, et al., 1999; Borsari and
Carey, 2001).
The individual risk model handles transitions that depend only on individual factors (e.g.,
mood, developmental transitions, individual traits). This component of the system involves a 135
fraction of individuals with a particular drinking style transitioning to a different drinking style
over a period of time. These transitions are modeled by terms of the form
iij Nr
(in which N
represents U or L, r models the fraction of those individuals transitioning, and the subscript ij
represents the transition out of drinking style i into drinking style j). Since the movement is from
i
to
j
, this term is a positive term in the
j
equation and a negative term in the
i
equation. 140
Social interaction transitions depend on individuals from two separate groups coming
into contact with one another, much like an epidemiological model of disease transmission. That
is, an individual with a certain type of drinking style convinces another individual with a
different drinking style to change behavior. We model these transitions by terms of the
form
, proportional to the number of pairings available among the two different drinking 145
styles. In this case, the movement may be in either direction, i.e., from
i
to
j
or vice versa. So,
jiij NNs
represents a net movement between the two compartments i and j, and thus
ij
s
may be
negative.
Social norms/misperception transitions occur due to perception of the level of a particular
drinking behavior. These movements occur in two situations: when abstainers become light 150
drinkers because they perceive an exaggeratedly large number of drinkers on campus, and when
social drinkers become HEDs because they perceive an exaggeratedly large number of HEDs.
Situation a) is modeled by the term
4
1
4
2
112
kkk
kkk
LU
LU
MNn
and situation b) is modeled by the
terms
4
1
44
5
kkk
ii LU
LU
MNn
, where
i
can be either 2 or 3. Again, N represents either U or L
here, an underage (U) or legal age (L) drinking style, as the changes in drinking style are 155
assumed to occur within an age group. The function M is the misperception function, modeling
how badly the students overestimate the fraction of individuals undertaking the role model
behavior (either the fraction of drinkers or the fraction of HEDs). Were M the identity function,
student perception would be entirely accurate. Research in social norms suggests (Reis and
Riley, 2000) that misperception is greatest when the model behavior is least prevalent and that 160
misperception decreases as the model behavior increases. For example, in an analysis of the
National College Health Assessment, 59.9% of students overestimate the drinking norms of their
peers at parties by three or more drinks on campuses where abstinence is the norm. Where six
drinks is the actual norm, 31.5% of students overestimate by three or more drinks (Perkins,
Haines, and Rice, 2005). For these reasons we have chosen the functional form 165
2
)1()( xxM
whose graph is illustrated in Figure 1.
Figure 1 is to be inserted here.
Figure 1. Example misperception function.
The hyperparameter
controls the level of misperception: as
0
the amount of
overestimation goes to 0, and M becomes the identity function. We use the term 170
“hyperparameter” here to distinguish from the basic transition rate parameters in the model and
to emphasize that those rate parameters depend on
.
The campus alcohol environment (i.e., level of campus wetness) is an additional
hyperparameter, w, which modifies the transfer rates between compartments as a function of
campus wetness. Each rate parameter
ijijij nsr ,,
depends linearly on the wetness. For example, 175
,)1( 1
23
0
2323 wrwrr
so that a completely “dry” campus, w=0, has rate parameter
,
0
23
r
and a
completely “wet” campus, w=1, has rate parameter
1
23
r
.
A version of the model without age structure has been successfully calibrated to survey
data obtained from 32 campuses across the United States in the Social Norms Marketing
Research Project, SNMRP (DeJong, et al., 2006; Ackleh, et al., 2009; Scribner, et al., 2009). 180
We have reasonable estimates of the “wet” and “dry” rate parameter values, the wetness
levels for each of the 32 campuses, and the misperception levels. Table 1 contains parameter
estimates for the wet and dry rate parameters.
185
Parameter Name
Value at w=0
Value at w=1
s12
0.0170
19.1313
s42
4.2113
3.9486
r31
4.6484
4.6133
r23
0.2538
0.3971
r24
1.2860
6.8722
rR42
6.3111
6.2014
r43
1.5545
1.5776
r21
0.58-0
0.1807
r12
0.5006
8.0899
r24
2.6021
4.3106
Table 1. Bounds for the rate parameters as estimated from SNMRP data.
