1. Influences of group Identity on Smoking, Alcohol, and Drug Use Kirsten Verkooijen, Ph.D. student Dep. of Health Promotion Research University of Southern Denmark Esbjerg Gert A. Nielsen, Ph.D. Dep. of Prevention and Documentation Danish Cancer Society Copenhagen

2. Adolescence Increased engagement in risk behaviour Increased affiliation with peers Focus of this study: How is adolescents’ engagement in smoking, hash and alcohol use related to group membership?

3. Group membership Subculture: a social group within a national culture that has distinctive patterns of behavior and beliefs (hyperdictionary) Related terms: peer group, crowd, youth culture, clique, etc. Function of peer groups (Urberg): Source of identity Channel for friendship selection

4. The balanced Identity Design (Greenwald et al., 2002) Reciprocal associations between the self, group and behaviour: 1. Self - Group 2. Group - Behaviour 3. Behaviour - Self People tend to keep the 3 associations balanced! Greenwald, A.G., Banaji, M.R., Rudman, L.A., Farnham, S.D., Nosek, B.A., Mellott, D.S. (2002). A unified theory of implicit attitudes, stereotypes, self-esteem, and self-concept. Psychological Review, 109, 3-25.

5. Data collection When: November 2002 What: MULD (Monitoring of Young people’s Lifestyle and Everyday life) survey conducted by The Danish Cancer Society and Danish Board of Health Who: 3956 Danes in the age of 16-20 completed the posted questionnaire (response-rate 60%)

6. Self-report meassures Items on smoking, alcohol and drug use Group identity items: ’would you agree if a friend called you [...]?’ Perceived group behaviour items: ’how likely is a member of [...] to smoke/use hash?’ 9 group names, based on prior discussions with the target population, were provided: sporty, pop boy/girl, hip-hopper/skater, bodybuilder, quiet boy/girl, techno freak, computer nerd, religious, hippie. Answers were given on a 5-point scale

7. Results The data analysis included only subjects with 1 single group affiliation (N=1444; 38,3% of the original sample) sporty (n=608) pop (n=160) skate/hiphop (n=61) quiet (n=296) techno (n=45) religious (n=60) hippie (n=136) computer nerds (n=59) Bodybuilders (n=19) were left out as their sample was too small

8. Results for smoking_1 General smoking prevalence: 31,8% (boys: 32,2%; girls: 31,5%) Fig. 1: Smoking prevalence (%) by group membership

9. Results for smoking_2 Fig. 2: Perceived smoking among own group (1=very unlikely; 5=very likely) by group membership

10. Results for smoking_3 Fig. 3: Smoking prevalence (%) by perceived smoking among own group

11. Results for smoking_4 Before adjustment for perceived group behaviour After adjustment for perceived group behaviour O.R.95% C.I.O.R.95% C.I. SEX1.050.82 - 1.361.090.84 - 1.42 AGE1.14*1.05 - 1.241.13*1.03 - 1.23 GROUP ID: -Sporty0.51**0.40 - 0.640.790.59 - 1.06 -Pop1.89**1.36 - 2.641.290.90 - 1.86 -Skate/hiphop1.61*1.00 - 2.611.050.63 - 1.75 -Quiet0.49**0.36 - 0.660.67*0.49 - 0.93 -Techno1.92*1.11 - 3.321.230.69 - 2.19 -Computer0.58*0.34 - 0.990.690.39 - 1.24 -Religious0.44*0.25 - 0.790.620.34 - 1.14 -Hippie1.79**1.26 - 2.541.220.84 - 1.77 PERCEPTION1.63**1.40 - 1.89 Table 1: Logistic regression odds ratios for smoking **p<.001, *p<.05

12. Results for hash_1 Fig. 4: Last month hash use prevalence (%) by group membership General last month hash use prevalence: 10,5% (boys: 17,0%; girls: 6,4%)

13. Results for hash_2 Fig. 5: Perceived group hash use (1=very unlikely; 5= very likely) by group membership

14. Results for hash_3 Fig. 6: % hash users (last month) by perceived group hash use

15. Results for hash_4 Before adjustment for perceived group behaviour After adjustment for perceived group behaviour O.R.95% C.I.O.R.95% C.I. SEX3.60**2.39 – 5.413.58**2.35 – 5.45 AGE1.17*1.02 – 1.331.120.97 – 1.28 GROUP IDENTITY: -Sporty0.40**0.26 – 0.600.660.41 – 1.06 -Pop1.020.59 – 1.750.790.44 – 1.41 -Skate/hiphop2.89**1.66 – 5.021.300.69 – 2.45 -Quiet0.44*0.26 – 0.760.650.35 – 1.12 -Techno1.770.86 – 3.631.300.61 – 2.78 -Computer0.520.23 – 1.160.650.28 – 1.51 -Religious0.410.14 – 1.190.820.28 – 2.51 -Hippie4.85**3.10 – 7.612.05*1.18 – 3.57 PERCEPTION1.73**1.18 – 3.57 Table 2: Logistic regression odds ratios for hash use **p<.001, *p<.05

16. Results for alcohol_1 General last month drunkeness prevalence: 68,3% (boys: 74,8%; girls: 64,3%) Fig. 7: % been drunk (last month) by group membership

17. Results for alcohol_2 O.R.95% C.I. SEX1.76**1.36 – 2.27 AGE1.11*1.02 – 1.20 GROUP IDENTITY: -Sporty1.130.88 – 1.46 -Pop1.47*1.00 – 2.16 -Skate/hiphop1.380.77 – 2.46 -Quiet0.55**0.42 – 0.74 -Techno1.080.59 – 1.99 -Computer0.640.38 – 1.09 -Religious0.29**0.17 – 0.48 -Hippie2.85**1.78 – 4.56 Table 3: Logistic regression odds ratios for last month drunkenness **p<.001, *p<.05

18. Summary results Group membership related to all 3 risk behaviours Results showed 4 ’high-risk’ groups and 4 ’low-risk’ groups. This distinction was most evident for smoking and least evident for alcohol Group perception related strongly to personal behaviour SmokingHashAlcohol Quiet Sporty Religious Computer Techno Skate/hiphop Pop Hippie Boys vs girls Significant lower riskSignificant higher risk

19. Discussion (1) Possible implications for health promotion: tailored activities to specific identity groups focus on undesirable group perceptions …however some essential questions are still unsolved…

20. Discussion (2) Unsolved questions: What underlies the different groups, what is the deeper meaning of risk behaviour to each group? High-risk groups more outgoing/more in contact with peers? How stable are group memberships over time? What are the directions of the observed relationships? Can group perceptions be manipulated?

21. Conclusion... more research is needed especially a longitudinal study may provide useful information..