1. 1 Strategic Intelligence, Inc. Youth Social Market Segmentation: Mining Data to Guide Program Planning Presented at the Centers for Disease Control and Prevention Conference on Tobacco or Health, San Francisco, CA, November 18-21, 2002 By Valerie J. Steffen, Ph.D., Lou Sternberg, Ph.D., Galen Louis, Ph.D.

2. 2 Goals Use available Idaho State surveillance data. Profile distinguishable groups of teens by their behaviors and beliefs to target those most likely to benefit from intervention and to tailor programs to their needs. Characterize the main social, belief, and behavioral factors related to tobacco use. Target & Tailor tobacco programs.

3. 3 Survey Methods Youth Tobacco Survey (YTS - Jr. High) Youth Risk Behavior Survey (YRBS - High School)

4. 4 Survey Method YTS - 1 Youth Tobacco Survey of Jr. High (YTS) Paper-pencil survey conducted in Idaho Jr. High Schools Data collected March 1 – April 15, 2001 Respondents in grades 7-8 Number = 1,878

5. 5 Survey Method YRBS - 2 Youth Risk Behavior Survey of High School (YRBS) Paper-pencil survey, conducted in Idaho High Schools Data collected March 1 – April 15, 2001 Respondents in grades 9-12 Number = 1,714

6. 6 Findings Order of Presentation YTS + YRBS Combined* Youth Tobacco Survey (YTS) Youth Risk Behavior Survey (YRBS) *Report of findings from questions that appear on both surveys.

7. 7 Jr. High & High School Teen Smoking – Combined Findings Summary Recommendations

8. 8 Conclusions –1 of 2 Steady increases in –Tobacco involvement with age – 25% of 7 th graders ever smoked vs. 58% of 12 th graders –Smoking increased by age 7% (7 th grade) to 28% (12 th grade ) Light smoking (1-2 cigarettes per day) is most common Quit attempts are very common: About 65% try quitting each year. Vast majority (ca. 94%) believe that ETS is harmful Number living with a smoker roughly equal to: –Number exposed to any ETS in a car –Number exposed to ETS in room 3+ days a week

9. 9 Conclusions –2 of 2 Teens estimate unrealistically low likelihood of smoking in 5 years (ca. 9%), regardless of age. –Predictors: 1-year smoking likelihood, grade, current smoking & history, ETS exposure in car, and living with a smoker. Teens estimate somewhat realistic likelihood of smoking in 1 year (10% in 7th grade to 28% in 12th grade) –Predictors: 5-year smoking likelihood, smoking history, current smoking, age.

10. 10 Recommendations –1 of 2 Start young (7 th grade or earlier) to prevent smoking –intensify and alter interventions with age in line with changing perceptions, habits, motives Message alerting teens and adults –You’re a teen smoker if you smoke just 1-2 cigarettes per day. Message - leverage the high frequency of quit attempts in social marketing messages and targeted cessation assistance Target messages to parents who smoke –Don’t smoke in the car with your kid Target message to teens whose parents smoke –You already know ETS is bad for you – tell your parent not to smoke in the car with you or in the house

11. 11 Recommendations –2 of 2 Target teens for smoking “prevention” and quitting based on predictors of 5-year smoking likelihood: Target teens –Early: the problem gets worse the older they are –Who have tried smoking, are current smokers, or hang out with teens who smoke –Whose parents or siblings use tobacco

12. 12 Youth Tobacco Survey: Findings Profile of Jr. High Smokers Factors Related to Jr. High Smoking

13. 13 Jr. High Teen Belief Segments Using Jr. High Teens’ Tobacco Beliefs Segmented teens into 4 distinct categories based on similarities in beliefs about substance use Found dramatic differences in current smoking rates across 4 segments Belief and ad-exposure differences as well

14. 14 Jr. High Teen Segments Belief-Inoculated, Clean-Air 58% of Teens, 3% Smoke Committed-Culture Smoker, ETS-Exposed 10% of Teens, 43% Smoke Average, ETS-Exposed 23% of Teens, 12% Smoke Harm-Immune, Clean- Air 9% of Teens, 9% Smoke Overall, 9.4% of these Jr. High Teens Smoke

15. 15 Jr. High Teen Segment Characteristics The sign of the score indicates the relative amount of the factor ascribed to each group (e.g, positive scores indicate greater cigarette smoking, higher ETS exposure, etc.). Colors indicate dramatic changes across the groups. On beliefs, high, positive scores indicate agreement (e.g., there is a social benefit to smoking, or smoking is harmful). Factor scores are standardized (Mean = 0; Standard Deviation = 1.0). Effective range: -4 to +4.

