Exploring the impact of message framing and physical activity levels on the effectiveness of health communication and its underlying cognitive processes

Abstract

Background

Message framing and individual characteristics are important factors influencing the effectiveness of health communication about physical activity promotion plans. However, the relationship has not been largely unexplored. The purpose of this study was to examine differences in health communication effectiveness and its neural activity in individuals with different levels of physical activity under gain- and loss-framed using fNIRS and a computerized laboratory task test.

Methods

The study design was a crossover design. Twenty-four people with low level of physical activity (mean age 18.42 ± 1.47 years, 13 males) and twenty-three people with high level of physical activity participated (mean age 22.22 ± 2.86 years, 11 males) in health communication under two experimental conditions: gain- and loss-framed messages. The Persuasive impacts of framed messages were measured by knowledge, attitude, and intention to engage in physical activity after participating in the health communication. fNIRS was used to measure activation in the prefrontal cortex. Analyses focused on both the mPFC and dlPFC regions, examining differences in HbO levels as a function of message framing and physical activity. To this end, a multifactor repeated measures analysis of variance (ANOVA) was employed.

Results

Participants’ knowledge[F_{(1, 45)} = 53.40, p < 0.001, η2 p = 0.543], attitude[F_{(1, 45)} = 12.98, p < 0.001, η2 p = 0.224], and intention[F_{(1, 45)} = 5.20, p = 0.027, η2 p = 0.104] increased more significantly after exposure to the loss-framed message compared to the gain-framed message. Additionally, there was a significant interaction between the two groups[F_{(1, 45)} = 8.53, p = 0.005, η2 p = 0.159]. The fNIRS results indicated that physical activity messages elicited significant positive activation (p < 0.06) in the medial prefrontal cortex (mPFC) and dorsolateral prefrontal cortex (dlPFC). There was a significant relationship (CH36: r = 0.395, p = 0.006) between the effectiveness of message framing and activation of the right dlPFC.

Conclusions

Health communication in loss-framed messages is more effective than gain-framed, especially for individuals with low level of physical activity. The prefrontal cortex (mPFC and dlPFC) is involved in the cognitive function of health communication. The right dlPFC is the area of loss-framed messages and may be able to predict the effectiveness of health communication.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-025-03943-y.

Introduction

In health communication, message framing—the strategic presentation of information to influence health decisions—has emerged as a powerful tool. This technique emphasizes either the benefits of adopting a behavior (gain framing) or the losses incurred by rejecting it (loss framing) [1, 2]. Message framing alters an audience’s receptivity to health messages, making the construction of optimally framed content for specific audiences a persistent challenge [3]. The effectiveness of different framing strategies can be complex and may vary depending on the target audience and the specific outcomes examined [4]. Indeed, the development of message framing, often tailored to specific individual characteristics or behaviors, alongside variations in message delivery format, can significantly influence decision-making preferences [5]. This nuanced approach offers a valuable avenue for exploring the presentation strategies that enhance health promotion efficacy [6]. Message framing interventions have been successfully applied to various health behaviors, including physical activity promotion [7, 8]. For example, a recent systematic review investigating message framing within diabetes health education found that both gain- and loss-framed messages positively impacted behavioral health-related outcomes, such as physical activity and self-management behaviors [9]. Recognizing the critical role of communication strategies in motivating individuals towards greater physical activity, research specifically on PA messaging highlights the importance of message content. Evidence consistently supports the use of gain-framed messages that emphasize short-term social and mental health benefits [4].

The effectiveness of gain- and loss-framed in health communication has been extensively compared and analyzed [10–12]. However, results on the use of gain- or loss-framed to increase persuasion have been mixed, and the matching effect between different domain-specific and message framing still needs to be explored. The currently more widely endorsed view is that loss-framed messages (messages that emphasize the costs of not taking action) are more effective in promoting health detection behaviors, whereas gain-framed messages (messages that emphasize the benefits of taking action) are more effective in promoting prevention behaviors [13]. In other words, gain-framed messages are more persuasive to people with low-risk behaviors, whereas loss-framed messages are more effective for people exposed to high-risk behaviors [11].

