ORIGINAL ARTICLE

Feasibility and Acceptability of a Pediatric Emergency Department Alcohol Prevention Intervention for Young Adolescents James G. Linakis, PhD, MD,* Julie Bromberg, MPH,* Janette Baird, PhD,* Ted D. Nirenberg, PhD,* Thomas H. Chun, MD, MPH,* Michael J. Mello, MD, MPH,* Kristina M. Jackson, PhD,Þ and Anthony Spirito, PhDþ

Objective: The objective of this study was to determine feasibility and acceptability of a brief pediatric emergency department (PED) prevention intervention to delay/prevent initiation of alcohol use in 12- to 14-year-olds. Methods: Medically stable 12- to 14-year-olds presenting to the PED who were accompanied by a parent and who had not initiated alcohol use were eligible. Adolescent-parent dyads completed a computerized assessment and were randomized to either brief targeted prevention intervention (BPI) or enhanced standard care (ESC). Families randomized to BPI participated in a PED-based motivational interviewing and skill buildingYbased session with a trained counselor. Parents randomized to BPI had telephone boosters at 1 and 3 months. Families randomized to ESC received standard care and adolescent substance use pamphlets. All dyads completed 6-month follow-up assessments to assess alcohol useYrelated outcomes. Results: Two hundred twenty-eight families were approached: 122 were eligible and 104 were enrolled (85%). Mean youth age was 13 (SD, 0.83) years, 51% were female, and 90% of parents were females. Of the 104 enrolled, 5 withdrew; 99 (94%) completed the assessment battery in the PED in less than 30 minutes. All BPI dyads completed the counseling session in the PED. However, only 53% of BPI parents completed the booster telephone sessions. Brief targeted prevention intervention acceptability items were rated favorably (82%Y100%) by both parents and adolescents. There were no differences between BPI and ESC on substancerelated outcomes, although the study was not adequately powered for this purpose because it was designed as a feasibility study. Conclusions: A BPI in the PED is both feasible and acceptable, but phone boosters proved less feasible. Larger samples and further study are needed to identify efficacy of the BPI in delaying onset of alcohol use in teens. Key Words: prevention, adolescent, alcohol, substance abuse (Pediatr Emer Care 2013;29: 1180Y1188)

B

oth alcohol use and high-volume alcohol use increase over the course of adolescence,1 yet the most dramatic increase in alcohol use appears to occur in relatively young adolescents,

From the *Injury Prevention Center, Department of Emergency Medicine, Rhode Island, Hospital/Alpert Medical School of Brown University, †Center for Alcohol and Addiction Studies, Brown University, and ‡Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI. Disclosure: The authors declare no conflict of interest. Reprints: James G. Linakis, PhD, MD, Pediatric Emergency Department, Claverick 2, Rhode Island Hospital, 593 Eddy St, Providence, RI 02903 (e = 0.87) and adolescent ratings (> = 0.87). The parent’s and adolescent’s assessment of parent-child communication was assessed through the Parent-Child Communication Form (PCCF).37 The parent and adolescent separately completed this measure that assessed the frequency of both positive and negative parent-to-adolescent communication over the prior 30 days. Responses are on a 5-point scale (ranging from strongly disagree = 1 to strongly agree = 5). This measure has demonstrated adequate internal consistency (Cronbach > = 0.70 for parent and 0.85 for adolescent).37 The adolescents answered 19 questions (10 negative communications and 9 positive), and parents responded to 18 questions (9 positive and 9 negative; the item ‘‘If I were in trouble, I could tell my mother/father’’ did not have an equivalent appropriate question for the parent). Negative items were reverse scored, allowing the items to be summed to provide a total communication scale score for this study, with higher scores indicating more positive or beneficial communication. The internal consistency coefficient was > = 0.58 for adolescents and > = 0.60 for parents.

Adolescent Intention to Drink and Attitudes Toward Alcohol Four questions on a 4-point scale (yes, probably yes, probably no, no) from the Youth Alcohol and Drug Survey38,39 were used to assess the adolescent’s intention to drink: ‘‘Do you plan to drink alcohol in the next year?’’ ‘‘Do you plan to drink in the next 6 months?’’ ‘‘Do you plan to drink in the next 30 days?’’ And, ‘‘If a friend offered you a drink, would you drink it?’’ In this study, the internal consistency coefficient for the 4 questions was 0.79.

