Abstract
Aim
To examine the relation between perceived exposure to parents, siblings, and peers’ substance use and self-reported substance consumption among early adolescents in Primorsko-goranska county, Croatia, and between perceived exposure to substance use and risk-taking behaviors such as going out late at night, gathering at secluded places, skipping school, and gambling.
Method
A self-reported cross-sectional survey was conducted in 2007 among 2219 eight-grade (14-year old) pupils in elementary schools in Primorsko-goranska county. Exposure to substance use in their immediate social environment, self-reported consumption of cigarettes, alcohol, inhalants, and marihuana, ways of spending free time, and family and peer relationships were assessed.
Results
There was a significant association between perceived exposure to substance use and self-reported consumption of cigarettes, alcohol, inhalants, and marihuana in both sexes (P < 0.001). Pupils whose parents, siblings, and peers used substances significantly more often developed the same behavioral patterns. Level of exposure to substance use in the immediate social environment had the strongest effect on experimenting with smoking among girls (from 26.6% in low exposure to 76.2% in high exposure group) and among boys (from 15.8% in low exposure to 69.4% in high exposure); on regular everyday smoking among girls (from 4.4% in low exposure to 45% in high exposure group) and among boys (from 2.7% in low exposure to 36.7% in high exposure group); on hard liquor consumption among girls (from 25.1% in low exposure to 79.5% in high exposure group) and among boys (from 28.1% in low exposure to 78.4% in high exposure group), as well as on binge drinking among girls (from 10.9% in low exposure to 56.6% in high exposure group) and among boys (from 15.5% in low exposure to 62.4% in high exposure group). Girls and boys exposed to substance use engaged more often in risk-taking and potentially delinquent behaviors (F(2, 1180) = 166 502; P < 0.001, two-way ANOVA).
Conclusion
High exposure to substance use in immediate social environment and its great impact on substance use among early adolescents indicate that there is a need for the introduction of preventive programs that would reduce inappropriate behavior among adolescents’ social models.
Substance use among children and adolescents is a substantial problem throughout the world. Smoking and alcohol consumption initiation occurs mainly during early adolescence (1). Many studies have reported an upward trend in the use of tobacco and illicit drugs and a significant proportion of children who begin to smoke before their 12th birthday (2-9). Health consequences of smoking and alcohol consumption among adolescents are well documented (10) and an early initiation is associated with an increased risk of developing addiction and adulthood dependence.
Researchers have tried to understand why some adolescents experiment with substances while others do not. According to Hawkins et al (11), there are numerous reasons of drug consumption: laws and norms favorable toward drug use; availability of drugs; extreme economic deprivation; neighborhood disorganization; personal psychological characteristics; early and persistent behavior problems including aggressive behavior in males, other conduct problems, and hyperactivity in childhood and adolescence; a family history of alcoholism and parental use of drugs; poor family management practices; family conflict; low bonding to family; academic failure; lack of commitment to school; early peer rejection; social influences to use drugs; alienation and rebelliousness; attitudes favorable to drug use; and early initiation of drug use. With so many potential causes, it is difficult to form a complete picture of experimental substance use. Among numerous theories that attempted this, one of the most influential is the social learning theory (12). This theory states that individuals learn new behaviors from observation, modeling, and imitation of significant others. Adolescents acquire their beliefs about experimental substance use from their role models, especially their friends, siblings, and parents. The development of substance use in adolescents has 3 phases: 1) observation and imitation of substance-specific behaviors; 2) social reinforcement (ie, encouragement and support) for experimental substance use; and 3) adolescents' expectation of positive social and physiological consequences from future substance use. An adolescent who expects substances to produce more personal benefits than costs will be at risk for experimental substance use (13). According to social learning theory, youngsters who are under implicit or explicit pressure of peers to start smoking are more prone to actually do it.
Behavioral and cognitive variables specified in the social learning process account for significant portions of the variations in adolescent substance use and mediate substantial effects of sex, socio-economic status, age, family structure, and community size on substance abuse (14).
