Hostname: page-component-f554764f5-rvxtl Total loading time: 0 Render date: 2025-04-12T05:11:57.076Z Has data issue: false hasContentIssue false
  • English
  • Français

Combined universal and selective prevention for adolescent alcohol use: a cluster randomized controlled trial

Published online by Cambridge University Press:  22 February 2017

M. Teesson ,
N. C. Newton ,
T. Slade ,
N. Carragher ,
E. L. Barrett ,
K. E. Champion ,
E. V. Kelly ,
N. K. Nair ,
L. A. Stapinski  and
P. J. Conrod
M. Teesson*
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
N. C. Newton
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
T. Slade
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
N. Carragher
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia Office of Medical Education, University of New South Wales, Sydney, NSW, Australia
E. L. Barrett
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
K. E. Champion
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
E. V. Kelly
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
N. K. Nair
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
L. A. Stapinski
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
P. J. Conrod
Affiliation:
Department of Psychiatry, Université de Montréal, Montréal, Quebec, Canada Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
*
*Address for correspondence: M. Teesson, B.Psych. (Hons), Ph.D., NHMRC Centre of Research Excellence in Mental Health and Substance Use (CREMS), National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW 2052, Australia. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

No existing models of alcohol prevention concurrently adopt universal and selective approaches. This study aims to evaluate the first combined universal and selective approach to alcohol prevention.

Method

A total of 26 Australian schools with 2190 students (mean age: 13.3 years) were randomized to receive: universal prevention (Climate Schools); selective prevention (Preventure); combined prevention (Climate Schools and Preventure; CAP); or health education as usual (control). Primary outcomes were alcohol use, binge drinking and alcohol-related harms at 6, 12 and 24 months.

Results

Climate, Preventure and CAP students demonstrated significantly lower growth in their likelihood to drink and binge drink, relative to controls over 24 months. Preventure students displayed significantly lower growth in their likelihood to experience alcohol harms, relative to controls. While adolescents in both the CAP and Climate groups demonstrated slower growth in drinking compared with adolescents in the control group over the 2-year study period, CAP adolescents demonstrated faster growth in drinking compared with Climate adolescents.

Conclusions

Findings support universal, selective and combined approaches to alcohol prevention. Particularly novel are the findings of no advantage of the combined approach over universal or selective prevention alone.

Keywords

Alcoholpreventionschool-based programmesselective preventionuniversal prevention.
Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 10 , July 2017 , pp. 1761 - 1770
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

†

Equally credited authors.

