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Annals of Behavioral Medicine
Erschienen in: Annals of Behavioral Medicine 5/2015

01.10.2015 | Original Article

Which Images and Features in Graphic Cigarette Warnings Predict Their Perceived Effectiveness? Findings from an Online Survey of Residents in the UK

verfasst von: Linda D. Cameron, Ph.D, Brian Williams, Ph.D

Erschienen in: Annals of Behavioral Medicine | Ausgabe 5/2015

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Abstract

Background

Many countries are implementing graphic warnings for cigarettes. Which graphic features influence their effectiveness remains unclear.

Purpose

To identify features of graphic warnings predicting their perceived effectiveness in discouraging smoking.

Method

Guided by the Common-Sense Model of responses to health threats, we content-analyzed 42 graphic warnings for attributes of illness risk representations and media features (e.g., photographs, metaphors). Using data from 15,536 survey participants, we conducted stratified logistic regressions testing which attributes predict participant selections of warnings as effective.

Results

Images of diseased body parts predicted greater perceived effectiveness; OR = 6.53–12.45 across smoking status (smoker, ex-smoker, young non-smoker) groups. Features increasing perceived effectiveness included images of dead or sick persons, children, and medical technology; focus on cancer; and photographs. Attributes decreasing perceived effectiveness included infertility/impotence, addictiveness, cigarette chemicals, cosmetic appearance, quitting self-efficacy, and metaphors.

Conclusions

These findings on representational and media attributes predicting perceived effectiveness can inform strategies for generating graphic warnings.
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Metadaten
Titel
Which Images and Features in Graphic Cigarette Warnings Predict Their Perceived Effectiveness? Findings from an Online Survey of Residents in the UK
verfasst von
Linda D. Cameron, Ph.D
Brian Williams, Ph.D
Publikationsdatum
01.10.2015
Verlag
Springer US
Erschienen in
Annals of Behavioral Medicine / Ausgabe 5/2015
Print ISSN: 0883-6612
Elektronische ISSN: 1532-4796
DOI
https://doi.org/10.1007/s12160-015-9693-4

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