16. 16 Summary: Jr. High Segment Attributes Belief-Inoculated, Clean-Air Teens –58% of teens; 4% smoke; lowest smoking involvement & chew or cigar use; lowest ETS exposure; average exposure to TV anti-tobacco ads; strongest beliefs against tobacco Harm-Immune, Clean-Air Teens -- 9% of teens; 9% smoke; low smoking involvement & chew or cigar use; low ETS exposure; lowest ad exposure; belief against social benefits of smoking, strongest disbelief in smoke’s harm. Average, ETS-Exposed Teens -- 23% of Teens; 12% smoke; moderate smoking involvement; low chew & cigar use; moderate ETS exposure; average ad exposure; belief in social benefits of smoking; average belief about harm of smoke. Committed-Culture Smoker, ETS-Exposed Teens -- 10% of teens; 43% Smoke; heavy smoking involvement & chew use; high ETS exposure, average ad exposure; strongest belief in social benefits of smoking; strong disbelief that smoke is harmful.

17. 17 Conclusions about Jr. High School Segmentation of YTS A full 9.4% of Jr. High students reported smoking Two very different groups contain 75% of jr. high smokers to be targeted: –Average, ETS-Exposed Teens (29% of jr. high smokers; moderate likelihood of having a family member who smokes* low chew / cigar use, belief in social benefits of smoking; average belief that ETS is harmful) –Committed-Culture Smoker, ETS-Exposed Teens (46% of jr. high smokers) heavy chew use; high likelihood of having a family member who smokes*, strongest belief in social benefits of smoking; strong disbelief that ETS is harmful. * ETS exposure appears to be strongly influenced by exposure to smoking by a parent or other family member (lives with a person who smokes). See slides 17-18 & Appendix A for details.

18. 18 YTS Map of Predictors Factors Related to Jr. High Smoking

19. 19 Predictors of Jr. High Teen Smoking Significant predictors of Jr. High teen smoking were –Belief in the social benefits of smoking –ETS Exposure* –Other tobacco use (e.g., chew) –Belief that smoke is (not) harmful Exposure to anti-tobacco TV ads had no relation to teen smoking** * ETS exposure appears to be strongly influenced by exposure to smoking by a parent or other family member (lives with a person who smokes). See slides 17-18 & Appendix A for details. ** This finding is insufficient evidence to conclude that anti-tobacco TV ads have no effect on teen beliefs or behavior because the single ad-exposure question concerned ads seen in the prior 30 days, a timeframe too short to indicate exposure and reaction to messages that may have strong, or lasting effects.

20. 20 Predictors of Jr. High Teen Smoking *Standard regression coefficient (beta), ranges from -1 to +1. The greater the absolute value, the stronger the prediction. Values in bold face were significant predictors. The predictors are listed in order of their strength. Only belief in harmfulness of ETS was negatively related to likely 5-year smoking. TV ad factor score based on one item: “During the past 30 days, have you seen or heard commercials on TV, the Internet, or on the radio about the dangers of cigarette smoking?” ** ETS exposure appears to be strongly influenced by exposure to smoking by a parent or other family member (lives with a person who smokes). See slides 17-18 & Appendix A for details.

21. 21 Recommendation about Jr. High School Smoking based on YTS –1 of 2 Address smoking at an early age – by Jr. High Across All Jr. High Teens: –Counter the beliefs that smoking has social benefits and ETS is not harmful –Empower teens to avoid ETS Exposure* –Link chew to smoking as equally harmful, addictive –Address the composite of related risk behaviors** * ETS exposure appears to be strongly influenced by exposure to smoking by a parent or other family member (lives with a person who smokes). See slides 17-18 & Appendix A for details. * * See YRBS findings in this report for evidence linking teen smoking to other behavioral risks, slides 46-56 for details.

22. 22 Recommendations about Jr. High School Smoking based on YTS –2 of 2 Use Segmentation to Target & Tailor Interventions: –Screen to identify, target, & tailor interventions to Average, ETS-Exposed Teens and Committed-Culture Smoker, ETS-Exposed Teens –Counter Average, ETS-Exposed Teens’ belief in the social benefits of smoking with their own belief in the harm of ETS –Reach Committed-Culture Smoker, ETS-Exposed Teens’ through counselors who assist teens with other problems* * Contact authors for complete information about how to target and reach teen smokers.

23. 23 YRBS (High-School) Findings Profile Map of Predictors

24. 24 High-School Teen Risk Behavior Segments Using High School Teens’ Risk Behaviors Segmented teens into 4 distinct categories based on similarities in risk behaviors Found dramatic differences in current smoking rates across 4 segments Risk-behavior differences as well

25. 25 High School Teen Segments Young, Athletic Boys 4% Smoke; 32% of Teens (n=553) Older, Active Boys who Chew 68% Smoke; 4% of Teens (n=71) Inactive, Adrift Teens 46% Smoke; 27% of Teens (n=470) Girls 8% Smoke; 36% of Teens (n=620)

26. 26 Characteristics of High School Teen Behavior Segments Young, Athletic Boys – They are 32% of Teens; 4% of them are Current Smokers Girls -- 36% of Teens; 8% are Current Smokers Inactive, Adrift Teens -- 27% of Teens; 46% are Current Smokers Older, Active Boys who Chew -- 4% of Teens; 68% are Current Smokers This slide describes the figure on the next slide.