The evaluation of health communication activities often hinges on the audience’s perception of health messages [14], where individual subjective evaluations encompassing knowledge [15], attitude [16], and intention [17] are significantly influenced by presentation strategies. Message framing, a prominent approach in this regard, has been extensively studied in health communication. While physical activity is often conceptualized as a low-risk behavior for which gain-framed messages are suggested to be optimal [18], empirical evidence reveals a more complex landscape. Although a majority of studies suggest gain-framed messages are more effective for promoting physical activity [4, 19, 20], a considerable body of research reports superior outcomes with loss-framed messages [21–23]. Furthermore, individual characteristics are increasingly recognized as crucial moderators, significantly influencing preferences for message framing [24–29]. This divergence in findings underscores a significant gap in our understanding: the underlying psychological mechanisms driving these differential responses remain largely unexplored. Consequently, a deeper comprehension of decision-making processes and the effective evaluation of communication strategies is limited.

While previous studies have examined the effectiveness of message framing on behavioral outcomes [4], the underlying neural mechanisms remain underexplored. Neurocommunication is a rapidly growing field. Technological advances in the field of neuroscience can help researchers observe neural changes and understand how cognitions or mechanisms work during health communication by analyzing neuroimages. These innovative studies play a very important role in the design of health promotion programs and help to develop programs more precisely tailored to the audience and health problems [30]. In recent years, researchers have found that the prefrontal cortex (PFC) is involved in higher human cognitive functions such as category learning, working memory problem solving, and benefit trade-offs [31]. Related studies have shown that brain regions involved in cognitive processes related to framing effects are mainly localized in the prefrontal cortex [32]. It has been shown that activation of the medial prefrontal cortex (mPFC) during the reception of persuasive information reliably predicts downstream behaviors [33, 34]. Recent research further elucidates this connection, finding that participants perceived gain-framed messages as more effective and exhibited greater mPFC activation when these messages addressed directly experienced outcomes, with self-reported perceptions of effectiveness positively correlating with this neural activity [35]. Researchers have discovered that message effectiveness hinges on the intricate interplay of framing, neural processing, and pre-existing behavioural patterns, with more active individuals showing increased physical activity post-intervention when their brain regions respond more strongly to loss-framed messages [36], although the underlying mechanisms remain incompletely understood. Understanding why certain message frames resonate more effectively necessitates delving into the cognitive processes mediating information reception and evaluation. Neuroimaging techniques, particularly functional near-infrared spectroscopy (fNIRS), offer a powerful non-invasive window into these neural correlates. fNIRS allows for the measurement of hemodynamic responses (e.g., changes in oxygenated hemoglobin, HbO) in cortical areas during cognitive tasks, providing insights into brain activity associated with attention, emotional processing, and decision-making processes fundamental to how individuals engage with and are persuaded by health messages. Therefore, this study leverages fNIRS to investigate how message framing and physical activity levels are processed at a neural level, aiming to uncover the underlying cognitive mechanisms that contribute to differences in health communication effectiveness. This approach not only complements existing behavioral findings but also provides a deeper, neurobiological understanding of persuasion in health contexts, thus establishing a clearer rationale for our neuroimaging approach and guiding the reader smoothly into the subsequent fNIRS-focused analyses.

In summary, this study aimed to improve the effectiveness of health communication by exploring the matching of individual characteristics with message framing. Using a sample of low and high levels of physical activity groups, differences in the effectiveness of health communication under the gain- or loss-framed were explored by highlighting the benefits of physical activity (gain-framed) as well as the costs of not participating in physical activity (loss-framed). On the basis of information effects, fNIRS was used to measure individuals’ neural activity in the PFC during health communication and to compare the behavioral and neural responses of participants in different situations.

