8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

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In1047298uences of behavior and academic problems at school entry on

marijuana use transitions during adolescence in an

African-American sample

Beth A Reboussin ab Nicholas S Ialongo c Kerry M Green d

a Department of Biostatistical Sciences Wake Forest School of Medicine Winston-Salem NC 27157 United Statesb Department of Social Sciences and Health Policy Wake Forest School of Medicine Winston-Salem NC 27157 United Statesc Department of Mental Health Johns Hopkins Bloomberg School of Public Health Baltimore MD 21205 United Statesd Department of Behavioral and Community Health University of Maryland School of Public Health College Park MD 20742 United States

H I G H L I G H T S

bull This study included data from 458 African Americans followed from 1st to 9th grade

bull Two problem behavior classes emerged externalizing and attentionconcentration

bull Academic problems co-occurred with both problem behavior subtypes

bull Externalizing problems were associated with increased risk of being offered marijuana

bull Attentionconcentration problems were associated with use given an opportunity to use

a b s t r a c ta r t i c l e i n f o

Available online 28 September 2014

Keywords

Academic dif 1047297culties

African-American

Behavior problems

Latent class analysis

Latent transition analysis

Marijuana

Background The aim of this study was to examine how patterns of academic and behavior problems in the 1047297rst

grade relate to longitudinal transitions in marijuana use from middle school through entry into high school

among African-AmericansMethods Latent class and latent transition analyses were conductedon a communitysampleof 458 low-income

urban-dwelling African-Americans

Results Two behavior problem classes emerged at school entry externalizing and attentionconcentration

Academic problems co-occurred with both problem behavior classes although more strongly with attention

concentration Youth in the attention concentration problem class were more likely to transition from no

marijuana involvement to use and problems beginning in the 7th grade and to use and problems given the op-

portunity to use marijuana early in high school compared to youth with no problems Youth in the externalizing

behavior problem class were signi1047297cantly more likely to transition from no involvement to having a marijuana

opportunity during the transition to high school compared to youth in the attentionconcentration problems

class

Conclusions These 1047297ndings highlight the importance of developing prevention programs and providing school

services that address the co-occurrence of academic and behavior problems as well as their subtype speci1047297c

risks for marijuana involvement particularly for low-income minority youth who may be entering school less

ready than their non-minority peers These 1047297ndings also provide evidence for a need to continue to deliver

interventions in middle school and high school focused on factors that may protect youth during these critical

transition periods when they may be especially vulnerable to opportunities to use marijuana based on theiracademic and behavioral risk pro1047297les

copy 2014 Elsevier Ltd All rights reserved

1 Introduction

Marijuana use now exceeds the rate of cigarette use among adoles-

cents rates of past 30 day cigarette smoking are49 108 and171 re-

spectively for 8th 10th and 12th graders compared to 65 170 and

229 for marijuana use ( Johnston OrsquoMalley Bachman amp Schulenberg

Addictive Behaviors 41 (2015) 51ndash57

Corresponding author at Departmentof Biostatistical Sciences Wake ForestSchool of

Medicine Winston-Salem NC 27157 United States Tel +1 336 713 5213 fax + 1 336

713 5308

E-mail address brebousswakehealthedu (BA Reboussin)

httpdxdoiorg101016jaddbeh201409030

0306-4603copy 2014 Elsevier Ltd All rights reserved

Contents lists available at ScienceDirect

Addictive Behaviors

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 27

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 37

Total Math and Total Reading normal curve equivalent scores for each

child in the 1047297rst grade to create a composite academic achievement

variable The average was then dichotomized to indicate those children

with the most achievement dif 1047297culties (ie bottom 25 on achieve-

ment) In addition to this standardized achievement measure we

included the teacher report of the childs overall progress in the fall of

the 1047297rst grade This item was rated on a 6-point scale (1 = excellent

to 6 = extremely poor) and dichotomized for analyses to indicate

those with poor to extremely poor progress versus those with good toexcellent progress

223 Marijuana involvement in 6th 7th 8th and 9th grades

We considered responses to1047297ve questions about marijuana involve-

ment gathered in the spring of the 6th 7th 8th and 9th grades Oppor-

tunity to usemarijuanainvolved askingwhether a youth hadldquoever been

offeredrdquo marijuana as described by Crum Lillie-Blanton and Anthony

(1996) Adolescent reports of marijuana use were based on asking

ldquoHave you ever used marijuanardquo Frequency of marijuana use was

measured based on questions from the Monitoring the Future survey

( Johnston OMalley amp Bachman 1995) and was de1047297ned as ever using

marijuana more than a couple of times ie on three or more occasions

This low threshold for frequent marijuana use was chosen to be

meaningful for this sample of young adolescents It also gave us the

opportunity to explore whether this level of use is problematic in

young adolescents For this reason we also looked at health and social

problems associated with marijuana use Health and social problems

were assessed by asking if they ever experienced any health problems

or social problems from using marijuana The speci1047297c problems

comprising these two questions are listed in Appendix A

224 Demographic information

The school district provided information on the students sex and

ethnicity School records indicating each students free or reduced-cost

meal status were collapsed into a dichotomous variable of free or

reduced lunch versus self-paid lunch as an indicator of students

socioeconomic status

23 Statistical analyses

A cross-sectional latent class analysis (LCA) was applied to examine

the structure underlying the 1047297ve indicators of academic and behavior

problems in the 1047297rst grade The basic premise of LCA is that within

classes behaviors are locally independent (Lazarsfeld 1950) The goal

is to identify the smallest number of classes that adequately describes

the association among the behaviors Information about the resultant

class structure is conveyed through two sets of parameters the

probability of having high levels of academic andor behavior problems

within a particular class (item probabilities) and the proportion of

youth in each class (class prevalences)

