| Literature DB >> 29450227 |
Hugh Webb1, Benjamin M Jones1, Kathleen McNeill1, Li Lim1, Andrew J Frain1, Kerry J O'Brien1, Daniel P Skorich2, Peta Hoffmann1, Tegan Cruwys2.
Abstract
This study tests a social identity based mechanism for the effectiveness of plain tobacco packaging legislation, introduced in Australia in December 2012, to reduce cigarette smoking. 178 Australian smokers rated their sense of identification with fellow smokers of their brand, positive brand stereotypes, quitting behaviours and intentions, and smoking intensity, both before and seven months after the policy change. Mediation analyses showed that smokers, especially those who initially identified strongly with their brand, experienced a significant decrease in their brand identity following the introduction of plain packaging and this was associated with lower smoking behaviours and increased intentions to quit. The findings provide the first quantitative evidence that brand identities may help maintain smoking behaviour, and suggest the role of social-psychological processes in the effectiveness of public health policy.Entities:
Keywords: Addiction; Plain tobacco packaging; Self-categorisation theory; Smoking cessation; Social cure; Social identity theory
Year: 2017 PMID: 29450227 PMCID: PMC5800577 DOI: 10.1016/j.abrep.2017.02.003
Source DB: PubMed Journal: Addict Behav Rep ISSN: 2352-8532
Characteristics of W2 responders and non-responders and independent samples t-tests (chi-square tests) to assess differential attrition.
| Responded to W2 | N | Mean (%) | Std. deviation | p | |
|---|---|---|---|---|---|
| W1 brand identification | No | 83 | 3.69 | 1.23 | 0.37 |
| Yes | 178 | 3.55 | 1.16 | ||
| W1HSI | No | 83 | 2.07 | 1.44 | 0.32 |
| Yes | 178 | 2.27 | 1.51 | ||
| Age | No | 83 | 28.98 | 10.18 | < 0.001 |
| Yes | 178 | 34.80 | 12.90 | ||
| Index of relative socio-economic disadvantage | No | 83 | 1015.73 | 127.82 | 0.18 |
| Yes | 178 | 1035.31 | 101.68 | ||
| Gender (male) | Yes | 83 | (67.5) | < 0.01 | |
| No | 178 | (50.6) | |||
| Completed university | Yes | 83 | (28.9) | 0.26 | |
| No | 178 | (36.0) | |||
| Intend to quit in next 6 months (%) | No | 83 | (75.0) | 0.64 | |
| Yes | 178 | (72.0) |
Within subjects t-tests assessing changes in brand identity, positive brand stereotypes, cigarettes smoked per day, and salience of health warning labels between W1 and W2, for those participants still smoking at W2 (N = 149).
| M W1 | M W2 | t | df | |
|---|---|---|---|---|
| Brand identification | 3.53 | 3.23 | − 2.68 | 148 |
| Positive brand stereotypes | 3.79 | 3.39 | − 3.38 | 148 |
| Cigarettes per day | 14.13 | 11.41 | − 4.88 | 148 |
| Salience of health warning labels | 2.86 | 3.01 | 1.18 | 148 |
p < 0.01.
p < 0.001.
Zero order correlation matrix for main study variables.
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Sex (1 = male, 0 = female) | 1.00 | |||||||||
| 2 | Age | − 0.017 | 1.00 | ||||||||
| 3 | Education (1 = university, 0 = less than university) | 0.010 | − 0.205 | 1.00 | |||||||
| 4 | SES (1 = above average, 0 = below average) | − 0.042 | − 0.099 | 0.093 | 1.00 | ||||||
| 5 | W1 HSI | 0.077 | 0.458 | − 0.236 | − 0.210 | 1.00 | |||||
| 6 | W1 Brand Identity | 0.143 | − 0.006 | − 0.025 | 0.107 | − 0.050 | 1.00 | ||||
| 7 | Residualised decrease in brand identity | − 0.157 | − 0.024 | − 0.038 | 0.045 | 0.012 | na | 1.00 | |||
| 8 | Quit for at least 7 days | 0.101 | − 0.218 | − 0.087 | 0.060 | − 0.033 | − 0.063 | 0.163 | 1.00 | ||
| 9 | W2 HSI | − 0.082 | 0.280 | − 0.142 | − 0.181 | 0.746 | − 0.127 | − 0.138 | na | 1.00 | |
| 10 | W2 at least 1 quit attempt (no attempts = 0, attempts = 1) | 0.008 | − 0.172 | 0.085 | − 0.017 | − 0.142 | − 0.025 | 0.199 | na | − 0.206 | 1.00 |
| 11 | W2 quit intentions (intend to quit in next 6 months = 1, no intent = 0) | − 0.072 | − 0.119 | − 0.020 | − 0.087 | 0.053 | − 0.332 | 0.261 | na | − 0.028 | 0.375 |
Decrease in brand identity, measured as: − 1 ×(residualised change in brand identity).
Correlations with quitting are calculated based on the full sample (N = 178), all other correlations are presented for the sample who had not quit (N = 149).