PED Alcohol Prevention Intervention

and adolescent report of the involvement by the adolescent with deviant and prosocial peers. There are 3 items measuring prosocial peer involvement and 5 items measuring deviant peer involvement. Each item is measured on a 5-point scale (1Y5), with higher scores on each scale reflecting greater involvement with deviant or prosocial peers, respectively. Internal consistencies for the parent version of prosocial peer score and the deviant peer involvement scale in this study were 0.79 and 0.64, respectively. The adolescent version had an internal consistency of 0.68 for the prosocial peer involvement scale and 0.85 for the deviant peer involvement scale.

Adolescent Alcohol Consumption At the baseline assessment and at subsequent bimonthly contacts, adolescent alcohol use was assessed with a 3-question panel: ‘‘During the past 30 days, on how many days (if any) did you have at least 1 drink of alcohol?’’41 ‘‘On the days that you drank alcohol during the past 30 days, what was the usual number of drinks that you had each day?’’42 and ‘‘During the past 30 days, on how many days, if any, did you have 4 or more drinks of alcohol on the same occasion?’’42

Data Analyses Descriptive statistics and percentage responding to an item, along with the mean, median, range, as well as confidence intervals (CIs), were used to describe responses to the acceptability measures. The demographic characteristics and the baseline assessment scores of the 2 intervention conditions were compared using W2 statistics and t tests. A 2-way analysis of variance (ANOVA) model (intervention condition by time) was used to compare effects of the intervention on the outcome measures.

RESULTS The sample consisted of 99 parent-adolescent dyads (10 in the open trial and 89 in the randomized controlled trial [RCT]). Data presented are from RCT participants only. The average age of the adolescent was 13 (SD, 0.83) years, 51% were female, and 90% of parents were mothers. At baseline, there were no differences between those assigned to the BPI condition (n = 44) and ESC (n = 45) conditions on demographic variables or any of the assessment measures (Table 1).

Objective 1: Feasibility and Acceptability As can be seen from the CONSORT diagram (Fig. 1), a total of 228 families were approached about enrollment: 122 were eligible and 104 were enrolled (85%). Five subsequently TABLE 1. Demographic Characteristics of the Adolescent Sample ESC (n = 45)

BPI (n = 44)

Sex

Mean, 13.1 (SD, 0.86) Female = 46%

Mean, 13.07 (SD, 0.79) Female = 700%

Latino

Yes = 30%

Yes = 27%

Race

White = 75%

White = 67%

Type of parent present in the ED

Mother = 86%

Mother = 91%

Variable Age

Peer Measures The Child Peer and Social Skills (CPSS) Scale was developed by Dishion and Kavanagh40 and is completed by both the parent and adolescent. This 8-item scale measures the parent * 2013 Lippincott Williams & Wilkins

Statistics F2,95 = 0.02, P = 0.98 W22 = 1.96, P = 0.37 W22 = 0.17, P = 0.92 W24 = 4.31, P = 0.37 W22 = 1.76, P = 0.42

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FIGURE 1. Recruitment flow for Project Parent.

withdrew from the study (2 from the open trial and 3 from the RCT) because they were discharged from the PED and did not want to stay longer to complete the intervention. Of these 104, 99 (10 in the open trial, 89 in the RCT) completed the assessment battery (95%) in the PED in less than 30 minutes. One additional family withdrew from the study during follow-up. The BPI was considered feasible because, of those randomized to this group, 100% finished the intervention in its entirety in the PED. Feasibility of the online research follow-up assessment protocol was demonstrated by our follow-up rates: 85% of adolescents completed all the bimonthly follow-ups assessing substance use, and 92% of adolescents (95% of control adolescents, 89% of intervention adolescents) and 90% of parents (89% of control adolescents, 91% of intervention adolescents) completed the 6-month follow-up. Telephone booster rates were not as encouraging, with only 53% and 38% of those in the BPI condition completing their first and second telephone booster contacts, respectively. Overall acceptability by the teen participants was evaluated with the items on the SEF. The percentage of teen participants

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rating the items as strongly agree or agree can be seen in Table 2, along with the mean, median, range, and CI for each item. Parents were also asked to complete 2 questions about the content of the session. A total of 93% of parents rated as ‘‘agree’’ or ‘‘strongly agree’’ with the item ‘‘Made me feel it was up to me to make choices about my parenting.’’ Also, 93% rated as ‘‘agree’’ or ‘‘strongly agree’’ with the item ‘‘Gave me some helpful ideas for helping my teen avoid alcohol, tobacco, and marijuana.’’

