Sequencing and Prediction of Adolescent Soft Drug Initiation:

Systematic Review, Quantitative Investigation, and Dual Cross-Validation

Rebecca J. Howell

DISSERTATION.COM

Boca Raton

Sequencing and Prediction of Adolescent Soft Drug Initiation:

Systematic Review, Quantitative Investigation, and Dual Cross-Validation

Copyright © 2008 Rebecca J. Howell All rights reserved. No part of this book may be reproduced or transmitted in any form or by any

means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without written permission from the publisher.

Dissertation.com

Boca Raton, Florida USA • 2010

ISBN-10: 1-59942-332-4

ISBN-13: 978-1-59942-332-6

iv

Title: Sequencing and Prediction of Adolescent Soft Drug Initiation: Systematic Review, Quantitative Investigation, and Dual Cross-Validation

Author: Rebecca J. Howell Dissertation Chair: Dr. David L. Myers Dissertation Committee Members: Dr. Dennis M. Giever Dr. Jamie Martin Dr. Jennifer Roberts

In providing a comprehensive investigation of alcohol, cigarette, and

marijuana initiation among adolescents, the overarching goals of the research

were to build upon extant findings, address important gaps found in the literature,

and contribute to the prevention science knowledge base. A four-fold purpose

founded the study: 1) provide a systematic review of the soft drug initiation

literature; 2) test a modified version of Kandel’s (2002) drug sequencing

hypothesis; 3) determine if predictors of soft drug initiation differ in kind or

saliency by biological age and drug type; and 4) examine age- and drug- specific

determinants of the timing at which soft drug initiation occurs. Supplemental

attention also was directed at evaluating the utility of Petraitis et al.’s (1995)

distal-proximal mediation hypothesis.

Through the quantitative component of the research, nine hypotheses

were tested. Cross-sectional data were derived from a rural sample of 6th, 9th,

and 12th grade students who completed the 2004 Primary Prevention Awareness,

Attitude, and Use Survey (PPAAUS). All of the hypotheses obtained some

degree of support; more support was yielded for the specific risk factor

hypothesis than the common factor model, and convincing evidence was

v

obtained for Kandel’s drug sequencing hypothesis and Petraitis et al.’s distal-

proximal mediation hypothesis.

The findings also supported the bulk of the directional hypotheses and

several of the direct and indirect effects propositions put forth in social learning

theory, the social development model, and the theory of planned behavior. In

contrast, the results called into question some of the direct effects articulated in

Hirschi’s original statement of social control and underscored some possible

limits of the social development model.

In an effort to gauge the validity of the findings, a dual cross-validation

scheme was employed. The systematic review cross-validation involved

comparing the quantitative findings for two major hypotheses to those yielded

from 36 primary studies examined in the systematic review. Through a further

quantitative cross-validation, the findings for the major and supplemental

hypotheses were compared to those derived from a sample of 6th, 9th and 12th

grade students who completed the 2001 PPAAUS. On balance, a relatively

strong degree of convergence was obtained. This confluence served to bolster

the reliability and validity of the results. Policy and programmatic implications

also were indicated.

vi

ACKNOWLEDGMENTS

First, and foremost, I want to thank and give credit to God for all of my

accomplishments, academic or otherwise. Ultimately, it’s due to His strength,

love, and care that I’m able to see my doctoral work to completion.

I’d also like to acknowledge my best friend, lifeline, and husband, David,

for supporting my goals and passion. Thank you for reminding me to “stop and

smell the roses.” Your selflessness and loyalty do not go unnoticed.

Much of the research I’ve had the opportunity to be involved with,

including the PPAAUS, is the direct result of Dave Myers’ generosity and

instrumental guidance. Dave, I’m extremely grateful for your mentorship, the

research opportunities that you provided, and the wisdom you departed along the

way. Not only were you the best dissertation chair one could wish for, but you

continue to be an inspirational role model. I have yet to meet an academic as

grounded, patient, and laid-back, yet professional and hard-core.

The suggestions and points of clarity that my committee members, Jamie,

Jen, and Dennis, provided were both instructive and helpful in solidifying this

research. Thank you all for your time, effort, and constructive feedback

throughout the process.