The wetness hyperparameters range from 0.05 to 0.55 in the 32 schools from the SNMRP
data. Wetness correlates (
30.0
2R
) with alcohol outlet density, a common measure of
availability, but clearly other phenomena are involved, such as enforcement and campus social 190
environment. However, lowering the MLDA would dramatically affect the effective alcohol
outlet density for underage students. We estimated the misperception hyperparameters for the
SNMRP campuses, and these values range from nearly 0 to 0.25.
We are interested in the exploration of the interplay between misperception and
availability. In particular, the Amethyst Initiative’s hypothesis is that a reduction in 195
misperception and attendant improper role model choices will lead to a reduction in HED
behavior. Toward that end, we consider a hypothetical college population behavior averaged
over a ten year period, and we conduct a series of experiments. We assume that the wet and dry
rate parameter values are the same for the under age and legal age groups; however, we take the
legal age group to have higher wetness (greater availability) and lower misperception levels. We 200
conducted a series of computer simulation experiments that we report here.
Results
We begin our exploration by considering a campus with medium wetness of 0.30,
applicable to the legal age students, who also have a small amount of misperception (
=0.05).
In order to examine the effect of misperception, we consider a number of simulated “treatment” 205
scenarios in which we assume a range of effects on the wetness and misperception parameters
for the underage population and observe the resulting drinking behavior.
Our first simulation involves the assumption that the wetness hyperparameter for the
underage population is the same as for the legal age (w=0.30), but that the misperception is at a
higher level (
=0.25). Our treatment is assumed to reduce the misperception from 0.25 down 210
to 0.05, the level of the legal age students, with 100% treatment implementation (Figure 2 upper
panel). The x-axis in the upper panel Figure 2 denotes this linear change of misperception,
where 0% implementation corresponds to
=0.25 and 100% to
=0.05. We can see that the
reduction in Heavy Episodic Drinkers is relatively small. We should note that it is not clear that
the legal age population would actually have less misperception than the underage population; 215
however, such an assumption leads to a slightly conservative estimate on heavy episodic
drinking.
A different approach might be to change the wetness parameter for the underage students.
Our second simulation, in the lower panel of Figure 2, shows the fraction of HEDs in the legal 220
and underage compartments as we reduce wetness in the underage group from 0.30 (0 percent
treatment on the x-axis ) down to 0.00 (100 percent treatment). Again, the legal age students
have a small misperception parameter (
=0.05) while the misperception of the underage
students is at a high level (
=0.25). One can see in the lower panel of Figure 2 that this
treatment has a much stronger impact on the HED fraction than does the reduction of 225
misperception.
Figure 2 is to be inserted here.
Figure 2. HED fraction as a function of simple one-variable treatments. Upper panel
shows the effect of reducing misperception from 0.25 to 0.05. Lower panel shows the effect
of lowering wetness from 0.30 to 0.00. 230
Neither of these simulations captures the actual effect of the Amethyst Initiative’s MLDA
reduction. One might expect that wetness for the underage population is somewhat less than it is
for the legal age population (exactly how much is of course a difficult matter to resolve) while
the amount of misperception is greater for the underage population. We have conducted a
number of simulations in which wetness and misperception for the underage population are 235
changed simultaneously. As a first illustrative example, we continue with the hypothetical
campus having wetness of 0.30 and misperception of 0.05 for the legal age students. We have
also simulated a wet campus (w=0.55). We assume in this example that the underage population
has a wetness parameter of half that of the legal age population, and a misperception parameter
of 0.25, while the misperception parameter is at the high end of those we have inferred from 240
SNMRP data. The treatment is to increase the underage wetness to that of the legal age group,
while reducing the misperception to 0.05, so that at the end of the treatment, the legal age and
underage students have the same parameters.
In Figure 3, we show the effect of simultaneously increasing the wetness and decreasing 245
the misperception in the underage population. In each of the simulated experiments (both
moderate and wet), the underage population goes from half the wetness of the legal population to
fully as wet, while simultaneously going from high misperception (0.25) to the low level of the
legal age population (0.05). In each of the three panels, the qualitative trend is the same: HED
drinking among underage students is increased. 250
Figure 3 is to be inserted here.
Figure 3. HED fractions as a function of changing underage wetness and
misperception. The upper panel shows a campus with moderate wetness (w=0.30) among
the legal age students; the lower panel shows a wet campus.
