Abstract

This randomized controlled trial evaluated the effectiveness of a multicomponent Health Promoting Schools (HPS) intervention program in improving self‐reported smoking outcomes among a cohort of adolescents in 22 public secondary schools in the Hunter Region of New South Wales, Australia. Pre‐test surveys were completed by students in the first 2 years of secondary school, with a 2‐year post‐test survey. Multivariate analyses examined intervention effect for the main outcome, post‐test smoking behavior, controlling for pre‐test smoking status, school and other confounders. The sample comprised the cohort of 1852 students who completed both surveys. The results demonstrated that the HPS program failed to improve smoking behavior over the 2 years (equal increase of 10% in both groups). The program was successful in improving smoking knowledge, but not attitudes, in intervention versus control group (P < 0.001). Independent predictors of post‐test smoking included: pre‐test smoking [odds ratio (OR) = 5.44; 95% confidence interval (CI) = 3.20–9.28], being female (OR = 0.55; CI = 0.35–0.87), having more close friends who smoked (OR = 1.42; CI = 1.33–1.52), peer group having no clear opinion about smoking (OR = 3.23; CI = 1.27–8.27), having more positive and less negative attitudes towards smoking, and being less involved in school activities. We discuss methodological issues in multicomponent community‐based interventions, and highlight the strengths and limitations of this study.

Introduction

Despite extensive smoking prevention activity, smoking rates among Australian adolescents remained stable during the 1990s. In 1996, 8% of boys and 7% of girls aged 12 were current smokers, increasing to 28% of boys and 34% of girls by age 17 (Hill et al., 1999). A British study of 9472 adolescents aged 11–16 reported that 4.8% smoked cigarettes daily at age 11, rising to 36% at age 16 (Sutherland and Shepherd, 2001). The US National Youth Tobacco Survey reported a prevalence of 15.1% for middle school students and 34.5% among high school students (MMWR, 2001).

Many predictors of smoking have been studied in an attempt to inform prevention activities (Barber et al., 1999; Burt et al., 2000). Factors which have been consistently associated with adolescent smoking include family smoking behavior and attitudes (Distefan et al., 1998; Farkas et al., 1999, 2000), family rules about smoking at home (Farkas et al., 2000; Proescholdbell et al., 2000), peer approval and smoking behavior (Barber et al., 1999; Unger et al., 2002), perceived prevalence of smoking among peers (Unger and Rohrbach, 2002), perceived access to cigarettes (Unger et al., 2002), gender (Barber et al., 1999; Sutherland and Shepherd, 2001), school involvement (Dornbusch et al., 2001), and personal characteristics such as rebelliousness and risk taking (Burt et al., 2000). Such research confirms the complexity of smoking determinants and the need for more comprehensive prevention programs.

Schools have long been a priority setting for adolescent health promotion activity (National Academy of Sciences, 1997; National Health and Medical Research Council, 1996), and increasing interest has been given to more systemic and ecological approaches such as the Health Promoting Schools (HPS) model of health promotion (WHO, 1995; National Health and Medical Research Council, 1996; Rasmussen and Rivett, 2000). However, a review of 600 published articles on smoking, alcohol and sun protection in schools over 1983–1995 indicated that only 14% involved evaluation of school‐based health promotion interventions, and none successfully implemented the HPS concept in its entirety and/or evaluated its effectiveness in changing health behaviors (Lynagh et al., 1997). Furthermore, few trials have focused specifically on secondary schools (Lowe et al., 1999; Lynagh et al., 1999; Moon et al., 1999), the time of maximum smoking uptake, although some have addressed both primary and secondary schools (Heckert and Matthews, 2000).

The Hunter HPS project aimed to evaluate the effectiveness of a 2‐year collaborative community‐based HPS program in improving health knowledge, attitudes and practice among a cohort of young adolescents in New South Wales (NSW) secondary schools. This paper reports the smoking outcomes. The specific aims were to determine whether the HPS intervention led to lower uptake of smoking, and improved knowledge and attitudes among the cohort of students in intervention schools compared with control schools, after controlling for pre‐test smoking and other confounders. We also examined factors independently predicting post‐test smoking status.

Methods

Design and sample

The design was a randomized controlled trial with 24 secondary schools randomly selected from a population of 31 schools in the Hunter and Taree school districts of NSW, and then randomly allocated to control and intervention groups prior to recruitment. All participating schools accepted their randomly allocated status. Financial and practical constraints limited the number of selected schools to 24, a number which provides adequate design integrity (Feldman and McKinlay, 1994) and is consistent with the approach taken in the large‐scale COMMIT study of 22 US communities (COMMIT Research Group, 1995). Cluster randomization has been widely used in evaluating community‐based health programs and is particularly suitable for school‐based studies (Carlin and Hocking, 1999). A cohort pre–post design over 2 years was chosen to evaluate the effectiveness of the intervention so that exposure to the intervention would be standardized within schools and received by students over the maximum time frame of 2 years. Cohort designs are considered more efficient than cross‐sectional designs, especially when successive cross‐sectional samples within schools are likely to be highly correlated (Feldman and McKinlay, 1994).

Procedure

A pre‐test survey of all consenting Year 7–8 students was conducted in November 1995, and a post‐test survey of the same cohort in November 1997 when they were in Years 9–10. Active parental consent was required by schools prior to the pre‐test survey. Schools distributed information and parent consent forms to students, with one follow‐up reminder to non‐respondents. Surveys were completed in classrooms under supervision of teaching and research staff. Surveys were anonymous, and matched on gender, age, school, school year and first three letters of first name. A similar procedure was implemented at post‐test. Pre–post surveys which could not be matched by identification codes were discarded.

Intervention

The Hunter Region HPS Project evolved as a collaborative partnership between the Hunter Area Health Service, the University of Newcastle, the NSW Department of Education and Training and the University of New England. The intervention was based on community organization theory in which intervention schools were encouraged to adopt and own their HPS program, and commit to implementing health promotion strategies to address the health risk behaviors. A pilot study involving six secondary schools from the Hunter Region was conducted from 1994 to 1996 (Lynagh et al., 1999). From this pilot study, a four‐stage model was developed: (1) establishing baseline health risk behaviors and gaining school‐wide commitment to HPS, (2) identifying key individuals and the optimal HPS structure for each school, (3) planning, implementing and monitoring HPS strategies, and (4) ongoing support and maintenance of HPS structures and activities. Key interventions included development of a minimum set of health promotion actions for schools which targeted knowledge and skills, availability of products, the environment, and role models. Strategies included ensuring that a formal school curriculum adequately addressed health risks associated with smoking, information leaflets and biweekly school newsletters for parents, letters to tobacco retailers, smoke‐free school policy development, encouragement of non‐smoking parents, peers and teachers as role models, peer influence programs, and incentive programs. Most strategies were implemented by the majority of intervention schools as presented in Table I.