A longitudinal latent class model (or latent stage model) was then

applied to examine the structure underlying the 1047297ve items comprising

the marijuana involvement pro1047297le over time While in principle it ispossible to allow the item probabilities and hence latent structure to

vary over time forthe 6thto 9th grade marijuana indicators this implies

that the de1047297nition of marijuana involvement is changing which would

substantially complicate the interpretation of a longitudinal model

Therefore we constrained the item probabilities to be constant over

time ie the probability of reporting a behavior within a latent stage

was thesame in each grade This is analogous to constraining the factor

loadings to be equal over time in a longitudinal factor analysis model

(sometimes referred to as factor invariance) The latent stage preva-

lences however were allowed to vary over time ie the proportion of

youth in each stage could change over time

Our model building strategy for the two sets of latent class models

involved starting with the most parsimonious one-class (or one-stage)

model and 1047297tting successive models with an increasing number of

latent classes (or stages) in order to determine the most parsimonious

model that provided an adequate 1047297t to the data The goodness-of-1047297t of

various models was evaluated using the Akaikes Information Criteria

(AIC) a global 1047297t index that combines goodness-of-1047297t and parsimony

Because we were concerned that the statistical power in this study

may be limited by the sample size we chose to rely on the AIC over

other global 1047297t indices as it is known to favor more complex models

(Lin amp Dayton 1997) Entropy was calculated to provide an indication

of the overall degree of classi1047297

cation uncertainty in the solution(Celeuxamp Soromenho 1996) Lower valuesof AIC are preferable where-

as higher values (or values closer to 1) are better for entropy For latent

class models there are considerations other than global goodness-of-1047297t

indices In particular an examination of thevalidityof thelocal indepen-

dence assumption which is the hallmark of LCA is critical We used a

modi1047297ed version of Garrett and Zegers (2000) Log-Odds Ratio Check

This method involves calculating thelog-oddsratio in both theobserved

and expected two-way tables for pairs of behaviors The observed data

log-odds ratio is then expressed as a z-score relative to the expected

data log-odds ratio The z-value is then used as a guide to detect items

that are locally dependent A threshold of plusmn15 was conservatively

chosen as suggestive of local dependence

Next we estimated the probability of transitioning between the

latent stages of marijuana involvement from the 6th through the 9th

grade and the in1047298uence of academic and behavior problem subtypes

on transition rates using latent transition analysis (LTA) LTA is an

extension of latent class analysis to the longitudinal framework which

expresses change over time in terms of transition probabilities and

models the impact of covariates on transitions using a multinomial

logistic regression formulation It has been used extensively to estimate

stage-sequential models of drug use over time (eg Chung Kim

Hipwell amp Stepp 2013 La Flair et al 2013 Lanza amp Bray 2010 Lee

Chassin amp Villalta 2013) We controlled for student-level covariates of

gender free or reduced cost lunch status and intervention status in

the LTA model A robust estimate of the LTA parameter variance that

accounts for the variation due to the estimation of the two sets of LCA

parameters is applied This approach is described in greater technical

detail in the study of Reboussin and Ialongo (2010)

3 Results

31 Subtypes of early academic and behavior problems latent

class analysis

The AIC suggested a best-1047297tting model based on three classes (1 mdash

class = 9219 2 mdash class = 8548 3 mdash class = 8452 4 mdash class = 8482)

The entropy for the three class model was 097indicating high certainty

in classi1047297cation Theintroduction of a fourth class resulted in an entropy

of 086 suggesting less class separation A check of the local

00102030405060708

091

I t e m P

r o b a b i l i t i e

s

None (61)

Externalizing Behavior

(27)

Academic and

Aenon

Concentraon

Problems (12)

Fig 1 Academic and behavior problem item probabilities from the three class model at

school entry

53BA Reboussin et al Addictive Behaviors 41 (2015) 51ndash57

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 37

Total Math and Total Reading normal curve equivalent scores for each

child in the 1047297rst grade to create a composite academic achievement

variable The average was then dichotomized to indicate those children

with the most achievement dif 1047297culties (ie bottom 25 on achieve-

ment) In addition to this standardized achievement measure we

included the teacher report of the childs overall progress in the fall of

the 1047297rst grade This item was rated on a 6-point scale (1 = excellent

to 6 = extremely poor) and dichotomized for analyses to indicate

those with poor to extremely poor progress versus those with good toexcellent progress

223 Marijuana involvement in 6th 7th 8th and 9th grades

We considered responses to1047297ve questions about marijuana involve-

ment gathered in the spring of the 6th 7th 8th and 9th grades Oppor-

tunity to usemarijuanainvolved askingwhether a youth hadldquoever been

offeredrdquo marijuana as described by Crum Lillie-Blanton and Anthony

(1996) Adolescent reports of marijuana use were based on asking

ldquoHave you ever used marijuanardquo Frequency of marijuana use was

measured based on questions from the Monitoring the Future survey

( Johnston OMalley amp Bachman 1995) and was de1047297ned as ever using

marijuana more than a couple of times ie on three or more occasions

This low threshold for frequent marijuana use was chosen to be

meaningful for this sample of young adolescents It also gave us the

opportunity to explore whether this level of use is problematic in

young adolescents For this reason we also looked at health and social

problems associated with marijuana use Health and social problems

were assessed by asking if they ever experienced any health problems

or social problems from using marijuana The speci1047297c problems

comprising these two questions are listed in Appendix A

224 Demographic information

The school district provided information on the students sex and

ethnicity School records indicating each students free or reduced-cost

meal status were collapsed into a dichotomous variable of free or

reduced lunch versus self-paid lunch as an indicator of students

socioeconomic status

23 Statistical analyses

A cross-sectional latent class analysis (LCA) was applied to examine

the structure underlying the 1047297ve indicators of academic and behavior

problems in the 1047297rst grade The basic premise of LCA is that within

classes behaviors are locally independent (Lazarsfeld 1950) The goal

is to identify the smallest number of classes that adequately describes

the association among the behaviors Information about the resultant

class structure is conveyed through two sets of parameters the

probability of having high levels of academic andor behavior problems

within a particular class (item probabilities) and the proportion of

youth in each class (class prevalences)