Michelle Corcoran and Joyce Kensey from the IUP library were invaluable

throughout the literature collection stages of this study. I appreciate your

diligence in processing my ILL requests in a more than timely manner.

Finally, to the IUP criminology faculty-- thank you for the thorough training.

I enjoyed the experience, learned a ton, and hope to “pay it forward.”

vii

For Lucas, Mazzy, Katie, and all other like children.

viii

TABLE OF CONTENTS Chapter Page 1 INTRODUCTION ................................................................................ 1 A Cultural Mainstay ............................................................................ 2 A Social and Public Health Problem ................................................... 6 Utility of Prevention and Research ................................................... 17 Purpose of the Research ................................................................. 24 2 TRADITIONAL ETIOLOGY .............................................................. 30 Social Control Theory ....................................................................... 31 Differential Association Theory ......................................................... 42 Social Learning Theory .................................................................... 44 Conclusion ....................................................................................... 60 3 DEVELOPMENTAL ETIOLOGY ...................................................... 69 The Developmental Approach .......................................................... 70 Stage Theory ................................................................................... 75 Social Development Model .............................................................. 97 Conclusion ..................................................................................... 126 4 SEQUENCING AND PREDICTION RESEARCH ........................... 131 Sequencing Research .................................................................... 131 Prediction Research ....................................................................... 158 Conclusion ..................................................................................... 186 5 SYSTEMATIC REVIEW METHODS .............................................. 192 Nature of Comprehensive Literature Reviews ................................ 193 Quality and Focus of Extant Reviews ............................................. 199 Systematic Review Methodology ................................................... 209 Systematic Review Analysis Plan .................................................. 220 Systematic Review Cross-Validation .............................................. 225 Conclusion ..................................................................................... 239 6 QUANTITATIVE METHODS .......................................................... 241 Secondary Data Source and Sample Attributes ............................. 241 Research Questions and Hypotheses ............................................ 248 Dependent Variables ...................................................................... 261 Independent and Control Variables ................................................ 263

ix

Chapter Page Analytic Techniques ....................................................................... 272 Model Development and Logistics ................................................. 293 Quantitative Cross-Validation ......................................................... 303 7 SYSTEMATIC REVIEW RESULTS ................................................ 322 Summary Description of the Primary Studies ................................. 323 Soft Drug Initiation .......................................................................... 331 Time to Soft Drug Initiation ............................................................. 373 Overview of Key Findings and Attendant Gaps .............................. 378 8 UNIVARIATE AND BIVARIATE RESULTS .................................... 396 Sample Descriptives ...................................................................... 396 Bivariate Correlations ..................................................................... 403 Research Question #1 ................................................................... 423 Conclusion ..................................................................................... 434 9 MULTIVARIATE RESULTS............................................................ 435 Research Question #2 ................................................................... 435 Research Question #3 ................................................................... 461 Drug- and Age-Specific Predictors ................................................. 513 Hypotheses Results ....................................................................... 528 Conclusion ..................................................................................... 548 10 DUAL CROSS-VALIDATION RESULTS ........................................ 550 Systematic Review Cross-Validation .............................................. 550 Quantitative Cross-Validation ......................................................... 570 Validity of the 2004 PPAAUS Results ............................................ 592 Conclusion ..................................................................................... 623 11 DISCUSSION AND CONCLUSIONS ............................................. 626 General Contributions of the Research .......................................... 628 Theoretical and Empirical Implications ........................................... 634 Policy and Programmatic Implications ........................................... 669 Study Limits.................................................................................... 678 Recommendations for Further Research ....................................... 682 Conclusion ..................................................................................... 691 REFERENCES ............................................................................................ 693

x

Chapter Page APPENDICES ............................................................................................. 784 A: 2004 PPAAUS Instrument ................................................................. 784 B: 2004 PPAAUS Administration Instructions and Teacher Script ......... 785 C: Independent and Control Variables: Coding Schemes ...................... 786 D: Detailed Account of Guttman Scale Development ............................. 795 E: 2001 PPAAUS Instrument ................................................................. 801 F: Primary Studies for Systematic Review ............................................. 802 G: 2001 PPAAUS Univariate, Bivariate, and Multivariate Results .......... 838

xi

LIST OF TABLES

Table Page

1 Prominent Integrated Developmental Theories of Adolescent Drug Use ............................................................................................. 71 2 Empirical Tests of Kandel’s Drug Sequencing Hypothesis ............... 133 3 Historical Time Periods in which Drug Sequencing

