A

K

imrnnitgalgiea

M

nmc

CP

1d

Adolescent health brief

Gambling Initiation in PreadolescentsHallam Hurt, M.D.a,*, Joan M. Giannettaa, Nancy L. Brodsky, Ph.D.a, David Shera, Sc.D.b,

and Daniel Romer, Ph.D.caNeonatology, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania

bBiostatistics and Epidemiology, The Children’s Hospital of Philadelphia, Philadelphia, PennsylvaniacInstitute for Adolescent Risk Communication, Annenberg Public Policy Center, The University of Pennsylvania, Philadelphia, Pennsylvania

Manuscript received September 2007; manuscript accepted December 21, 2007

bstract Gambling has increased in the past decade, with growing opportunities for initiation by adolescents.More limited data, however, are available regarding gambling in preadolescents. In the investigationreported here, gambling for money was the most common risk behavior in 10- to 12-year-olds.Gamblers were more likely to be white, have tried alcohol, have positive affect toward gambling,and have friends who gamble. © 2008 Society for Adolescent Medicine. All rights reserved.

Journal of Adolescent Health 43 (2008) 91–93

eywords: Gambling; Risk behaviors; Impulsivity; Sensation seeking; Neurocognitive function

TcroygimwdititSbuAfiaSScita

In the past decade, gambling and gambling venues havencreased in the United States [1]. Although it is illegal for

inors under the ages of 18 to 21 years to gamble inegulated venues, evidence is accumulating that a growingumber of youth are participating in both regulated andonregulated gambling including cards, sports betting, andnternet gambling [2–4] . Turchi and Derevensky [5] statehat, although most adolescents are “occasional” or “social”amblers, as many as 10% to 15% are at risk for developinggambling problem, with 3% to 8% having serious prob-

ems. There has been growing public concern regardingambling in youth, with research beginning to address thisssue as a health risk for adolescents. Now we report an evenarlier age of onset—gambling for money in preadolescentsges 10 to 12 years.

ethods

In a prospective study of risk taking, impulsivity, andeurocognitive functioning, youth ages 10 to 12 years ofixed racial and socioeconomic backgrounds were re-

ruited from Philadelphia public and parochial schools.

*Address correspondence to: Hallam Hurt, M.D., Neonatology, Thehildren’s Hospital of Philadelphia, 3535 Market Street, Room 1435,hiladelphia, PA 19104.

CE-mail address: hurt@email.chop.edu

054-139X/08/$ – see front matter © 2008 Society for Adolescent Medicine. Alloi:10.1016/j.jadohealth.2007.12.018

hree-hundred eighty-four participants with the followingharacteristics have been enrolled: gender—48% male;ace—58% white, 28% African-American, 8% Asian, 7%ther; ethnicity—8% Hispanic; mean age—11.4 � 0.9ears; grade—11% fourth grade, 50% fifth grade, 26% sixthrade, 14% seventh grade; parent education—median Holl-ngshead category 3 (13–15 years); parent occupation—edian Hollingshead category 4 (clerical/sales). The studyas approved by the institutional review board of the Chil-ren’s Hospital of Philadelphia. Assessments of risk taking,mpulsivity, and neurocognitive functioning are being ob-ained annually on four occasions (2005–2009). Measuresnclude: (1) risk behavior initiation: assessed through ques-ionnaires (selected portions of the Youth Risk Behaviorurvey [http://www.cdc.gov; 2003] and National Annen-erg Survey of Youth [6]) easily understood by subjects,sing slang terms for drugs and behavior, administered byudio Computer-Assisted Self-Interviewing to ensure con-dentiality and maximum comprehension; (2) impulsivity:ssessed using portions of the Eysenck I7 Junior Impulsivitycale (� � 0.76) [7] and Reduced Brief Sensation Seekingcale (four self-report items, � � 0.74) [8]; and (3) neuro-ognitive function: three frontal systems associated withmpulse control and cognitive capacity are assessed withasks as follows: (a) cognitive control, with Counting Stroopnd Eriksen Flanker; (b) working memory, with 2-Back,

orsi Block Tapping, Digit Span—Wechsler Intelligence

rights reserved.