References

Andrews, G, Henderson, S, Hall, W (2001). Prevalence, comorbidity, disability and service utilisation. Overview of the Australian National Mental Health Survey. British Journal of Psychiatry 178, 145–153.Google Scholar
Botvin, GJ (2004). Advancing prevention science and practice: challenges, critical issues, and future directions. Prevention Science 5, 69–72.Google Scholar
Botvin, GJ, Griffin, KW, Diaz, T, Scheier, LH, Williams, C, Epstein, JA (2000). Preventing illicit drug use in adolescents: long-term follow-up data from a randomized control trial of a school population. Addictive Behaviors 25, 769–774.Google Scholar
Brown, EC, Catalano, RF, Fleming, CB, Haggerty, KP, Abbott, RD (2005). Adolescent substance use outcomes in the Raising Healthy Children project: a two-part latent growth curve analysis. Journal of Consulting and Clinical Psychology 73, 699–710.Google Scholar
Browne, M, Cudeck, R (1993). Alternative ways of assessing model fit. Sociological Methods and Research 21, 230–258.Google Scholar
Cameron, AC, Miller, DL (2015). A practitioner's guide to cluster-robust inference. Journal of Human Resources 50, 317–372.Google Scholar
Castellanos-Ryan, N, O'Leary-Barrett, M, Sully, L, Conrod, P (2013). Sensitivity and specificity of a brief personality screening instrument in predicting future substance use, emotional, and behavioral problems: 18-month predictive validity of the substance use risk profile scale. Alcoholism: Clinical and Experimental Research 37, E281–E290.Google Scholar
Conrod, PJ, Castellanos, N, Mackie, C (2008). Personality-targeted interventions delay the growth of adolescent drinking and binge drinking. Journal of Child Psychology and Psychiatry 49, 181–190.Google Scholar
Conrod, PJ, O'Leary-Barrett, M, Newton, N, Topper, L, Castellanos-Ryan, N, Mackie, C, Girard, A (2013). Effectiveness of a selective, personality-targeted prevention program for adolescent alcohol use and misuse: a cluster randomized controlled trial. JAMA Psychiatry 70, 334–342.Google Scholar
Del Boca, FK, Darkes, J (2003). The validity of self-reports of alcohol consumption: state of the science and challenges for research. Addiction 98 (Suppl. 2), 1–12.Google Scholar
Fleming, P, Koletsi, D, Polychronopoulou, A, Eliades, T, Pandis, N (2013). Are clustering effects accounted for in statistical analysis in leading dental specialty journals? Journal of Dentistry 41, 265–270.Google Scholar
Foxcroft, DR (2014). Can prevention classification be improved by considering the function of prevention? Prevention Science 15, 818–822.Google Scholar
Foxcroft, DR, Tsertsvadze, A (2011). Universal school-based prevention programs for alcohol misuse in young people. Cochrane Database of Systematic Reviews, issue 5, CD009113.Google Scholar
Foxcroft, DR, Tsertsvadze, A (2012). Universal alcohol misuse prevention programmes for children and adolescents: Cochrane systematic reviews. Perspectives in Public Health 132, 128–134.Google Scholar
Gore, FM, Bloem, PJ, Patton, GC, Ferguson, J, Joseph, V, Coffey, C, Sawyer, SM, Mathers, CD (2011). Global burden of disease in young people aged 10–24 years: a systematic analysis. Lancet 377, 2093–2102.Google Scholar
Gowing, LR, Ali, RL, Allsop, S, Marsden, J, Turf, EE, West, R, Witton, J (2015). Global statistics on addictive behaviours: 2014 status report. Addiction 110, 904–919.CrossRefGoogle ScholarPubMed
Gratz, K, Tull, M, Levy, R (2014). Randomized controlled trial and uncontrolled 9-month follow-up of an adjunctive emotion regulation group therapy for deliberate self-harm among women with borderline personality disorder. Psychological Medicine 44, 2099–2112.CrossRefGoogle ScholarPubMed
Henry, KL, McDonald, JN, Oetting, ER, Walker, PS, Walker, RD, Beauvais, F (2011). Age of onset of first alcohol intoxication and subsequent alcohol use among urban American Indian adolescents. Psychology of Addictive Behaviors 25, 48–56.Google Scholar
Hibell, B, Guttormsson, U, Ahlström, S, Balakireva, O, Bjarnason, T, Kokkevi, A, Kraus, L (2007). The 2007 ESPAD Report: Substance Use Among Students in 35 European Countries, European School Survey Project on Alcohol and Other Drugs. Stockholm, Sweden (http://www.ias.org.uk/uploads/pdf/News%20stories/espad-report-mar09.pdf).Google Scholar
