关键词: 动机性推理, 动机类型, 健康信念, 信息框架, 贝叶斯推理

Abstract:

Health-related motivated reasoning refers to a specific form of motivated reasoning within the health domain, wherein individuals’ cognitive processing is influenced by their health-related goals, desires, or emotions. In health contexts, individuals are inclined to accept, interpret, and recall information that aligns with their pre-existing health motivations, while disregarding or rejecting information that contradicts these motivations. This process leads to systematic biases in information selection, interpretation, and memory. Although previous research has highlighted the “double-edged sword” nature of health-related motivated reasoning, the literature lacks a comprehensive systematic review of this phenomenon. Moreover, discussions regarding its theoretical foundations, influencing factors, underlying mechanisms, and practical implications remain limited and fragmented.

Accurately categorizing health motivation is a critical prerequisite for elucidating the mechanisms underlying individual health information processing. Health motivation can be classified from multiple theoretical perspectives, including temporal orientation, individual psychological characteristics, reasoning goals, regulatory strategies, and the information life cycle. Early research often adopted a temporal orientation, distinguishing between “because” motives and “in order to” motives based on the timing of individual behaviors. Self-Determination Theory conceptualizes motivation along a continuum, differentiating intrinsic motivation, extrinsic motivation, and amotivation. Cognitive Dissonance Theory, from the perspective of reasoning goals, identifies accuracy motivation and directional motivation as two distinct types. Regulatory Orientation Theory offers an alternative framework, positing that motivation can be categorized according to self-regulatory strategies, specifically distinguishing between promotion-focused and prevention-focused motivation. More recent studies have further refined the classification of motivation in health information processing by considering the temporal dimension of the information life cycle. This approach segments the process into stages—generation, reception, and dissemination of information—and examines the predominant motivational drivers at each stage.

While categorization of motivation offers a foundational framework for understanding health-related motivated reasoning, the actual reasoning process is subject to the moderating effects of various internal and external factors. In this paper, the influences on health-related motivated reasoning are systematically classified into individual, informational, and cultural dimensions, each exerting distinct effects on the reasoning process. Specifically, individual factors pertain to the psychological and behavioral motivational sources of individuals, encompassing health beliefs, cognitive traits, and discrete emotions. Informational factors highlight the characteristics and presentation of information, with particular attention to conflicting information and information framing. Cultural factors, on the other hand, provide a broader contextual lens, involving social identity and cultural norms. Collectively, these dimensions interact to shape the manifestation and development of health-related motivated reasoning.

The mechanisms underlying motivated reasoning in health can be more comprehensively understood by integrating traditional cognitive bias perspectives with Bayesian modeling approaches. While early theories attribute motivated reasoning primarily to cognitive biases—where individuals preferentially seek information that confirms pre-existing beliefs and avoid counter-attitudinal evidence—this view is limited in its ability to capture the dynamic process of belief updating. Recent advances propose that health-related motivated reasoning can be conceptualized as a systematic deviation from normative Bayesian updating, characterized by a “triple deviation”: prior beliefs exert disproportionate influence, evidence is selectively processed, and posterior beliefs are directionally biased. This Bayesian framework not only elucidates the quantitative dynamics of belief adjustment under motivational influences but also provides a robust methodological foundation for analyzing the complexities of health-related motivated reasoning.

With the advancement of theoretical frameworks and the diversification of research topics, there remains a pressing need for deeper inquiry into health-related motivated reasoning. Future research should prioritize three key directions: (1) constructing interactive models to elucidate how individual traits, informational attributes, and cultural contexts jointly shape health-related motivated reasoning; (2) advancing the application of Bayesian modeling to clarify how various health motivations influence Bayesian reasoning processes and to identify the neural mechanisms underlying motivation-driven belief updating; and (3) investigating the impact of motivated reasoning on health intervention strategies, with the aim of developing targeted interventions tailored to distinct motivated profiles and addressing the complexities introduced by the era of networked intelligence.

Key words: motivated reasoning, motivation type, health beliefs, information framework, Bayesian inference