Data were Drawn .............................................................................. 138 4 Empirical Support using Guttman Scaling: Coefficients

of Reproducibility and Scalability ...................................................... 144

5 Community Domain Risk Factors and Empirical Support ................. 159

6 School Domain Risk Factors and Empirical Support ........................ 161

7 Family Domain Risk Factors and Empirical Support ......................... 162

8 Peer Domain Risk Factors and Empirical Support ............................ 165

9 Individual Domain Risk Factors and Empirical Support .................... 166

10 Major Calls for Future Research ....................................................... 174

11 Drawbacks of Extant Comprehensive Literature Reviews ................ 201

12 Inclusion Criteria for Systematic Review ........................................... 211

13 Electronic Databases and Organization/Agency Internet Websites Searched ........................................................................... 218

14 Prediction Models Eligible for Systematic Review, by Drug Type .................................................................................... 219 15 Primary Studies for Systematic Review ............................................ 219

16 Major Study Characteristics with Examples ...................................... 221

17 Ecological Domains and Related Predictor Categories .................... 223

18 Overview of Research Questions, Attendant Hypotheses, and Analytic Techniques .................................................................. 249

xii

Table Page 19 Prediction Analyses: Community Domain Predictors, Theoretical/Empirical Grounding ....................................................... 264 20 Prediction Analyses: School Domain Predictors, Theoretical/Empirical Grounding ....................................................... 266

21 Prediction Analyses: Family Domain Predictors, Theoretical/Empirical Grounding ....................................................... 267

22 Prediction Analyses: Peer Domain Predictors, Theoretical/Empirical Grounding ....................................................... 268 23 Prediction Analyses: Individual Domain Predictors, Theoretical/Empirical Grounding ....................................................... 269 24 Prediction Analyses: Control Variables and

Theoretical Constructs ...................................................................... 271

25 Example of Guttman Response Matrix that Incorporates Age of Initiation ................................................................................. 279 26 Example of Error-Counting for Supplemental Analysis ..................... 281 27 Primary Studies, Basic Descriptives ................................................. 323 28 Community Domain Predictors of Soft Drug Initiation: Directional Relationships by Period of Adolescent Development ...... 332 29 School Domain Predictors of Soft Drug Initiation: Directional Relationships by Period of Adolescent Development ...... 337 30 Family Domain Predictors of Soft Drug Initiation: Directional Relationships by Period of Adolescent Development ...... 341 31 Peer Domain Predictors of Soft Drug Initiation: Directional Relationships by Period of Adolescent Development ...... 353 32 Individual Domain Predictors of Soft Drug Initiation:

Directional Relationships by Period of Adolescent Development ...... 361 33 Family Domain Predictors of Time to Soft Drug Initiation: Directional Relationships, Early-Late Adolescence ........................... 375

xiii

Table Page 34 Peer Domain Predictors of Time to Soft Drug Initiation: Directional Relationships, Early-Late Adolescence ........................... 376

35 Individual Domain Predictors of Time to Soft Drug Initiation: Directional Relationships, Early-Late Adolescence ........................... 377

36 Primary Studies: Select Design, Domain, and

Predictor Descriptives by Outcome and Sample Population ............. 380 37 Soft Drug Initiation: Most and Least Researched Stages of Adolescent Development by Ecological Domain............... 383

38 Dependent Measures: Descriptives for Total Sample ....................... 397 39 Dichotomous Predictors/Controls: Percentage

Frequencies (N = 753) .......................................................................398

40 Ordinal/Continuous Predictors and Controls: Descriptives (N = 753) ...................................................................... 399

41 Dichotomous Initiation: Bivariate Correlations .................................. 405

42 Age of Initiation: Bivariate Correlations ............................................. 414

43 Predictors and Controls: Bivariate Correlations ± .400

or Greater (N = 753) ......................................................................... 419

44 Temporal Ordering in Soft Drug Sequences ..................................... 425

45 Dichotomous Initiation and Time to Initiation Models (Total Sample): Predictor Listing ....................................................... 436