Ichiyama, MA, Fairlie, AM, Wood, MD, Turrisi, R, Francis, DP, Ray, AE, Stanger, LA (2009). A randomized trial of a parent-based intervention on drinking behavior among incoming college freshmen. Journal of Studies on Alcohol and Drugs 16, 67–76.Google Scholar
Lai, HMX, Cleary, M, Sitharthan, T, Hunt, GE (2015). Prevalence of comorbid substance use, anxiety and mood disorders in epidemiological surveys, 1990–2014: a systematic review and meta-analysis. Drug and Alcohol Dependence 154, 1–13.Google Scholar
Newton, NC, Barrett, EL, Castellanos-Ryan, N, Kelly, E, Champion, KE, Stapinski, L, Conrod, PJ, Slade, T, Nair, N, Teesson, M (2016 a). The validity of the Substance Use Risk Profile Scale (SURPS) among Australian adolescents. Addictive Behaviors 53, 23–30.Google Scholar
Newton, NC, Conrod, PJ, Slade, T, Carragher, N, Champion, KE, Barrett, EL, Kelly, E, Nair, N, Stapinski, L, Teesson, M (2016 b). The long-term effectiveness of a selective, personality-targeted prevention program in reducing alcohol use and related harms: a cluster randomised controlled trial. Journal of Child Psychology and Psychiatry 57, 1056–1065.Google Scholar
Newton, NC, Teesson, M, Barrett, EL, Slade, T, Conrod, PJ (2012). The CAP study, evaluation of integrated universal and selective prevention strategies for youth alcohol misuse: study protocol of a cluster randomized controlled trial. BMC Psychiatry 12, 118.Google Scholar
Newton, NC, Teesson, M, Vogl, LE, Andrews, G (2010). Internet-based prevention for alcohol and cannabis use: final results of the Climate Schools course. Addiction 105, 749–759.Google Scholar
Newton, NC, Vogl, LE, Teesson, M, Andrews, G (2009). CLIMATE Schools: alcohol module: cross-validation of a school-based prevention programme for alcohol misuse. Australian and New Zealand Journal of Psychiatry 43, 201–207.Google Scholar
Preisser, JS, Reboussin, BA, Song, EY, Wolfson, M (2007). The importance and role of intracluster correlations in planning cluster trials. Epidemiology 18, 552–560.Google Scholar
Sartor, CE, Lynskey, MT, Heath, AC, Jacob, T, True, W (2007). The role of childhood risk factors in initiation of alcohol use and progression to alcohol dependence. Addiction 102, 216–225.CrossRefGoogle ScholarPubMed
Schafer, JL, Graham, JW (2002). Missing data: our view of the state of the art. Psychological Methods 7, 147–177.Google Scholar
Strøm, HK, Adolfsen, F, Fossum, S, Kaiser, S, Martinussen, M (2014). Effectiveness of school-based preventive interventions on adolescent alcohol use: a meta-analysis of randomized controlled trials. Substance Abuse Treatment, Prevention, and Policy 9, 48.Google Scholar
Teesson, M, Hall, W, Slade, T, Mills, K, Grove, R, Mewton, L, Baillie, A, Haber, P (2010). Prevalence and correlates of DSM-IV alcohol abuse and dependence in Australia: findings of the 2007 National Survey of Mental Health and Wellbeing. Addiction 105, 2085–2094.Google Scholar
White, H, Labouvie, E (1989). Towards the assessment of adolescent problem drinking. Journal of Studies on Alcohol 50, 30–37.Google Scholar
Whiteford, HA, Degenhardt, L, Rehm, J, Baxter, AJ, Ferrari, AJ, Erskine, HE, Charlson, FJ, Norman, RE, Flaxman, AD, Johns, N, Burstein, R, Murray, CJL, Vos, T (2013). Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet 382, 1575–1586.Google Scholar
Woicik, PA, Stewart, SH, Pihl, RO, Conrod, PJ (2009). The substance use risk profile scale: a scale measuring traits linked to reinforcement-specific substance use profiles. Addictive Behaviors 34, 1042–1055.Google Scholar
Wood, MD, Fairlie, AM, Fernandez, AC, Borsari, B, Capone, C, Laforge, R, Carmona-Barro, R (2010). Brief motivational and parent interventions for college students: a randomized factorial study. Journal of Consulting and Clinical Psychology 78, 349–361.Google Scholar
Worley, MJ, Trim, RS, Roesch, SC, Mrnak-Meyer, J, Tate, SR, Brown, SA (2012). Comorbid depression and substance use disorder: longitudinal associations between symptoms in a controlled trial. Journal of Substance Abuse Treatment 43, 291–302.Google Scholar
Supplementary material: File

Teesson supplementary material

Teesson supplementary material

Download Teesson supplementary material(File)
File 346.6 KB