Cameron Linda D, Williams Brian
University of California, Merced, 5200 North Lake Road, Merced, CA, 95343, USA,
Ann Behav Med. 2015 Oct;49(5):639-49. doi: 10.1007/s12160-015-9693-4.
Many countries are implementing graphic warnings for cigarettes. Which graphic features influence their effectiveness remains unclear.
To identify features of graphic warnings predicting their perceived effectiveness in discouraging smoking.
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.
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.
These findings on representational and media attributes predicting perceived effectiveness can inform strategies for generating graphic warnings.
许多国家正在实施香烟图形警示。哪些图形特征会影响其效果尚不清楚。
确定预测图形警示在劝阻吸烟方面感知效果的特征。
以应对健康威胁的常识模型为指导,我们对42个图形警示进行了内容分析,分析疾病风险呈现的属性和媒体特征(如照片、隐喻)。利用来自15536名调查参与者的数据,我们进行了分层逻辑回归分析,以测试哪些属性预测参与者选择的警示是有效的。
患病身体部位的图像预测了更高的感知效果;在吸烟者、曾经吸烟者、年轻非吸烟者等吸烟状况组中,优势比为6.53至12.45。提高感知效果的特征包括死亡或患病者、儿童和医疗技术的图像;关注癌症;以及照片。降低感知效果的属性包括不育/阳痿、成瘾性、香烟化学成分、外观、戒烟自我效能感和隐喻。
这些关于预测感知效果的呈现和媒体属性的发现可为生成图形警示的策略提供参考。