Do tobacco industry websites target content to specific demographic groups?

Escobedo, Patricia; Tsai, Kai-Ya; Majmundar, Anuja; Allem, Jon-Patrick; Soto, Daniel W.; Pattarroyo, Monica; Unger, Jennifer B.; Cruz, Tess Boley

doi:10.1016/j.drugalcdep.2020.107852

Cited by 6 publications

(4 citation statements)

References 32 publications

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“…Global smoking rates are still higher among men than women (16). Taking up smoking at a young age is directly correlated with low income, low education levels, and membership of the working class (17). In agreement with the previous literature, the prevalence of smoking in the present study was 21%, with a male/female ratio of 2.81, and exposure to smoking was observed at an approximate level of 21.1%.…”

Section: Participant Characteristicssupporting

confidence: 90%

The Invisible Danger: Third-hand Smoke and Families’ Knowledge Levels

Akça,

Akça

2024

Türkiye Çocuk Hast Derg

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Objective: The objective of this study was to idenitfy the knowledge levels of families regarding third-hand smoke (THS), which represents the most significant health risk currently, and to raise awareness of the subject. Material and Methods: The ’Beliefs About Third-hand Smoke’ (BATHS) scale was applied to 1016 caregivers. The BATHS scale and sub-factor scale results were compared in terms of participant-related variables such as smoking behaviors, THS awareness and beliefs, and sociodemographic findings. Results: Awareness of the term THS was very low (8.7%). Statistically significantly low smoking habits and high BATHS scale scores were determined among participants who owned their own homes, those with higher levels of education and income, and in non-parent relatives (p

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Section: Participant Characteristicssupporting

confidence: 90%

The Invisible Danger: Third-hand Smoke and Families’ Knowledge Levels

Akça,

Akça

2024

Türkiye Çocuk Hast Derg

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“…Potential explanations underlie an observed trend wherein smoking often aligns with greater acceptability and anticipation among males within several traditional African societies [ 47 , 48 ]. Moreover, historical marketing strategies by tobacco companies have specifically targeted males through promotional campaigns that associate smoking with traits such as ‘masculinity’, ‘adventure’, or ‘toughness’ [ 49 , 50 ]. Such tailored marketing approaches might exert a more pronounced influence on males, potentially prompting them to initiate or sustain smoking behaviour.…”

Section: Discussionmentioning

confidence: 99%

Exposure to pro-tobacco and anti-tobacco media messages and events and smoking behaviour among adolescents in Gambia

Addo,

Acquah,

Nyarko

et al. 2024

BMC Public Health

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Background Despite the widespread prevalence of adolescent smoking in Gambia, a West African country, there is limited research exploring the relationships between exposure to pro-tobacco and anti-tobacco media messages and events and smoking behaviour among young people. This study investigates the interplay of these exposures and smoking behaviour among 11-17-year-old adolescents in Gambia. Methods Secondary data analysis was conducted using the 2017 Gambia Global Youth and Tobacco Survey (GYTS), which included a total of 9,127 respondents. Descriptive and inferential analyses, including proportions, Pearson’s chi-squared tests, and multivariable logistic regression models, were employed to estimate adjusted odds ratios (aOR) with 95% confidence intervals (CI). Results The final model revealed significant associations between exposure to anti-tobacco media messages and events and smoking behaviour. Adolescents exposed to anti-tobacco media messages had a 29% increased odds of smoking (aOR 1.29,CI = 1.08,1.53) compared to those unexposed, while exposure to anti-tobacco media events showed a 31% increased odds (aOR 1.31,CI = 1.09,1.59) compared to those unexposed. Exposure to pro-tobacco messages, such as witnessing tobacco use on TV (aOR 1.41, CI = 1.17,1.69) and owning objects with tobacco brand logos (aOR 1.49,CI = 1.19,1.86), was associated with higher odds of smoking. Covariates, including sex, age, and exposure to smoking behaviour by significant others, also demonstrated associations with smoking behaviour. Notably, male respondents showed significantly higher odds of smoking (aOR = 4.01,CI = 3.28,4.89) compared to females. Respondents aged 15 years and older had increased odds of smoking (aOR = 1.47,CI = 1.22,1.76) compared to those below 15 years old. Those whose fathers smoke displayed higher odds of smoking (aOR = 1.35, CI = 1.04,1.76) compared to individuals with non-smoking parents. Additionally, those whose closest friends smoke showed remarkably higher odds of smoking (aOR = 2.87,CI = 2.37, 3.48) compared to those without such influence. Conclusion This study underscores the significant impact of exposure to both anti-tobacco and pro-tobacco media messages and events on smoking behaviour among adolescents in Gambia. However, pro-tobacco messages had a greater influence on smoking prevalence than anti-tobacco messages and events. Understanding these associations is crucial for devising effective public health interventions aimed at reducing tobacco use in this population.

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“…There is evidence that individualized public health communications have led to behavioral changes [ 48 , 49 , 50 ]. The tobacco industry and health agencies are already tailoring their respective messages using social media [ 51 , 52 ]. Further research should examine how these organizations might leverage behavioral economic profiles to increase the relevance of messages and the influence of individual behaviors.…”

Section: Discussionmentioning

confidence: 99%

Tailored Cigarette Warning Messages: How Individualized Loss Aversion and Delay Discounting Rates Can Influence Perceived Message Effectiveness

Tripp

Strickland

Mercincavage

et al. 2021

IJERPH

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Current text-only cigarette warning labels (long-term, loss-framed messages) may not motivate positive changes in smoking behavior. The current project was a cross-sectional study examining the effects of tailored cigarette warnings on perceived message effectiveness (PME) in adult smokers (n = 512) conducted using Amazon Mechanical Turk (M-Turk) in January–February 2020. Participants were an average age of 40.7 (SD = 11.6), with the majority of the sample being female (62.2%) and White (88.9%). Participants reported smoking an average of 14.6 cigarettes/day (SD = 9.2) with an average FTND score of 4.6 (SD = 2.2). Participants were asked to complete a tobacco use history questionnaire, and mixed gambles and delay discounting tasks before random assignment to one of five message groups. The groups were based on a 2 (gain versus loss framing) × 2 (short-term versus long-term framing) between-subject design; a fifth group served as the control group. All experimental messages reported higher PME scores than the control (p values < 0.001, Cohen’s d = 1.88–2.48). Participants with shallower delayed reward discounting and lower loss aversion rates reported higher total PME scores, p values < 0.05. Our findings also suggest that loss aversion rates vary widely among smokers and that individuals are more responsive to messages congruent with their behavioral economic profile. Specifically, smokers who viewed messages congruent with their loss aversion and delay discounting rates reported higher PME scores than those who viewed incongruent messages (p = 0.04, Cohen’s d = 0.24). These preliminary findings suggest that anti-smoking campaigns may best impact smokers by tailoring messages based on individual loss aversion and delay discounting rates versus a one-size-fits-all approach.

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Do tobacco industry websites target content to specific demographic groups?

Cited by 6 publications

References 32 publications

The Invisible Danger: Third-hand Smoke and Families’ Knowledge Levels

The Invisible Danger: Third-hand Smoke and Families’ Knowledge Levels

Exposure to pro-tobacco and anti-tobacco media messages and events and smoking behaviour among adolescents in Gambia

Tailored Cigarette Warning Messages: How Individualized Loss Aversion and Delay Discounting Rates Can Influence Perceived Message Effectiveness

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