With any computer simulation model of a real-world phenomenon, but most especially 255
with the highly challenging modeling problems of social systems, the prediction of events that
are out of the scope of observation must be viewed with some skepticism. We have endeavored
to calibrate and validate our model as accurately as possible (Ackleh, et al., 2009), and we have
also conducted a large number of simulation studies to examine the dependence on assumptions
about the legal age population, dropout and recruitment rates, and other parameters. Such 260
sensitivity analyses of the model to its parameters are a necessary step for developing confidence
in the resulting predictions. We have found across a wide spectrum of such analyses that the
structure of the basic findings presented here is remarkably consistent.
Discussion
Limitations 265
It is of course a risky exercise to attempt to predict possible behavior based on inferred
parameterizations. Rather than viewing these results as quantitative predictions of the actual
levels of drinking that will occur under an MLDA change, we prefer to interpret the model
output in terms of the trends and joint behavior as wetness index and misperception are changed
simultaneously. The inescapable conclusion is that the misperception must be very great among 270
the underage population and very significantly reduced by allowing the underage population to
drink in order to compensate for the increased availability of drinking venues to the underage
population. Indeed, further studies are required to quantify with accuracy how these parameters
might actually change in the presence of an MLDA reduction. We do, however, interpret our
simulations to date as pessimistic for the Amethyst Initiative’s proposal that an MLDA reduction 275
will have beneficial consequences for college drinking.
Conclusions
The preliminary insights provided by this model suggest that a reduction in the MLDA
may not produce the desired reduction in heavy episodic drinking that is the goal of the
Amethyst Initiative’s strategy, based on the Initiative’s reasoning about why “21 is not 280
working.”(20). The analysis we have conducted suggests that effects of a reduction in
misperception from the largest observed values to the lowest is overcome by a 25 percent
increase in campus wetness. One might expect a much larger increase in wetness from the
increased physical availability of alcohol associated with making the entire college population,
rather than approximately half, to be of legal drinking age. 285
Appendix
The eight-compartment set of equations is given by
442244434422
4
1
44
242244244
4
442244434422
4
1
44
242244244
4
3344322333133
3
3344322333133
3
224422242232212
4
1
44
24
42242122121
4
1
4
2
1222
2
224422242232212
4
1
44
24
42242122121
4
1
4
2
1222
2
11331221221121
4
1
4
2
1211
1
11331221221121
4
1
4
2
1211
1
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)(
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ULrLrLrL
LU
LU
fnLULsLd
dt
dL
UUrUrUrU
LU
LU
fnLUUsUd
dt
dU
ULrLrLrLd
dt
dL
UUrUrUrUd
dt
dU
ULrLrLrLrL
LU
LU
fn
LLUsLLUsL
LU
LU
fnLd
dt
dL
UUrUrUrUrU
LU
LU
fn
ULUsULUsU
LU
LU
fnUd
dt
dU
ULrLrLULsL
LU
LU
fnLd
dt
dL
UUrUrLUUsU
LU
LU
fnUd
dt
dU
iii
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... For example, after New Zealand lowered its MLDA from 20 to 18, there were substantial increases in alcohol-related hospitalizations [20]. Recent system models simulating lowered MLDA changes also suggest "pessimistic" outcomes resulting from the Amethyst Initiative, including an increased social availability of alcohol (campus wetness) that will likely overshadow any anticipated benefits stemming from allowing those 18 and older to consume alcohol legally [21]. Therefore, university chancellors and presidents should strongly consider Fitzpatrick et al.'s [21] warning that, "lowering the current MLDA represents an enormous social experiment with potentially major consequences" (p2). ...
... Recent system models simulating lowered MLDA changes also suggest "pessimistic" outcomes resulting from the Amethyst Initiative, including an increased social availability of alcohol (campus wetness) that will likely overshadow any anticipated benefits stemming from allowing those 18 and older to consume alcohol legally [21]. Therefore, university chancellors and presidents should strongly consider Fitzpatrick et al.'s [21] warning that, "lowering the current MLDA represents an enormous social experiment with potentially major consequences" (p2). ...
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... To gain some insight into the problem of college drinking on US college campuses, we have embarked on an agent-based modeling effort to examine the impact of social interactions on alcohol consumption. Distinct from compartmental models Rasul et al. 2011;Fitzpatrick et al. 2012) and other agent-based models (Garrison & Babcock 2009;Gorman et al. 2006;Giabbanelli & Crutzen 2013), the model we have developed is a simple model of a single drinking event that incorporates Identity Control Theory and Peer Influence as social mechanisms affecting drinking rates. The deterministic compartmental models of Scribner and colleagues partition the college population into four drinking styles (abstainer, social, problem, and binger) and use contact transitions to model the dynamics of the population as in an epidemic model. ...