46 Model #1: Predictors of Alcohol Initiation, Total Sample ................... 439

47 Model #2: Predictors of Cigarette Initiation, Total Sample ................ 441

48 Model #3: Predictors of Marijuana Initiation, Total Sample ............... 443 49 Model #4: Predictors of Time to Alcohol Initiation, Total Sample ...... 451

50 Model #5: Predictors of Time to Cigarette Initiation, Total Sample ... 452

51 Model #6: Predictors of Time to Marijuana Initiation, Total Sample .. 454

xiv

Table Page

52 Dependent Measures: Descriptives for Age-Graded Subsamples .... 464 53 Model #7: Predictors of Alcohol Initiation among

6th Grade Students ............................................................................ 466 54 Model #8: Predictors of Alcohol Initiation among

9th Grade Students ............................................................................ 468 55 Model #9: Predictors of Alcohol Initiation among

12th Grade Students .......................................................................... 470 56 Model #10: Predictors of Cigarette Initiation among

6th Grade Students ............................................................................ 474 57 Model #11: Predictors of Cigarette Initiation among

9th Grade Students ............................................................................ 475 58 Model #12: Predictors of Cigarette Initiation among

12th Grade Students .......................................................................... 477 59 Model #13: Predictors of Marijuana Initiation among

9th Grade Students ............................................................................ 482 60 Model #14: Predictors of Marijuana Initiation among

12th Grade Students .......................................................................... 484 61 Model #15: Predictors of Time to Alcohol Initiation among

6th Grade Students ............................................................................ 489 62 Model #16: Predictors of Time to Alcohol Initiation among

9th Grade Students ............................................................................ 491 63 Model #17: Predictors of Time to Alcohol Initiation among

12th Grade Students .......................................................................... 493 64 Model #18: Predictors of Time to Cigarette Initiation among

6th Grade Students ............................................................................ 498 65 Model #19: Predictors of Time to Cigarette Initiation among

9th Grade Students ............................................................................ 500 66 Model #20: Predictors of Time to Cigarette Initiation among

12th Grade Students .......................................................................... 501

xv

Table Page 67 Model #21: Predictors of Time to Marijuana Initiation among

9th Grade Students ............................................................................ 507 68 Model #22: Predictors of Time to Marijuana Initiation among

12th Grade Students .......................................................................... 509 69 Total Sample and Age-Graded Results: Drug and Age-Specific

Predictors (p <.05 or lower)............................................................... 516 70 Total Sample and Age-Graded Findings: Possible

Age X Factor Interaction Effects ....................................................... 527

71 Hypothesis 7 Findings, 2004 PPAAUS: Percentage Decrease in Final Model R2/ 2 Attributed to the Community Domain ................ 539

72 Hypothesis 8 Findings, 2004 PPAAUS: Direct Effect of Parental Pro-Drug Norms on Respective Outcomes ........................ 542

73 Hypothesis 9 Findings, 2004 PPAAUS: Direct Effects of Peer Soft Drug Use and Pro-Drug Norms on Respective Outcomes ........ 544

74 Proportion of Extraneous Effects as Indirect, 2004 PPAAUS: Total Sample and Age-Graded Models ............................................. 547

75 Systematic Review Cross-Validation Findings: H2 Results for Soft Drug Initiation among the Total Sample .................................... 553

76 Systematic Review Cross-Validation Findings: H2 Results for Soft Drug Initiation among Early, Mid-, and Late Adolescents .......... 555

77 Systematic Review Cross-Validation Findings: H2 Results for Time to Soft Drug Initiation among the Total Sample ....................... 562

78 Systematic Review Cross-Validation Findings: H3 Results for

Soft Drug Initiation among the Total Sample .................................... 564 79 Systematic Review Cross-Validation Findings: H3 Results for

Soft Drug Initiation among Early, Mid-, and Late Adolescents .......... 567 80 Differential Model Fit: 2004 and 2001 PPAAUS ................................ 573 81 2004 and 2001 PPAAUS: H2 Counter Findings ................................ 577