A longitudinal latent class model (or latent stage model) was then

applied to examine the structure underlying the 1047297ve items comprising

the marijuana involvement pro1047297le over time While in principle it ispossible to allow the item probabilities and hence latent structure to

vary over time forthe 6thto 9th grade marijuana indicators this implies

that the de1047297nition of marijuana involvement is changing which would

substantially complicate the interpretation of a longitudinal model

Therefore we constrained the item probabilities to be constant over

time ie the probability of reporting a behavior within a latent stage

was thesame in each grade This is analogous to constraining the factor

loadings to be equal over time in a longitudinal factor analysis model

(sometimes referred to as factor invariance) The latent stage preva-

lences however were allowed to vary over time ie the proportion of

youth in each stage could change over time

Our model building strategy for the two sets of latent class models

involved starting with the most parsimonious one-class (or one-stage)

model and 1047297tting successive models with an increasing number of

latent classes (or stages) in order to determine the most parsimonious

model that provided an adequate 1047297t to the data The goodness-of-1047297t of

various models was evaluated using the Akaikes Information Criteria

(AIC) a global 1047297t index that combines goodness-of-1047297t and parsimony

Because we were concerned that the statistical power in this study

may be limited by the sample size we chose to rely on the AIC over

other global 1047297t indices as it is known to favor more complex models

(Lin amp Dayton 1997) Entropy was calculated to provide an indication

of the overall degree of classi1047297

cation uncertainty in the solution(Celeuxamp Soromenho 1996) Lower valuesof AIC are preferable where-

as higher values (or values closer to 1) are better for entropy For latent

class models there are considerations other than global goodness-of-1047297t

indices In particular an examination of thevalidityof thelocal indepen-

dence assumption which is the hallmark of LCA is critical We used a

modi1047297ed version of Garrett and Zegers (2000) Log-Odds Ratio Check

This method involves calculating thelog-oddsratio in both theobserved

and expected two-way tables for pairs of behaviors The observed data

log-odds ratio is then expressed as a z-score relative to the expected

data log-odds ratio The z-value is then used as a guide to detect items

that are locally dependent A threshold of plusmn15 was conservatively

chosen as suggestive of local dependence

Next we estimated the probability of transitioning between the

latent stages of marijuana involvement from the 6th through the 9th

grade and the in1047298uence of academic and behavior problem subtypes

on transition rates using latent transition analysis (LTA) LTA is an

extension of latent class analysis to the longitudinal framework which

expresses change over time in terms of transition probabilities and

models the impact of covariates on transitions using a multinomial

logistic regression formulation It has been used extensively to estimate

stage-sequential models of drug use over time (eg Chung Kim

Hipwell amp Stepp 2013 La Flair et al 2013 Lanza amp Bray 2010 Lee

Chassin amp Villalta 2013) We controlled for student-level covariates of

gender free or reduced cost lunch status and intervention status in

the LTA model A robust estimate of the LTA parameter variance that

accounts for the variation due to the estimation of the two sets of LCA

parameters is applied This approach is described in greater technical

detail in the study of Reboussin and Ialongo (2010)

3 Results

31 Subtypes of early academic and behavior problems latent

class analysis

The AIC suggested a best-1047297tting model based on three classes (1 mdash

class = 9219 2 mdash class = 8548 3 mdash class = 8452 4 mdash class = 8482)

The entropy for the three class model was 097indicating high certainty

in classi1047297cation Theintroduction of a fourth class resulted in an entropy

of 086 suggesting less class separation A check of the local

00102030405060708

091

I t e m P

r o b a b i l i t i e

s

None (61)

Externalizing Behavior

(27)

Academic and

Aenon

Concentraon

Problems (12)

Fig 1 Academic and behavior problem item probabilities from the three class model at

school entry

53BA Reboussin et al Addictive Behaviors 41 (2015) 51ndash57

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 47

independence assumption via the log-odds ratio residuals for the three

class model indicated that there were no residual dependencies Under

the three-class model that is displayed in Fig 1 61 of youth do not

have academic or behavior problems in the1047297rst grade based on teacher

report and standardized achievement scores Approximately 27 of

youth have high probabilities of falling into the top quartile for opposi-

tionalde1047297ant and aggressive disruptive behaviors as well as having

moderate probabilities of havingattention concentration and academic

problems We refer to this class as the ldquo

externalizing behavior prob-lemsrdquo class because it is primarily dominated by externalizing prob-

lems The least prevalent class (12) was a class of children with high

probabilities of being in the top quartile for attentionconcentration

problems and lowest quartile for both academic achievement and

teacher-reported overall progress We refer to this class as theldquoacadem-

ic and attentionconcentration problemsrdquo class

32 Stages of marijuana involvement longitudinal latent class analysis

Even though a longitudinal latent stage model of the 1047297ve marijuana

involvement behaviors suggested a best 1047297tting one stage model based

on the AIC (1 mdash class = 77395 2 mdash class = 85197 3 mdash class =

115208 4 mdash class = 117893) there was evidence of local dependence

under the one two and three stage models suggesting that additional

stages were necessary to explain the association among the marijuana

behaviors The addition of a fourth stage removed all local dependen-

cies however the prevalence of this fourth stage was only 1 in the

6th grade hindering our ability to obtain stable parameter estimates in

the latent transition models Entropy for the four stage model was also

relatively low (087) suggestive of more classi1047297cation uncertainty com-

pared to the three stage model with entropy of 094 To probe further

whether introductionof a third stage yielded a model that was clinically

meaningful in addition to its ability to improve the local independence

assumption we examined the resultant latent structure to evaluate its

interpretability and clinical meaningfulness and determined this to be

the most appropriate model

As shown in Fig 2 the most prevalent stage is a class with no mari-

juana exposure opportunities or marijuana use We refer to this as the

ldquono marijuana involvementrdquo stage The estimated prevalence of thisstage was 84 in the 6th grade 71 in the 7th grade 56 in the 8th