Each school had a liaison officer responsible for introducing the minimum set of actions, and facilitating the tailoring and implementation of these actions, and was provided with regular feedback on progress in achieving the minimum actions. Schools were also encouraged to undertake additional health promotion activities of their own choice, some of which included drama skits performed by students and poster competitions to promote World No Tobacco Day. Further, the project team provided a range of activities to intervention schools such as training workshops, regular newsletters, quarterly reports and information resources such as computer interactive programs supplied to schools for defined periods of time for use by students in school libraries. Control schools were not offered any of the resources or actions to reduce smoking; however, if they requested assistance, then the project team offered support for other health‐related issues and promised smoking‐specific support at the completion of the study period. A more detailed description of the intervention program is provided elsewhere (Lynagh et al., 1999).

Measures

The principal outcome measure was smoking status at post‐test measured by self‐reported retrospective diary of having smoked within the past 7 days. Students were asked: ‘Have you EVER smoked even part of a cigarette?’. Response options were: Yes (just a few puffs); Yes (less than 10 cigarettes in my life); Yes (more than 10 cigarettes in my life); No. Those who had ever smoked were asked: ‘Have you smoked at all IN THE LAST 4 WEEKS?’ and ‘Have you smoked at all IN THE LAST WEEK?’. Yes respondents were asked to record the number of cigarettes smoked using a 7‐day retrospective diary.

Smoking of significant others

Students were asked whether or not the following people smoked cigarettes: their father/stepfather; their mother/stepmother; any brothers/sisters; and how many of their close friends.

Influences on smoking

To determine peer attitudes, students were asked: ‘Do your friends think that smoking cigarettes is: a cool thing to do; an uncool thing to do; neither cool nor uncool; or don’t know?’. Parental attitudes were assessed by asking: ‘What are the rules about smoking in your home?’. Response options included: ‘I can smoke anywhere in my house’; ‘I can smoke only in certain rooms in the house’; ‘I can smoke at home at anytime’; ‘I can smoke at home only sometimes’; ‘I’m not allowed to smoke at home at all’; ‘There are no rules about smoking at home’. Finally they were asked their expectations about future smoking: ‘One year from now, do you think that you will be: smoking cigarettes regularly; smoking cigarettes occasionally; not smoking at all?’.

Knowledge about smoking

Students were asked about the laws relating to sale of cigarettes to minors and what they think is a safe level of smoking. A score of 2 was classified as ‘good’ knowledge.

Attitudes towards smoking

Students were asked 20 questions about their attitudes towards smoking, using a four‐point response scale from ‘strongly agree’ to ‘strongly disagree’. Fourteen items measured positive perceptions about smoking, such as: ‘People who smoke are usually more popular than non‐smokers’, and six items measured negative perceptions (reverse scaled), such as: ‘Smoking can harm your health’.

Attitudes towards school

Positive perceptions of the school health environment were assessed by 17 questions, such as: ‘Teachers and parents try hard to make the school a healthy place’, coded using a four‐point scale from ‘strongly disagree’ to ‘strongly agree’.

Sociodemographics

Students were asked about their age, gender, country of birth of mother and father, and father/stepfather’s occupation, classified from 1 (highest) to 7 (Daniel, 1983).

Analysis

Exploratory factor analysis using principal components method and varimax rotation was performed on the 20 ‘attitude to smoking’ items and separately on the 17 items measuring ‘attitudes to school’. Items which cross‐loaded on several factors were eliminated. Items with a factor loading of 0.5 and above on one factor were retained. Inter‐item reliability for each factor was assessed using Cronbach’s α coefficients for standardized variables. Kaiser’s measure of sampling adequacy (MSA) estimated the degree of intercorrelations among items (Sharma, 1996).

Attitudes to smoking. Two factors measuring ‘perceived positives’ (10 items) and ‘perceived negatives’ (four items) of smoking were confirmed at both pre‐ and post‐test, keeping 14 of the original 20 items (Appendix Table AI). The factors accounted for at least 44% of total variance. Sampling adequacy was 0.86, indicating that factor analysis was appropriate.

Attitudes to school. For ‘attitudes to school’ items, four factors were confirmed at both pre‐ and post‐test, which included 13 of the original 17 items (Appendix Table AII). The factors were interpreted as ‘healthy school’ (five items), ‘support for sun protection’ (three items), ‘student involvement’ (three items) and ‘barriers to smoking’ (two items). They explained 59% of total variance; the Kaiser measure of sampling adequacy was 0.83. Factor scores for both scales were used in further analysis.

For the test of intervention effect, we had planned to use a cluster‐based multilevel analytic method. However, preliminary analysis of variability between and across schools revealed that the cluster effect of schools was relatively small, and the effect of schools in predicting smoking rates was not statistically significant.

Exploratory analyses of predictors of having smoked in the last 7 days involved calculating crude ORs for a range of categorical variables including: intervention group, school, age, gender, country of birth of mother and father, father’s occupation, parents’ risk status, sibling risk status, peer risk status, family rules about risk behaviors, knowledge and attitudes, expectations about future smoking, and attitudes towards school. Logistic regression was used to estimate the independent effects of explanatory variables after adjustment for all other factors, using PROC LOGISTIC in SAS (SAS Institute, 1989). Results are presented as odds ratios (OR) and 95% confidence intervals (CIs). As there were large variations in baseline smoking rates across schools (11–33%), pre‐test smoking and school were controlled for in the regression analysis.

