心理健康问题是一种全球普遍常见，但常常被社会系统所忽视的健康问题。潜在问诊需求与实际就医人数的差距受到多种因素的影响。在这一背景下，互联网和人工智能技术的快速发展为治疗心理健康问题提供了新的可能性。现有的基于人工智能技术的心理健康服务涵盖了广泛的应用面，然而，受限于使用者对数据和隐私的担忧、现有科学技术的局限性，当前可投入使用的有效应用更多地应用于焦虑、抑郁等常见的心理健康问题。数字媒体在人们获取信息和寻求心理健康服务方面发挥着重要的作用，而如何通过数字媒体了解正确的心理健康知识、降低公众对心理健康问题的抵触，以增强人们寻求心理健康服务的素养，从而提高AI心理健康服务使用率，这一问题仍然亟待解决。当前基于理论的应用型研究在心理健康求助行为领域仍然较少，且多分别讨论媒体的影响或行为意愿的影响因素。本研究整合认知中介模型与计划行为理论，旨在系统性地深入了解数字媒体背景下，人工智能心理健康服务使用意愿的形成机制。本研究于2024年2月28日至3月6日期间进行了两次问卷调查。首先筛选出1107名患有轻度及以上心理健康问题的参与者，并定向发放问卷，共回收608份有效回答。本文使用结构方程模型，证实了媒体关注对精细加工正相关，以及精细加工与事实知识、感知知识、主观规范、描述性规范和感知行为控制间均存在正相关性。此外，研究发现事实知识水平、态度、主观规范、感知行为控制均与行为意愿正相关，而感知知识和描述性规范与行为意愿的相关性不显著。结果表明，精细加工在不同程度上与感知知识和事实知识相关，媒体重复性地推送和故事化的叙述更倾向于强化人们对议题的熟悉度，而不一定增加了对信息内容的掌握，而事实知识在推动行为意愿方面起着关键作用。主观规范在激励求助行为方面表现出较为显著的作用，而描述性规范的相关性不甚明显，即共性的行为需要转化为对社会压力的认知，才能形成相应的行为意愿。本研究拓展并整合了认知中介模型和计划行为理论，为亚健康群体的健康求助行为提供了新的理论和实践视角。
Mental health problems are a pervasive yet often overlooked global health concern. The gap between the potential demand for mental health services and the actual number of consultations is influenced by several factors, including low levels of mental health knowledge and the stigmatization of mental disorders around society. Against this backdrop, the rapid development of the internet and artificial intelligence （AI） technologies offer new possibilities for addressing such challenges. However, concerns about data privacy and the limitations of existing technology mean that effective applications are predominantly focused on common mental health problems such as anxiety and depression.Digital media plays a critical role in how people access information and seek mental health services. The challenge of how digital media can be used to impart accurate mental health knowledge, reduce public aversion to mental disorders, and enhance literacy in seeking mental health services—thereby increasing the utilization of AI mental health services—remains urgent. Current research grounded in theory is scant in the domain of mental health help-seeking behaviors and often separately discusses the impacts of media or the factors influencing behavioral intentions. In light of this, this study integrates the Cognitive Mediation Model with the Theory of Planned Behavior to deepen our understanding of the mechanisms behind the formation of intentions to use AI mental health services in a digital media context.This study was conducted with two surveys taking place from February 28 to March 6, 2024. The first survey identified 1107 participants with light to severe depression or anxiety, and the second targeted these individuals, yielding 608 valid responses. Using structural equation modeling, the study confirmed positive correlations between media attention and elaboration, as well as between elaboration and factual knowledge, perceived knowledge, attitude, subjective norms, descriptive norms, and perceived behavioral control. Additionally, the study found that levels of factual knowledge, attitudes, subjective norms, and perceived behavioral control were positively correlated with behavioral intentions, whereas the correlations between perceived knowledge, descriptive norms, and behavioral intentions were not significant.The results indicate that elaboration is related to perceived knowledge and factual knowledge at varying degrees. Media’s repetitive and narrative-driven content tends to reinforce familiarity with issues rather than increasing mastery of information, with factual knowledge playing a key role in promoting behavioral intentions. In the digital media era, subjective norms play a significant role in motivating help-seeking behavior, while the relevance of descriptive norms is less apparent, suggesting that common behaviors need to be transformed into perceptions of social pressure to form corresponding behavioral intentions. This study extends and integrates the Cognitive Mediation Model and the Theory of Planned Behavior, offering new theoretical and practical perspectives on the help-seeking behaviors of the sub-healthy population.