grade and 38 in the 9th grade The next most prevalent stage is one

in which almost everyone has been offered marijuana but the probabil-

ity of using marijuana is less than 20 We refer to this as the ldquooffered

marijuanardquo stage the prevalence was 14 in the 6th grade 20 in the

7th grade 28 in the 8th grade and 32 in the 9th grade The third

stage is a class of youth who have been offered and used marijuana

(N95) In addition almost 60 have used marijuana more than a

couple of times and almost all youth have experienced social problems

as a result of their marijuana use Just more than 40 have experienced

health problems We refer to this as the ldquomarijuana use and problemsrdquo

stage The prevalence of this stage was 2 in the 6th grade 9 in the

7th grade 16 in the 8th grade and 30 in the 9th grade

33 Transitions between stages of marijuana involvement latent transition

analysis

Asseenin Table 1 the probability of transitioning from no marijuana

involvement to being offered marijuana increases over time and is

signi1047297

cantly greater between the 8th and 9th compared to the 6thand 7th grades (OR = 210 p b 0001) The likelihood of transitioning

from no involvement to use and problems also increases over time

and is signi1047297cantly greater between the 8th and 9th grades (OR =

256 p b 005) and the 7th to 8th grades (OR = 222 p b 005)

compared to the 6th and 7th grades The probability of transitioning

from being offered marijuana to use and problems however is greater

between the 6th and 7th grades compared to between the 7th and 8th

grades (OR = 303 p b 005)

As seen in Table 2 relative to youth with academic and attention

concentration problems at school entry youth with externalizing

behavior problems are more likely to advance from no involvement to

being offered marijuana at entry to high school (ie 9th grade) after

adjustment for gender free and reduced lunch status and intervention

status (AOR = 725 p b 005) They are also more likely to transition

from no marijuana involvement to use and problems between the 7th

and 8th grades relative to youth with no problems (AOR = 1083

p b 005) Youth with academic and attentionconcentration problems

were also more likely to make this transition relative to youth with no

problems between the 7th and 8th grades (AOR = 1069 p b 005)

Youth with academic and attentionconcentration problems were

more likely to advance from being offered marijuana to use and

problems between the 8th and 9th grades relative to youth with no

problems (AOR = 599 p b 005)

4 Discussion

Our results suggest that academic problems occur in combination

with both externalizing and attentionconcentration problems in

African-Americans although to a lesser extent with externalizingproblems In contrast to the work of Reinke et al (2008) that included

both minorities and non-minorities we did not 1047297nd a subtype of

children that were experiencing academic or behavior problems in

isolation Further attention and concentration problems were also

present with moderate probability in the subtype of children with

externalizing behavior problems This is consistent with reports that

African-American youth are more likely to have teachers rate them as

inattentive (DuPaul amp Eckert 1997) and youth from families with

lower socioeconomic status are less likely to be engaged in school

(Smerdon 1999) Our 1047297nding that the subtype of children with exter-

nalizing behavior problems was the most prevalent problem behavior

subtype is also consistent with research that show African-Americans

are more likely than Whites to receive an educational diagnosis of

emotional disturbance (Kaufman 2005) This study demonstrates theneed for future prevention research as well as school services that

focus on the co-occurrence of academic achievement and behavior

problems It also emphasizes the need to intervene early in low income

African-American populations that may be less prepared for school

before this lack of readiness becomes intertwined with classroom

behavior problems setting children off on a path that places them at

risk for marijuana involvement in adolescence

We found that the greatest risk period for making the transition

from no involvement to being offered marijuana was later in middle

school and early in high school This 1047297nding is consistent with Storr

et al (2011) in a similar predominantly African-American urban sample

in which the opportunity to use marijuana rose markedly after the

age of 13 Rates of marijuana use and problems are also increasing

quickly over this time period suggesting a narrow window of

0

01

02

03

04

05

06

07

08

091

offered ever used used on

mulple

occasions

social

problems

from use

health

problems

from use

I t e m P

r o b a b i l i t i e s

No involvement

(84 71 56 38)

Offered Marijuana

(14 20 28 32)

Use and Problems

(2 9 16 30)

Fig 2 Marijuana involvement item probabilities from the three class model for 6th 7th

8th and 9th grades

54 BA Reboussin et al Addictive Behaviors 41 (2015) 51ndash57

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 57

opportunity for prevention during this developmental period Just as

early elementary school is a critical transition period failure to adapt

to the academic and social task demands of middle and high schools

may precipitate ldquodriftrdquo into a deviant peer group wherein a wide

array of antisocial and delinquent behavior including alcohol and

drug use may be reinforced (Brook Nomura amp Cohen 1989 Jessor amp

Jessor 1978 Patterson et al 1992)

