Patient and Healthcare Provider Barriers in the LDCT Lung Cancer Screening Continuum

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Authors: Rodica Anghel, Antonia-Ruxandra Folea, Vlad-Luca Moga, Cristian Pavel, Diana Troncota, Corneliu-Octavian Dumitru, A. T. Serban, Liviu Bîlteanu
Cited by: 1
References: 122

Abstract

Background/Objectives: Despite demonstrated mortality benefits, annual low-dose computed tomography (LDCT) screening faces challenges in real-world adoption due to low uptake and poor longitudinal adherence. This review evaluates patient- and provider-level factors that influence screening participation and highlights strategies to strengthen equitable engagement throughout the screening pathway. Methods: A structured literature search of PubMed and Web of Science was performed to identify studies published between 2013 and November 2025 (search conducted on 25 November 2025). Eligible publications included qualitative and quantitative studies, study protocols, and reviews examining LDCT screening uptake, adherence, and follow-up practices. Extracted evidence was synthesized, with particular attention being paid to patient- and provider-level determinants. Results: The evidence demonstrates that both patient- and provider-level factors substantially influence screening participation and continuity. At the patient level, limited awareness of screening, misconceptions regarding asymptomatic disease, and psychosocial factors such as fear, fatalism, stigma, and medical mistrust were consistently associated with reduced uptake and adherence. At the provider level, gaps in guideline familiarity, time constraints, and challenges in delivering high-quality shared decision-making limited referrals and follow-up. Conclusions: Improving real-world effectiveness of LDCT lung cancer screening requires reframing screening as a longitudinal program of care. Strategies that support patient navigation, enhance provider capacity for sustained engagement, and integrate tobacco dependence treatment into screening pathways are central to improving adherence and reducing disparities.

Fields of Study & Subjects

Lung Cancer Diagnosis and Treatment Global Cancer Incidence and Screening Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Diagnostics
Publisher
MDPI AG
Volume
16
Issue
7
Pages
1092–1092
Publication date
4 April 2026
Language
EN