Integrating the Situational Theory of Problem Solving and Technology Acceptance Model to Predict Intention to Practice Health Protective Behavior for Influenza-Like Illness Among TikTok Users: Cross-Sectional Study

Abstract

Background: Outbreaks of influenza-like illness (ILI) pose ongoing public health challenges, prompting widespread demand for timely and accessible health information. TikTok, a leading short video platform, has emerged as an overarching channel for disseminating health-related content, particularly in mainland China. While previous studies have examined health communication on social media, few have integrated complementary theoretical frameworks to understand how user perceptions and motivations jointly influence health behaviors.

Objective: This study integrates the situational theory of problem solving (STOPS) and the technology acceptance model (TAM) to examine the communicative actions and intentions of Chinese TikTok users to adopt health protective behaviors in response to ILI.

Methods: A cross-sectional web-based survey was conducted in China between June and July 2023 using convenience and snowball sampling. A total of 1109 valid responses were analyzed using partial least squares structural equation modeling. Constructs from STOPS (problem recognition, constraint recognition, involvement recognition, situational motivation, and communicative action in problem solving) and TAM (perceived usefulness, perceived ease of use, and attitude) were measured alongside risk perception and intention to engage in protective behaviors.

Results: Perceived usefulness (β=.344; P<.001) and ease of use (β=.359; P<.001) positively influenced the attitude toward using TikTok. Risk perception (β=.050, P=.02) had a small but significant impact on attitude. Situational motivation was positively predicted by risk perception (β=.154; P<.001), problem recognition (β=.153; P<.001), and involvement recognition (β=.248; P<.001) but negatively predicted by constraint recognition (β=-.265; P<.001). Both attitude (β=.390; P<.001) and situational motivation (β=.471; P<.001) significantly influenced communicative action, which in turn predicted intention to practice protective behaviors (β=.570; P<.001). Mediation analyses confirmed the partial mediating roles of attitude and situational motivation.

Conclusions: TikTok is an effective platform for public health communication in China, particularly for ILI-related content. Integrating the STOPS and TAM provides a robust framework for explaining how user perceptions and motivations translate into digital engagement and health protective intentions. These findings suggest that interventions should not only enhance technological usability and credibility but also tailor content to elevate perceived personal relevance and reduce psychological or contextual constraints. Future public health campaigns can benefit from engaging influencers, using participatory content formats, and targeting specific motivational cues to increase user involvement in health communication and behavioral change. Caution is warranted in generalizing these results because of the culturally specific and demographically skewed nature of the sample.

Keywords: behavioral intention; digital health literacy; health communication; risk perception; social media engagement.