Children in the externalizing behavior class in the1047297rst grade were at

greater risk for transitioning from no involvement to being offered

marijuana across all years and signi1047297cantly so between the 8th and

9th grades compared to youth with attentionconcentration problems

This is consistent with the work of Rosenberg and Anthony (2001)who found that aggressive youth are more likely to be approached

with offers to buy drugs This could be theresult of an outward persona

that makes them targets of drug dealers or a greater af 1047297liation with de-

viant peers that are using drugs On the other hand children with

attentionconcentration problems were signi1047297cantly more likely to

transition to use given an opportunity between the 8th and 9th grades

but were not more likely to transition to opportunities This lack of

opportunities (or offers) may be a re1047298ection of rejection by their

peers however given an opportunity to use the impulsivity which

often co-occurs with attentionconcentration problems may cause

them to act without carefully thinking about the consequences of

marijuana use Therefore interventions for those with externalizing

problems may be more peer-focused while interventions for those

with attentionconcentration problems may be more inwardly focused

on strategies for controlling impulsivity Given that the highest risk

period for these transitions is entry into high school strategies for

dealing with the increased academic and social demands of high school

is critical in these problem behavior subgroups in which academic

problems are co-occurring

Limitations of the study should be noted Reliance on self-reported

marijuana use could be subject to underreporting bias however this

study was designed to be sensitive to ethnic-minority populations

with the intent of maximizing participation and minimizing under-

reporting of drug-using behaviors The small number of non-

minorities in the original sample precluded our ability to make anymeaningful (or statistically stable) comparisons between minorities

and non-minorities A larger and more diverse sample may have

allowed not only for ethnic comparisons but identi1047297cation of more

subgroups

Limitations in our sample size may have also hindered our ability to

detect group differences as evidence by a limited number of statistically

signi1047297cant 1047297ndings in the LTA modeling A focus of future work which

we did not consider should be other factors known to be associated

with substance use such as family peer and neighborhood factors

and how they might modify the in1047298uence of academic and problem be-

havior subtypes on transitions in marijuana use in a low-income ethnic

minority population We also caution the reader that the current study

maynot be generalizable to non-urban settings in which early academic

Table 1

Estimated probabilities and odds ratios of transitioning by grade

Estimated transition probability OR (95 CI) p-value

6th to 7th 7th to 8th 8th to 9th 7th to 8th vs 6th to 7th 8th to 9th vs 6th to 7th 8th to 9th vs 7th to 8th

No involvement to offered marijuana 012 017 022 150 (099 227)

p = 0053

210 (136 322)

p b 0001

139 (091 212)

p = 0123

No involvement to use and problems 003 004 007 115 (052 255)

p = 0381

256 (122 541)

p = 0013

222 (105 469)

p = 0036

Offered marijuana to use and problems 022 009 016 033 (012 090)

p = 0030

064 (028 148)

p = 0230

196 (075 514)

p = 0168

Table 2

Estimated transition probabilities and adjusted odds by grade and subtype of academic and behavior problems

Estimated transition probability AOR (95 CI)a

p-value

No problems Externalizing

behavior

problems

Academic and

attentionconcentration

problems

Externalizing vs

no problems

Academic and

attentionconcentration

problems vs no problems

Externalizing vs academic

and attentionconcentration

problems

No involvement to offered marijuana

6th to 7th 011 015 010 133 (066 267)

p = 0422

090 (028 283)

p = 0857

148 (043 510)

p = 0534

7th to 8th 020 015 010 072 (035 149)

p = 0376

044 (013 154)

p = 0199

163 (042 637)

p = 0482

8th to 9th 021 031 005 163 (079 337)

p = 0187

022 (004 121)

p = 0082

725 (125 4192)

p = 0027

No involvement to use and problems

6th to 7th 002 005 007 237 (065 859)

p = 0189

340 (078 1481)

p = 0103

070 (014 341)

p = 0659

7th to 8th 001 009 008 1083 (216 5439)

p = 0004

1069 (173 6613)

p = 0011

101 (023 439)

p = 0989

8th to 9th 004 009 019 196 (053 718)

p = 0310

355 (099 1276)

p = 0052

055 (012 260)

p = 0451

Offered marijuana to use and problems

6th to 7th 027 018 017 065 (015 279)

p = 0562

070 (010 900)

p = 0784

095 (009 1049)

p = 0967

7th to 8th 011 006 000 034 (006 186)

p = 0213

ndashb

ndashb

8th to 9th 011 018 050 127 (018 880)

p = 0809

599 (137 2612)

p = 0017

021 (004 106)

p = 0059

a Models adjusted for gender intervention status and free or reduced lunch statusb

Youth with academic andattentionconcentrationproblems hada zero probability of transitioningfrom being offeredmarijuana to marijuanause andproblems in 7thto 8thgrades

55BA Reboussin et al Addictive Behaviors 41 (2015) 51ndash57

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 67

and behavioral pro1047297les school readiness and access to and norms

around marijuana use may differ

Despite these limitations the greatest strength of this study is the

availability of a large sampleof African-Americans participatingin a lon-

gitudinal study designed to be sensitive to ethnic-minority populations

with annualdata collection Prospective studies like this onemdash featuring

a representative cohort of an entire entering class of 1047297rst graders are

relatively rareparticularly bridging the development periods from mid-

dle school to high school Even rarer are prospective studies of African-American youth from neighborhoods that are characterized by high

levels of community violence crime and poverty An understanding

of the ldquosurvivorsrdquo in such an environment canpotentially greatly inform

the next stage of preventive intervention efforts While a larger and

more diverse sample may have allowed the identi1047297cation of more

subgroups cohort differences and ethnic comparisons a community

cohorthas thebene1047297t of identifying within-group differencesin a highly

vulnerable and under-investigated population not always fully cap-

tured in national surveys Our ability to more accurately re1047298ect the

true nature of African-American drug use is what makes this a unique

contribution to the literature

In summary our 1047297ndings highlight the importance of developing

prevention programs and providing school services that address the

co-occurrence of academic and behavior problems as well as their

subtype speci1047297c risks for marijuana involvement particularly for low-

income urban-dwelling African-American youth who may be entering

school less ready than their non-minoritypeers These1047297ndingsalso pro-

vide evidence for a need to continue to deliver interventions in middle

school andhigh school focused on factors that mayprotect youth during

these critical transition periodswhen they may be especially vulnerable

to opportunities to use marijuana based on their academic and behav-

ioral risk pro1047297les

Role of funding source

Funding for this secondary data analysis was provided by the National Institute of