Results

Sample characteristics

Twenty‐two of the 24 schools participated, yielding a 92% consent rate for schools (12 intervention; 10 control). Two control schools refused to participate due to major changes in school management at the time of recruitment. At pre‐test, 2573 students from intervention schools participated and 2268 from control schools (n = 4841, 60% consent for both groups). This consent rate was considered acceptable given the special challenges in recruiting adolescents in school‐based research, and the multilevel recruitment process involving district, school, teacher, parent and student (Harrington et al., 1997). The post‐test conducted 2 years later yielded average consent rates for control and intervention groups of 84.1 and 79.2% respectively, using all Year 9–10 students as the denominator. After matching pre‐post data, the final sample for analysis was 1852 (38% of pre‐test sample).

Of the 1852 participants, 55% were female and 27% had at least one parent born overseas. The occupational status of fathers was: lower status 61%, middle status 35% and high status 7% (17% missing data and 2.1% no occupation). At pre‐test, 19% had smoked in the last month; 8% had smoked in the last week (3.9% intervention and 4.1% control); 42% had at least one parent who smoked; 20% had at least one sibling who smoked. Smoking was seen by their peer group as a ‘cool thing’ to do by 9%, as ‘uncool’ by 24% and as ‘neither cool nor uncool’ by 67%. A total of 67% reported that they were not allowed to smoke at home, 6% were allowed and 11% reported no rules about smoking at home. At pre‐test, only 3% of students thought they would be smoking regularly in 1 year’s time, 12% smoking occasionally and 82% not smoking at all.

Pre‐test respondents who were lost to follow‐up comprised 48% from intervention and 52% from control groups (P = 0.05). A higher proportion of smokers were lost to follow‐up compared with non‐smokers (18% of those lost to follow‐up had smoked in last week and 32% had smoked in the last month, compared with 8 and 19%, respectively). Reasons for attrition included a high turnover in student enrolments over the 2 years, loss of year 10 students due to exam pressures, early school leaving and school excursions on survey days. The attrition rate is roughly comparable with the 25% annual rate reported by the High 5 Alabama Project, a whole‐school‐based intervention study conducted in 28 high schools over 2 years (Harrington et al., 1997).

Knowledge about smoking

At pre‐test, 53% of all students had good knowledge about smoking, 41% fair knowledge and 6% poor knowledge. At pre‐test, 30% of smokers had good knowledge about smoking compared with 55% of non‐smokers.

Attitudes to smoking

At pre‐test, smokers had less positive attitudes than non‐smokers (smokers’ mean = 4.3; non‐smokers’ mean = 4.7, mean difference = 0.4, 95% CI = 0.3, 0.5) and fewer perceived negatives about smoking (smokers’ mean = 3.6; non‐smokers’ mean = 3.9; mean difference = 0.2, 95% CI = 0.1, 0.3).

Attitudes to school

Pre‐test attitudes to school differed by smoking status on the ‘healthy school’ factor and the ‘student involvement’ factor. Smokers had fewer positive attitudes towards having a healthy school (smokers’ mean = 2.5; non‐smokers’ mean = 2.7; mean difference = 0.2, 95% CI = 0.1, 0.3) and towards being an active student compared with non‐smokers (smokers’ mean = 2.4; non‐smokers’ mean = 2.7; mean difference = 0.3, 95% CI = 0.2, 0.4).

Evaluation of smoking outcomes

Smoked in the last week

At post‐test, 20.5% of students reported having smoked in the last week in the control group compared with 17.5% in the intervention group. However, there was no pre–post difference in the proportion of students who had smoked in the last week by experimental group (10.0 and 9.7% increase in control and intervention groups, respectively).

Smoking knowledge

The HPS intervention program was successful in improving knowledge about smoking between pre‐ and post‐test. At post‐test, 64% of the intervention group had the maximum knowledge score compared with 60% in the control group, representing a pre‐ to post‐test increase of 12% in the intervention group versus 7% in the control group (P = 0.001).

Smoking attitudes

There were no significant differences between intervention and control groups at either pre‐test or post‐test for the perceived positives of smoking or the perceived negatives. Positive attitudes to smoking decreased from pre‐ to post‐test among smokers, but not among non‐smokers (P = 0.01).

Multivariate analyses of post‐test smoking status

Crude ORs indicated numerous predictors for student smoking behavior over the previous week at post‐test (Table II). For instance, if both parents were non‐smokers, students were considerably less likely to have smoked in the last week compared with students whose parents smoked. However, the adjusted ORs markedly reduced the number of significant predictors to six: smoking status at pre‐test, gender, number of close friends who smoke (at post‐test), peer group attitude at post‐test, attitude to smoking at post‐test and student involvement at school.

The strongest predictor of post‐test smoking was the students’ pre‐test smoking status, with pre‐test smokers more than 5 times as likely as non‐smokers to have smoked during the previous week. Boys were half as likely to have smoked in the last week as girls. Peer smoking at post‐test was also predictive: for each additional friend who smoked, students were 1.4 times more likely to smoke.

Smokers differed on several attitudes. Those who said their peer group had no attitude to whether smoking was ‘cool’ or not were 3.2 times more likely to smoke than students whose peers thought it was ‘cool’. As student disagreement with the ‘perceived positives’ of smoking increased from pre‐test to post‐test, then they were less likely to engage in smoking behavior. Similarly, as their agreement with ‘perceived negatives’ increased, they were less likely to have smoked in the previous week. Students who valued being involved in school activities were less likely to smoke than less involved students.

Summary of results

The intervention failed to reduce smoking uptake or improve smoking attitudes among this cohort of secondary students. However, it did result in increased knowledge about smoking. Several factors independently predicted post‐test smoking behavior including pre‐test smoking status, gender, number of close friends who smoked, perceived peer attitude to smoking, as well as attitudes towards both smoking and school.

Discussion and conclusions

This HPS project involved a strong multidisciplinary and collaborative partnership between health and education organizations. Such partnerships have the potential to maximize health promotion activities and outcomes at the community level, and have been strongly endorsed by a wide range of peak health bodies (WHO, 1995; National Health and Medical Research Council, 1996; Rasmussen and Rivett, 2000). A cohort of over 1800 students from 22 schools was followed over 2 years to overcome previous limitations of clustered designs and inadequate sample size, in keeping with the rationale underlying the COMMIT trials in the US (COMMIT Research Group, 1995). Another innovation of the project was its focus on secondary schools, which represent a more difficult and complex environment than primary schools for building strong partnerships. In addition, the study targeted a broad range of health outcomes, making the intervention program more complex to develop, implement and maintain.