Parental use of tobacco, alcohol, and other drugs increases the likelihood that children will also engage in substance use (11,15). Parents who espouse norms favorable to substance use and who model such behavior, encourage imitation by children. Although parental use is a strong risk factor for children's use, substance use by peers may be even more influential. The psychological peer cluster theory views the peer group as critical in adolescent substance use (16,17). Imitation of deviant behavior is most likely to occur when role-models are very salient and peers are the most important role models in adolescents' lives. Reviews on the development of substance abuse all report that substance use by peers and friends is a major risk factor for adolescent drug use (11,18). Siblings may also act as powerful role models, particularly given that their influence extends from the family to the peer domain (19,20).
The aim of this study was to examine the relationship of exposure to substance use by parents, siblings, and peers to experimenting with substance use in early adolescence in eight-graders from a Croatian county and investigate the association of exposure to substance use and other forms of risk-taking behaviors.
Participants and methods
Participants
The survey was conducted during November and December 2007 in all elementary schools in Primorsko-goranska County, except schools for children with special needs and the elementary school on the island of Rab. Out of a total of 2597 eight-grade pupils in the county, 2219 who were at school on the day of the assessment were included in the study (85.4% response rate) (Table 1). There were 51.4% of girls and the average age of the participants was 14.3 ± 0.44 years.
Table 1.
General demographic characteristics of the pupils (n = 2219)
| Parameter | No (%) of pupils |
|---|---|
| Sex: | |
| girls | 1141 (51.4) |
| boys | 1078 (48.6) |
| Living with: | |
| both parents | 1906 (85.9) |
| with mother only | 251 (11.3) |
| with father only | 40 (1.8) |
| not living with parents | 22 (1.0) |
| Number of household members (including the pupil): | |
| 2 | 62 (2.8) |
| 3 | 348 (15.7) |
| 4 | 1105 (49.8) |
| 5 | 406 (18.3) |
| 6 | 182 (8.2) |
| 7 and more | 115 (5.2) |
Measures
We applied a self-reporting questionnaire addressing important aspects of adolescents’ life: free-time, relationship with peers, family, school life, self-concept, life satisfaction, risk-taking behaviors, and demographic variables (21). The questionnaire we used is an adaptation of a standardized questionnaire (21), used in a longitudinal study of pupils’ risk-taking behaviors in Primorsko-goranska county. It was validated on large samples of adolescents and showed satisfactory metric characteristics. For this study, we used two subscales of the questionnaire – “Exposure to substance use” and “Pupils’ risk-taking behavior” scale.
“Exposure to substance use” scale consists of the following 7 items: “My friends smoke;” “My parents smoke;” “My older siblings smoke;” “My friends drink alcohol;” “My parents drink alcohol;” “My older siblings drink alcohol;” and “I hang out at the places frequented by drug users.” Answers for each item were given on a 4-point scale, ranging from never to very often, and all 7 items were summed up to obtain a total exposure to substance usage index. Higher scores indicated higher level of exposure. Internal consistency coefficient (Cronbach α) for this measure in this sample was 0.73. The average correlation among items was r = 0.29 (ranging from r = 0.13 to r = 0.68), that confirmed satisfactory range of correlations.
“Pupils’ risk-taking behavior” scale consisted of 6 items assessing the frequency of behaviors potentially linked to substance abuse: “I go out at night (cafes, clubs, parties);” “I hang out at secluded places with my friends;” “I gamble (betting, slot machines);” “I skip school when I feel like it;” “Whenever possible I avoid lessons;” and “I drink alcohol in school or around the school.” Answers for each item were given on a 4-point scale, ranging from never to very often, and all 6 were summed up to obtain a reliable measure of pupils’ risk-taking behavior. Higher scores indicated more frequent involvement in potentially risk-taking behavior. Internal consistency coefficient (Cronbach α) for this measure in this sample was 0.78. The average correlation among items was r = 0.37 (from r = 0.23 to r = 0.60), that confirmed satisfactory range of correlations.
Procedure
After having obtained an approval from the school authorities (Educational and Teacher Training Agency) and school founders (City of Rijeka and Primorsko-goranska County) to conduct the study, schools were informed about the procedure and they organized the administration of the questionnaire. A trained research team of psychology students administered the questionnaire, and teachers and school administrators were not in the room during the completion. Pupils completed the survey material in groups (up to 25 students) in their school setting and the survey took about 45-50 minutes to complete. Participation was voluntary and anonymous.