Objective 2: Parental Monitoring and Communication, Adolescent Intentions Regarding Substance Use, and Peer Influence on Intentions to Use Substances The PCCF, completed by adolescents and parents at baseline and at the 6-month follow-up surveys, was used to assess parent-adolescent communication (Table 3). Two-way ANOVAs were conducted on the difference between adolescent and parental reports of parental communication over time as a function of treatment received. Adolescent report of parental * 2013 Lippincott Williams & Wilkins

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PED Alcohol Prevention Intervention

TABLE 2. Baseline Intervention Session Acceptability Among Adolescent and Parent Participants

Adolescent (n = 39) From this session Learned a lot Able to apply what I learned Given an opportunity to participate Session was well organized Topic of session was interesting Presenter stimulated my interest Topic of this session was relevant to my life Session was enjoyable I would recommend session I felt comfortable participating Parent (n = 39) The counselor was Easy to talk to Concerned about me Understood me Helped me believe that I can help my teenager Argued with me Told me what to do Treated me like an equal Made me feel that it is up to me to make choices about my parenting Gave me some helpful ideas for helping my teen avoid alcohol, tobacco, and marijuana Gave me the chance to ask questions

Percentage Rating Agree/Strongly Agree

Mean

Median

Range

95% CI

97% 100% 97% 100% 100% 97% 82% 100% 95% 95%

2.54 2.69 2.51 2.67 2.49 2.46 2.21 2.51 2.54 2.54

3 3 3 3 2 2 2 3 3 3

1Y3 2Y3 1Y3 2Y3 2Y3 1Y3 0Y3 2Y3 1Y3 1Y3

2.45Y2.63 2.62Y2.76 2.42Y2.60 2.59Y2.75 2.40Y2.58 2.38Y2.54 2.06Y2.36 2.43Y2.59 2.44Y2.64 2.44Y2.64

100% 87% 100% 100% 17% 27% 100% 93%

2.97 2.43 2.83 2.86 0.53 0.90 2.78 2.50

3 3 3 3 0 0 3 3

2Y3 0Y3 2Y3 2Y3 0Y3 0Y3 2Y3 1Y3

2.90Y3.03 2.10Y2.77 2.69Y2.97 2.74Y3.00 0.16Y0.91 0.43Y1.37 2.61Y2.93 2.26Y2.74

93%

2.50

3

1Y3

2.26Y2.74

100%

2.80

3

2Y3

2.65Y2.95

communication skills did not significantly vary by group (F1,165 = 1.78, P = 0.19), but did significantly increase over time (F1,165 = 5.93, P = 0.02), although this significant increase over time was not significantly different between groups (F1,165 = 1.02, P = 0.31). As seen in Table 3, parental reports of communication were lower at baseline than that of the adolescents and significantly increased over time (F1,165 = 182.48, P G 0.001), although this difference did not vary by group (F1,165 = 1.09, P = 0.30). Parental monitoring was assessed with the PMQ, which was completed by the adolescents and parents at baseline and at the 6-month follow-up surveys (Table 3). The adolescent report of parental monitoring was not significantly different between groups (F1,165 = 0.42, P = 0.52) and did significantly decrease over time across the groups (F1,165 = 3.85, P = 0.05), but the decrease over time was not significantly different between

groups (F1,165 = 1.74, P = 0.19). Parental reports of monitoring also significantly decreased over time (F1,165 = 151.52, P G 0.001), but this difference did not vary by group (F1,165 = 0, P = 0.99). Collapsing the percentage decrease in the reports of parental monitoring from baseline to the 6-month survey, the adolescents mean decrease of 5% (95% CI, 1%Y9%) is significantly less than the 25% (95% CI, 19%Y39%) mean decrease in parental reports of monitoring behavior. Adolescent intentions toward alcohol use at baseline and 6-month follow-up are presented in Table 4. We created a binary outcome for each response yes or no for intent to drink in the 4 listed scenarios. Using a binomial test of proportions, it can be seen from Table 4 that participants in both groups reported increased likelihood to drink in the 4 scenarios, but the only significant increase for both groups between the baseline and