82 2004 and 2001 PPAAUS: H3 Counter Findings ................................ 578

xvi

Table Page 83 Hypothesis 7 Findings, 2001 PPAAUS: Percentage Decrease

in Final Model R2/ 2 Attributed to the Community Domain ................ 585 84 Hypothesis 9 Findings, 2001 PPAAUS: Direct Effects of Peer

Soft Drug Use and Pro-Drug Norms on Respective Outcomes ........ 588 85 Proportion of Extraneous Effects as Indirect, 2001 PPAAUS:

Total Sample and Age-Graded Models ............................................. 590

86 Triangulation of the H2 and H3 Counter Findings from the Systematic Review Cross-Validation ................................................ 595

87 Possible Explanations for Conflicting Findings: Major Differences

between the 2004 PPAAUS and Relevant Primary Studies.............. 596 88 Major Research Gaps Identified through the Systematic Review ..... 688

xvii

LIST OF APPENDICED TABLES

Appendix/Table Page

C1 Block #1: Community Domain Predictors.......................................... 786 C2 Block #2: School Domain Predictors ................................................. 787 C3 Block #3: Family Domain Predictors ................................................. 789 C4 Block #4: Peer Domain Predictors .................................................... 790 C5 Block #5: Individual Domain Predictors............................................. 791 C6 Block #6: Control Variables ............................................................... 794

G1 2001 PPAAUS, Dependent Measures: Descriptives for Total Sample ..................................................................................... 838 G2 2001 PPAAUS, Dependent Measures: Descriptives for Age-Graded Subsamples .................................................................. 838 G3 2001 PPAAUS, Dichotomous Predictors/Controls: Percentage Frequencies (N = 723) ...................................................................... 839

G4 2001 PPAAUS, Ordinal/Continuous Predictors and Controls: Descriptives (N = 723) ...................................................................... 841

G5 2001 PPAAUS, Bivariate Correlations, Dichotomous Initiation ......... 843

G6 2001 PPAAUS, Bivariate Correlations, Age of Initiation.................... 845

G7 2001 PPAAUS, Predictors and Control Variables: Bivariate Correlations ± .400 (N = 723) ............................................................ 847 G8 2001 PPAAUS, Predictors of Alcohol Initiation, Total Sample .......... 850

G9 2001 PPAAUS, Predictors of Cigarette Initiation, Total Sample ....... 852 G10 2001 PPAAUS, Predictors of Marijuana Initiation, Total Sample ...... 854 G11 2001 PPAAUS, Predictors of Time to Alcohol Initiation, Total Sample ..................................................................................... 856 G12 2001 PPAAUS, Predictors of Time to Cigarette Initiation, Total Sample ..................................................................................... 858

xviii

Appendix/Table Page

G13 2001 PPAAUS, Predictors of Time to Marijuana Initiation, Total Sample ..................................................................................... 860 G14 2001 PPAAUS, Predictors of Alcohol Initiation among 6th Grade Students ............................................................................ 863

G15 2001 PPAAUS, Predictors of Alcohol Initiation among 9th Grade Students ............................................................................ 864

G16 2001 PPAAUS, Predictors of Alcohol Initiation among 12th Grade Students .......................................................................... 866

G17 2001 PPAAUS, Predictors of Cigarette Initiation among 6th Grade Students ............................................................................ 867

G18 2001 PPAAUS, Predictors of Cigarette Initiation among 9th Grade Students ............................................................................ 868

G19 2001 PPAAUS, Predictors of Cigarette Initiation among 12th Grade Students .......................................................................... 870

G20 2001 PPAAUS, Predictors of Marijuana Initiation among 9th Grade Students ............................................................................ 871 G21 2001 PPAAUS, Predictors of Marijuana Initiation among 12th Grade Students .......................................................................... 873

G22 2001 PPAAUS, Predictors of Time to Alcohol Initiation among 6th Grade Students ............................................................................ 875

G23 2001 PPAAUS, Predictors of Time to Alcohol Initiation among 9th Grade Students ............................................................................ 876

G24 2001 PPAAUS, Predictors of Time to Alcohol Initiation among 12th Grade Students .......................................................................... 877

G25 2001 PPAAUS, Predictors of Time to Cigarette Initiation among 6th Grade Students ............................................................................ 879