... The deterministic compartmental models of Scribner and colleagues partition the college population into four drinking styles (abstainer, social, problem, and binger) and use contact transitions to model the dynamics of the population as in an epidemic model. The result is a drinking structure of the population evolving over multiple academic years Ackleh et al. 2009;Rasul et al. 2011;Fitzpatrick et al. 2012). Garrison and Babcock (2008) model an academic year but treat the motivation to drink based on the agent's "use rate," the agent's attitude toward drinking, and peer pressure. ...
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... Calls for a reduction in the minimum legal drinking age suggest the undertaking of a complex, large scale social and political experiment with potentially major consequences. Computational decision aids can support policy investigation when experimentation and testing must necessarily be limited (McCardell 2008;Fitzpatrick et al. 2012Fitzpatrick et al. , 2016a. Again, exhaustive simulation of control strategies may not be a desirable or even viable option, and developing mathematically tractable tools for winnowing the vast array of control strategies or policies into a manageable set for simulation can enhance this type of model tremendously. ...
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Agent-based models (ABMs) have become an increasingly important mode of inquiry for the life sciences. They are particularly valuable for systems that are not understood well enough to build an equation-based model. These advantages, however, are counterbalanced by the difficulty of analyzing and using ABMs, due to the lack of the type of mathematical tools available for more traditional models, which leaves simulation as the primary approach. As models become large, simulation becomes challenging. This paper proposes a novel approach to two mathematical aspects of ABMs, optimization and control, and it presents a few first steps outlining how one might carry out this approach. Rather than viewing the ABM as a model, it is to be viewed as a surrogate for the actual system. For a given optimization or control problem (which may change over time), the surrogate system is modeled instead, using data from the ABM and a modeling framework for which ready-made mathematical tools exist, such as differential equations, or for which control strategies can explored more easily. Once the optimization problem is solved for the model of the surrogate, it is then lifted to the surrogate and tested. The final step is to lift the optimization solution from the surrogate system to the actual system. This program is illustrated with published work, using two relatively simple ABMs as a demonstration, Sugarscape and a consumer-resource ABM. Specific techniques discussed include dimension reduction and approximation of an ABM by difference equations as well systems of PDEs, related to certain specific control objectives. This demonstration illustrates the very challenging mathematical problems that need to be solved before this approach can be realistically applied to complex and large ABMs, current and future. The paper outlines a research program to address them.
... Most recently, the Amethyst Initiative (Amethyst Initiative, 2008 ), a coalition of more than 130 university presidents in the US, advocated for a reduction in the minimum legal drinking age (MLDA) to age 18, with advocates suggesting that such a policy change could reduce harms associated with illegal drug use among young adults by giving them legal access to alcohol. The evidence for such a claim, however, remains unclear (DeJong and Blanchette, 2014;Fitzpatrick et al. 2012;Nelson et al. 2010). Other policies related to alcohol such as changes in the minimum acceptable BAC to operate a vehicle, changes in tax, import, and export policy remain in flux both in the US and worldwide (Rehm and Greenfield, 2008). ...
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Alcohol and marijuana are among the most commonly used drugs by adolescents and young adults. The question of whether these two drugs are substitutes or complements has important implications for public policy and prevention strategies, especially as laws regarding the use of marijuana are rapidly changing. Data were drawn from fatally injured drivers aged 16 to 25 who died within 1 h of the crash in nine states with high rates of toxicology testing based from 1999 to 2011 on the Fatality Analysis Reporting System (N = 7,191). Drug tests were performed using chromatography and radioimmunoassay techniques based on blood and/or urine specimens. Relative risk regression and Joinpoint permutation analysis were used. Overall, 50.5% of the drivers studied tested positive for alcohol or marijuana. Univariable relative risk modeling revealed that reaching the minimum legal drinking age was associated with a 14% increased risk of alcohol use (RR = 1.14, 95% CI: 1.02 to 1.28), a 24% decreased risk of marijuana use (RR = 0.76, 95% CI: 0.53 to 1.10), and a 22% increased risk of alcohol plus marijuana use (RR=1.22, 95% CI: 0.90 to 1.66). Joinpoint permutation analysis indicated that the prevalence of alcohol use by age is best described by two slopes, with a change at age 21. There was limited evidence for a change at age 21 for marijuana use. These results suggest that among adolescents and young adults, increases in alcohol availability after reaching the MLDA have marginal effect on marijuana use.
