"We need to work towards it, whatever it takes."-participation factors in the acceptability and feasibility of lung cancer screening in Australia: the perspectives of key stakeholders.

Translational lung cancer research(2024)

引用 0|浏览1
暂无评分
摘要
Background:Low dose computed tomography (LDCT) screening, targeted at those at high-risk, has been shown to significantly reduce lung cancer mortality and detect cancers at an early stage. Practical, attitudinal and demographic factors can inhibit screening participation in high-risk populations. This study aimed to explore stakeholders' views about barriers and enablers (determinants) to participation in lung cancer screening (LCS) in Australia. Methods:Twenty-four focus groups (range 2-5 participants) were conducted in 2021 using the Zoom platform. Participants were 84 health professionals, researchers, policy makers and program managers of current screening programs. Focus groups consisted of a structured presentation with facilitated discussion lasting about 1 hour. The content was analysed thematically and mapped to the Consolidated Framework for Implementation Research (CFIR). Results:Screening determinants were identified across each stage of the proposed screening and assessment pathway. Challenges included participant factors such as encouraging participation for individuals at high-risk, whilst ensuring that access and equity issues were carefully considered in program design. The development of awareness campaigns that engaged LCS participants and health professionals, as well as streamlined referral processes for initial entry and follow-up, were strongly advocated for. Considering practical factors included the use of mobile vans in convenient locations. Conclusions:Participants reported that LCS in Australia was acceptable and feasible. Participants identified a complex set of determinants across the proposed screening and assessment pathway. Strategies that enable the best chance for program success must be identified prior to implementation of a national LCS program.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要