Statistical analysis
Descriptive statistics is presented using percentages and frequencies. Normality of results distributions was tested by Kolmogorov-Smirnov test. χ2 and t test were used to test the sex differences of exposure level and substance use. Correlation between exposure to substance use and pupils risk behavior was calculated with the Pearson correlation coefficient. Two-way analysis of variance was used to test the effect of sex and levels of exposure to substance use on risk-taking behaviors of pupils. All statistical analyses were performed with the Statistica 7.1 statistical package (StatSoft Inc., Tulsa, OK, USA).
Results
Exposure to substance use
Almost 3 quarters of elementary school pupils in Primorsko-goranska county were exposed to their friends’ smoking (74.1% – sum of frequencies in “rarely,” “often,” and “very often” categories) (Table 2). Also, more than half of the parents smoked (55.9%). Alcohol was also frequently consumed both by peers (67.8%) and parents (61.2%). Girls and boys were equally exposed to substance use (t value = 0.095, P = 0.924). The distribution of results on cumulative scale was asymmetric, showing that a smaller number of pupils reported higher level of exposure to substance use (Kolmogorov-Smirnov Z = 4.41; P < 0.001).
Table 2.
Exposure to substance use items – frequencies of responses within response categories
| No (%) of examinees who answered* |
||||
|---|---|---|---|---|
| Items | never | rarely | often | very often |
| My friends smoke | 517 (25.9) | 570 (28.6) | 435 (21.8) | 473 (23.7) |
| My parents smoke | 908 (44.1) | 378 (18.4) | 379 (18.4) | 394 (19.1) |
| My older siblings smoke | 1481 (76.1) | 171 (8.8) | 134 (6.9) | 161 (8.3) |
| My friends drink alcohol | 642 (32.2) | 647 (32.4) | 383 (19.2) | 324 (16.2) |
| My parents drink alcohol | 790 (38.8) | 108 (49.5) | 174 (8.5) | 64 (3.1) |
| My older siblings drink alcohol | 1258 (65.6) | 427 (22.3) | 136 (7.1) | 98 (5.1) |
| I hang out at places frequented by drug users | 1661 (82.6) | 219 (10.9) | 66 (3.3) | 64 (3.2) |
*Percentages were calculated using the number of valid answers. The percentages of missing data for the whole sample varied between 7.0% for “My parents smoke” and 13.4% for “My older siblings drink alcohol.”
Self-reported substance consumption
Self-reported substance consumption and sex differences in substance use are presented in Table 3. Pupils mostly experimented with alcohol (Table 3). More than 70% of eight-graders consumed beer and wine and more than half of them consumed hard liquor. There were 50.9% of girls and 44.4% of boys who experimented with smoking cigarettes. Almost 40% of boys and more than 30% of girls had episodes of binge drinking.
Table 3.
Prevalence and sex differences of substance use among eight graders
| No. (%)* of examinees |
||||
|---|---|---|---|---|
| Type of behavior | girls | boys | χ2 | P |
| Consumption of beer | 752 (72.2) | 729 (76.8) | 5.633 | 0.018 |
| Consumption of wine | 719 (69.7) | 686 (72.4) | 1.750 | 0.186 |
| Consumption of hard liquor | 536 (51.8) | 535 (56.9) | 5.114 | 0.024 |
| Consumption of cigarettes | 537 (50.9) | 420 (44.4) | 8.206 | 0.004 |
| Participation in binge drinking | 311 (30.4) | 371 (39.6) | 18.373 | <0.001 |
| Daily cigarette smoking | 197 (18.9) | 162 (17.3) | 0.910 | 0.340 |
| Consumption of inhalants, glue | 94 (9.0) | 102 (10.9) | 1.898 | 0.168 |
| Consumption of marihuana | 50 (4.8) | 68 (7.3) | 5.444 | 0.020 |
*Percentages were calculated using the number of valid answers.
Girls and boys smoked cigarettes, drank wine, and used inhalants at about the same rate. Significantly more girls experimented with smoking cigarettes (P = 0.004), while more boys experimented with drinking beer (P = 0.016) and hard liquor (P = 0.024), had episodes of binge drinking (P < 0.001), and used marihuana (P = 0.02).