... The present study builds on prior work on attitudes toward underage drinking, but it goes beyond that work in assessing whether underage college students agree that they should adhere to drinking laws-regardless of whether they support those laws or think that the laws are fair-and whether that agreement is related to important public health and legal outcomes (e.g., underage drinking, sexual assault, and physical assault). The issue of adherence is directly relevant to the goals of public policy in reducing negative consequences of underage drinking, and to a widespread view that underage drinking laws should be repealed as counterproductive with respect to reducing these consequences (Fitzpatrick et al., 2012). Underage drinking laws, and the motivation of underage drinkers to adhere to those laws, continue to be hotly debated and the subject of new legislation (e.g., a new law in Pennsylvania raises fines for underage drinking and a proposed law would allow municipalities that include a university or college to impose a fee for alcohol-related offenses to help finance local prevention programs). ...
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Background and aims: The drinking environment is a complex system consisting of a number of heterogeneous, evolving, and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. Methods: A complex systems paradigm, grounded in socioecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological, and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. Results: The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models, can further increase stakeholder buy-in, understanding, and policymaking. Conclusions: A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions.
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Recognition of the complexity of many public health problems has led to the search for analytic methods capable of capturing more fully than traditional study designs and statistical tests the underlying dynamic processes at work. Similarly, those with an interest in public health interventions have begun to see the limitations of standard methods in understanding the consequences of programs and policies designed to influence population-level health. While there are a number of system science methods with potential to further public health research, there are three methods most often applied: agent-based modeling, social network analysis, and system dynamics modeling. The first discussion reviews both theoretical and practical applications of these three methods in the literature, as each has strengths and weaknesses and is better suited to studying some aspects of complex dynamic phenomena than others. Such a discussion provides practical guidance for those who wish to use these system methods in their own research. Following this, there is a discussion of different perspectives on how these methods relate to traditional behavioral research methods, and how these perspectives affect understanding of and explanation of public health problems. Beginning with a detailed analysis of the three systems methods used in public health and following with a discussion of how different perspectives affect understanding of public health problems sets the stage for the development of a systems model of a complex public health problem. The final section applies these lessons by developing and testing a system dynamics model of type 2 diabetes in the area known as Health Service Region 11. The model framed the problem of diabetes in this region using assumptions implicit within selecting a system dynamics model. The focus was on the effectiveness of physical activity interventions to guide decision-makers in future resource allocation and public health professionals to use appropriate methodologies for complex health problems that traditional linear approaches are unable to capture and thus unable to suggest informed routes for change. The model evaluated different “what if” scenarios of prevention and intervention strategies for reducing prevalence of (and ultimately incidence of) type 2 diabetes. http://hdl.handle.net/1969.1/156292
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The application of systems method to the understanding of public health problems (e.g., alcohol and drug abuse, chronic disease, obesity, tobacco use, and violence) has grown considerably in the past decade. System methods are seen by many of their advocates within public health as complimenting traditional behavioral and epidemiological research methods, while others see them as a fundamentally different way of understanding and explaining public health problems. Those who see the methods as complimentary often use empirical data from studies employing traditional methods and statistical analysis to validate the output of simulation models. As in other fields of applied research in which modeling has become popular, this tendency to equate a model's correspondence to data with the model corresponding to reality is especially pronounced when the goal of the modeling is to inform public policy. The present paper discusses the problems that arise when using data from an empirical study to assess the validity of a simulation model. It illustrates these problems through an examination of a specific example from the public health literature. The example demonstrates that, rather than empirical data being superior to the model, each is better considered as simply capturing a different aspect of a real-world system. Alternative means of assessing model usefulness are also discussed.
