Journal of Health Communication最新文献

Research suggests associations between public understanding and support for evidence-based responses to the ongoing opioid crisis, yet communication inequality theory indicates that social position may systematically influence access to health information. This study examines demographic correlates of both active information seeking and passive information exposure across multiple channels, analyzing a nationally representative sample of 6,543 US adults. The findings advance communication inequality theory by revealing distinct information pathways: lower educational attainment was associated with actively seeking information on television, while higher attainment correlated with web searches. Political affiliations aligned with distinct media ecosystems, and racial identity corresponded with significantly different rates of passive exposure from sources like healthcare professionals and television. These patterns, along with higher information seeking from personal and medical networks among those with a family or personal history of opioid use, suggest that social groups inhabit fundamentally different information realities, potentially contributing to divergent understandings of the crisis. These findings highlight the need to design communication strategies that account for how social position shapes information pathways. Future research should examine whether exposure through these channels relates to public understanding and policy support.

This study employs an experimental design to examine the effects of expert didactic corrective TikTok videos on motivating people's intentions to engage in citizen fact-checking and vaccine promotion. Our findings reveal that participants who watched expert didactic debunking videos, compared to those viewing layperson testimonial videos, reported higher intentions to correct others' misperceptions of COVID-19 vaccines and promote COVID-19 vaccines to those who have not completed the recommended vaccination. The impacts of expert didactic videos on fact-checking and vaccine-promoting intention are mediated by participants' perceived expertise of the video's source. Our findings contribute to the theoretical understanding of how multimodal correction messages motivate individuals' intentions for interpersonal behavioral outcomes. Practically, our research emphasizes the "whole-of-society" approach to combating health misinformation on video-based platforms such as TikTok.

With recent drops in organ donation support exacerbating the organ shortage, the current investigation sought to explore the potential for organ donor gratitude letters to be utilized in organ donation promotion. To this end, we conducted a content analysis of gratitude letters shared on Korean Organ Donation Agency's (KODA) website (N = 98), with an emphasis on identifying the emotions recipients experienced throughout their transplant journey, tribute messages to donors, and supportive messages to donor families. Results revealed that when writing about pre-transplantation, hopelessness was mentioned most often, followed by sadness. During transplant, hopelessness was again mentioned most often, however, there was no mention of sadness. In the post-transplant phase, recipients most often mentioned gratitude, followed by happiness and guilt. Such shifts in emotions created an emotional flow within the narrative, from hopelessness and sadness, through sheer hopelessness, to gratitude. Tributes often described donors as heroes and rarely referenced religion, contradicting the belief that religiosity is a barrier to organ donation in East Asia. Currently, organ donation promotional efforts do not make organ recipient letters available to the public. Further implications of donor tribute letters in promoting organ donation are discussed.

Infotainment is an effective and widely used way of spreading health information. However, the specific mechanism of its effects remains unclear. This study analyzed 215,020 user comments under a popular health animation - the Cells at Work - on Bilibili.com, using the GPT-2 method. The analysis found that when faced with such an infotainment health communication text, audiences' subsequent expressions of health attitudes and related changes were limited, indicating that the effectiveness of infotainment as a means of health communication should not be overestimated. Audiences have different reactions to the health information and entertainment parts of such infotainment. The effect of health information in arousing changes in audiences' health attitudes is lower than that of the entertainment. This indicates that we need to reconsider the balance between the health information and entertainment parts involved.

This study tests how AI-based health chatbots' message framing, along with the explanations about human knowledge involvement in their algorithms, influence users' attitudes toward chatbots' recommendation. Based on a two-level human-machine communication framework,an online experiment (N = 374) revealed that a chatbot's explanations of the high (vs. low) involvement of human knowledge in its algorithms increased users' trust in the chatbot, which further improved their attitudes toward help-seeking. The message target (targeted vs. mistargeted) employed in the chatbot's recommendations, the involvement of human knowledge in the algorithms, and users' depression tendency jointly influenced users' psychological reactance, which further affected their attitudes toward seeking help from friends and family members. Our findings can contribute to current understandings of how AI shapes the persuasive mechanism of health promotion messages and offer insights into using AI for mental health promotion.