Relationship between exposure to substance use and self-reported substance consumption
For further analysis, participants were divided into low, medium, and high level exposure groups according to their results on “Exposure to substance use” scale. Tobacco, alcohol, inhalants, and marihuana usage was analyzed regarding to sex and exposure to substance use level (Table 4). There was a significant relation between the level of perceived exposure to substance use and reported usage for all substances (P < 0.001). Pupils whose friends, older siblings, and parents smoked and drank alcohol more often developed the same behavioral pattern. Greater exposure to substance use increased the probability of incidence.
Table 4.
Substance usage in relation to exposure to substance use level and sex
| Substance | Exposure level | Girls |
Boys |
||
|---|---|---|---|---|---|
| No. (%)* | χ2 | No. (%)* | χ2 | ||
| Cigarette smoking at last once | low | 67 (26.6) | 126.715† | 36 (15.8) | 137.982† |
| medium | 76 (52.8) | 52 (43.7) | |||
| high | 199 (76.2) | 170 (69.4) | |||
| Daily cigarette smoking | low | 11 (4.4) | 134.432† | 6 (2.7) | 89.271† |
| medium | 16 (11.3) | 18 (15.1) | |||
| high | 117 (45.0) | 90 (36.7) | |||
| Consumption of beer | low | 136 (54.4) | 55.132† | 128 (56.4) | 72.287† |
| medium | 106 (73.6) | 92 (78.0) | |||
| high | 215 (84.3) | 225 (90.7) | |||
| Consumption of wine | low | 123 (50.0) | 77.738† | 114 (50.0) | 85.182† |
| medium | 105 (73.4) | 86 (72.7) | |||
| high | 220 (85.9) | 220 (88.7) | |||
| Consumption of hard liquor | low | 62 (25.1) | 149.986† | 64 (28.1) | 121.824† |
| medium | 78 (54.9) | 70 (59.3) | |||
| high | 205 (79.5) | 192 (78.4) | |||
| Binge drinking | low | 27 (10.9) | 122.936† | 35 (15.5) | 107.470† |
| medium | 36 (26.3) | 46 (39.3) | |||
| high | 146 (56.6) | 151 (62.4) | |||
| Consumption of inhalants | low | 69 (2.8) | 21.923† | 13 (5.8) | 27.558† |
| medium | 9 (6.4) | 8 (6.8) | |||
| high | 37 (14.0) | 50 (20.4) | |||
| Consumption of marihuana | low | 0 (0.0) | 39.605† | 2 (0.9) | 49.385† |
| medium | 2 (1.4) | 3 (2.5) | |||
| high | 29 (11.2) | 42 (17.4) | |||
*Percentages were calculated using the number of valid answers. The percentages of missing data for the whole sample varied between 8.0% for smoking cigarettes at least once and 9.2% for drinking hard liquor.
†Significant, P < 0.001, χ2 test.
The effect was strongest on experimenting with smoking among girls (from 26.6% in low exposure to 76.2% in high exposure group) and among boys (from 15.8% in low exposure to 69.4% in high exposure group); on regular everyday smoking among girls (from 4.4% in low exposure to 45% in high exposure group) and among boys (from 2.7% in low exposure to 36.7% in high exposure group); on hard liquor consumption among girls (from 25.1% in low exposure to 79.5% in high exposure group) and among boys (from 28.1% in low exposure to 78.4% in high exposure group), as well as on binge drinking among girls (from 10.9% in low exposure to 56.6% in high exposure group) and among boys (from 15.5% in low exposure to 62.4% in high exposure group). All differences were statistically significant (P < 0.001; Table 4).
Other forms of risk-taking behavior
Exposure to substance use was further explored in relation to other potentially risk-taking behaviors of early adolescents. Going out at night and spending time in cafés, clubs, or at parties was common among pupils (Table 5). Around 44% of girls and boys rarely went out at night and around 30% did it often or very often. Another potentially risk-taking type of behavior was hanging out at secluded places, which was often or very often practiced by more than one fifth of 14-year-old pupils. There were no differences according to sex in the two types of behavior. Boys were significantly more often involved in betting and gambling – around 48% of boys and 18% of girls spent money on slot machines or betting. More than 33% of boys and around 25% of girls skipped school and intentionally avoided lessons. The difference between the sexes in skipping school was significant (P < 0.001), as well as the difference in drinking alcohol in school surroundings (P = 0.05).
Table 5.