Materials and methods

Participants

Participant characteristics

Participants were recruited from Shanghai Jiao Tong University through posters. A total of 187 undergraduate students completed the International Physical Activity Questionnaire – Short Form (IPAQ-SF) [Chinese version] to initially assess their physical activity levels. Based on the pre-defined classification criteria of the IPAQ-SF, participants meeting the criteria for “high physical activity” and “low physical activity” were subsequently invited to participate in the main experiment. Participants whose activity levels fell between the high and low categories were excluded from the primary experimental sessions.

To ensure an adequate sample size for our study, a power analysis was conducted using G*Power 3.1. For a repeated measures ANOVA, we set a medium effect size (f = 0.25) at a significance level (α) of 0.05, with a statistical power (1-β) of 0.8. The power analysis indicated that a minimum of 22 participants were required per group to achieve sufficient statistical power. Consequently, we aimed to recruit 28 participants in the high physical activity (High PA) group and 28 participants in the low physical activity (Low PA) group, for a total target sample of 56 participants.

To ensure that participants completed the experiment conscientiously, we set up an attention check (5 questions in total) to exclude data from subjects who did not study carefully (≥ 2 wrong questions). Data from a total of 9 participants were excluded (2 participants in the low PA group and 1 participant in the high PA group were discarded because of failing the attention check, and 2 participants in the low PA group and 4 participants in the high PA group were discarded because of insufficient signal quality for fNIRS). The final sample consisted of 24 participants in the low PA group (mean age 18.42 ± 1.47 years, 13 males) and 23 participants in the high PA group (mean age 22.22 ± 2.86 years, 11 males), totaling 47 participants. Participant demographic characteristics and physical activity levels across the experimental conditions are summarized in Table 1. All participants signed a written informed consent form provided by the Ethics Committee of Shanghai Jiao Tong University, which is in accordance with the Declaration of Helsinki (ethical code: H2020042). Every participant received ¥50 for their participation.

Table 1.

Demographic characteristics and physical activity levels by study condition

Variable	Low PA Group (N = 24)	High PA Group (N = 23)
Demographic Characteristics
Age (years)	18.42 ± 1.47	22.22 ± 2.86
Sex (Male, %)	13 (54.17%)	11 (47.83%)
Vigorous-intensity PA (minutes/week)	16.46 ± 12.20	221.09 ± 81.42
Moderate-intensity PA (minutes/week)	35.42 ± 21.82	208.04 ± 68.83
Walking PA (minutes/week)	53.75 ± 32.75	218.91 ± 87.63
Total PA Volume (METs-minutes/week)	450.71 ± 103.42	3323.28 ± 599.84

Physical activity measurement

The International Physical Activity Questionnaire (IPAQ) [Chinese short form] was administered to all potential participants before the commencement of the formal experiment. Participants were then classified into three distinct physical activity categories: high, moderate, and low, based on their self-reported data from the IPAQ. To ensure a diverse range of physical activity profiles, only participants categorized as either high or low in physical activity were subsequently invited to join the formal experimental sessions. The IPAQ questionnaire, its scoring methodology, and the classification criteria are further detailed in Supplementary Material S1.

Experimental materials

The experimental materials were manipulated by varying the type of information used in the health promotion argument. The messages were taken from “WHO Guidelines on Physical Activity and Sedentary Behavior”. We added information from different message framings for each argument. For example, the gains-framed (physical activity confers benefits for the following health outcomes: mental health, cognitive health, and sleep), the loss-framed (compared to those with sufficient physical activity, individuals with insufficient PA face a 20%-30% increased risk of mortality).

Prior to the start of the experiment, 20 university students were recruited to rate the prepared materials in terms of arousal (1 completely calm − 9 completely agitated), clarity (1 completely vague − 9 completely clear), and difficulty (1 not completely understood − 9 completely understood). A total of 20 materials were prepared, and in order to balance the number of stimuli between the gain- and loss-framed, 16 persuasive messages were ultimately selected that did not differ.