Drug Abuse (NIDA)GrantDA032550 Thecontentis solelythe responsibilityof theauthors

and does not necessarily represent the of 1047297cial views of NIDA or the National Institutes of

Health NIDA and NIH had no further role in the analysis and interpretation of the data

in the writing of the report or in the decision to submit the paper for publication

Contributors

Beth Reboussin Nicholas Ialongo and Kerry Green conceptualized the analyses Beth

Reboussin conducted the analyses Beth Reboussin wrote the 1047297rst draft of the paper and

all authors reviewed and edited the drafts and approved the 1047297nal version

Con1047298ict of interest

All authors declare that they have no con1047298ict of interest

Acknowledgments

Funding for this secondary data analysis was provided by the National Institute of

Drug Abuse (NIDA) Grant DA032550 The original data collection was funded by

DA11796 amp MH57005

Appendix A Social and health problems

Some people have bad effects from using marijuana The next set of

questions is about some problems you might have had from using

marijuana

Social problems (Yes or No)

1 Has any friend told you that you shouldnt be using marijuana

2 Has any member of your family ever told you that you shouldnt be

using marijuana

3 Has any friend ever scolded or fussed at you because you used

marijuana

4 Has any family member ever scolded or fussed at you because you

used marijuana

5 Has any teacher ever scolded or fussed at you because you used

marijuana

6 Have you ever gotten into trouble at school because you used

marijuana

7 Have you ever gotten into trouble at home because you used

marijuana

8 Have you ever gotten into trouble with the police because you used

marijuana

Health problems (Yes or No)

1 Did you have any health problems like feeling panicky or frightenedbecause you were using marijuana

2 How about a problem like feeling sad upset or depressed because

you were using marijuana

3 Did you have a health problem like a lasting cough due to using

marijuana

4 How about a health problem like getting sick to your stomach or an

overdose caused by marijuana

5 Have you ever used marijuana every dayor almost every day for two

weeks or more

6 Did you ever wake up and feel somethinglike hunger for marijuana

References

Bradshaw C P Buckley J A amp Ialongo N S (2008) School-based service utilization

among urban children with early onset educational and mental health problemsThe squeaky wheel phenomenon School Psychology Quarterly 23(2) 169ndash186Brook J S Nomura C amp Cohen P (1989) A network of in1047298uences on adolescent

drug involvement Neighborhood school peer family Genetic Social and GeneralPsychology Monographs 115 123ndash145

Brown T L Flory K Lynam D R Leukefeld C amp Clayton R R (2004) Comparingthe developmental trajectories of marijuana use of African American and Caucasianadolescents Patterns antecedents and consequences Experimental and ClinicalPsychopharmacology 12(1) 47ndash56

Celeux G amp Soromenho G (1996) An entropy criterion for assessing the number of clusters in a mixture model Journal of Classi 1047297cation 13 195ndash212

Centers for Disease Control and Prevention (2012) Youth risk behavior surveillance mdashUnited States 2011 Surveillance summaries June 8 2012 MMWR 61 (No SS-4)

Chung T Kim K H Hipwell A E amp Stepp S D (2013) White and black adolescentfemalesdifferin pro1047297les and longitudinalpatterns of alcohol cigarette and marijuanause Psychology of Addictive Behaviors 27 (4) 1110ndash1121

Clark TT BelgraveF Z amp Nasim A(2008) Risk andprotective factors forsubstance useamong urban African American adolescents considered high-risk Journal of Ethnicityin Substance Abuse 7 (3) 292ndash303

Colder C R Scalco M Trucco E M Read J P Lengua L J Wieczorek W F et al(2013) Prospective associations of internalizing and externalizing problems andtheir co-occurrence with early adolescent substance use Journal of Abnormal ChildPsychology 41(4) 667ndash677

Comprehensive test of basic skills (4th ed) (1990) Monterey CA CTBMcGraw-HillCompton W M Grant B F Colliver JD Glantz MD amp Stinson F S (2004) Prevalence

of marijuana use disorders in the United States 1991ndash1992 and 2001ndash2002 Journalof the American Medical Association 291(17) 2114ndash2121

Crum R M Lillie-Blanton M amp Anthony J C (1996) Neighborhood environment andopportunity to use cocaine and other drugs in late childhood and early adolescenceDrug and Alcohol Dependence 43 155ndash161

DuPaul G J amp Eckert T L (1997) The effects of school-based interventions for attentionde1047297cit hyperactivity disorder A meta-analysis School Psychology Review 26 5ndash27

Garrett E S amp Zeger S L (2000) Latent class model diagnosis Biometrics 56 1055ndash1067

Ialongo N S Werthamer L Kellam S G Brown C H Wang S amp Lin Y (1999) Prox-imal impact of two 1047297rst-grade prevention interventions on the early risk behaviorsfor later substance abuse depression and antisocial behavior American Journal of Community Psychology 27 (5) 599ndash641

Jessor R amp Jessor S L (1978) Theory testing in longitudinal research on marijuana useIn D Kandel (Ed) Longitudinal research on drug use Washington DC HemispherePublishing Corporation

Johnston L D OMalley PM amp Bachman J G (1995) National survey results on drug use from the Monitoring the Future Study 1975ndash1994 Volume I Secondary schoolstudents Rockville MD National Institute on Drug Abuse (NIH Publication No 95-4026)

