No more messages! A systematic review of predictors and outcomes of message fatigue

Today’s media environment facilitates the distribution and reach of health campaigns and intervention messages to target audiences. However, the overwhelming volume of messages may exceed individuals’ cognitive capacities (Sweller, 1994), leaving them susceptible to message fatigue—a state of exhaustion and boredom resulting from repeated exposure to similar, redundant messages (So et al., 2017). While these messages are designed to promote better public health, they can inadvertently lead to counterproductive outcomes, such as heightened resistance to health recommendations (So & Popova, 2018).

To offer a comprehensive, evidence-based analysis of predictors and outcomes of health-related message fatigue and to inform the theoretical development of message fatigue, this study conducted a systematic analysis of existing research. Following the PRISMA guidelines (Page et al., 2021), we used keywords including “information/messages” and fatigue-related words, such as “exhaustion,” “burnout,” and “overload” to search for studies published between January 2004 and December 2024 in five databases: Web of Science, PubMed, EBSCO, Jstor, and Google Scholar. Through title and abstract screening and full-text evaluations, we removed duplicate, ineligible, irrelevant, and mismatched studies, yielding a total of 35 studies included in the final review (see Figure 1).

Results of our systematic review showed that most studies were conducted in the United States (N = 23) (see Figure 2). The topics predominantly focused on COVID-19 (N = 13) and obesity/weight loss (N = 4) (see Figure 3). The most common research design was survey (45.7%, N = 16), followed by experimental design (N = 7) and qualitative interviews (N = 5) (see Table 1).

Most studies adopted So et al.’s (2017) definition of message fatigue (Articles 1–3, 5–9, 11, 17–21, 26, 29, 30, 32–34). Among the 27 quantitative studies, the majority measured message fatigue using So et al.’s (2017) operational definition with four key dimensions: perceived overexposure, redundancy, exhaustion, and boredom (Articles 3, 5–8, 13, 14, 17–20, 24, 26, 29, 31). A few studies focused more selectively on specific subdimensions such as exhaustion or tedium (Articles 1, 28, 33, 34).

Psychological reactance theory emerged as the dominant theoretical framework (Articles 5, 8, 14, 20, 28, 31, 34). Notably, fourteen studies did not indicate the use of any theoretical framework (Articles 2, 4, 6, 9, 12, 15, 19, 21, 23, 25, 27, 30, 32, 35), suggesting a potential gap in theoretical grounding in the study of message fatigue.

Antecedents of message fatigue identified in existing literature include demographic factors, healthrelated factors, risk behaviors, health literacy, knowledge, social media use, exposure, framing, cognitive factors, and affective responses. The relationship between demographic factors (i.e., age, gender, race, income, education) and message fatigue was inconsistent (Articles 2, 9, 18, 19), with some studies finding no significant links (Article 28), suggesting demographics alone may not predict fatigue levels.

Regarding health-related factors, individuals with multiple medical conditions reported higher fatigue, while healthier individuals experienced less (Article 9). Engagement in risk behaviors, such as tobacco use (Article 2), alcohol consumption (Article 19), and sexual activity (Article 12), was related to higher fatigue, indicating high-risk individuals’ greater sensitivity to repeated health messages.

While general health literacy did not influence fatigue (Article 13), topic-specific knowledge (e.g., HIV awareness) showed mixed effects on message fatigue (Article 33). Social media use had inconsistent associations with message fatigue (Articles 11, 13), though active health informationseeking was linked to lower fatigue (Article 47). Cognitive and emotional responses were also found to have mixed effects on message fatigue. Anxiety about future health risks (e.g., COVID-19) increased message fatigue (Article 28), while positive emotions like hope and pride reduced it (Article 29). Sadness increased message fatigue but fear had no significant impact (Article 29).

Exposure to health messages—volume, frequency, modality—was a strong antecedent of message fatigue (Articles 4, 8, 9, 20, 23). Excessive exposure to official sources increased message fatigue (Article 29), while exposure to unofficial sources did not (Article 29). Message framing was another significant antecedent. Controlling language increased message fatigue, especially in HPV-related messages (Article 30), while valence framing showed no significant effect (Articles 5, 13, 24).

Previous studies also identified several consequences of message fatigue, including cognitive, behavioral, and emotional outcomes. A key cognitive impact of message fatigue is perceived threats to personal freedom, with studies linking message fatigue to feelings of autonomy restriction (Articles 5, 9, 20, 34).

Behaviorally, message fatigue reduced intentions to perform recommended health behaviors (e.g., vaccination willingness) (Article 30), resulting in poorer health practices in realms of medication adherence and handwashing (Articles 27, 32), and decreased engagement with health information (Articles 5, 6, 14, 19, 20). Message fatigue also exacerbated inattention, heuristic processing, and reduced critical thinking (Articles 7, 13, 21), while discouraging active information-seeking and promoting information avoidance (Articles 3, 6, 7, 21).

Emotionally, message fatigue intensified negative reactions such as annoyance, anger, fear, and embarrassment (Articles 3, 11, 21). It also increased reactance, namely resistance to health messages (Articles 6, 8, 14, 19, 20, 26, 31), and heightened the likelihood of counterarguing, where individuals actively challenged persuasive messages (Article 21).

The findings indicate that excessive exposure can trigger message fatigue, leading to adverse outcomes such as disengagement, reactance, and negative emotional responses among recipients. Besides, personal background factors and individual emotional responses play a significant role in the development of message fatigue.

Finally, our systematic review identifies several strategies recommended in existing literature that inspire more effective public health messaging. These include adopting an autonomy-supportive approach instead of forceful and controlling language to promote receptivity and trust, managing the quantity of message dissemination to avoid fatigue, and incorporating strategic timing and personalized message delivery to optimize impact.