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Background: The application of social norms theory in the study of college drinking centers on the ideas that incorrect perceptions of drinking norms encourage problematic drinking behavior and that correcting misperceptions can mitigate problems. The design and execution of social norms interventions can be improved with a deeper understanding of causal mechanisms connecting misperception to drinking behavior. Methods: We develop an agent-based computational simulation that uses identity control theory and peer influence (PI) to model interactions that affect drinking. Using data from the College Alcohol Survey and Social Norms Marketing Research Project, we inform model parameters for agent drinking identities and perceptions. We simulate social norms campaigns that reach progressively larger fractions of the student population, and we consider the strength of the campaign in terms of changing student perception and resulting behavior. Results: We observe a general reduction in heavy episodic drinking (HED) as students are affected by the intervention. As campaigns reached larger fractions of students, the reduction rate diminishes, in some cases actually making a slight reverse. The way in which students "take the message to heart" can have a significant impact as well: The psychological factors involved in identity control and PI have both positive and negative effects on HED rates. With whom agents associate at drinking events also impacts drinking behavior and intervention effectiveness. Conclusions: Simulations suggest that reducing misperception can reduce HED. When agents adhere strongly to identity verification and when misperceptions affect identity appraisals, social norms campaigns can bring about large reductions. PI, self-monitoring, and socializing with like-drinking peers appear to moderate the effect.
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Objective: The goal of this article is to review critically the extant minimum legal drinking age (MLDA) research literature and summarize the current state of knowledge regarding the effectiveness of this policy. Method: Comprehensive searches of four databases were conducted to identify empirical studies of the MLDA published from 1960 to 1999. Three variables were coded for each study regarding methodological quality: (1) sampling design, (2) study design and (3) presence or absence of comparison group. Results: We identified 241 empirical analyses of the MLDA. Fifty-six percent of the analyses met our criteria for high methodological quality. Of the 33 higher quality studies of MLDA and alcohol consumption, 11 (33%) found an inverse relationship; only 1 found the opposite. Similarly, of the 79 higher quality analyses of MLDA and traffic crashes, 46 (58%) found a higher MLDA related to decreased traffic crashes; none found the opposite. Eight of the 23 analyses of other problems found a higher MLDA associated with reduced problems; none found the opposite. Only 6 of the 64 college-specific studies (9%) were of high quality; none found a significant relationship between the MLDA and outcome measures. Conclusions: The preponderance of evidence indicates there is an inverse relationship between the MLDA and two outcome measures: alcohol consumption and traffic crashes. The quality of the studies of specific populations such as college students is poor, preventing any conclusions that the effects of MLDA might differ for such special populations.
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This article represents the proceedings of a symposium at the 2000 RSA Meeting in Denver, Colorado. John Schulenberg and Jennifer L. Maggs were Organizers. Stephen W. Long was Chair and provided opening remarks. The presentations were: (1) I'm not a drunk, just a college student: Binge drinking during college as a developmental disturbance, by John Schulenberg; (2) Course of alcohol use disorders during college, by Kenneth J. Sher; (3) How do students experience alcohol and its effects? Positive versus negative expectancies and consequences, by Jennifer L. Maggs; and (4) Brief intervention in the context of developmental trends in college drinking, by G. Alan Marlatt. Critique and commentary were provided by Robert A. Zucker.
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The misuse and abuse of alcohol among college students remain persistent problems. Using a systems approach to understand the dynamics of student drinking behavior and thus forecasting the impact of campus policy to address the problem represents a novel approach. Toward this end, the successful development of a predictive mathematical model of college drinking would represent a significant advance for prevention efforts. A deterministic, compartmental model of college drinking was developed, incorporating three processes: (1) individual factors, (2) social interactions, and (3) social norms. The model quantifies these processes in terms of the movement of students between drinking compartments characterized by five styles of college drinking: abstainers, light drinkers, moderate drinkers, problem drinkers, and heavy episodic drinkers. Predictions from the model were first compared with actual campus-level data and then used to predict the effects of several simulated interventions to address heavy episodic drinking. First, the model provides a reasonable fit of actual drinking styles of students attending Social Norms Marketing Research Project campuses varying by "wetness" and by drinking styles of matriculating students. Second, the model predicts that a combination of simulated interventions targeting heavy episodic drinkers at a moderately "dry" campus would extinguish heavy episodic drinkers, replacing them with light and moderate drinkers. Instituting the same combination of simulated interventions at a moderately "wet" campus would result in only a moderate reduction in heavy episodic drinkers (i.e., 50% to 35%). A simple, five-state compartmental model adequately predicted the actual drinking patterns of students from a variety of campuses surveyed in the Social Norms Marketing Research Project study. The model predicted the impact on drinking patterns of several simulated interventions to address heavy episodic drinking on various types of campuses.