Data acquisition and analysis

Message framing effects

Message framing effects were assessed by three questions after participating in the health communication (1). I have incation (2). I have increased my positive attitude toward participating in physical activity through this communication (3). I have increased my intention to participate in physical activity through this communication. Participants rated the statements on a nine-point scale. Knowledge, attitude, and intention are valid indicators for assessing the persuasive effectiveness of message framing in health communication [3].

fNIRS measurement

Functional Near-Infrared Spectroscopy (fNIRS) was employed to assess participants’ hemodynamic changes in prefrontal areas related to processing persuasive health messages during the experimental task. fNIRS is a non-invasive neuroimaging technique that measures brain activity by detecting changes in hemoglobin concentration (oxygenated and deoxygenated hemoglobin) in the cerebral cortex [37]. This method utilizes the principle of near-infrared light transmission through the scalp and the detection of reflected light, which is modulated by blood oxygenation levels. We selected fNIRS due to its unique advantages, including its portability, relative insensitivity to motion artifacts compared to electroencephalography (EEG), and its ability to be used during moderate physical activity [38]. In addition, fNIRS has high temporal resolution and spatial resolution [39]. These advantages make fNIRS a very promising brain imaging modality [40]. These features make fNIRS particularly suitable for investigating the neural correlates of persuasive message processing in our participant population, where participants were engaged in actively evaluating health messages and performing related cognitive tasks.

Data collection was performed in the Sport Cognitive Psychology Laboratory at Shanghai Jiao Tong University. The fNIRS measurement was conducted with a NIRSport2 continuous wave fNIRS system (NIRx Medical Technologies LLC). The absorptions of the near-infrared lights at two wavelengths (785 nm and 830 nm) were measured with a sampling rate of 7.81 Hz. A proof set containing 16 emitters and 16 detectors was placed on the frontal area, forming 48 measurement channels in total (Fig. 1A). The source-detector distance was 3 cm. With the participant wearing an fNIRS cap, the experimenter checked the signal from each channel by running test data through NIRStar software to ensure signal quality was achieved.

Fig. 1.

Scheme of the experiment. A The configuration of the fNIRS probes. B The paradigm of the experiment

In previous studies, some brain regions (mPFC and dlPFC) were activated during similar tasks [34, 41]. Therefore, the ROIs in this study included both mPFC and dlPFC regions. For the definition of ROI, the Brodmann [42] auto-anatomical labeling atlas was used in this study. Regions included left mPFC (channels 1, 2, 6, 9, 10, 11, 12) and right mPFC (channels 25, 26, 27, 28, 29, 33, 34), left dlPFC (channels 8, 14, 17, 19) and right dlPFC (channels 30, 31, 36, 37). This channel layout measures the activation of mPFC and dlPFC very well.

Procedure

To ensure that all participants received consistent information, they completed an automated tutorial prior to the formal experiment. Before commencing the formal experiment, all participants verbalized their understanding of the instructions. Both the practice and formal experimental procedures were programmed using E-Prime 3.0 (Psychology Software Tools Inc., United States). The entire procedure consisted of 16 trials, comprising 8 gain-framed and 8 loss-framed stimuli. Each trial began with a fixation cross displayed on the screen for 500 ms, followed by the presentation of a message. Participants were instructed to view the message for a maximum of 20 s. After viewing the message, participants pressed the SPACE bar to indicate they had finished and then responded to questions about the message framing effects. A central black fixation cross was then presented for 12 s, during which participants were instructed to relax and rest before the next trial. The messages were presented in a random sequence. The entire procedure lasted approximately 10 min (Fig. 1B).

Following the completion of the primary experimental tasks, participants were administered a brief assessment on the computer. This assessment consisted of five true/false items, for which participants indicated their response by pressing ‘yes’ or ‘no’. The purpose of this test was to ensure participants’ careful engagement with the experimental materials and to verify their comprehension of the study’s context. Crucially, participants who answered two or more questions incorrectly were excluded from the final dataset to maintain data quality and ensure participant attentiveness. The questionnaire, which is based on the first author’s doctoral dissertation research, is provided in its entirety as Supplementary Material S2.

