Article Text

The impact of social norm change strategies on smokers' quitting behaviours
1. Xueying Zhang,
2. David W Cowling,
3. Hao Tang
1. California Department of Public Health, Tobacco Control Program, Sacramento, California, USA
1. Correspondence to Ms Xueying Zhang, California Department of Public Health, Tobacco Control Program, MS 7206, P.O. Box 997377, Sacramento, CA 95899-7377, USA; xueying.zhang{at}cdph.ca.gov

## Abstract

Objective Using a social norm change paradigm model that reflects the California Tobacco Control Program's (CTCP) priorities, we compare the strength of the relationship of the social norm constructs to key smoking behavioural outcomes.

Methods Social norm constructs that correspond to CTCP's priority areas were created from selected California Adult Tobacco Survey knowledge, attitude and belief questions using confirmatory factor analysis. We then examined the relationship between these constructs and quitting behaviours using logistic regression.

Results The secondhand smoke (SHS) and countering pro-tobacco influences'(CPTI) constructs followed a dose-response curve with quitting behaviours. Respondents who rated high on the SHS construct were about 70% more likely to have made a recent quit attempt in the last 12 months and about 100% more likely to intend to quit in the next 6 months than respondents who rated low on the SHS construct. For CPTI, respondents who rated high on this construct were 67% more likely to have made a recent quit attempt in the last 12 months and 62% more likely to have intentions to quit in the next 6 months than respondents who rated low on the CPTI construct.

Conclusion Social norm change constructs represent CTCP's priorities and are strongly related to desired individual behaviour outcomes. This analysis provides strong support for the framework underlying CTCP—namely, that changing social norms affects behaviour change at the individual level through changing population-level smoking-related behaviours.

• Tobacco
• attitudes
• factor analysis
• social behaviour
• surveillance and monitoring
• tobacco products

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## Introduction

### Confirmatory factor analysis

Confirmatory factor analysis (CFA) was used to investigate whether the established dimensionality of attitudes and beliefs and its factor-loading pattern fit the data. Figure 1 presents the latent factors and the subsets of attitudinal variables of each factor. We used SHS, CPTI, tobacco availability and tobacco product regulation as the four underlying dimensions. These four latent factors were chosen using the CTCP's social norm change framework. To test the stability of the factor structure over years, and whether it is appropriate to combine multiple years' CATS data for future analysis, 11 survey years (1997–2007) were sorted into three time periods: 1997–2000, 2000–2003 and 2004–2007. CFA was conducted for each combined sample for each time period, and the factor loadings from the three models were compared. No meaningful difference was observed among the factor loadings of the three time periods. Because the factor-loading pattern of attitudes and beliefs did not change over time, we combined data from 1997 to 2007 and fitted the CFA using the combined data set. The CFA analysis was conducted in SAS V.9.1 using the CALIS procedure with a set of structural equations described in the LINEQS statement.

Figure 1

Latent structure and factor loadings for attitudes/beliefs from the California Adult Tobacco Survey 1997–2007. CPTI, countering pro-tobacco influences in the community; SHS, secondhand smoke; TI, tobacco industry.

The CFA yielded good fit indices: the Root Mean Square Error of Approximation Test, a measure of model residuals, was equal to 0.06, and the Goodness Fit Index adjusted for degrees of freedom was 0.92 (0.90 and higher indicating good fit).23

In order to categorise the factor scores into groups, we scaled the factor scores to values between zero and 100 to allow for divergent social norms in the low and high groups. Based on the distribution of the four constructs, we categorised individuals into the low group if factor scores fell below 70 and high if above 90. For each factor, a high score meant respondents had attitudes and beliefs that were more closely aligned with desired tobacco control attitudes and beliefs.

Multivariate logistic regression was used to relate the latent variables with quitting behaviours of interest—a quit attempt in the last 12 months and intentions to quit in the next 6 months. The regression model also included other known predictors of quitting behaviours, including age, gender, race/ethnicity and SES.

## Results

As shown in figure 2, among the four social norm constructs, SHS norms consistently produced the highest scores and CPTI had the lowest scores over the 10-year period. The four constructs showed small incremental increases over time. Quitting behaviours also showed a similar upward trend during this period.

Figure 2

Social norm index trend from 1997 to 2007. CPTI, countering pro-tobacco influences in the community; SHS, secondhand smoke.

