Lung Cancer Screening: Identifying Factors Associated With Participation

肺癌筛查：确定与参与相关的因素

基本信息

批准号：
9302070
负责人：
SUSAN M RAWL
金额：
$ 45.83万
依托单位：
INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-04-05 至 2020-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9302070
关键词：
Address Advisory Committees Analysis of Variance Behavior Characteristics Cognitive Colorectal Cancer Complement Data Data Analyses Data Display Data Reporting Decision Making Diagnosis Disease Elements Eligibility Determination Equation Focus Groups Foundations Fright Future Health Health Personnel Health Status Healthcare Systems Individual Intervention Interview Knowledge Life Style Linear Regressions Link Logistic Regressions Lung Malignant Neoplasms Malignant neoplasm of lung Malignant neoplasm of pancreas Malignant neoplasm of prostate Measures Mediation Mediator of activation protein Medical Methods Modeling Nicotine Online Systems Outcome Participant Patient Self-Report Patient risk Patients Population Preventive service Process Provider Questionnaires Recommendation Recording of previous events Research Design Research Personnel Review Literature Sampling Screening for cancer Secondary to Series Smoker Smoking Survey Methodology Surveys Survival Rate Testing Thoracic Radiography Time Tobacco Tobacco use Trust Work addiction base cancer type design experience health belief high risk improved killings low-dose spiral CT lung cancer screening malignant breast neoplasm mortality programs psychologic randomized trial screening shared decision making social social stigma therapy development

项目摘要

Abstract Lung cancer screening is a recent recommendation and new screening programs are currently being implemented. However, we do not yet know what factors influence screening-eligible smokers to screen. Smokers are a unique population and psychological variables (stigma, medical mistrust, cancer fatalism, worry, and fear) may be important and have very different relationships in lung cancer screening participation than participation in other types of cancer screening. The purpose of this mixed methods study is to develop an explanatory framework for lung cancer screening participation from the perspective of the individual to inform future patient-level tailored interventions through testing a model of factors related to screening. Specific aims include: 1) test the relationships among variables depicted in the conceptual model for lung cancer screening participation using structural equation modeling including mediation effects in a sample of screening-eligible long-term current and former smokers; 2) provide robust descriptions of factors that influence lung cancer screening and elucidate the relationships among the factors based on in-depth narratives of screening-eligible smokers; and 3) integrate findings drawn from both survey and narrative data to inform patient-level tailored intervention development. Study design: Sequential explanatory mixed methods design using survey methods and individual interviews. Measures: Quantitative self-reported data will be collected via a web-based survey comprised of the following elements: Cataldo Lung Cancer Stigma Smoking Subscale, Patient Trust in the Medical Profession Scale, Revised Powe Fatalism Scale, Lung Cancer Worry Scale, Lung Cancer Fear Scale, Demographic and Health Status Characteristics Questionnaire (including healthcare provider recommendation, media exposure, and lung cancer screening participation), Knowledge: Lung Cancer and Lung Cancer Screening Scale, Social Influence Scale, and Lung Cancer Screening Health Beliefs Scales. Qualitative data will be collected via audio- taped individual in-depth interviews. Data analysis: Quantitative data will be analyzed using bivariate analyses between variables in the conceptual model including t-tests, analysis of variance, linear regression, and logistic regression. The entire conceptual model will then be analyzed using path analysis via structural equation modeling. Content analysis and a series of data display tables will be used to analyze data from the in-depth interviews. The integration of qualitative and quantatitive will occur at two time points: (1) quantitative data will be used to develop individual participant profiles in order to selectively sample participants and design interview guides for the in-depth interviews; and (2) the quantitative and qualitative findings will be integrated at the stage of data interpretation. By augmenting quantitative findings with qualitative data, we will generate new knowledge to inform future tailored interventions.

抽象的肺癌筛查是最近的一项建议，目前正在制定新的筛查计划实施的。然而，我们尚不知道哪些因素会影响符合筛查资格的吸烟者进行筛查。吸烟者是一个独特的人群和心理变量（耻辱、医疗不信任、癌症宿命论、担忧、和恐惧）可能很重要，并且在肺癌筛查参与中的关系与参与其他类型的癌症筛查。这项混合方法研究的目的是开发肺癌筛查的解释框架从个人角度参与，为未来的患者级定制干预措施提供信息测试与筛查相关的因素模型。具体目标包括：1）测试之间的关系使用结构方程描述肺癌筛查参与概念模型中的变量建模，包括对符合筛查资格的长期当前和以前吸烟者样本的中介效应； 2）提供影响肺癌筛查的因素的有力描述并阐明其关系基于对符合筛查资格的吸烟者的深入叙述的因素； 3) 整合得出的结论从调查和叙述数据中为患者制定量身定制的干预措施提供信息。研究设计：使用调查方法和个人访谈的序贯解释性混合方法设计。措施：将通过网络调查收集定量的自我报告数据，其中包括以下内容要素：Cataldo 肺癌耻辱吸烟量表、患者对医疗行业的信任量表、修订后的 Powe 宿命论量表、肺癌担忧量表、肺癌恐惧量表、人口统计与健康状态特征调查问卷（包括医疗保健提供者推荐、媒体曝光度和肺癌筛查参与），知识：肺癌和肺癌筛查量表，社会影响量表和肺癌筛查健康信念量表。定性数据将通过音频收集录制个人深度访谈。数据分析：将使用概念中变量之间的双变量分析来分析定量数据模型包括 t 检验、方差分析、线性回归和逻辑回归。整个概念然后将通过结构方程建模使用路径分析来分析模型。内容分析和一系列数据展示表将用于分析深度访谈的数据。的整合定性和定量将在两个时间点发生：（1）定量数据将用于开发个体参与者概况，以便有选择地抽样参与者并设计深入访谈指南采访； (2)定量和定性研究结果将在数据解释阶段进行整合。通过用定性数据增强定量发现，我们将产生新知识来为未来提供信息量身定制的干预措施。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

DOI：
10.1097/nur.0000000000000555
发表时间：
2020
期刊：
Clinical nurse specialist CNS
影响因子：
0
作者：
Draucker CB;Rawl SM;Vode E;Fields M;Elkins C;Morgan O;Perez SR;Straber L;Carter-Harris L
通讯作者：
Carter-Harris L

Integration Through Connecting in Explanatory Sequential Mixed Method Studies.