The major finding of this study was that the intensive HPS program had no significant effect over 2 years in modifying smoking uptake among junior secondary school students. There was a 10.0% increase over the 2 years in the uptake of smoking for both groups. This highlights the difficulty of impacting on adolescent smoking behavior. It may be that the intervention program needed to occur earlier, before students reach high school (Elder et al., 1996), since attitudes may well have developed by the beginning of Year 8–9 when the intervention started in this study. However, evaluation of a HPS program in elementary schools also produced nil effect (McIntyre et al., 1996).

A positive outcome of the HPS program was the improved knowledge about smoking in the intervention group compared with the control group. Previous research and health promotion theory suggests that changes in knowledge precede behavior change (Green and Kreuter, 1991). Therefore, it could be that with further sustained effort in implementing the program within schools, a higher level of behavioral change would result. Duration of intervention and timing of follow‐up surveys are critical issues in the evaluation of health promotion programs (Basen‐Engquist et al., 1997).

There are a number of design limitations in the study that may partly account for the failure to influence smoking uptake. First, the baseline consent rate of students was less than desirable (60%), due to the requirement for active parental consent and difficulty in accessing the population for follow‐up. This is a well‐recognized limitation of school‐based research (Harrington et al., 1997). The pre–post attrition, while high, was not unusual for school populations (Mills et al., 2000). Nevertheless, it may have biased the results towards no effect since those lost to follow‐up had more than double the smoking rate (18% had smoked in last week) compared with the continuing sample (8%). This finding accords with a US study on longitudinal tracking and retention in school‐based studies which found that students classified as ever smokers in Grade 6 were the hardest to locate at each follow‐up (Mills et al., 2000). However, there was only a small difference in attrition between the intervention and control groups (48 versus 52%, respectively), making it unlikely that this attrition pattern substantially influenced results.

A further limitation is the difference in baseline smoking rates between control and intervention schools, with the control group having a higher smoking rate than the intervention group (10.5 versus 7.8%, respectively). Such a difference suggests that despite the random allocation of schools to groups, there may well have been differences which impacted on the potential to attain an intervention effect. Such bias would, however, be largely mitigated by the inclusion of school and a number of confounders in the multivariate model. While clustering is a potential design issue in community‐based research, intra‐class correlation coefficients in school‐based studies are consistently low for adolescent regular smoking (Carlin and Hocking, 2000), suggesting minimal cluster effect, and this was supported in our preliminary analysis of cluster effect in this study.

There are a number of structural factors that may also have mitigated against a greater intervention effect. The occurrence of major structural changes in the education sector caused delays in building the crucial partnership between the health and education sectors, which in turn impacted on the delivery of the program. Such political changes are difficult to control for and have a flow‐on effect, leading to changes in school staffing, policy and priorities, and a need to re‐negotiate with new stakeholders throughout the study. Reports from the School Liaison Officers demonstrated that there were considerable variations in the level of implementation of the intervention both between schools and over time within schools. However, there was a high level of compliance with the key components (the minimum set of action strategies) across intervention schools. This is inevitable due to the well‐acknowledged complexity of school environments (Green and Tones, 1999). Other barriers to the successful establishment of HPS have been reported elsewhere (Lynagh et al., 1999).

Another caution relates to the time frame of the pre–post evaluation, as has been noted by others (Mitchell et al., 2000). This time frame was considered minimal in terms of influencing smoking behavior. Given the more positive finding indicating change in knowledge, it is possible that a later follow‐up may show a longer term effect, although such a possibility is not supported by past research in which early positive findings tend to cancel out over time (Flay et al., 1989).

Although the randomized controlled study design has been acknowledged as a strength in clinical research, the use of this design to evaluate the effectiveness of the HPS program may be questioned. First, the large number of schools, organizations and individuals involved, together with the geographic ‘separateness’ of school communities, made monitoring the process of implementation very problematical. This made it difficult to assess whether the failure to find significant behavior change was due to the intervention being ineffective or because it was not properly implemented (Lister‐Sharp et al., 1999). Second, the HPS approach, by its nature, encourages empowerment and active participation of school community members. Randomization of schools does not consider the frame of mind of individual schools at the time of entering the study. Thus, some schools who may have been enthusiastic and committed to the HPS approach may have been randomized to the control group, thus potentially contaminating the study (Lister‐Sharp et al., 1999). Further, the randomized controlled trial gains its rigor in clinical research because of its power to control confounding variables. However, the complexity of school and community‐based research does not allow us to capitalize on this design strength.

Finally, this study focused on changes to health behavior as the main outcome used to assess the effectiveness of a HPS program. There is currently on‐going debate over what outcomes should be used to evaluate HPS interventions (Lister‐Sharp et al., 1999). Given the difficulties of trying to change young people’s smoking behavior, the positive impact of the intervention on student knowledge is encouraging. The fact that the majority of intervention schools implemented the minimum set of health promotion actions is also an encouraging achievement, given the HPS philosophy which recognizes the importance of establishing the right social and environmental conditions for achieving behavior change (Lister‐Sharp et al., 1999).

Despite these limitations, the results are important since they represent the first‐large scale evaluation of the HPS program in Australia targeted at the smoking behavior of young adolescents during the prime uptake period. The study confirmed the results of earlier studies that uptake of smoking among young adolescents is difficult to influence even with a multicomponent community‐based intervention (COMMIT Research Group, 1995). This creates a dilemma for health promotion practitioners, since multicomponent interventions are difficult and potentially costly to implement in a setting where there are many competing pressures on the time of teachers and school administrators, and among student priorities. Some have argued that randomized controlled trials may not be the most appropriate design for the evaluation of such complex social environments (Green and Tones, 1999). Further work is needed to assess the most efficient approach to promoting health among adolescents and to determine the most useful evaluation paradigms. In particular, there is increasing interest in the potential value of more qualitative approaches to evaluation (Macdonald et al., 1996).

Smoking knowledge and attitudes

The HPS program improved knowledge about smoking, but not attitudes. It is not clear why it failed to impact on attitudes to smoking. It is possible that the peer group influence is stronger than the potentially more diffuse impact of a school‐wide intervention program. Further research is needed to examine the effect of varying the intensity of the intervention package and the components addressing peer influence, as well as exploring measurement issues.

