Evaluating Knowledge, Attitudes, and Beliefs About Lung Cancer Screening Using Crowdsourcing

Chest. 2020 Jul;158(1):386-392. doi: 10.1016/j.chest.2019.12.048. Epub 2020 Feb 7.

Abstract

Background: Lung cancer screening, despite its proven mortality benefit, remains vastly underutilized. Previous studies examined knowledge, attitudes, and beliefs to better understand the reasons underlying the low screening rates. These investigations may have limited generalizability because of traditional participant recruitment strategies and examining only subpopulations eligible for screening. The current study used crowdsourcing to recruit a broader population to assess these factors in a potentially more general population.

Methods: A 31-item survey was developed to assess knowledge, attitudes, and beliefs regarding screening among individuals considered high risk for lung cancer by the United States Preventive Services Task Force. Amazon's crowdsourcing platform (Mechanical Turk) was used to recruit subjects.

Results: Among the 240 respondents who qualified for the study, 106 (44%) reported knowledge of a screening test for lung cancer. However, only 36 (35%) correctly identified low-dose CT scanning as the appropriate test. A total of 222 respondents (93%) reported believing that early detection of lung cancer has the potential to save lives, and 165 (69%) were willing to undergo lung cancer screening if it was recommended by their physician. Multivariable regression analysis found that knowledge of lung cancer screening, smoking status, chronic pulmonary disease, and belief in the efficacy of early detection of lung cancer were associated with willingness to screen.

Conclusions: Although a minority of individuals at high risk for lung cancer are aware of screening, the majority believe that early detection saves lives and would pursue screening if recommended by their primary care physician. Health systems may increase screening rates by improving patient and physician awareness of lung cancer screening.

Keywords: early-detection cancer; lung cancer; smoking.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Crowdsourcing
  • Early Detection of Cancer*
  • Female
  • Health Knowledge, Attitudes, Practice*
  • Humans
  • Lung Neoplasms / diagnosis*
  • Male
  • Middle Aged
  • Patient Acceptance of Health Care*
  • Socioeconomic Factors
  • Surveys and Questionnaires
  • Tomography, X-Ray Computed