SMi

Wir

R

i1(

fb(ayb

hgpp“gh

92 H. Hurt et al. / Journal of Adolescent Health 43 (2008) 91–93

cale for Children-Fourth Edition, and Spatial Workingemory; and (c) reward processing, with Reversal Learn-

ng and Balloon Analogue Risk Task, Adolescent Version.Data were analyzed using chi-square, t-tests, or Mann-

hitney U, as appropriate, and multivariate analysis utiliz-ng logistic regression with backward variable selectionemoving the least significant covariate until all p � .15.

esults

The first evaluation of participant risk behaviors showednitiation as follows: marijuana use 0.5%, sexual intercourse.6%, cigarette use 2.9%, inhalant use 4.9%, alcohol usemore than sip for religious reasons) 17.4%, and gambling

Table 2Multivariate analysis: logistic regression with backw

Outcome: Have you ever gambledfor money?

First step

Odds ratio

Gender, male 1.57Race, white 1.87Age, years 0.73School grade 1.62Alcohol use 2.90Positive affect toward gambling 2.05Have friends who gamble 4.27Friends disapprove of gambling 0.56Impulsivity, total score 1.07Sensation-seeking, total score 1.03Stroop effect, milliseconds 0.31

Test value: �2 � Pearson chi-square; t � t-test; Z

Table 1Characteristics and risk behaviors: gamblers versus

Gamblersn � 105

Gender, male 64 (61)a

Race, white 69 (66)Positive affect toward gambling 58 (55)Friends who gamble 69 (66)Friends disapprove of gambling 17 (16)Marijuana use 1 (1)Cigarette use 6 (6)Alcohol use 37 (35)Caffeine use 94 (90)Inhalant use 7 (7)Sexual intercourse 3 (3)School grade, median 6th gradeAge, years 11.6 � 0.1Impulsivity, total score 6.1 � 3.0Sensation-seeking, total score 9.9 � 3.2Stroop effectc, milliseconds 227.1 � 179

Test value: �2 � Pearson chi-square; t � t-test; Za n (%).b Mean � SD.c Incongruent minus congruent reaction time.

* Dropped in backward selection process (p � .15).

or money 27.2%. Characteristics of participants who gam-led (gamblers) versus participants who did not gamblenongamblers) are shown in Table 1. Gamblers were defineds individuals who answered “yes” to the question “haveou ever gambled for money, such as playing the lottery oretting on sports or a card game?”

Gamblers were more likely male, white, older, in aigher school grade, to use alcohol, and to have friends whoamble; they were less likely to have friends who disap-rove of gambling. Gamblers were more likely to expressositive affect toward gambling (defined as respondingvery good” to the question “how would you feel if youambled for money?”) than nongamblers. Gamblers alsoad higher Impulsivity and Sensation Seeking Total Scores

ection

Last step

e p-value Odds ratio Z-value p-value

.134 * * *

.044 1.73 1.86 .063

.307 * * *

.121 * * *

.002 3.52 �3.75 �.001�.001 2.35 4.44 �.001�.001 4.37 5.00 �.001

.11 0.49 �2.08 .037

.233 * * *

.580 * * *

.151 * * *

nn-Whitney U.

blers

Nongamblersn � 279

Test value p-value

121 (43) �2 � 9.45 .003152 (54) �2 � 3.94 .04740 (14) �2 � 67.14 �.00154 (19) �2 � 75.31 �.001

144 (52) �2 � 40.42 �.0011 (0.4) �2 � 0.52 .475 (2) �2 � 4.22 .08

30 (11) �2 � 31.76 �.001227 (81) �2 � 3.71 .0612 (4) �2 � 0.91 .433 (1) �2 � 1.58 .35

5th grade Z � �3.44 .00111.3 � 0.1 t � 2.73 .0074.0 � 2.9 t � 6.04 �.0018.1 � 2.9 t � 5.24 �.001

289.0 � 254.8 t � �2.28 .023

nn-Whitney U.

ard sel

Z-valu

1.502.01

�1.021.55

�3.013.50

�4.76�1.60

1.190.55

�1.44

� Ma

nongam

b

.0

� Ma

towbdvghwd

D

ebbvesgoswnsttptteLa

ofipwwtbrw

C

mgheailg

A

N

R

[

93H. Hurt et al. / Journal of Adolescent Health 43 (2008) 91–93

han nongamblers. Gamblers differed from nongamblers innly one neurocognitive task, the Counting Stroop, forhich gamblers exhibited better performance than nongam-lers. Using variables in which gamblers and nongamblersiffered, we performed logistic regression with backwardariable selection. As shown in Table 2, in the last stepamblers were more likely to be white, to have tried alco-ol, to have positive affect toward gambling, to have friendsho gamble, and were less likely to have friends whoisapprove of gambling.