Johnston L D OMalley PM Bachman J G amp Schulenberg J E (2013) Monitoring the future national results on adolescent drug use Overview of the key 1047297ndings 2012 AnnArbor Institute for Social Research The University of Michigan

Kaufman J M (2005) Characteristics of emotional and behavioral disorders of children and youth (8th ed) Upper Saddle River NJ Prentice Hall

La Flair L N Reboussin BA Storr C L Letourneau E Green K M Mojtabai R et al(2013) Childhood abuse and neglect and transitions in alcohol involvement amongwomen A latent transition analysis approach Drug and Alcohol Dependence 132(3)491ndash498

Lanza S T amp Bray B C (2010) Transitions in drug use among high-risk women Anapplication of latent class and latent transition analysis Advances and Applications

in Statistical Science 3(2) 203ndash

235

56 BA Reboussin et al Addictive Behaviors 41 (2015) 51ndash57

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 67

and behavioral pro1047297les school readiness and access to and norms

around marijuana use may differ

Despite these limitations the greatest strength of this study is the

availability of a large sampleof African-Americans participatingin a lon-

gitudinal study designed to be sensitive to ethnic-minority populations

with annualdata collection Prospective studies like this onemdash featuring

a representative cohort of an entire entering class of 1047297rst graders are

relatively rareparticularly bridging the development periods from mid-

dle school to high school Even rarer are prospective studies of African-American youth from neighborhoods that are characterized by high

levels of community violence crime and poverty An understanding

of the ldquosurvivorsrdquo in such an environment canpotentially greatly inform

the next stage of preventive intervention efforts While a larger and

more diverse sample may have allowed the identi1047297cation of more

subgroups cohort differences and ethnic comparisons a community

cohorthas thebene1047297t of identifying within-group differencesin a highly

vulnerable and under-investigated population not always fully cap-

tured in national surveys Our ability to more accurately re1047298ect the

true nature of African-American drug use is what makes this a unique

contribution to the literature

In summary our 1047297ndings highlight the importance of developing

prevention programs and providing school services that address the

co-occurrence of academic and behavior problems as well as their

subtype speci1047297c risks for marijuana involvement particularly for low-

income urban-dwelling African-American youth who may be entering

school less ready than their non-minoritypeers These1047297ndingsalso pro-

vide evidence for a need to continue to deliver interventions in middle

school andhigh school focused on factors that mayprotect youth during

these critical transition periodswhen they may be especially vulnerable

to opportunities to use marijuana based on their academic and behav-

ioral risk pro1047297les

Role of funding source

Funding for this secondary data analysis was provided by the National Institute of

Drug Abuse (NIDA)GrantDA032550 Thecontentis solelythe responsibilityof theauthors

and does not necessarily represent the of 1047297cial views of NIDA or the National Institutes of

Health NIDA and NIH had no further role in the analysis and interpretation of the data

in the writing of the report or in the decision to submit the paper for publication

Contributors

Beth Reboussin Nicholas Ialongo and Kerry Green conceptualized the analyses Beth

Reboussin conducted the analyses Beth Reboussin wrote the 1047297rst draft of the paper and

all authors reviewed and edited the drafts and approved the 1047297nal version

Con1047298ict of interest

All authors declare that they have no con1047298ict of interest

Acknowledgments

Funding for this secondary data analysis was provided by the National Institute of

Drug Abuse (NIDA) Grant DA032550 The original data collection was funded by

DA11796 amp MH57005

Appendix A Social and health problems

Some people have bad effects from using marijuana The next set of

questions is about some problems you might have had from using

marijuana

Social problems (Yes or No)

1 Has any friend told you that you shouldnt be using marijuana

2 Has any member of your family ever told you that you shouldnt be

using marijuana

3 Has any friend ever scolded or fussed at you because you used

marijuana

4 Has any family member ever scolded or fussed at you because you

used marijuana

5 Has any teacher ever scolded or fussed at you because you used

marijuana

6 Have you ever gotten into trouble at school because you used

marijuana

7 Have you ever gotten into trouble at home because you used

marijuana

8 Have you ever gotten into trouble with the police because you used

marijuana

Health problems (Yes or No)

1 Did you have any health problems like feeling panicky or frightenedbecause you were using marijuana

2 How about a problem like feeling sad upset or depressed because

you were using marijuana

3 Did you have a health problem like a lasting cough due to using

marijuana

4 How about a health problem like getting sick to your stomach or an

overdose caused by marijuana

5 Have you ever used marijuana every dayor almost every day for two

weeks or more

6 Did you ever wake up and feel somethinglike hunger for marijuana

References

Bradshaw C P Buckley J A amp Ialongo N S (2008) School-based service utilization

among urban children with early onset educational and mental health problemsThe squeaky wheel phenomenon School Psychology Quarterly 23(2) 169ndash186Brook J S Nomura C amp Cohen P (1989) A network of in1047298uences on adolescent

drug involvement Neighborhood school peer family Genetic Social and GeneralPsychology Monographs 115 123ndash145

Brown T L Flory K Lynam D R Leukefeld C amp Clayton R R (2004) Comparingthe developmental trajectories of marijuana use of African American and Caucasianadolescents Patterns antecedents and consequences Experimental and ClinicalPsychopharmacology 12(1) 47ndash56

Celeux G amp Soromenho G (1996) An entropy criterion for assessing the number of clusters in a mixture model Journal of Classi 1047297cation 13 195ndash212

Centers for Disease Control and Prevention (2012) Youth risk behavior surveillance mdashUnited States 2011 Surveillance summaries June 8 2012 MMWR 61 (No SS-4)