Social media influencers (SMIs) increasingly serve as role models for young people, shaping their health-related attitudes and behavioral intentions. In two pre-registered online experiments with Gen Z participants (total N = 1,548; age 16-27), we investigated how different message types by non-expert SMIs influence belief accuracy and intentions toward harmful health behaviors. Using a 3 × 2 between-subjects design, we manipulated the type of message (misinformation, overgeneralized, or correct) and the type of the SMI (famous or fictitious), with health literacy as a moderator. Our findings showed that both misinformation and overgeneralized health messaging (OHM) led to equally detrimental outcomes across various health contexts, undermining belief accuracy and encouraging harmful behavioral intentions. Furthermore, the familiarity of the SMI had minimal impact on the susceptibility to misleading health content. Also, the moderating effect of health literacy was limited. These results highlight the need for more research on the influence of SMIs and OHM on public health.

Many health and public health issues involve heterogeneous factors and processes that interact with one another and combine to form complex systems that make them challenging to communicate to the public. Words alone often aren't enough to communicate what's happening with a complex system, which is where and how visualizations can play an important role. A systems map is one such visualization tool that can be useful as it graphically shows the different components that make up a complex system and their relationships with one another. While systems mapping is not new as a concept or tool and in fact is used in other fields, its potential for health and public health communications still remains largely untapped. There is a series of sequential steps to follow to develop a systems map for health communications that allows for various perspectives to be included and minimizes bias, setting up a process to create a fuller representation of the system. Future directions of systems mapping for public health communications should leverage emerging technologies like artificial intelligence (AI) and virtual and extended reality (VR/XR) to further advance the usefulness systems mapping can have to improve our understanding of complex systems in public health and better communicate them to the public.

Female chronic pain patients often report perceiving that their character (i.e. credibility, reputation) has been attacked by clinicians during healthcare interactions. Although initially developed to examine political communication, we argue that character assassination (CA) is an inherently communicative phenomenon that also occurs within patient-clinician interactions. Utilizing CA as a sensitizing concept, this study examined experiences of CA among a racially, socioeconomically, and globally diverse sample of 450 female chronic pain patients during their interactions with clinicians. Our findings illuminate specific tactics employed by clinicians to attack patients' character, including making false attributions, lying and misquoting, triggering stereotypes, bullying, and emphasizing alleged flaws. Our findings also illustrate how CA might catalyze other deleterious outcomes, including fueling self-doubt, delaying further help-seeking and diagnosis, intensifying physical and mental health conditions, and turning relationally close others against the patient. We offer theoretical implications for utilizing CA as a conceptual lens and practical implications for patients and clinicians.

Misinformation during the COVID-19 pandemic was linked to noncompliance. Nonadherence, such as vaccine hesitancy, in a health emergency can lead to costly and deadly consequences. In an environment of mistrust and misinformation, quality, effective information that engages the public, shapes attitudes, and encourages behavior change is crucial. However, communicating effectively and ensuring compliance during the pandemic was challenging for health communicators, resulting in burnout and attrition. Generative artificial intelligence (AI), therefore, may be useful for communicators designing targeted health messages, particularly for vulnerable populations that are prone to misinformation. In this study, the authors explored the use of ChatGPT 3.5, a generative AI software, in the design of targeted COVID-19 booster vaccine messages for a variety of demographic groups (e.g. political leaning, religion, and conspiracy theorists). Sentiment and inductive thematic analyses revealed variations in targeted group messaging that leaned heavily on positive valence and situated adherence to public health guidelines within narratives about individuals' roles and responsibilities to protect self, community, and values. The authors posit that an audience-centered, positive framing messaging approach that appeals to individuals' shared values and responsibilities may be effective in priming audiences and shaping attitudes to minimize the impact of misinformation.

While there is ample research on the influence of retracted scientific publications on author reputation, less is known about how a health organization's retraction of scientific guidance can impact public perceptions of the organization. This study centers on the aerosol guidance retraction of the Centers for Disease Control and Prevention (CDC) in 2020. X/Twitter social media data were collected via ForSight from September 15 to October 8, 2020, with a machine learning algorithm specifically developed and used to detect sentiment toward the CDC. Regression analyses of the non-bot sample (N = 265,326) tested for differences in CDC sentiment across four stages: 1) baseline; 2) CDC guidance change; 3) CDC retraction of the prior guidance change; and 4) CDC reversion to a tempered form of the initial guidance change. The results show that sentiment toward the CDC increased from Time 1 to Time 2, then decreased for Time 3 with the "posted in error" retraction, but then increased for Time 4 back to a level similar to Time 2. That public perceptions of the CDC could improve after these changes in scientific guidance may be attributed to its self-report of the retraction and reporting that the retraction was a result of unintentional error. This study connects theories of reputation management and trust repair with the growing empirical research on retractions of published scientific research to provide a theoretical explanation for how a major public health organization can mitigate damage to its reputation in the short term.