Background <p>Effective communication of nursing science through social media platforms represents a critical strategy for bridging the gap between professional nursing knowledge and public health needs. However, empirical research on nursing science popularization through international social media platforms remains limited, with existing studies often focusing on single determining factors without examining their complex interactions.</p> Methods <p>This study employed fuzzy-set qualitative comparative analysis (fsQCA) to identify configurational pathways that drive effective communication of nursing science popularization on WeChat. Guided by the Elaboration Likelihood Model (ELM), we analyzed 269 nursing popularization articles published on the official WeChat account of the Chinese Nursing Association from April 2022 to April 2024. The purpose was to examine how central route factors (topic, content complexity, information entropy, organizational structure, presentation mode) and peripheral route factors (publication time, position, title sentiment, title tone) combine to enhance communication effectiveness, measured by the Single Text Communication Index.</p> Results <p>Our findings revealed eight distinct pathways (H1-H8) for achieving effective communication of nursing popularization articles. These pathways fell into two categories: seven configurations where publication position was the sole core variable, and one configuration where article topic, information entropy, organizational structure, and title sentiment were core variables. The first category comprised three sub-types: Media Integration Type, Health Knowledge Popularization Type, and Disease Knowledge Popularization Type. Results demonstrated equifinality and causal asymmetry—multiple pathways achieve similar outcomes, and factors promoting success differ from those causing failure.</p> Conclusion <p>Communication effectiveness of nursing popularization articles results from multiple interacting factors rather than single variables. This study advances health communication knowledge by demonstrating how ELM’s dual-route framework operates in digital contexts through configurational rather than additive interactions. Healthcare communicators should establish topic classification mechanisms, develop targeted strategies, leverage multimedia elements, and enhance publication techniques based on content quality. These findings provide an evidence-based framework for enhancing nursing science communication effectiveness through social platforms.</p> Clinical trial number <p>Not applicable.</p>

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Disentangling the configurational drivers of nursing science popularization: a fuzzy-set qualitative comparative analysis using WeChat data

  • Yubin Chen,
  • Linghui Zhang,
  • Zhenhuan Ding,
  • Guangshen Pei,
  • Yuqiu Zhou,
  • Yu Wang,
  • Qi Li,
  • Zhengjun Wang

摘要

Background

Effective communication of nursing science through social media platforms represents a critical strategy for bridging the gap between professional nursing knowledge and public health needs. However, empirical research on nursing science popularization through international social media platforms remains limited, with existing studies often focusing on single determining factors without examining their complex interactions.

Methods

This study employed fuzzy-set qualitative comparative analysis (fsQCA) to identify configurational pathways that drive effective communication of nursing science popularization on WeChat. Guided by the Elaboration Likelihood Model (ELM), we analyzed 269 nursing popularization articles published on the official WeChat account of the Chinese Nursing Association from April 2022 to April 2024. The purpose was to examine how central route factors (topic, content complexity, information entropy, organizational structure, presentation mode) and peripheral route factors (publication time, position, title sentiment, title tone) combine to enhance communication effectiveness, measured by the Single Text Communication Index.

Results

Our findings revealed eight distinct pathways (H1-H8) for achieving effective communication of nursing popularization articles. These pathways fell into two categories: seven configurations where publication position was the sole core variable, and one configuration where article topic, information entropy, organizational structure, and title sentiment were core variables. The first category comprised three sub-types: Media Integration Type, Health Knowledge Popularization Type, and Disease Knowledge Popularization Type. Results demonstrated equifinality and causal asymmetry—multiple pathways achieve similar outcomes, and factors promoting success differ from those causing failure.

Conclusion

Communication effectiveness of nursing popularization articles results from multiple interacting factors rather than single variables. This study advances health communication knowledge by demonstrating how ELM’s dual-route framework operates in digital contexts through configurational rather than additive interactions. Healthcare communicators should establish topic classification mechanisms, develop targeted strategies, leverage multimedia elements, and enhance publication techniques based on content quality. These findings provide an evidence-based framework for enhancing nursing science communication effectiveness through social platforms.

Clinical trial number

Not applicable.