Predictors of smoking

Pre‐test smoking was the strongest predictor of post‐test smoking, highlighting the importance of targeting smoking prevention and cessation programs at early uptake smokers. Our findings strongly support the more widespread gender trend in which girls are nearly twice as likely as boys to be smokers in this early adolescent period. Gender‐specific smoking prevention and cessation programs are clearly necessary. Interventions also need to address attitudes to smoking and a positive culture of involvement in school activities.

Our analysis of predictors of post‐test smoking confirms clearly that peer smoking is a powerful influence on adolescent smoking, in line with other research (Distefan et al., 1998; Barber et al., 1999). Previous findings of a positive relationship between adolescent smoking and parental smoking, sibling smoking, smoking intention and family rules about smoking (Distefan et al., 1998; Farkas et al., 1999, 2000) were not supported in this study. Most of the research on risk factors has occurred in the US. Perhaps these influences are less important among Australian adolescents. Alternatively, it may be that the measures used in this study were less effective in eliciting these effects.

The multivariate analysis provided some support for previous findings that involvement in, or attachment to, school was associated with less likelihood of smoking uptake (Dornbusch et al., 2001). Strategies which encourage student involvement in stimulating activities are thus likely to help prevent uptake of unhealthy behaviors, consistent with the HPS concept.

In summary, the poor behavioral outcomes for smoking from this multicomponent health promotion intervention suggest that schools need to review their smoking prevention strategies and commit to more intensive programs to fight tobacco use, still the major cause of premature deaths. In particular, smoking prevention programs in schools need to be tailored to the specific needs of girls and boys, who demonstrate different patterns of uptake and consumption, as well as predictors of smoking uptake. Future research would benefit from employing a wider range of evaluation strategies to map more comprehensively what happens in intervention schools, and how interventions impact on both students and the school environment.

Acknowledgements

The Hunter Region Health Promoting Schools Project is a collaborative project funded jointly by the National Health and Medical Research Council (Australia) and the Hunter Centre for Health Advancement. We are grateful for the support offered by staff of the Department of Education and Training (Hunter and Taree Regions), the Hunter Area Health Service, the Mid‐North Coast Area Health Service and the NSW Cancer Council. We would also like to thank key advisors across many stages of the project, including Bruce Dietz, Lynne Hancock, Trevor Hazell, Wendy Honan, Jenny Knight, Sandra Lloyd, Neil Pratten, Rob Sanson‐Fisher, Deborah Sullivan and Ros Wells‐Davies. The project is also much indebted to the valuable contributions of the following project assistants: Deborah Huff, Dianne McCaffrey, Lorraine Paras and Maria Rees.

Appendix

Table I.

Level of implementation of the minimum set of actions targeting smoking in intervention schools

Minimum set of smoking prevention actions Schools implementing each action (N = 12) 
 n 
Ensure curriculum covers smoking effects 12 100 
Distribute parent smoking pamphlet 12 100 
School smoking policy implemented 10 83 
Tobacco retailer letters distributed 10 83 
Discussion group/survey conducted with parents 10 83 
Follow‐up action from discussion group/survey 58 
Training of SRC/peer leaders to deal with smoking issues 33 
Minimum set of smoking prevention actions Schools implementing each action (N = 12) 
 n 
Ensure curriculum covers smoking effects 12 100 
Distribute parent smoking pamphlet 12 100 
School smoking policy implemented 10 83 
Tobacco retailer letters distributed 10 83 
Discussion group/survey conducted with parents 10 83 
Follow‐up action from discussion group/survey 58 
Training of SRC/peer leaders to deal with smoking issues 33 
Table II.

Number and percentage of students who smoked in the last 7 days, ORs and 95% CIs from multiple logistic regression model for factors associated with smoking for students in Grade 9–10 in Australia in 1997