Chung T Kim K H Hipwell A E amp Stepp S D (2013) White and black adolescentfemalesdifferin pro1047297les and longitudinalpatterns of alcohol cigarette and marijuanause Psychology of Addictive Behaviors 27 (4) 1110ndash1121

Clark TT BelgraveF Z amp Nasim A(2008) Risk andprotective factors forsubstance useamong urban African American adolescents considered high-risk Journal of Ethnicityin Substance Abuse 7 (3) 292ndash303

Colder C R Scalco M Trucco E M Read J P Lengua L J Wieczorek W F et al(2013) Prospective associations of internalizing and externalizing problems andtheir co-occurrence with early adolescent substance use Journal of Abnormal ChildPsychology 41(4) 667ndash677

Comprehensive test of basic skills (4th ed) (1990) Monterey CA CTBMcGraw-HillCompton W M Grant B F Colliver JD Glantz MD amp Stinson F S (2004) Prevalence

of marijuana use disorders in the United States 1991ndash1992 and 2001ndash2002 Journalof the American Medical Association 291(17) 2114ndash2121

Crum R M Lillie-Blanton M amp Anthony J C (1996) Neighborhood environment andopportunity to use cocaine and other drugs in late childhood and early adolescenceDrug and Alcohol Dependence 43 155ndash161

DuPaul G J amp Eckert T L (1997) The effects of school-based interventions for attentionde1047297cit hyperactivity disorder A meta-analysis School Psychology Review 26 5ndash27

Garrett E S amp Zeger S L (2000) Latent class model diagnosis Biometrics 56 1055ndash1067

Ialongo N S Werthamer L Kellam S G Brown C H Wang S amp Lin Y (1999) Prox-imal impact of two 1047297rst-grade prevention interventions on the early risk behaviorsfor later substance abuse depression and antisocial behavior American Journal of Community Psychology 27 (5) 599ndash641

Jessor R amp Jessor S L (1978) Theory testing in longitudinal research on marijuana useIn D Kandel (Ed) Longitudinal research on drug use Washington DC HemispherePublishing Corporation

Johnston L D OMalley PM amp Bachman J G (1995) National survey results on drug use from the Monitoring the Future Study 1975ndash1994 Volume I Secondary schoolstudents Rockville MD National Institute on Drug Abuse (NIH Publication No 95-4026)

Johnston L D OMalley PM Bachman J G amp Schulenberg J E (2013) Monitoring the future national results on adolescent drug use Overview of the key 1047297ndings 2012 AnnArbor Institute for Social Research The University of Michigan

Kaufman J M (2005) Characteristics of emotional and behavioral disorders of children and youth (8th ed) Upper Saddle River NJ Prentice Hall

La Flair L N Reboussin BA Storr C L Letourneau E Green K M Mojtabai R et al(2013) Childhood abuse and neglect and transitions in alcohol involvement amongwomen A latent transition analysis approach Drug and Alcohol Dependence 132(3)491ndash498

Lanza S T amp Bray B C (2010) Transitions in drug use among high-risk women Anapplication of latent class and latent transition analysis Advances and Applications

in Statistical Science 3(2) 203ndash

235

56 BA Reboussin et al Addictive Behaviors 41 (2015) 51ndash57

8102019 Addictive Behaviors - Influences of Behavior and Academic Problems at School Entry on Marijuana Use Transitions hellip

httpslidepdfcomreaderfulladdictive-behaviors-influences-of-behavior-and-academic-problems-at-school 77

Lazarsfeld P F (1950) The logical and mathematical foundation of latent structureanalysis In S Stouffer (Eds) Measurement and prediction (pp 365ndash412) PrincetonPrinceton University Press

Lee M R Chassin L amp Villalta I K (2013) Maturing out of alcohol involvement Tran-sitions in latent drinking statuses from late adolescence to adulthood Development and Psychopathology 25(4 Pt 1) 1137ndash1153

Lin T H amp Dayton C M (1997) Model selection information criteria for non-nestedlatent class models Journal of Educational and Behavioral Statistics 22 249ndash264

Patterson G R Reid J B amp Dishion T J (1992) A social learning approach IV Antisocialboys Eugene OR Castalia

Reboussin BA amp Ialongo N S (2010) Latent transition models with latent class

predictors ADHD subtypes and high school marijuana use Journal of Royal StatisticsSociety Series A 173(1) 145ndash164Reinke W M Herman K C Petras H amp Ialongo N S (2008) Empirically derived

subtypes ofchild academicand behaviorproblems Co-occurrence anddistal outcomes Journal of Abnormal Child Psychology 36 759ndash770

Rosenberg M F amp Anthony J C (2001) Aggressive behavior and opportunities topurchase drugs Drug and Alcohol Dependence 63(3) 245ndash252

Smerdon BA (1999) Engagement and achievement Differences between African-American and White high school students Research in Sociology of Education andSocialization 12 103ndash134

Storr C L Wagner F A Chen C Y amp Anthony J C (2011) Childhood predictors of 1047297rstchance to use and use of cannabis by young adulthood Drug and Alcohol Dependence117 (1) 7ndash15

Substance Abuse and Mental Health Services Administration (2013) Results from the 2012 National Survey on Drug Use and Health Summary of national 1047297ndings NSDUH Series H-46 HHS Publication No (SMA) 13-4795 Rockville MD Substance Abuseand Mental Health Services Administration

Werthamer-Larsson L Kellam S amp Wheeler L (1991) Effects of 1047297rst-grade classroom

environment on shy behavior aggressivedisruptive behavior and concentrationproblems American Journal of Community Psychology 19 585ndash602Wilson M N (1989) Child development in the context of the black extended family

American Psychologist 44 380ndash385

57BA Reboussin et al Addictive Behaviors 41 (2015) 51ndash57