TABLE 3. Adolescent and Parent Report on Parenting Measures of Monitoring and Communication Measure

Baseline Mean (SD)

PCCF adolescent version PCCF parent version PMQ adolescent version PMQ parent version

ESC BPI ESC BPI ESC BPI ESC BPI

(n (n (n (n (n (n (n (n

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= 44); = 45); = 44); = 45); = 44); = 45); = 44); = 45);

mean, mean, mean, mean, mean, mean, mean, mean,

71.38 (9.06); range, 41Y85 70.81 (8.31); range, 52Y84 53.73 (9.24); range, 44Y69 58.28 (9.18); range, 44Y79 93.91 (13.92); range, 59Y120 95.51 (15.99); range, 54Y93 101.64 (21.17); range, 11Y120 102.62 (10.19); range, 77Y117

6-mo Mean (SD) ESC (n = 41); mean, 77.41 (10.53); range, 55Y93 BPI (n = 39); mean, 73.31 (16.50); range, 52Y95 ESC (n = 37); mean, 73.96 (8.93); range, 44Y86 BPI (n = 39); mean, 75.61 (7.20); range, 57Y86 ESC (n = 41); mean, 92.38 (15.99); range, 32Y112 BPI (n = 39); mean, 87.68 (17.18); range, 43Y112 ESC (n = 37); mean, 72.32 (13.00); range, 33Y87 BPI (n = 39); mean, 73.35 (13.30); range, 30Y89 www.pec-online.com

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TABLE 4. Adolescent Intention to Drink and Attitudes Toward Alcohol Use

Would drink if a friend offered you a drink Intend to use alcohol in the next year Intend to use alcohol in the next 6 mo Intend to use alcohol in the next month

Treatment

Baseline % Yes

6-mo % Yes

ESC BPI ESC BPI ESC BPI ESC BPI

5 7 7 7 7 2 0 2

10 16 27 25 10 11 5 5

6-month surveys was in the intent to use alcohol sometime in the next year (ESC increase 7% to 27%, Z = 2.71, P = 0.006; BPI increase 7% to 25%, Z = 2.49, P = 0.012). Peer influences on the CPSS Scale are reported in Table 5. Two-way ANOVAs were conducted to examine adolescent and parent ratings of adolescent prosocial and deviant peer involvement at the baseline and 6-month surveys. The adolescents’ ratings of their association with prosocial peers showed a decrease from baseline to 6 months for both groups, although this change was not significant across groups (F1,165 = 2.11, P = 0.15) or between groups (F1,165 = 0.27, P = 0.60). Adolescents’ report of association with deviant peers did not significantly increase over time (F1,165 = 2.38, P = 0.13), and there was no difference across groups (F1,165 = 0.08, P = 0.77). For parent ratings of their adolescents’ association with prosocial peers, there were no effects of group (F1,165 = 0.22, P = 0.64) or time (F1,165 = 0.71, P = 0.40) or an interaction (F1,165 = 0, P = 0.96). There were also no significant effects for parents’ ratings of their adolescent’s association with deviant peers-bygroup (F1,165 = 1.24, P = 0.27), time (F1,165 = 0.93, P = 0.34), or group-by-time interaction (F1,165 = 0.02, P = 0.88).

Objective 3: Adolescent Alcohol Use Three adolescents reported alcohol use, of more than a sip, at baseline. There was very little alcohol use reported in the 6-month time frame in the group of young adolescents who did not use alcohol at baseline. During the 6-month follow-up period, 4 teens in the BPI condition and 1 teen in the ESC condition reported alcohol use, of more than a sip, during follow-up. Only one of the teens, in the BPI condition, who reported baseline use also reported use at follow-up.

