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首页> 外文期刊>Asian Pacific Journal of Cancer Prevention >Smoking Habits of Relatives of Patients with Cancer: Cancer Diagnosis in the Family is an Important Teachable Moment for Smoking Cessation
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Smoking Habits of Relatives of Patients with Cancer: Cancer Diagnosis in the Family is an Important Teachable Moment for Smoking Cessation

机译:患有癌症患者亲属的吸烟习惯:家庭中的癌症诊断是吸烟的重要教育时刻

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Background: In this study we aimed to determine the rate and habitual patterns of smoking, intentions of cessation, dependence levels and sociodemographic characteristics of relatives of patients with a diagnosis of cancer. Materials and Methods: This study was designed by the Turkish Oncology Group, Epidemiology and Prevention Subgroup. The relatives of cancer patients were asked to fill a questionnaire and Fagerstrom test of nicotine dependence. Results: The median ages of those with lower and higher Fagerstrom scores were 40 years and 42 years, respectively. We found no evidence of variation between the two groups for the remaining sociodemographic variables, including the subject's medical status, gender, living in the same house with the patient, their educational status, their family income, closeness to their cancer patients or spending time with them or getting any help or wanting to get some help. Only 2% of the subjects started smoking after cancer was diagnosed in their loved ones and almost 20% of subjects had quit smoking during the previous year. Conclusions: The Fagerstrom score is helpful in determining who would be the most likely to benefit from a cigarette smoking cessation program. Identification of these people with proper screening methods might help us to pinpoint who would benefit most from these programs.
机译:背景:在这项研究中,我们旨在确定吸烟的速率和习惯模式,停止的疾病,依赖水平和患者亲属的患者诊断癌症的血管阶段性特征。材料和方法:本研究由土耳其肿瘤组,流行病学和预防亚组设计。要求癌症患者的亲属填写尼古丁依赖的调查问卷和Fagerstrom试验。结果:较低较高且比手淫分数较​​低的中位数分别为40年,42年。我们没有发现两组之间的剩余社会学变量之间的变化证据,包括受试者的医学状态,性别,生活在与患者的同一房屋中,他们的教育地位,他们的家庭收入,亲近他们的癌症患者或花费时间他们或获得任何帮助或想要了解一些帮助。只有2%的受试者在癌症中被诊断出来吸烟,并且近20%的受试者在去年期间戒烟。结论:Fagerstrom分数有助于确定谁是谁将是从吸烟停止计划中受益的最有可能受益。使用适当的筛选方法识别这些人可能会有助于我们查明从这些计划中受益的决定。

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