SHS attitudes were strongly related to smoking status (AOR=0.19 for high vs low; 95% CI: 0.14, 0.24). In this instance, attitudes may not be a precursor of smoking behaviour as a large portion of these attitudes may be determined by an individual's smoking status. A stronger set of attitudes and beliefs for CPTI (AOR=0.67 for high to low; 95% CI: 0.53, 0.86) were also strongly related to smoking status.

SHS and CPTI norms demonstrated a dose–response relationship with having made a quit attempt and having intentions to quit. As shown in table 2, respondents with higher SHS scores were over 1.7 times more likely to have made a quit attempt in the last 12 months compared to respondents with low factor scores (AOR=1.7 for high vs low; 95% CI: 1.40, 2.07). Respondents with higher SHS scores were twice as likely to have an intention to quit in the next 6 months than respondents with low factor scores (AOR=2.0 for high vs low; 95% CI: 1.55, 2.46).

Table 2

Adjusted odds ratios for the association between attitude scales and quitting behaviors

Respondents with higher CPTI factor scores were about 70% more likely to have made a quit attempt in last 12 months than respondents with low factor scores (AOR=1.67 for high vs low; 95% CI: 1.26, 2.22) and 1.6 times more likely to have an intention to quit in next 6 months than respondents with low factor scores (AOR=1.62 for high vs low; 95% CI: 1.14, 2.30).

Tobacco product regulation was not associated with quit attempts (AOR=1.2 for high vs low; 95% CI: 0.85, 1.60) or intentions to quit in the next 6 months (AOR=1.1 for high vs low; 95% CI: 0.73, 1.60). Also, Tobacco Availability was not associated with quit attempts (AOR=0.9 for high vs low; 95% CI: 0.66, 1.26) or intentions to quit in the next 6 months (AOR=1.2 for high vs low; 95% CI: 0.83, 1.86).

## Discussion

Tobacco-related knowledge, attitude and belief questions from a population-based survey were used as representative factors (latent variables) that are presumed to measure CTCP's progress in changing tobacco-related social norms and population-level smoking behaviours. CPTI and SHS were shown to be associated with quitting behaviours. Smokers with more positive attitudes towards CPTI and SHS reported more quit attempts and intentions. Programmatically, CTCP has had tremendous success in these two priority areas: reducing SHS exposure through implementing SHS laws locally and exposing the predatory marketing practices of the tobacco industry through a comprehensive, multi-cultural and multi-lingual advertising campaign. Although CTCP does not actively focus on individual behaviour change through promoting its cessation services, the programme's social norm change strategies still make smokers quit smoking.

Besides quitting behaviours, we examined the association between the constructs and smoking status. We found a strong association between SHS constructs and smoking status. Because we used repeated cross-sectional surveys, it is not clear whether desired attitudes and beliefs determine smoking status or whether smoking status determines attitudes and beliefs. However, by focusing only on smokers we were able to control for smoking status as a major predictor of tobacco-related attitudes.

The CTCP has had and is currently achieving local programme success around Tobacco Availability; however, this area was not associated with quit attempts nor quit intentions. Attitudes about Tobacco Availability were not related to norms but were related to the enforcement of laws. Consequently, future attitude questions will need to tactfully address the CTCP's messages and activities around Tobacco Availability.

In California, the SHS construct in the future could be improved by including measures of items to address the expansion of outdoor SHS laws, such as on beaches and parks. Additionally, the introduction of harm reduction products necessitates adjustment to tobacco product regulation questions and potentially to the CPTI measures. Since we used data from 1997 to 2007, we could only examine the trend of the four constructs after 1997. But social norms prior to the first survey (1997) are also likely to have changed because the CTCP has been implementing the social norm change strategy since 1989.

We found a compelling link between the social norm change paradigm and quitting behaviours. This relationship provides evidence for theoretical underpinnings of this paradigm, demonstrates that the social norm change approach can lead to meaningful changes in tobacco-related health behaviours, and provides support for being an effective public health model applicable to other tobacco control programmes worldwide.

The California Tobacco Control Program (CTCP) was the first tobacco control program to integrate a ‘social norm change’ approach as its core strategy to achieve its goals. This paper used a social norm change paradigm model to reflect CTCP's priorities and compared the strength of the relationship of the social norm constructs to key smoking behavioral outcomes. This paper provides strong support for the framework underlying CTCP – namely, that changing social norms affects behavior change at the individual level through changing population-level smoking-related behaviors.

## Acknowledgments

We thank Dr Michael K Cummings for his invaluable comments.

## Footnotes

• Competing interests None.

• Provenance and peer review Not commissioned; externally peer reviewed.