 Na Smoked cigarettes in the last 7 days at post test 
   Crude OR (95% CI) Adjusted OR (95% CI) 
Intervention group     
    control 845 20.5 1.00 NS 
    interventiona 1007 17.5 0.82 (0.65–1.04)  
School no.     
    3 82 28.1 1.00 1.00 
    2a 40 22.5 0.75 (0.31–1.80) 2.78 (0.67–11.4) 
    4a 70 22.9 0.76 (0.36–1.59) 0.57 (0.15–2.18) 
    5 85 12.9 0.38 (0.17–0.85) 0.36 (0.10–1.28) 
    6a 74 9.5 0.27 (0.11–0.67) 0.38 (0.09–1.65) 
    7a 120 28.3 1.01 (0.54–1.89) 0.46 (0.15–1.42) 
    8a 56 8.9 0.25 (0.09–0.71) 0.20 (0.02–2.31) 
    9a 74 21.6 0.71 (0.34–1.47) 0.32 (0.09–1.15) 
    10 113 18.6 0.59 (0.30–1.51) 0.26 (0.08–0.82) 
    11a 34 8.2 0.25 (0.07–0.92) 0.09 (0.01–1.11) 
    12 100 18.0 0.56 (0.28–1.14) 0.44 (0.13–1.54) 
    13a 84 8.3 0.23 (0.09–0.58) 0.30 (0.07–1.34) 
    15a 160 10.6 0.31 (0.15–0.61) 0.27 (0.07–1.11) 
    16a 41 17.1 0.53 (0.21–1.36) 0.26 (0.05–1.27) 
    18 55 20.0 0.64 (0.28–1.45) 0.32 (0.08–1.31) 
    20 150 21.3 0.70 (0.37–1.29) 0.61 (0.21–1.78) 
    21 76 18.4 0.58 (0.27–1.23) 0.45 (0.10–2.15) 
    22a 108 13.9 0.41 (0.29–0.86) 0.66 (0.18–2.46) 
    23 40 27.5 0.97 (0.42–2.27) 1.61 (0.31–8.43) 
    24a 146 27.4 0.97 (0.53–1.77) 1.50 (0.51–4.16) 
    25 68 23.5 0.79 (0.38–1.65) 1.90 (0.47–7.69) 
    26 76 21.1 0.64 (0.33–1.42) 0.44 (0.12–1.54) 
School year at pre‐test     
    7 962 15.4 1.00 NS 
    8 980 22.6 1.60 (1.27–2.03)  
Gender     
    female 1011 22.0 1.00 1.00 
    male 841 15.1 0.63 (0.50–0.80) 0.55 (0.35–0.87) 
Parents’ ethnicity     
    both Australian 1361 18.0 1.00  
    one Australian 204 20.6 1.18 (0.82–1.70) NS 
    other 287 21.6 1.26 (0.92–1.72)  
Father’s occupation (level)     
    1–2 133 11.3 1.00 NS 
    3–4 648 18.4 1.77 (1.00–3.14)  
    ≥5 720 18.9 1.83 (1.04–3.24)  
    0 40 20.0 1.97 (0.77–5.05)  
    missing 311 22.8 2.33 (1.28–4.24)  
Smoking at pre‐test     
    non‐smoker 1678 14.6 1.00 1.00 
    smoked in the last month 148 67.6 7.77 (5.96–10.13) 5.44 (3.20–9.28) 
Alcohol use at pre‐test     
    no consumption 1115 11.9 1.00 NS 
    consumption within the last month 726 29.6 3.11 (2.44–3.95)  
Parents’ smoking status     
    one 496 22.2 1.00 NS 
    both 284 27.5 1.33 (0.95–1.86)  
    none 1072 15.0 0.62 (0.47–0.82)  
Sibling smoking status     
    none (includes no siblings and missing) 1483 15.7 1.00 NS 
    at least one 369 31.4 2.46 (1.89–3.19)  
Peer group smoking attitude at pre‐test     
    cool 171 16.4 1.00 NS 
    uncool 436 9.4 0.53 (0.32–0.89)  
    neither 1245 22.5 1.48 (0.97–2.27)  
Family smoking rules at pre‐test     
    no rules 197 14.7 1.00 NS 
    allow 116 31.9 2.71 (1.56–4.73)  
    not allow 1246 18.3 1.30 (0.85–1.97)  
    other/missing 293 18.8 1.34 (0.82–2.19)  
Smoking intention at pre‐test     
    smoking regularly 62 66.1 1.00 1.00 
    smoking occasionally 227 47.6 0.47 (0.26–0.84) 0.92 (0.33–2.57) 
    not smoking 1521 12.4 0.07 (0.04–0.13) 0.40 (0.14–1.10) 
    missing 42 26.2 0.18 (0.08–0.43) 0.26 (0.05–1.42) 
Score for smoking knowledge at pre‐test     
    0 110 30.0 1.00 NS 
    1 757 23.1 0.70 (0.41–1.09)  
    2 961 18.4 0.38 (0.24–0.59)  
Number of close friends who smoke at     post‐test (mean ± SD) 344 8.0 ± 2.84 1.45 (1.39–1.51) 1.42 (1.33–1.52) 
Peer group smoking attitude at post‐test     
    cool 150 8.7 1.00 1.00 
    uncool 273 1.8 0.20 (0.07–0.56) 1.32 (0.31–5.62) 
    neither 1429 23.2 3.18 (1.78–5.69) 3.23 (1.27–8.27) 
Feeling towards school at post‐test     
    like it a lot 211 14.2 1.00 NS 
    like it a bit 848 13.8 0.97 (0.63–1.49)  
    dislike it a bit 425 23.1 1.81 (1.56–2.83)  
    dislike it a lot 329 29.2 2.49 (1.58–3.91)  
Teacher’s assessment of student (student view)     
    very good 314 11.2 1.00 NS 
    good 747 17.4 1.68 (1.13–2.50)  
    average 639 20.5 2.06 (1.38–3.07)  
    below average 108 36.1 4.51 (2.66–7.63)  
Intention for continuing education at post‐test     
    no 114 37.8 1.00 NS 
    yes 1685 17.4 0.36 (0.24–0.54)  
    missing 53 26.4 0.62 (0.30–1.26)  
Attitude to smoking at post‐test     
    perceived positives (mean ± SD) 206 –0.04 ± 1.1 1.00 (0.86–1.17) 0.12 (0.58–0.89) 
    perceived negatives (mean ± SD) 206 –0.2 ± 1.2 0.93 (0.81–1.07) 0.72 (0.59–0.88) 
Attitude to school at post‐test     
    healthy school (mean ± SD) 301 2.5 ± 0.8 0.74 (0.63–0.86) 0.78 (0.59–1.02) 
    student activity (mean ± SD) 301 2.4 ± 0.8 0.64 (0.56–0.75) 0.73 (0.57–0.94) 
 barriers (mean ± SD) 301 1.5 ± 0.9 0.89 (0.77–1.02) NS 