Sex differences in potentially risk-taking behaviors – frequencies of responses within response categories
| Potentially risk-taking behaviors | No. (%)* of examinees |
|||||
|---|---|---|---|---|---|---|
| never | rarely | often | very often | χ2 | P | |
| I hang out at night (cafés, clubs, parties) | 0.247 | 0.970 | ||||
| girls | 276 (25.2) | 483 (44.1) | 217 (19.8) | 118 (10.8) | ||
| boys | 264 (25.5) | 459 (44.3) | 208 (20.1) | 105 (10.1) | ||
| I hang out at secluded places with my friends | 1.828 | 0.609 | ||||
| girls | 491 (45.3) | 354 (32.7) | 155 (14.3) | 83 (7.7) | ||
| boys | 467 (44.7) | 365 (35.0) | 143 (13.7) | 69 (6.6) | ||
| I gamble (betting, slot machines) | 251.494† | <0.001 | ||||
| girls | 904 (81.7) | 165 (14.9) | 23 (2.1) | 14 (1.3) | ||
| boys | 542 (51.9) | 281 (26.9) | 130 (12.4) | 92 (8.8) | ||
| I skip school when I feel like it | 30.320† | <0.001 | ||||
| girls | 762 (72.0) | 219 (20.7) | 34 (3.2) | 43 (4.1) | ||
| boys | 633 (63.2) | 229 (22.9) | 74 (7.4) | 66 (6.6) | ||
| Whenever possible I avoid lessons | 32.150† | <0.001 | ||||
| girls | 831 (76.9) | 181 (16.7) | 37 (3.4) | 32 (3.0) | ||
| boys | 680 (67.3) | 202 (20.0) | 71 (7.0) | 58 (5.7) | ||
| I drink alcohol in school or around school | 7.587 | 0.05 | ||||
| girls | 875 (82.1) | 117 (11.0) | 45 (4.2) | 29 (2.7) | ||
| boys | 778 (77.3) | 146 (14.5) | 49 (4.9) | 33 (3.3) | ||
*Percentages were calculated using the number of valid answers. The percentages of missing data for the whole sample varied between 1.0% for gambling and 5.2% for avoiding school.
Results on aggregated “Pupils’ risk-taking behavior” scale showed that boys engaged in risk-taking behaviors significantly more often than girls (t value = 7.15; P < 0.001). Both girls’ and boys’ results showed a significant deviation from normal distribution (Kolmogorov-Smirnov Z = 8.55; P < 0.001). A smaller number of boys and girls engaged in risk-taking behaviors frequently.
Relationship between exposure to substance use and risk-taking behavior
The Pearson correlation coefficient between the “cumulative exposure to substance use” scale and “pupils’ risk-taking behavior” scale was 0.612 (P < 0.001) in girls and 0.534 (P < 0.001) in boys. The effect of sex and exposure to substance use on risk-taking behaviors was also tested by two-way (sex vs exposure to substance use) analysis of variance (Figure 1). Analysis showed the significant effect of sex (F(1, 1180) = 33.253, P < 0.001) and exposure to substance use (F(2, 1180) = 166.502, P < 0.001) on risk-taking behaviors of girls and boys. Interactional effect was not significant (F(2, 1180) = 0.398, P = 0.672). Boys tended to more often engage in risk-taking behaviors, regardless of the level of exposure.
Figure 1.
Exposure to substance (mean) use in relation to pupils’ risk-taking behavior and sex. Squares – boys, circles – girls, vertical bars denote 0.95 confidence intervals.
Discussion
Our study found a moderately strong association between perceived exposure to substance use and reported smoking and alcohol, inhalants, and marihuana consumption in early adolescents. According to these findings, a higher level of exposure leads to more frequent consumption of cigarettes and hard liquor, and binge drinking, equally for girls and boys. These results are in line with previous findings (2-7,9,22). If adolescents’ best friends smoked, adolescents were more likely to smoke themselves. Moreover, they were more likely to drink alcohol, suggesting that modeling any addictive behavior can lead to modeling other addictive behaviors as well (9,22). Peer influence or socialization has often been attributed to modeling peer behavior, as postulated by social learning theorists (14). The similarity between peers in the substances use may be explained by the process of peer socialization (23). Besides peer socialization, positive perceptions about substances use among adolescents, may also play an important role. Nearly a quarter of boys think that boys who smoke have more friends and girls have the same attitude, regardless their smoking status (2). In addition, smokers find themselves more appealing than what their non-smoking peers perceive them to be. In addition to being related to friends’ smoking, adolescents smoking onset is also related to parents’ smoking (24).