Statistical analyses

Message framing effects data analysis

A multifactor repeated measures analysis of variance (ANOVA) was used in this study. The independent variables were the gain/loss framework and the type of subject, and the dependent variables were the scores for knowledge, attitude, and intention. The total mean score of knowledge, attitude, and intention was used as the information effect value for the persuasion effect.

fNIRS data analysis

The oxygenated (HbO) and the deoxygenated (HbR) signals were calculated by using the modified Beer-Lambert law.

Data analysis of fNIRS was performed using nirsLAB (v2019.4). Changes in oxygenated hemoglobin (HbO), deoxygenated hemoglobin concentration (HbR), and total hemoglobin concentration (HbT) in the monitored area were obtained according to the modified Bierenberg law. To eliminate baseline drift and physiological noise, we filtered the hemoglobin data using 0.01 Hz and 0.3 Hz bandpass filters [43]. HbO was used as a marker of regional activation in this study because previous studies have shown that HbO is the most sensitive marker of task-related hemodynamic changes. The β-value of HbO which is representative of valid trials in each case was calculated according to SPM. Statistical analyses were performed using SPSS 27.0 on the derived β-values of HbO.

We collected data 5 s before stimulus onset as a baseline. Considering the delay between the onset of neural activity and the peak of the associated hemodynamic response, we observed a peak change in HbO from 0 to 10 s after stimulus onset; therefore, this period was used as the analysis window. ANOVA was used to calculate the difference between the target and baseline periods of HbO to determine the brain regions activated in each case [44].

Results

Self-reported outcomes

A significant main effect of message framing was found for knowledge, attitude, and intention. Specifically, participants exposed to loss-framed messages reported significantly higher scores in knowledge [F_{(1, 45)} = 53.40, p < 0.001, η2 p = 0.543], attitude [F_{(1, 45)} = 12.98, p < 0.001, η2 p = 0.224], and intention [F_{(1, 45)} = 5.20, p = 0.027, η2 p = 0.104] compared to those exposed to gain-framed messages.

A main effect of individual characters on knowledge [F_{(1, 45)} = 4.25, p = 0.045, η2 p = 0.086], with the low PA group eliciting more enhancement of knowledge compared to the high PA group. No main effect of individual characters was found when message framing effectiveness was assessed by attitude [F_{(1, 45)} = 1.62, p = 0.209, η2 p = 0.035] or intention [F_{(1, 45)} = 0.58, p = 0.449, η2 p = 0.013].

As shown in Fig. 2, there was a significant interaction between individual characters and levels of physical activity [F_{(1, 45)} = 8.53, p = 0.005, η2 p = 0.159] when persuasion was assessed by knowledge. The simple effect analysis revealed that for loss-framed [M = 5.40, SE = 0.36] induced significantly higher enhancement than gain-framed [M = 5.08, SE = 0.47, p < 0.001, η2 p = 0.476] among low PA group, and loss-framed [M = 5.40, SE = 0.36] induced significantly higher enhancement than gain-framed [M = 4.52, SE = 0.48, p = 0.001, η2 p = 0.212] among high PA group. In the loss-framed condition, the low PA group showed higher knowledge enhancement than the high PA group[ p = 0.001, η2 p = 0.212], but not in the gain-framed condition [p = 0.408, η2 p = 0.015]. No significant interaction was found when persuasion was assessed by attitude [F_{(1, 45)} = 1.62, p = 0.209, η2 p = 0.035] or intention [F_{(1, 45)} = 0.58, p = 0.449, η2 p = 0.013].

Fig. 2.