 Na Smoked cigarettes in the last 7 days at post test 
   Crude OR (95% CI) Adjusted OR (95% CI) 
Intervention group     
    control 845 20.5 1.00 NS 
    interventiona 1007 17.5 0.82 (0.65–1.04)  
School no.     
    3 82 28.1 1.00 1.00 
    2a 40 22.5 0.75 (0.31–1.80) 2.78 (0.67–11.4) 
    4a 70 22.9 0.76 (0.36–1.59) 0.57 (0.15–2.18) 
    5 85 12.9 0.38 (0.17–0.85) 0.36 (0.10–1.28) 
    6a 74 9.5 0.27 (0.11–0.67) 0.38 (0.09–1.65) 
    7a 120 28.3 1.01 (0.54–1.89) 0.46 (0.15–1.42) 
    8a 56 8.9 0.25 (0.09–0.71) 0.20 (0.02–2.31) 
    9a 74 21.6 0.71 (0.34–1.47) 0.32 (0.09–1.15) 
    10 113 18.6 0.59 (0.30–1.51) 0.26 (0.08–0.82) 
    11a 34 8.2 0.25 (0.07–0.92) 0.09 (0.01–1.11) 
    12 100 18.0 0.56 (0.28–1.14) 0.44 (0.13–1.54) 
    13a 84 8.3 0.23 (0.09–0.58) 0.30 (0.07–1.34) 
    15a 160 10.6 0.31 (0.15–0.61) 0.27 (0.07–1.11) 
    16a 41 17.1 0.53 (0.21–1.36) 0.26 (0.05–1.27) 
    18 55 20.0 0.64 (0.28–1.45) 0.32 (0.08–1.31) 
    20 150 21.3 0.70 (0.37–1.29) 0.61 (0.21–1.78) 
    21 76 18.4 0.58 (0.27–1.23) 0.45 (0.10–2.15) 
    22a 108 13.9 0.41 (0.29–0.86) 0.66 (0.18–2.46) 
    23 40 27.5 0.97 (0.42–2.27) 1.61 (0.31–8.43) 
    24a 146 27.4 0.97 (0.53–1.77) 1.50 (0.51–4.16) 
    25 68 23.5 0.79 (0.38–1.65) 1.90 (0.47–7.69) 
    26 76 21.1 0.64 (0.33–1.42) 0.44 (0.12–1.54) 
School year at pre‐test     
    7 962 15.4 1.00 NS 
    8 980 22.6 1.60 (1.27–2.03)  
Gender     
    female 1011 22.0 1.00 1.00 
    male 841 15.1 0.63 (0.50–0.80) 0.55 (0.35–0.87) 
Parents’ ethnicity     
    both Australian 1361 18.0 1.00  
    one Australian 204 20.6 1.18 (0.82–1.70) NS 
    other 287 21.6 1.26 (0.92–1.72)  
Father’s occupation (level)     
    1–2 133 11.3 1.00 NS 
    3–4 648 18.4 1.77 (1.00–3.14)  
    ≥5 720 18.9 1.83 (1.04–3.24)  
    0 40 20.0 1.97 (0.77–5.05)  
    missing 311 22.8 2.33 (1.28–4.24)  
Smoking at pre‐test     
    non‐smoker 1678 14.6 1.00 1.00 
    smoked in the last month 148 67.6 7.77 (5.96–10.13) 5.44 (3.20–9.28) 
Alcohol use at pre‐test     
    no consumption 1115 11.9 1.00 NS 
    consumption within the last month 726 29.6 3.11 (2.44–3.95)  
Parents’ smoking status     
    one 496 22.2 1.00 NS 
    both 284 27.5 1.33 (0.95–1.86)  
    none 1072 15.0 0.62 (0.47–0.82)  
Sibling smoking status     
    none (includes no siblings and missing) 1483 15.7 1.00 NS 
    at least one 369 31.4 2.46 (1.89–3.19)  
Peer group smoking attitude at pre‐test     
    cool 171 16.4 1.00 NS 
    uncool 436 9.4 0.53 (0.32–0.89)  
    neither 1245 22.5 1.48 (0.97–2.27)  
Family smoking rules at pre‐test     
    no rules 197 14.7 1.00 NS 
    allow 116 31.9 2.71 (1.56–4.73)  
    not allow 1246 18.3 1.30 (0.85–1.97)  
    other/missing 293 18.8 1.34 (0.82–2.19)  
Smoking intention at pre‐test     
    smoking regularly 62 66.1 1.00 1.00 
    smoking occasionally 227 47.6 0.47 (0.26–0.84) 0.92 (0.33–2.57) 
    not smoking 1521 12.4 0.07 (0.04–0.13) 0.40 (0.14–1.10) 
    missing 42 26.2 0.18 (0.08–0.43) 0.26 (0.05–1.42) 
Score for smoking knowledge at pre‐test     
    0 110 30.0 1.00 NS 
    1 757 23.1 0.70 (0.41–1.09)  
    2 961 18.4 0.38 (0.24–0.59)  
Number of close friends who smoke at     post‐test (mean ± SD) 344 8.0 ± 2.84 1.45 (1.39–1.51) 1.42 (1.33–1.52) 
Peer group smoking attitude at post‐test     
    cool 150 8.7 1.00 1.00 
    uncool 273 1.8 0.20 (0.07–0.56) 1.32 (0.31–5.62) 
    neither 1429 23.2 3.18 (1.78–5.69) 3.23 (1.27–8.27) 
Feeling towards school at post‐test     
    like it a lot 211 14.2 1.00 NS 
    like it a bit 848 13.8 0.97 (0.63–1.49)  
    dislike it a bit 425 23.1 1.81 (1.56–2.83)  
    dislike it a lot 329 29.2 2.49 (1.58–3.91)  
Teacher’s assessment of student (student view)     
    very good 314 11.2 1.00 NS 
    good 747 17.4 1.68 (1.13–2.50)  
    average 639 20.5 2.06 (1.38–3.07)  
    below average 108 36.1 4.51 (2.66–7.63)  
Intention for continuing education at post‐test     
    no 114 37.8 1.00 NS 
    yes 1685 17.4 0.36 (0.24–0.54)  
    missing 53 26.4 0.62 (0.30–1.26)  
Attitude to smoking at post‐test     
    perceived positives (mean ± SD) 206 –0.04 ± 1.1 1.00 (0.86–1.17) 0.12 (0.58–0.89) 
    perceived negatives (mean ± SD) 206 –0.2 ± 1.2 0.93 (0.81–1.07) 0.72 (0.59–0.88) 
Attitude to school at post‐test     
    healthy school (mean ± SD) 301 2.5 ± 0.8 0.74 (0.63–0.86) 0.78 (0.59–1.02) 
    student activity (mean ± SD) 301 2.4 ± 0.8 0.64 (0.56–0.75) 0.73 (0.57–0.94) 
 barriers (mean ± SD) 301 1.5 ± 0.9 0.89 (0.77–1.02) NS 