27. 27 Summary: High School Teen Segmentation Young, Athletic Boys – (32% of teens, 4% smoke) involved in PE, exercise and team sports, low substance abuse, many are A students, low ETS exposure, high seat belt use, high milk consumption Girls – (36% of teens, 8% smoke) low substance abuse, more than half involved in sports and exercise, low rate of PE, majority are A students, engaged in weight control behaviors, low ETS exposure Inactive, Adrift Teens – (27% of teens, 46% smoke) boys and girls, many report severe drug use, sadness and suicidal ideation, high alcohol use, highest rape rate, drugs at school, highest ETS exposure, C students, poor nutrition, little exercise, sports, PE Older, Active Boys who Chew – (4% of teens, 68% smoke) most smoke, all are current chew/snuff users, high lifetime severe drug use, high alcohol use, high exercise and sports involvement, mostly B and C students, high ETS exposure in cars (but less exposure at home)

28. 28 Conclusions about High School Smoking Segments YRBS Four segments of teens differ by age, gender, smoking likelihood, and other risk behaviors Key Target Opportunity: Inactive, Adrift Teens comprise 65% of high school smokers - the group is large (27% of teens) and highly vulnerable to tobacco (46% smoke): –Equally populated by girls & boys –More likely than other groups to report severe drug use, sadness & suicidal ideation, alcohol use, highest rape rate, low grades, poor nutrition, and highest ETS exposure* * ETS exposure appears to be strongly influenced by exposure to smoking by a parent or other family member (lives with a person who smokes). See slides 17-18 & Appendices A & B for details.

29. 29 Predictors of Smoking Tobacco among High School Teens Factors Related to High School Smoking (YRBS)

30. 30 Behavioral Risk Factors Factor Analysis of YRBS Responses Produced 19 Factors* Regression Analysis of 18 YRBS Factors’ prediction of Smoking Factor identified 4 significantly predictive factors *See Appendix B for listing of YRBS factors, correlation matrix, etc.

31. 31 Top 8 Predictors of Smoking Tobacco in Order of Strength *Standard regression coefficient (beta), ranges from -1 to +1. The greater the absolute value, the stronger the prediction. Values in bold face were significant predictors. The predictors are listed in order of their strength. *Strength Alcohol / Marijuana / Sex0.25 ETS Exposure 0.22 Severe Drug Use0.14 Smoke 1-2 Puffs / Drug Offers at School0.08 Junk Food / TV / School Grades0.06 Exercise / Sports0.05 Milk Consumption0.04 Height / Weight / Gender0.04

32. 32 Other Factors Not Significantly Predictive of High School Teens’ Smoking Tobacco Weight Loss Harmful Practices Weight Control Fighting / Safety / ETS Beliefs PE Class Health Foods Suicide / Sadness Fights / Weapons / Seatbelts Abuse / Rape Grade / Age Chew / Snuff / Cigars

33. 33 Recommendations about High School Smoking based on YRBS –1 of 2 Screen to identify and target Inactive, Adrift Teens Tailor prevention and quit-promotion interventions to Inactive, Adrift Teens’ experiences and needs Reach them through counselors who provide assistance with their other teen problems i.e., –drug use, sadness & suicidal ideation, alcohol use, date rape, low grades, poor nutrition, and hanging out with others who smoke

34. 34 Recommendations about High School Smoking based on YRBS –2 of 2 Prevent and intervene in high school –Address all teens using interventions and messages concerning the key risks associated with tobacco - sex, alcohol, and marijuana –Use messages empowering them to avoid or prevent ETS exposure at home and among friends –Help teens avoid offers of tobacco or other substances from friends and acquaintances

35. 35 Conclusions & Recommendations on Using YTS & YRBS to Guide Tobacco Control 5-7 Question overlap in databases’ content allows triangulation of data comparability (linear progression across years) Advanced, summary analyses of YTS, YRBS reveal insights to guide program planning Presence of ETS & parental smoking qsts. in YTS shows those factors’ importance Presence of risk factor data in YRBS enriches the predictive power and ability to identify at-risk targets groups, and tailor interventions to teens’ broader needs Teens manifesting other risk factors (sex, drugs, alcohol) Certain group of male athletes Emergence of gender difference in segments of non-smoker youths in YRBS (HS) suggests gender-tailored prevention strategies

36. 36 Strategic Intelligence, Inc. Youth Social Market Segmentation: Mining Data to Guide Program Planning Presented at the Centers for Disease Control and Prevention Conference on Tobacco or Health, San Francisco, CA, November 18-21, 2002 by Valerie J. Steffen, Ph.D. vsteffen@strategic-IQ.com 208-343-0629