iscussion

Our report, generated from data for the first of fourvaluations to be conducted in this cohort, showed gam-ling for money to be the most commonly initiated riskehavior in 10- to 12-year-olds. Consistent with other in-estigations of risk behaviors in youth, having friends whongage in risk behaviors, in this case gambling, wastrongly associated with gambling as was positive affect forambling [6]. Interestingly, in univariate analysis, scores ofur two self-report measures (impulsivity and sensationeeking) were higher in gamblers than nongamblers,hereas gamblers differed from nongamblers on only oneeurocognitive task. The association of gambling with theelf-report measures but not the majority of neurocognitiveasks suggests that peer influences may be more important athis early age than neurocognitive functions related to im-ulse control. In our sample, white youth were more likelyo gamble than youth of other ethnicities. Other investiga-ions have found different results, ranging from no differ-nce in ethnicity [9], to more frequent gambling amongatin American, African American, and American Indiandolescents [3].

Our report has a number of limitations. Our data are fromne city and from self-report measures. In designing ourrst evaluation, we had not anticipated the robust number ofreadolescents who gamble for money. Thus, for this report,e do not have data regarding type of gambling activities inhich youth participate—sports, lottery, poker—or where

hey gamble. As we now have expanded our evaluationeyond a simple yes/no interrogative to include questionsegarding specific gambling venues and activities, such data

ill be forthcoming.

onclusion

In these 10- to 12-year-olds, gambling for money was theost commonly initiated risk behavior. Preadolescents who

amble are more likely to be white, to have tried alcohol, toave a positive affect toward gambling, to have friends whongage in gambling, and less likely to have friends who dis-pprove of gambling. As gambling at a young age placesndividuals at risk for problem and pathologic gambling later inife [10], adaptation of interventions aimed at adolescents whoamble should be considered for preadolescent youth as well.

cknowledgments

This work was supported by NIDA RO1 DA 18913-01,ICHD 3P30 HD26979, and GCRC RR00240.

eferences

[1] Hardoon KK, Derevensky JL. Child and adolescent gambling behav-ior: current knowledge. In: Clinical Child Psychology and Psychiatry.London: SAGE Publication; 2002:263–81.

[2] Turchi RM, Derevensky JL. Youth gambling: not a safe bet. CurrOpin Pediatr 2006;18(4):454–8.

[3] Jacobs DF. Juvenile gambling in North America: an analysis of longterm trends and future prospects. J Gambl Stud 2000;16(2–3):119–52.

[4] Derevensky JL, Gupta R. Internet gambling amongst adolescents: agrowing concern. Int J Ment Health Addict 2007;5:93–101.

[5] LaBrie RA, Shaffer HJ. Gambling with adolescent health. J AdolescHealth 2007;40(5):387–9.

[6] Romer D, Hennessy M. A biosocial-affect model of adolescent sen-sation seeking: the role of affect evaluation and peer-group influencein adolescent drug use. Prev Sci 2007;8:89–101.

[7] Kuo P, Chih Y, Soong W, Yang H, Chen W. Assessing personalityfeatures and their relations with behavioral problems in adolescents:tridimensional personality questionnaire and junior eysenck person-ality questionnaire. Compr Psychiatry 2004;45(1):20–8.

[8] Hoyle RH, Stephenson MT, Palmgreen P, Lorch EP, Donohew RL.Reliability and validity of a brief measure of sensation seeking.Personal IndivDiff 2002;32:401–14.

[9] Pietrzak RH, Petry NM. Gambling severity and health functioning inadolescents recruited from urban primary care settings. J AdolescHealth 2006;39(5):764–6.

10] Griffiths M. Adolescent gambling: risk factors and implications forprevention, intervention, and treatment. In: Romer D, ed. ReducingAdolescent Risk—Toward an Integrated Approach. Thousand Oaks,

CA: Sage Publications, 2003:223–38.