Digital Interventions to Support Lung Cancer Screening: A Systematic Review

Am J Prev Med. 2024 May;66(5):899-908. doi: 10.1016/j.amepre.2024.01.007. Epub 2024 Jan 20.

Abstract

Introduction: Lung cancer remains a leading cause of cancer-related deaths globally. Lung cancer screening (LCS) with low-dose computed tomography (LDCT) can reduce lung cancer mortality, but its adoption in the U.S. has been limited. Digital interventions have the potential to improve uptake of LCS. This systematic review aims to summarize the evidence for the effectiveness of digital interventions in promoting LCS.

Methods: A systematic search of three electronic databases (PubMed, Embase, and Medline) was conducted to identify studies published between January 2014 and May 2023. Studies were reviewed and abstracted between February 2023 and July 2023. Outcomes related to knowledge, decision-making and screening were measured. Study quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal tools.

Results: Of 1,979 screened articles, 30 studies were included in this review. Digital interventions evaluated included decision aids (n=20), electronic health record (EHR)-based interventions (n=7), social media campaigns and mobile applications (n=3). Decision aids were the most commonly studied digital interventions, with most studies showing improved knowledge (13/13) and reduced decisional conflict (7/9) but most did not show a substantial change in screening use. Fewer studies tested clinician-facing or multi-level interventions.

Discussion: Digital interventions, particularly decision aids, have shown promise in improving knowledge and the quality of decision-making around LCS. However, few interventions have been shown to substantially alter screening behavior and few clinician-facing or multi-level interventions have been rigorously tested. Further research is needed to develop effective tools for engaging patients in LCS, to compare the efficacy of different interventions, and evaluate implementation strategies in diverse healthcare settings.

Publication types

  • Systematic Review
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Decision Making
  • Decision Support Techniques
  • Early Detection of Cancer* / methods
  • Early Detection of Cancer* / statistics & numerical data
  • Electronic Health Records
  • Humans
  • Lung Neoplasms* / diagnosis
  • Lung Neoplasms* / diagnostic imaging
  • Mass Screening / methods
  • Social Media / statistics & numerical data
  • Tomography, X-Ray Computed