There were significant correlations between the exposure to substance use and risk-taking behaviors in boys and girls. We found significantly higher proportion of everyday smokers among pupils who engaged in other risk-taking behaviors. The pupils who more often went out at night smoked cigarettes and drank alcohol more often. More than one third of pupils reported that they very often went out at night and more than one fifth of them reported hanging out at secluded places with their friends. The results suggest that adolescents whose parents, siblings, and peers indulged in risk-taking behaviors were more likely to indulge in other forms of risk-taking behavior themselves, confirming the crossover effect.
These findings are concordant with previous findings (9) and have important implications for the prevention and treatment of adolescent smoking and drinking. The influence of models of addictive behaviors may be stronger than was originally thought.
Although the results of this study provide a strong evidence for the social learning of substance use, there are some limitations. First, data on substance use by significant others were based on self-reports. The validity of such data are open to question, since adolescents have consistently overestimated how similar they are to their friends in substance use (23). It is also possible that some adolescents overreport their substance use because they think it is ‘‘cool.'' Thus, if asked directly if and how much they smoke, drink alcoholic beverages, or use marihuana, adolescents may provide answers that are socially desirable but not completely true. We tried to address this problem by emphasizing that answers would be analyzed anonymously. The importance of assessing the prevalence of substance use or other health-risk behaviors as part of research activities involving children and adolescents often necessitates the use of self-report measures. However, these are often affected by cognitive and situational factors in varying degrees (25).
In conclusion, we confirmed that exposure to substance use can lead not only to adoption of similar behavior, but also to adoption of other forms of risk-taking, criminal, or delinquent behavior. Such findings have important implications for prevention programs aiming at reduction of substance use and other forms of risk-taking behavior. While current smoking and alcohol prevention programs focus on improving communication and interactions at schools, social learning theories suggest that prevention should be based on making substance-using role models less salient and substance-abstaining role models more salient. Therefore, there is a need to include parents, siblings, and peers in the prevention efforts, or at least address issues relating to close social relationships and influences as a part of these efforts.
Acknowledgments
We thank Andreja Dodig Blašković, Darko Roviš, Andrea Mataija-Redžović, and their co-workers for their contribution to this study. The survey was financially supported by the County Health Authority, Department of Health and Social Care Primorsko-Goranska County, Croatia.
References
- 1.Sasco AJ, Laforest L, Benhaim-Luzon V, Poncet M, Little RE. Smoking and its correlates among preadolescent children in France. Prev Med. 2002;34:226–34. doi: 10.1006/pmed.2001.0980. [DOI] [PubMed] [Google Scholar]
- 2.Ćorić T, Hrabak-Žerjavić V, Kuzman M, Mayer D. Global Youth Tobacco Survey 2002. Results for Croatia [in Croatian]. Zagreb: Croatian National Institute of Public Health; 2006. [Google Scholar]
- 3.Kuzman M. Addictive behaviour predictors for youth [dissertation in Croatian]. Zagreb: Zagreb University School of Medicine; 2003. [Google Scholar]
- 4.Ljubotina D, Galic J, Jukic V. Prevalence and risk factors of substance use among urban adolescents: questionnaire study. Croat Med J. 2004;45:88–98. [PubMed] [Google Scholar]
- 5.Kuzman M, Franelić-Pejnović I, Šimetin-Pavić I, Pejak M. The European school survey project on alcohol and other drugs [in Croatian]. Zagreb: Croatian National Institute of Public Health; 2008. [Google Scholar]
- 6.Kuzman M, Pejnović-Franelić I, Pavić-Šimetin I. Health behavior in school-aged children 2001/2002 [in Croatian]. Zagreb: Croatian National Institute of Public Health; 2004. [Google Scholar]
- 7.World Health Organization; Regional Office for Europe. Health behaviour in school-aged children (HBSC) study: international report from the 2001/2002 survey. Copenhagen: WHO-Europe; 2004. [Google Scholar]
- 8.Malatestinic D, Micovic V, Kendel G, Baricev-Novakovic Z. Assessment of psychological and social factors in adolescents risk behavior: questionnaire study. Croat Med J. 2005;46:81–7. [PubMed] [Google Scholar]
- 9.Kuzman M, Pavić-Šimetin I, Pejnović-Franelić I. Health behavior in school-aged children 2005/2006 [in Croatian]. Zagreb: Croatian National Institute of Public Health; 2008. [Google Scholar]
- 10.Department of Health and Human Services. Centers for Disease Control and Prevention. 2000 Surgeon General's report – reducing tobacco use. Available from: http://www.cdc.gov/tobacco/data_statistics/sgr/sgr_2000/index.htm Accessed: Jun 5, 2008.