Conference Paper
Animal House is the name of a 1978 movie celebrating the excesses of binge drinking by college students. The Amethyst Initiative is an effort by college presidents to prevent binge drinking on their campuses by lowering the legal alcohol purchase age to 18 combined with education-based policies that encourage adoption of the Mediterranean drinking style, a pattern of alcohol use characterized by moderate consumption of alcoholic beverages like wine, mostly during meals. This presentation reviews epidemiological data and policy research relevant to the emergence of binge drinking cultures in countries where the Mediterranean drinking style was once considered dominant. The public health implications of the European countries' diverse drinking cultures and lower legal drinking age limits are discussed in the context of binge drinking by American youth. Population surveys of adolescent drinking trends in the US, Canada and the European countries suggest that youthful binge drinking is as prevalent in the Mediterranean countries as in the US, and much more prevalent in countries with a lower alcohol purchase age. A natural experiment derived from alcohol policy changes in the United Kingdom indicates that excessive drinking rather than moderation results from relaxed controls on alcohol availability. An international review of scientific support for 32 alcohol policy options shows that controls on alcohol availability, such as the minimum legal drinking age, are among the most effective youth prevention policies, whereas institution-based alcohol education programs are rated least effective. Implications for the Amethyst Initiative are discussed.
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While college attendance has been shown to be associated with increased drinking behaviors, there are no studies to our knowledge that have examined whether college attendance moderates genetic influences for drinking. We first tested for changes in alcohol consumption in adolescents who did and did not subsequently attend college, and then tested for variation of the genetic and environmental determinants of drinking in these 2 groups. Participants eligible for this study were selected from 2 samples from the National Longitudinal Study of Adolescent Health (Add Health), a national probability sample (n=7,083) and a sample of sibling pairs (n=855 pairs). Participants were assessed for measures of drinking behaviors as adolescents (wave I) and reinterviewed at 1 (wave II) and 6 years (wave III) following the initial survey. Changes in binge drinking and average quantity of alcohol consumed in the past year were estimated among 4 groups (2-year college students, 4-year college students, college withdrawers, noncollege participants) in sequential cohorts which spanned the ages of 13 to 24 across the 3 Add Health waves. Gene by environment interactions were then tested at wave III using biometrical models in the genetically informative pairs. Participants who did not attend college reported more binge drinking and consumed greater quantities of alcohol as adolescents than participants who subsequently attended college. However, the college students not only surpassed their noncollege peers in alcohol use as young adults, but also exhibited a greater genetic influence on quantity of alcohol consumed per drinking episode. Exposure to a college environment acts as an environmental moderator, supporting the hypothesis that the magnitude of genetic influence on certain aspects of alcohol consumption is greater in environments where drinking behaviors are more likely to be promoted.
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Recently we developed a model composed of five impulsive differential equations that describes the changes in drinking patterns (that persist at epidemic level) amongst college students. Many of the model parameters cannot be measured directly from data; thus, an inverse problem approach, which chooses the set of parameters that results in the "best" model to data fit, is crucial for using this model as a predictive tool. The purpose of this paper is to present the procedure and results of an unconventional approach to parameter estimation that we developed after more common approaches were unsuccessful for our specific problem. The results show that our model provides a good fit to survey data for 32 campuses. Using these parameter estimates, we examined the effect of two hypothetical intervention policies: 1) reducing environmental wetness, and 2) penalizing students who are caught drinking. The results suggest that reducing campus wetness may be a very effective way of reducing heavy episodic (binge) drinking on a college campus, while a policy that penalizes students who drink is not nearly as effective.
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A 14-site randomized trial tested the effectiveness of social norms marketing (SNM) campaigns, which present accurate student survey data in order to correct misperceptions of subjective drinking norms and thereby drive down alcohol use. Cross-sectional student surveys were conducted by mail at baseline and at posttest 3 years later. Hierarchical linear modeling was applied to examine multiple drinking outcomes, taking into account the nonindependence of students grouped in the same college. Controlling for other predictors, having a SNM campaign was not significantly associated with lower perceptions of student drinking levels or lower self-reported alcohol consumption. This study failed to replicate a previous multisite randomized trial of SNM campaigns, which showed that students attending institutions with a SNM campaign had a lower relative risk of alcohol consumption than students attending control group institutions (W. DeJong et al. J Stud Alcohol. 2006;67:868-879). Additional research is needed to explore whether SNM campaigns are less effective in campus communities with relatively high alcohol retail outlet density.