DISCUSSION The primary focus of this study was to conduct a pilot study within the PED to determine the acceptability of an

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alcohol prevention intervention among parent and adolescents and to demonstrate that such a prevention intervention can be feasibly conducted within the PED. Our data suggest that most eligible parents and adolescents were willing to engage in such a prevention intervention and reported finding it a helpful experience. About 85% of the eligible parents approached to participate agreed to do so, and all completed the assessment in the PED while awaiting their medical care. Five families completed the assessment but not the intervention because they were discharged from the PED and did not want to stay longer. Interestingly, there were a few families who were discharged but did choose to stay and finish the intervention. The large majority of adolescents and parents completed the online follow-up assessments suggesting that families seen in a PED can be successfully contacted to provide data online. Completing follow-ups online decreases cost and therefore greatly increases the feasibility of future studies due to the fact that a large sample will be necessary to establish the potential effects of the prevention intervention in an appropriately powered RCT. The BPI described here is unique in that it is primarily parent-targeted, delivered where parents are foundVthe PEDV and individually tailored to the parent rather than being a generic skills-based program that is identical for all participants. Individually tailored approaches, while common in intervention protocols, are uncommon in prevention intervention programs. Nonetheless, even with the personal tailoring, sessions were typically completed in 25 to 40 minutes, which would appear to be a feasible duration for most PEDs given current lengths of stay. Comments about the session indicated that nearly all of the teen participants felt it was useful, relevant, and enjoyable and would recommend it to others. Parents were equally, if not more, positive about the content of the intervention. Parent willingness to complete telephone booster sessions was low, suggesting that continued booster intervention by phone is neither acceptable to parents nor feasible for investigators. As this was a prevention intervention, parents may have felt less motivated to participate in an active booster intervention because the boosters were set within 3 months of enrollment, and few teens would have initiated alcohol use, and parents would typically not have new issues to address with the counselor. Future studies might consider other methods of administering booster prevention interventions. Mailings, online material, or text messaging, over a longer period, may be better ways to provide booster information to parents after a brief intervention in PEDs. Although the primary goal of this project was to determine if it was feasible to deliver a prevention intervention in the PED, we also collected data regarding any change in teen intentions to use alcohol and attitudes toward alcohol use, given that these are strongly predictive of subsequent use.43,44 We did find in both groups an increase in adolescent intentions to use alcohol.

TABLE 5. Adolescent and Parent CPSS Scale Measure

Baseline Mean (SD)

Prosocial peer involvement, adolescent version Prosocial peer involvement, parent version Deviant peer involvement, adolescent version Deviant peer involvement, parent version

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ESC BPI ESC BPI ESC BPI ESC BPI

(n (n (n (n (n (n (n (n

= = = = = = = =

44); 45); 44); 45); 44); 45); 44); 45);

mean, mean, mean, mean, mean, mean, mean, mean,

9.56 (2.01); range, 3Y13 9.02 (2.52); range, 1Y12 8.11 (1.21); range, 4Y10 8.00 (1.30); range, 5Y12 7.58 (2.92); range, 2Y16 8.21 (4.29); range, 5Y24 22.39 (4.50); range, 2Y25 22.93 (3.23); range, 9Y25

6-mo Mean (SD) ESC (n = 41); mean, 9.20 (2.32); range, 4Y13 BPI (n = 39); mean, 8.26 (2.95); range, 1Y13 ESC (n = 37); mean, 7.92 (8.93); range, 44Y86 BPI (n = 39); mean, 7.84 (1.43); range, 3Y10 ESC (n = 41); mean, 8.38 (4.01); range, 5Y22 BPI (n = 39); mean, 9.37 (4.81); range, 5Y23 ESC (n = 37); mean, 22.85 (3.87); range, 7Y25 BPI (n = 39); mean, 23.55 (1.89); range, 19Y25 * 2013 Lippincott Williams & Wilkins