- 11.Hawkins JD, Catalano RF, Miller JY. Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychol Bull. 1992;112:64–105. doi: 10.1037/0033-2909.112.1.64. [DOI] [PubMed] [Google Scholar]
- 12.Bandura A. Social learning theory. Englewood Cliffs (NJ): Prentice-Hall; 1977. [Google Scholar]
- 13.Petraitis J, Flay BR, Miller TQ. Reviewing theories of adolescent substance use: organizing pieces in the puzzle. Psychol Bull. 1995;117:67–86. doi: 10.1037/0033-2909.117.1.67. [DOI] [PubMed] [Google Scholar]
- 14.Lee G, Akers RL, Borg MJ. Social learning and structural factors in adolescent substance use. Western Criminology Review. 2004;5:17–34. [Google Scholar]
- 15.DeWitt DJ, Silverman G, Goodstadt M, Stoduto G. The construction of risk and protective factor indices for adolescent alcohol and other drug use. J Drug Issues. 1995;25:837–63. [Google Scholar]
- 16.Oetting ER, Beauvais F. Peer cluster theory: Drugs and the adolescent. J Couns Dev. 1986;65:17–22. [Google Scholar]
- 17.Oetting ER, Beauvais F. Common elements in youth drug abuse: Peer clusters and other psychosocial factors. J Drug Issues. 1987;17:133–51. [Google Scholar]
- 18.Belcher HM, Shinitzky HE. Substance abuse in children: prediction, protection, and prevention. Arch Pediatr Adolesc Med. 1998;152:952–60. doi: 10.1001/archpedi.152.10.952. [DOI] [PubMed] [Google Scholar]
- 19.Boyle MH, Sanford M, Szatmari P, Merikangas K, Offord DR. Familial influences on substance use by adolescents and young adults. Can J Public Health. 2001;92:206–9. doi: 10.1007/BF03404307. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Vakalahi HF. Adolescent substance use and family-based risk and protective factors: a literature review. J Drug Educ. 2001;31:29–46. doi: 10.2190/QP75-P9AR-NUVJ-FJCB. [DOI] [PubMed] [Google Scholar]
- 21.Bezinović P. Analysis of risk behavior of secondary school pupils in Primorsko-goranska County. Report for County Council [in Croatian]. Zagreb: Institute for Social Research in Zagreb; 1999. [Google Scholar]
- 22.Taylor JE, Conard MW, O'Byrne KK, Haddock CK, Poston WS. Saturation of tobacco smoking models and risk of alcohol and tobacco use among adolescents. J Adolesc Health. 2004;35:190–6. doi: 10.1016/j.jadohealth.2004.01.008. [DOI] [PubMed] [Google Scholar]
- 23.Andrews JA, Tildesley E, Hops H, Li F. The influence of peers on young adult substance use. Health Psychol. 2002;21:349–57. doi: 10.1037/0278-6133.21.4.349. [DOI] [PubMed] [Google Scholar]
- 24.Engels RC, Vitaro F, Blokland ED, de Kemp R, Scholte RH. Influence and selection processes in friendship and adolescent smoking behavior: The role of parental smoking. J Adolesc. 2004;27:531–44. doi: 10.1016/j.adolescence.2004.06.006. [DOI] [PubMed] [Google Scholar]
- 25.Brener ND, Billy JO, Grady WR. Assessment of factors affecting the validity of self-reported health-risk behavior among adolescents: evidence from the scientific literature. J Adolesc Health. 2003;33:436–57. doi: 10.1016/S1054-139X(03)00052-1. [DOI] [PubMed] [Google Scholar]