G26 2001 PPAAUS, Predictors of Time to Cigarette Initiation among 9th Grade Students ............................................................................ 880 G27 2001 PPAAUS, Predictors of Time to Cigarette Initiation among 12th Grade Students .......................................................................... 882

xix

Appendix/Table Page

G28 2001 PPAAUS, Predictors of Time to Marijuana Initiation among 9th Grade Students ............................................................................ 883 G29 2001 PPAAUS, Predictors of Time to Marijuana Initiation among 12th Grade Students .......................................................................... 884

xx

LIST OF FIGURES

Figure Page

1 Hobbes gives Calvin some sound advice, by Bill Watterman, 1994.

© 1990 Universal Press Syndicate. Reprint permission granted

through education provision ................................................................ 20

2 This transition diagram depicts H1, the most common soft drug

initiation sequence found in the data (n = 713) ................................. 427

3 This transition diagram depicts cigarettes>alcohol>marijuana, the

second most common soft drug initiation sequence (n = 713) .......... 429

1

CHAPTER 1

INTRODUCTION

In the grocery store, a 5-year-old boy selected wine and asked, “Is this alcohol?” The researcher replied, “Yes,” and the boy said, “I want it, and I want some smokes.”

At the check-out counter, a 3-year-old girl identified the cigarettes she was buying. Camels: “Animal ones for Daddy.” Marlboros: “Mommy smokes these.”

(Dalton et al., 2005)

Quite perceptive, some children as young as age 3 already have begun to

develop an awareness of (and cognitive expectation for) alcohol and cigarette

use. In a recent adult role-playing study (Dalton et al., 2005), substantial

percentages of preschoolers (2 to 6 years of age) purchased cigarettes (29%)

and alcohol (62%) at a toy grocery store in preparation for a make-believe

evening with friends. Disconcerting are the findings that about half of these

children correctly identified alcohol (58%) and cigarettes (50%) by brand name,

with some children more adept at identifying the names of these products than

the names of those that are more age-appropriate, such as snacks and cereal.

Dalton et al.’s (2005) findings not only speak to the ability that young children

have for internalizing and emulating general social cues to which they have been

exposed; these researchers also found that compared to children whose parents

self-reported cigarette and alcohol abstinence, children whose parents drank on

a monthly basis or smoked were 3 and 4 times more likely, respectively, to

purchase alcohol and cigarette products.

Given the multiple cultural forces (e.g., media, pharmaceutical

corporations, and the alcohol, tobacco, and music industries) that glamorize,

celebrate, and encourage drug use, along with the prevalence of soft drug use

2

among adults and the emerging finding that parents constitute the #1 source of

alcohol for a considerable number of adolescents (American Medical Association

[AMA], 2005), it is not surprising that young children are developing a keen

awareness of the central role that these drugs play in the lives of many parents

and adults (see, e.g., Cieply, 2007; Dombrink, 1993; Grube, 2004; Jurgensen,

2007; Strasburger, 1995; Wakefield, Flay, Nichter, & Giovino, 2003; Watson,

2005). Although troubling, it also is hardly a surprise that national and statewide

epidemiologic drug surveys conducted over the past 15 years suggest as many

as 10% of typical 4th graders in the U.S. already have initiated alcohol use

(Donovan, 2007). In an effort to understand why cognitive expectations

concerning soft drug use may develop in American children by 5 years of age, it

is important to place the issue of soft drug use within a historical context.

A Cultural Mainstay

To begin, as the oldest known psychoactive drug in the U.S. and the

world, alcohol has been firmly embedded in American culture since its first

migration aboard Puritan ships (Inaba & Cohen, 2004). Today, alcohol remains a

focal point of American life, from its incorporation into holiday traditions and

religious ceremonies, to social gatherings, weekday happy hours, and weekend

parties.

The current legal drinking age in the U.S., 21 years, is the highest of any

country in the world (Babor et al., 2003). The prohibition of alcohol to minors first

began in the mid 1800s with the enactment of various state laws. The push for

establishing these laws originated from various puritanical temperance groups in

3

the early 1800s, whose interest was to restrict both adult and youth access to

alcohol (Alcohol and Tobacco Tax and Trade Bureau, 2006). Major subsequent

curtailments of legal access to alcohol included the enactment of the 1920

National Prohibition Act and the passage of the 18th Amendment to the U.S.