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This finding suggests a normal developmental trajectory for adolescents and suggests that the parent-focused intervention did not have any dampening effect on this trajectory. These findings suggest that future intervention research should place more emphasis on addressing adolescent cognitions in the parent portion of the BPI. Alternatively, or in addition to this added emphasis with parents, working directly with the adolescent to address cognitions in the prevention program might lead to greater effects on such cognition. The finding that parental monitoring decreased in both groups may reflect the fact that only a few teens in the study reported alcohol use over the course of the follow-up, so parents may have not felt the need to increase their monitoring over this short period and, in fact, may have become somewhat complacent. Alternatively, failure of our booster sessions to increase the strength of the preventive intervention may be at fault here. It may be necessary to implement more powerful boosters, whether they be in-person or through the use of more engaging technology such as text messaging and Web-based programs because we had difficulty completing our phone boosters. Another less likely explanation might be that the difference in the data collection method at baseline and follow-up, that is, on a computer tablet in the ED and completion on a home computer or over the telephone with research staff (if internet not available), may have resulted in differential reporting of parental monitoring. We were not able to detect any between-group differences in these constructs. It is likely that this was, at least in part, due to the small number of subjects in each group. In addition, the endorsement of intent to drink under different circumstances was reported by very few teens at baseline and remained low at the 6-month follow-up for both groups, suggesting that there was a ceiling effect; that is, there was not much room to improve at the 6-month follow-up, regardless of treatment condition. Other measurement issues may have also affected our ability to detect differences in the constructs studied here. The internal consistency of several of our measures was lower than that found by the scale developers. Thus, the applicability of some of the measures, especially those assessing parenting, could be questioned. Future studies might consider more sensitive measures of parent-adolescent interaction. Several factors may have affected our ability to detect differences between conditions. First, younger adolescents are more strongly affected by attitudes of their parents45 than older adolescents, which was part of the rationale for selecting 12- to 14-year-olds for this study. If we had selected an older cohort for inclusion in the project, then it is possible that we would have been able to detect a treatment condition difference because the rates of use would have, in all likelihood, been higher. Second, if we had selected adolescents who were at high risk to start drinking, for example, those with older siblings drinking alcohol, teens with existing behavioral and/or school problems, teens seen at the ED for an alcohol-related event, or teens presenting to the ED without a parent, then we might have been able to detect an effect on initiation of alcohol use. And third, any positive effects of the intervention may have been much more likely to be detected at a longer follow-up period as the teens transitioned into high school and had more exposure to AOD use. Because the major goal of this study was to test the feasibility of conducting a prevention intervention in the PED, we did not have sufficient resources to conduct such long-term follow-up.

CONCLUSIONS The PED is an important site for alcohol screening and brief intervention. The National Institute on Alcohol and * 2013 Lippincott Williams & Wilkins

PED Alcohol Prevention Intervention

Alcoholism’s Alcohol Screening and Brief Intervention for Youth: A Practitioner’s Guide27 recommends brief advice for teens identified as having low alcohol risk. This research protocol utilized a brief MI-based approach, addressing parental monitoring and communication. The 2 approaches complement each other. Nonetheless, in order for PED clinicians to consider implementing AOD prevention, research is necessary in PEDs to determine if alcohol prevention interventions can be conducted in the PED. This study demonstrated that a preventive intervention with young adolescents and their parents is feasible and acceptable and can be presented while the adolescent is being treated in the PED for a medical concern. Sessions were typically completed in 25 to 40 minutes, which would appear to be a feasible duration for most PEDs given current lengths of stay. If such a preventive intervention is shown to be effective in a larger trial, then a computerized version of the program might be developed and tested in the PED to improve its potential for dissemination. Although some outcome data are presented here, this study was primarily a feasibility study. The current study did not allow us to recruit an adequate number of families to measure prevention/delay of teen alcohol initiation over an adequately long period. Prevention studies are typically conducted with much larger samples. For example, to find a 20% improvement in parenting in the experimental group versus a 10% improvement in the control group, the study would require 200 subjects per group. Future, larger, fully powered studies are necessary to determine the effectiveness of PEDbased prevention interventions. REFERENCES 1. SAMHSA. Results From the 2006 National Survey on Drug Use and Health: National Findings. Rockville, MD: Office of Applied Studies; 2007. 2. 1991-2011 High School Youth Risk Behavior Survey Data. Available at: http://apps.nccd.cdc.gov/youthonline. Accessed July 18, 2012. 3. Dawson DA, Goldstein RB, Chou SP, et al. Age at first drink and the first incidence of adult-onset DSM-IV alcohol use disorders. Alcohol Clin Exp Res. 2008;32:2149Y2160. 4. Gruber E, DiClemente RJ, Anderson MM, et al. Early drinking onset and its association with alcohol use and problem behavior in late adolescence. Prev Med. 1996;25:293Y300. 5. Hawkins JD, Catalano RF, Kosterman R, et al. Preventing adolescent health-risk behaviors by strengthening protection during childhood. Arch Pediatr Adolesc Med. 1999;153:226Y234. 6. Williams R, Chang S. A comprehensive and comparative review of adolescent substance abuse treatment outcome. Clin Psychol Sci Pract. 2000;7:138Y166. 7. Monti PM, Colby SM, Barnett NP, et al. Brief intervention for harm reduction with alcohol-positive older adolescents in a hospital emergency department. J Consult Clin Psychol. 1999;67:989Y994. 8. Spirito A, Monti PM, Barnett NP, et al. A randomized clinical trial of a brief motivational intervention for alcohol-positive adolescents treated in an emergency department. J Pediatr. 2004;145:396Y402. 9. Mason WA, Kosterman R, Hawkins JD, et al. Reducing adolescents’ growth in substance use and delinquency: randomized trial effects of a parent-training prevention intervention. Prev Sci. 2003;4:203Y212. 10. Spoth R, Redmond C, Lepper H. Alcohol initiation outcomes of universal family-focused preventive interventions: one- and two-year follow-ups of a controlled study. J Stud Alcohol Suppl. 1999;13: 103Y111. 11. Faggiano F, Vigna-Taglianti FD, Versino E, et al. School-based prevention for illicit drugs’ use. Cochrane Database Syst Rev. 2005:CD003020.

