医学
肺癌
焦点小组
拒绝
主题分析
心理干预
严重性
癌症
家庭医学
定性研究
精神科
病理
心理学
内科学
心理治疗师
业务
营销
社会学
法学
社会科学
政治学
作者
Mohamad M. Saab,Brendan Noonan,Caroline Kilty,Serena FitzGerald,Abigail Collins,Áine Lyng,Úna Kennedy,Maidy O’Brien,Josephine Hegarty
标识
DOI:10.1016/j.ejon.2020.101880
摘要
PurposeLung cancer is the most common malignancy and the leading cause of cancer death globally. Lung cancer incidence and mortality are highest among socioeconomically deprived individuals. This study explored awareness and help-seeking for early signs and symptoms of lung cancer among high-risk individuals.MethodsParticipation was sought from multiple community centres and organisations in high-incidence and socioeconomically deprived areas in Ireland. Semi-structured focus groups were conducted with individuals at risk for lung cancer. Data were analysed using thematic analysis.ResultsFive focus groups were conducted with 46 participants. Two themes were identified: (i) lung cancer awareness, beliefs, and experiences and (ii) help-seeking for early signs and symptoms of lung cancer. Participants had fragmented knowledge of lung cancer and associated this malignancy with death. Symptom change, persistence, seriousness, and family history of lung cancer served as triggers to help-seeking. General practitioners were identified as the first point of contact for symptoms of concern, yet their presumed negative attitudes towards smokers served as barriers to help-seeking. Other barriers included symptom misappraisal, fear, denial, use of self-help measures, being inherently a non-help seeker, and machoism and stoicism among men.ConclusionStudy findings offer guidance regarding lung cancer knowledge gaps and barriers to help-seeking that ought to be considered in public health interventions aimed to promote lung cancer awareness and early detection.Clinical implicationsThis study highlights the need for healthcare professionals to adopt a non-judgmental approach during consults for symptoms indicative of lung cancer. This can potentially help detect lung cancer early.
科研通智能强力驱动
Strongly Powered by AbleSci AI