Research on the Improvement Path of Human-AI Collaborative Consultation Effectiveness From the Perspective of Information Ecology: Configurational Analysis.

BACKGROUND

Enhancing the effectiveness of human-AI collaborative consultation in online health communities (OHCs) constitutes a core requirement for optimizing the allocation of medical resources and promoting the sustainable development of medical services. Nevertheless, the pathways to improving such effectiveness remain insufficiently understood.

OBJECTIVE

This study aimed to conduct an in-depth exploration of the multiple factors influencing the effectiveness of human-AI collaborative consultation in OHCs and to assess the causal relationships among these factors, thereby providing a theoretical foundation and practical guidance for advancing the clinical application of human-AI collaboration.

METHODS

Grounded in the information ecology theory, we constructed an analytical framework encompassing four dimensions: information human, information, environment, and technology. We collected 296 valid questionnaire responses and used fuzzy set qualitative comparative analysis to systematically investigate the configurational mechanisms through which these four types of factors jointly influence consultation effectiveness.

RESULTS

The findings are as follows: (1) no single factor constitutes a sufficient condition for high consultation effectiveness (consistency <0.9); rather, such effectiveness emerges from the synergistic interplay of multiple configurations involving technology, information, human information, and environment; (2) five distinct configurational pathways lead to high consultation effectiveness, demonstrating clear equifinality; (3) system responsiveness, information usefulness, perceived service empathy, perceived service accuracy, and perceived service effectiveness are all core or important conditions across these pathways; and (4) substitutability exists among antecedent conditions-specifically, perceived uncertainty and social norms, as well as operational convenience and platform ethical norms, can substitute for one another in different configurations to enhance patient satisfaction jointly.

CONCLUSIONS

This study reveals multiple pathways to achieving high effectiveness in human-AI collaborative consultation within OHCs. It not only offers a novel theoretical perspective for understanding the complex mechanisms of human-AI collaboration in medical contexts, but also provides significant practical implications for the design optimization of digital health platforms and related policy formulation.