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Background <p>Lung cancer is the leading cause of cancer-related death in China. Low-dose computed tomography (LDCT) improves early detection and reduces mortality among high-risk populations, but uptake remains low in rural settings. The interrelationships among psychological, cognitive, and health belief-related factors remain unclear. In this study, used network analysis was used to examine the factors associated with lung cancer screening (LCS) behavior among high-risk rural adults in Fujian Province, China, and to compare networks by socioeconomic status (SES).</p> Methods <p>A cross-sectional survey was conducted from February to October 2024 among high-risk rural adults who were recruited from eight township health centers in Fuzhou and Putian. The data covered demographic information, knowledge, health beliefs, anxiety, depression, smoking-related stigma, trust in medical professionals and LCS behavioral stage. A mixed graphical model was estimated. Centrality and bridge indices were calculated, SES-based networks were compared using network comparison tests, and stability was assessed with bootstrapping.</p> Results <p>Among the 1,975 individuals who received the questionnaire, 1,905 completed the survey and were included, yielding a completion rate of 96.5%. The strongest edge was between depression and anxiety, followed by the edge between knowledge and the LCS behavioral stage. Excluding the LCS behavioral stage node, depression had the highest strength centrality and expected influence, followed by perceived barriers. Depression and anxiety were the main bridge nodes, whereas knowledge and depression had the highest bridge expected influence. Network comparison revealed no significant difference in global strength between SES groups, but network structure differed significantly. In the medium-low SES group, perceived barriers and depression were most central, and the self-efficacy–LCS behavioral stage edge was relatively strong. In the high SES group, depression and smoking-related stigma were key nodes, and the knowledge–LCS behavioral stage edge was more prominent. Bootstrapping indicated good stability.</p> Conclusions <p>Among high-risk rural adults in Fujian, LCS behavior was embedded in a network of psychological, cognitive, health belief-related and social-contextual factors. Depression was a stable central and bridging factor across SES groups. Interventions may need to reduce perceived barriers and strengthen self-efficacy in medium-low SES populations while improving knowledge translation and reducing smoking-related stigma in higher SES populations. Further validation in diverse, probability-based samples is warranted.</p>

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Network analysis of factors associated with lung cancer screening behavior among high-risk rural adults in Fujian, China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月10日

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  • Fangfang Wang,
  • Yujia Chen,
  • Yuezhen Hong,
  • Yonglin Li,
  • Yu-an Lin,
  • Rachel Arbing,
  • Wei-Ti Chen,
  • Feifei Huang

摘要

Background

Lung cancer is the leading cause of cancer-related death in China. Low-dose computed tomography (LDCT) improves early detection and reduces mortality among high-risk populations, but uptake remains low in rural settings. The interrelationships among psychological, cognitive, and health belief-related factors remain unclear. In this study, used network analysis was used to examine the factors associated with lung cancer screening (LCS) behavior among high-risk rural adults in Fujian Province, China, and to compare networks by socioeconomic status (SES).

Methods

A cross-sectional survey was conducted from February to October 2024 among high-risk rural adults who were recruited from eight township health centers in Fuzhou and Putian. The data covered demographic information, knowledge, health beliefs, anxiety, depression, smoking-related stigma, trust in medical professionals and LCS behavioral stage. A mixed graphical model was estimated. Centrality and bridge indices were calculated, SES-based networks were compared using network comparison tests, and stability was assessed with bootstrapping.

Results

Among the 1,975 individuals who received the questionnaire, 1,905 completed the survey and were included, yielding a completion rate of 96.5%. The strongest edge was between depression and anxiety, followed by the edge between knowledge and the LCS behavioral stage. Excluding the LCS behavioral stage node, depression had the highest strength centrality and expected influence, followed by perceived barriers. Depression and anxiety were the main bridge nodes, whereas knowledge and depression had the highest bridge expected influence. Network comparison revealed no significant difference in global strength between SES groups, but network structure differed significantly. In the medium-low SES group, perceived barriers and depression were most central, and the self-efficacy–LCS behavioral stage edge was relatively strong. In the high SES group, depression and smoking-related stigma were key nodes, and the knowledge–LCS behavioral stage edge was more prominent. Bootstrapping indicated good stability.

Conclusions

Among high-risk rural adults in Fujian, LCS behavior was embedded in a network of psychological, cognitive, health belief-related and social-contextual factors. Depression was a stable central and bridging factor across SES groups. Interventions may need to reduce perceived barriers and strengthen self-efficacy in medium-low SES populations while improving knowledge translation and reducing smoking-related stigma in higher SES populations. Further validation in diverse, probability-based samples is warranted.