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12. Tobler N, Roona NS, Ochshorn MR, et al. School-based adolescent drug prevention programs: 1998 meta-analysis. J Prim Prev. 2000;20: 275Y336. 13. Chun TH, Linakis JG. Interventions for adolescent alcohol use. Curr Opin Pediatr. 2012;24:238Y242. 14. Foxcroft DR, Tsertsvadze A. Universal school-based prevention programs for alcohol misuse in young people. Cochrane Database Syst Rev. 2011;5:CD009113. 15. Foxcroft DR, Tsertsvadze A. Universal multi-component prevention programs for alcohol misuse in young people. Cochrane Database Syst Rev. 2011;9:CD009307. 16. Mauss AL, Hopkins RH, Weisheit RA, et al. The problematic prospects for prevention in the classroom: should alcohol education programs be expected to reduce drinking by youth? J Stud Alcohol. 1988;49:51Y61. 17. McKnight A. Intervention with alcohol-impaired drivers by peers, parents and purveyors of alcohol. Health Educ Res. 1990;3:225Y236. 18. Smit E, Verdurmen J, Monshouwer K, et al. Family interventions and their effect on adolescent alcohol use in general populations; a meta-analysis of randomized controlled trials. Drug Alcohol Depend. 2008;97:195Y206.

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29. Miller WR, Rollnick S. Motivational Interviewing: Preparing People for Change. New York, NY: Guilford Press; 2002. 30. Miller WR. Motivation for treatment: a review with special emphasis on alcoholism. Psychol Bull. 1985;98:84Y107. 31. Miller WR, Sovereign RG. The check-up: a model for early intervention in addictive behaviors. In: Loberg T, Nathan PE, Marlatt GA, eds. Addictive Behaviors: Prevention and Early Intervention. Amsterdam: Swits & Zeitlinger; 1989:219Y231. 32. Revised Global Scales: Motivational Interviewing Treatment Integrity 3.1.1 (MITI 3.1.1). University of New Mexico, 2010. Available at: http:// casaa.unm.edu/download/MITI3_1.pdf. Accessed December 12, 2012. 33. Clifford PR, Maisto SA. Subject reactivity effects and alcohol treatment outcome research. J Stud Alcohol. 2000;61:787Y793. 34. McCambridge J, Kypri K. Can simply answering research questions change behaviour? Systematic review and meta analyses of brief alcohol intervention trials. PLoS One. 2011;6:e23748. 35. Harper G, Contreras R, Bangi A, et al. Collaborative process evaluation: enhancing community relevance and cultural appropriateness in HIV prevention. J Prev Interv Community. 2003;26:53Y71.

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Feasibility and acceptability of a pediatric emergency department alcohol prevention intervention for young adolescents.

The objective of this study was to determine feasibility and acceptability of a brief pediatric emergency department (PED) prevention intervention to ...
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