The association between brand identity and residualised change, is zero by definition. The latent decrease score analysis shown in Fig. 1 provides a valid method for statistically analysing the relationship between W1 brand identity and the decrease in brand identity (see McArdle, 2009 for a statistical discussion of this issue).
p < 0.05.
p < 0.01.
Regression of smoking behaviours and quit intentions on (residualised) brand identity decrease, prior smoking intensity, and increased salience of health warning labels.
| Outcome variable and predictor variables | Model 1 | Model 2a | Model 2b | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AdjOR (β) | 95% CI | N | p | AdjOR (β) | 95% CI | N | p | AdjOR (β) | 95% CI | N | p | |
| Quit at W2 | 178 | 178 | 142 | |||||||||
| Brand identity decrease | 1.67 | 1.06,2.61 | 0.024 | 1.61 | 1.02,2.54 | 0.040 | 1.91 | 1.17,3.11 | 0.01 | |||
| W1 Heaviness of Smoking Index | 1.16 | 0.81,1.65 | 0.42 | 1.04 | 0.73,1.49 | 0.83 | ||||||
| Increased warning label salience | 1.02 | 0.64,1.64 | 0.92 | 1.03 | 0.63,1.68 | 0.90 | ||||||
| W2 HSI | 149 | 149 | 113 | |||||||||
| Brand identity decrease | (− 0.10) | − 0.43,0.09 | 0.19 | (− 0.17) | − 0.45,−0.10 | < 0.01 | − 0.12 | − 0.41,−0.02 | 0.035 | |||
| W1 Heaviness of Smoking | (0.80) | 0.74,1.01 | < 0.001 | 0.82 | 0.73,1.0 | < 0.001 | ||||||
| Increased warning label salience | (− 0.025) | − 0.22,0.14 | 0.64 | − 0.05 | − 0.27,0.12 | 0.43 | ||||||
| At least 1 quit attempt | 148 | 148 | 113 | |||||||||
| Brand identity decrease | 1.44 | 1.01,2.05 | 0.044 | 1.47 | 1.03,2.11 | 0.036 | 1.35 | 0.88,2.07 | 0.16 | |||
| W1 Heaviness of Smoking Index | 0.88 | 0.68,1.15 | 0.36 | 0.95 | 0.71,1.28 | 0.74 | ||||||
| Increased warning label salience | 1.56 | 1.08,2.25 | 0.017 | 1.78 | 1.16,2.72 | < 0.01 | ||||||
| W2 intention to quit in next 6 months | 149 | 149 | 113 | |||||||||
| Brand identity decrease | 1.80 | 1.20,2.71 | < 0.01 | 1.75 | 1.16,2.63 | < 0.01 | 1.94 | 1.17,3.21 | 0.01 | |||
| W1 Heaviness of Smoking Index | 1.22 | 0.91,1.63 | 0.18 | 1.24 | 0.89,1.71 | 0.20 | ||||||
| Increased warning label salience | 1.26 | 0.86,1.85 | 0.23 | 1.46 | 0.93,2.28 | 0.10 | ||||||
Model 1 adjusted for gender, age, education, and socio-economic status.
Model 2a adjusted for Model 1 covariates in addition to W1 HSI, and residualised increase in W2 salience of health warning labels.
Model 2b was identical to Model 2a but excluded participants who stated they no longer regularly smoked the same brand at W2.
Fig. 1Hybrid structural equation model, testing mediation between brand identity and smoking behaviours (HSI). All exogeneous variables were covaried (not depicted here).1 The model depicted shows the standardised path coefficients and significance levels (*p < .05, **p < .01, ***p < .001) for the model testing the direct and indirect effects between W1 Brand ID and W2 HSI (n = 149). An otherwise identical model was tested, replacing the main DV presented here (W2 HSI), with the outcome variables: quitting smoking (N = 178), quit attempts (N = 148), and W2 quit intentions (N = 149).
Direct and indirect effects estimated in hybrid structural equation model predicting outcome variables from W1 brand identity (direct effect), and W1 brand identity via latent decrease in brand identity (indirect effect).
| Outcome variable | Standardised direct effect of W1 brand identity | 95%CI | Standardised indirect effect of W1 brand identity via latent decrease in brand identity | 95% CI | Model fit statistics | ||
|---|---|---|---|---|---|---|---|
| Quit at W2, N = 178 | − 0.204 | − 0.435 | 0.050 | 0.167 | 0.019 | 0.312 | PPP = 0.42 |
| W2 HSI, N = 149 | 0.078 | − 0.045 | 0.207 | − 0.116 | − 0.200 | − 0.048 | RMSEA < 0.01 |
| At least one quit attempt, N = 148 | − 0.248 | − 0.460 | − 0.001 | 0.167 | 0.025 | 0.311 | PPP = 0.46 |
| Quit intentions, N = 149 | − 0.642 | − 0.847 | − 0.403 | 0.217 | 0.076 | 0.364 | PPP = 0.46 |
All SEM models controlled for age, gender, education, SES, W1HSI, and increased salience of health warning labels. PPP = posterior predictive probability (Lee & Song, 2003).