aIntervention schools.

Table AI.

Factor loadings, cumulative percentage of variation, and internal reliability on attitude towards smoking scale at pre‐ and post‐test (n = 2038)

Item Pre‐test Post‐test 
 Perceived positives Perceived negatives Perceived positives Perceived negatives 
Smoking makes you look more attractive 0.68 0.21 0.73 0.16 
Kids who smoke seem more grown up than kids who don’t 0.66 0.04 0.74 0.06 
I would smoke if it helped me stay thin 0.66 0.07 0.64 0.07 
Students should be allowed to smoke 0.65 0.18 0.62 0.20 
Smoking is a good way to keep your weight down 0.64 0.14 0.68 0.11 
People who smoke are better at sport than non‐smokers 0.63 0.18 0.66 0.21 
People enjoy life more when they smoke 0.62 0.10 0.70 0.14 
Coaches of sporting teams approve of smoking 0.58 0.13 0.60 0.23 
Most of my sports idols smoke 0.55 0.05 0.67 0.11 
People who smoke are usually more popular 0.51 –0.04 0.58 –0.12 
     
Smoking can harm your healtha 0.11 0.79 0.13 0.81 
Smoking makes you short of breatha 0.03 0.74 0.09 0.81 
Breathing other people’s cigarette smoke is harmful to your healtha 0.12 0.70 0.14 0.72 
When you smoke you look awfula 0.15 0.61 0.10 0.62 
     
Cumulative percentage of variation ‘explained’ 0.31 0.44 0.36 0.49 
Cronbach’s α coefficients 0.83 0.68 0.86 0.75 
Item Pre‐test Post‐test 
 Perceived positives Perceived negatives Perceived positives Perceived negatives 
Smoking makes you look more attractive 0.68 0.21 0.73 0.16 
Kids who smoke seem more grown up than kids who don’t 0.66 0.04 0.74 0.06 
I would smoke if it helped me stay thin 0.66 0.07 0.64 0.07 
Students should be allowed to smoke 0.65 0.18 0.62 0.20 
Smoking is a good way to keep your weight down 0.64 0.14 0.68 0.11 
People who smoke are better at sport than non‐smokers 0.63 0.18 0.66 0.21 
People enjoy life more when they smoke 0.62 0.10 0.70 0.14 
Coaches of sporting teams approve of smoking 0.58 0.13 0.60 0.23 
Most of my sports idols smoke 0.55 0.05 0.67 0.11 
People who smoke are usually more popular 0.51 –0.04 0.58 –0.12 
     
Smoking can harm your healtha 0.11 0.79 0.13 0.81 
Smoking makes you short of breatha 0.03 0.74 0.09 0.81 
Breathing other people’s cigarette smoke is harmful to your healtha 0.12 0.70 0.14 0.72 
When you smoke you look awfula 0.15 0.61 0.10 0.62 
     
Cumulative percentage of variation ‘explained’ 0.31 0.44 0.36 0.49 
Cronbach’s α coefficients 0.83 0.68 0.86 0.75 

Italic highlights items which contribute most to each factor.

aItem responses reversed for coding.

Table AII.

Factor loadings, cumulative percentage of variation and internal reliability on attitude towards school scale at post‐test

Item % (n = 2038)a Factor loadings Communality 
  Healthy school Support for sun protection Student involvement Barriers to smoking  
Teachers put a lot of effort into convincing us not to smoke cigarettes 42.3 0.77 0.14 0.00 0.13 0.63 
Teachers help me to learn how to refuse peer pressure to drink alcohol 36.9 0.77 0.14 0.04 0.06 0.61 
The health of students is seen as very important in this school 38.3 0.74 0.12 0.13 0.13 0.60 
Teachers and parents try hard to make this school a healthy place for students 22.4 0.69 0.19 0.15 0.04 0.53 
I am given lots of opportunities to voice my opinions and have a say about important issues in the school. 59.9 0.57 0.16 0.25 0.17 0.44 
I am often reminded by teachers to put on some sunscreen before outdoor PE/sport lessons and at sports carnivals 54.6 0.18 0.87 0.08 0.07 0.80 
I am often reminded by teachers to wear a hat during PE/sport lessons and at sports carnivals 50.4 0.17 0.83 0.11 0.08 0.74 
Sunscreen is always available at school if I want to use it 46.9 0.18 0.61 0.09 0.05 0.41 
I like to get involved in school extra‐curricula activities like student councils, school band, debating teams, plays, concerts, dances, etc. 62.0 0.03 0.13 0.76 0.00 0.60 
I believe it is important to make a useful contribution to my school 36.6 0.29 0.13 0.72 0.00 0.62 
I like to take part in most school sports activities 35.8 0.07 0.02 0.66 0.11 0.46 
It’s difficult for under 18 years to buy cigarettes in our local area 66.7 0.15 0.07 –0.05 0.78 0.64 
Other students in my school put a lot of effort into stopping students from smoking at school 86.4 0.15 0.08 0.17 0.74 0.61 
Cumulative percentage of variation ‘explained’  31 41 51 59  
Cronbach’s α coefficients  0.78 0.70 0.60 0.40  
Item % (n = 2038)a Factor loadings Communality 
  Healthy school Support for sun protection Student involvement Barriers to smoking  
Teachers put a lot of effort into convincing us not to smoke cigarettes 42.3 0.77 0.14 0.00 0.13 0.63 
Teachers help me to learn how to refuse peer pressure to drink alcohol 36.9 0.77 0.14 0.04 0.06 0.61 
The health of students is seen as very important in this school 38.3 0.74 0.12 0.13 0.13 0.60 
Teachers and parents try hard to make this school a healthy place for students 22.4 0.69 0.19 0.15 0.04 0.53 
I am given lots of opportunities to voice my opinions and have a say about important issues in the school. 59.9 0.57 0.16 0.25 0.17 0.44 
I am often reminded by teachers to put on some sunscreen before outdoor PE/sport lessons and at sports carnivals 54.6 0.18 0.87 0.08 0.07 0.80 
I am often reminded by teachers to wear a hat during PE/sport lessons and at sports carnivals 50.4 0.17 0.83 0.11 0.08 0.74 
Sunscreen is always available at school if I want to use it 46.9 0.18 0.61 0.09 0.05 0.41 
I like to get involved in school extra‐curricula activities like student councils, school band, debating teams, plays, concerts, dances, etc. 62.0 0.03 0.13 0.76 0.00 0.60 
I believe it is important to make a useful contribution to my school 36.6 0.29 0.13 0.72 0.00 0.62 
I like to take part in most school sports activities 35.8 0.07 0.02 0.66 0.11 0.46 
It’s difficult for under 18 years to buy cigarettes in our local area 66.7 0.15 0.07 –0.05 0.78 0.64 
Other students in my school put a lot of effort into stopping students from smoking at school 86.4 0.15 0.08 0.17 0.74 0.61 
Cumulative percentage of variation ‘explained’  31 41 51 59  
Cronbach’s α coefficients  0.78 0.70 0.60 0.40  

Italic highlights items which contribute most to each factor.

aPercentage of students who agree with the corresponding item.

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Author notes

School of Health, University of New England, Armidale, NSW 2351, and 1Faculty of Medicine and Health Sciences, and 2Department of Statistics, University of Newcastle, Callaghan, NSW 2308, Australia 3Present address: Medical Research Council Human Nutrition Unit, Cambridge CB1 9NL, UK

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