Constitution. After state ratification, the federal government repealed Prohibition

in 1933 with the passage of the 21st Amendment. Although the federal ban

against the manufacturing, transportation, and sale of alcohol was lifted,

prohibition laws remained intact in many states. States without these laws

allowed for the sale of alcohol to adults, while restricting the sale of alcohol to

anyone under the age of 21 years.

After the 26th Amendment was enacted in 1971, and those between the

ages of 18 and 21 years were afforded the right to vote, states began lowering

minimum drinking ages from 21 years to 20, 19, and 18 years (Inaba & Cohen,

2004). Influenced by federal coercion, states then reversed their legal drinking

ages in the 1980s, increasing them back to 21 years (Humfleet, Munoz, Sees,

Reus, & Hall, 1999). Decisions to increase the legal drinking age were founded

on concerns about the impact of alcohol consumption on youth psychosocial

development, along with the strong correlation found between lowered drinking

ages and motor vehicle accidents and fatalities (Cook & Tauchen, 1984).

In comparison to alcohol, tobacco use in the U.S. began as early as 1

B.C., when American Indians utilized tobacco leaves in religious rituals and

medicinal practice (Borio, 2005). Since 1847, when the first cigarette was sold in

the U.S. by a newly founded British company, Phillip Morris, cigarette production

4

and sales have evolved into one of the most profitable businesses ever

established in the U.S. (Randall, 2006).

First influenced by the 1964 U.S. Surgeon General’s report on the

negative health consequences of cigarette smoking, restrictions on cigarette

advertising and use have become increasingly stringent in modern times. Today,

all tobacco advertising on television and radio is banned; smoking is prohibited

on all commercial airline flights; many states restrict smoking in public

establishments; and tobacco companies also are mandated to inform the public

of the health dangers associated with smoking (Randall, 2006). Although there is

no federal law mandating that tobacco products only be sold to persons of a

specified minimum age, coercive encouragement by the federal government has

aided in the passage of legislation in all 50 states requiring the sale of tobacco

products only to persons over the age of 18 (Inaba & Cohen, 2004).

Finally, mankind has been using marijuana for at least 4,000 years

(Abadinsky, 2001). Not only has it been used for its euphoric properties and

ability to produce a “high,” but also for its medicinal properties in countries such

as China and India, and in areas of South America, the Middle East, and

southern Africa (Abadinsky, 2001). In the U.S., marijuana first was grown and

used as a source of fiber during Colonial Times. Over time, Americans began

utilizing it to treat various health conditions and illnesses, such as rheumatism

and labor pains during childbirth (Joy, Watson, & Benson, 1999).

The criminalization of marijuana has been a cornerstone of federal drug

policy, starting with the 1914 Harrison Narcotics Act (Gray, 2001). Through the

5

passage of the Controlled Substances Act (CSA), a subsidiary Act of the

Comprehensive Drug Abuse Prevention and Control Act (CDAPCA) of 1970,

marijuana was deemed a Schedule I substance (Drug Enforcement Agency

[DEA], 2006). In general, Schedule I drugs are viewed as having no medicinal

value and being dangerous in terms of the potential for abuse and dependence

(DEA, 2006).

In an effort to centralize federal drug enforcement under one agency, the

DEA was established in 1973 (Abadinsky, 2001). Since its inception, the DEA

has been responsible for the federal enforcement of drug laws and interdiction

efforts. The “war on drugs,” which initially began in the 1970s at the direction of

President Nixon, was employed in full force from the 1980s, under the Reagan

administration, through at least the early 1990s, under the Bush administration.

This “war on drugs” and the associated “zero tolerance” approach were geared

toward all illicit substances, including marijuana. During this time, mandatory

sentences for drug possession were re-introduced, and drug enforcement and

interdiction initiatives increased, as did arrests for drug offenses, including

marijuana possession (Abadinsky, 2001; Inaba & Cohen, 2004).

Although the “war on drugs” still continues in various capacities today,

increasing tolerance of marijuana use has led to amplified public support for its

legalization. Although its use remains a federal crime, 13 states have passed one

or more medical marijuana laws or have provided for exceptions to existing state

laws (Gray, 2001; Pacula, Chriqui, & King, 2004). Several cities also have