Message framing effects were assessed by (A) knowledge, (B) attitude, and (C) intention between low and high of physical activity. Data are expressed as mean ± standard error. * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001

fNIRS results

As shown in Fig. 3, a main effect of message framing on the left mPFC [CH1: F_{(2, 45)} = 3.24, p = 0.049, η2 p = 0.128; CH2༚F_{(2, 45)} = 11.77, p < 0.001, η2 p = 0.349༛ CH11༚F_{(2, 45)} = 4.66, p = 0.015, η2 p = 0.175], the right mPFC [CH25༚F_{(2, 45)} = 6.11, p = 0.005, η2 p = 0.217], the left dlPFC [CH19༚F_{(1, 45)} = 5.45, p = 0.008, η2 p = 0.198], and the right dlPFC[CH31༚F_{(2, 45)} = 6.43, p = 0.004, η2 p = 0.226༛ CH37༚F_{(2, 45)} = 3.79, p = 0.030, η2 p = 0.147]. The gain-framed condition showed significant positive activation in the left mPFC [CH2(p = 0.048)], whereas the loss-framed condition showed positive activation in the left mPFC [CH11(p = 0.012)], the right mPFC [CH25(p = 0.020)], the left dlPFC [CH19(p = 0.017)] and the right dlPFC [CH31 (p = 0.003), CH37(p = 0.043)].

Fig. 3.

Cortical activation during health communication in gain- and loss-framed conditions. A F-map of HbO reflecting the main effect of the message framing condition. F-values are displayed according to the color bar. B-J The mean difference of HbO concentrations among baseline, gain- and loss-framed conditions in both low and high physical activity participants

A main effect of individual characters on the left mPFC [CH11: F_{(1, 45)} = 5.31, p = 0.026, η2 p = 0.105], indicated that the low PA group showed higher responses in the left mPFC than the high PA group. And a main effect of individual characters on the right dlPFC [CH37༚F_{(1, 45)} = 4.51, p = 0.039, η2 p = 0.091], indicating that the low PA group showed a lower response in the right dlPFC than the high PA group.

There was a significant interaction on the left mPFC [CH11: F_{(2, 45)} = 4.72, p = 0.014, η2 p = 0.177], the right mPFC [CH27༚F_{(2, 45)} = 4.82, p = 0.013, η2 p = 0.180], the left dlPFC [CH17༚F_{(2, 45)} = 3.48, p = 0.039, η2 p = 0.137] and the right dlPFC [CH37༚F_{(2, 45)} = 4.05, p = 0.024, η2 p = 0.155]. Followup tests revealed that among the low PA group, the gain-framed condition showed significant positive activation in the left mPFC [CH11(p = 0.022)] than baseline. Among the high PA group, the loss-framed condition showed significant positive activation in the right dlPFC [CH37(p = 0.001)]. In the gain-framed condition, the low PA group showed higher response in the left [CH11(p = 0.004)] and right [CH27(p = 0.020)] mPFC than the high PA group. And in the loss-framed condition, the low PA group showed a lower response in the right dlPFC [CH37(p = 0.001)] than the high PA group.

Relationship between PFC and persuasion

A Pearson correlation analysis was adopted to assess to examine the association between the message framing effects and brain activation. As shown in Fig. 4, the positive correlation between persuasive outcomes and the right dlPFC activation in the loss-framed condition (CH36: r = 0.395, p = 0.006).

Fig. 4.

Correlations between message framing effects and brain activation in the loss-framed condition

Discussion

Message framing and individual characteristics are important factors that influence the effectiveness of health communication. The present study manipulated both message framing (gain- and loss-framed) and the physical activity level (high and low) of the participants. We measured the participants’ neural activity by using fNIRS when they were watching health messages, and compared the participants’ self-reported outcomes and neural responses between the two conditions. According to self-reported outcomes, we found that low level of physical activity participants showed significantly higher message framing effects when watching loss-framed messages than gain-framed messages, while high level of physical activity participants showed the same trend. Additionally, participants with low level of physical activity have the best message effectiveness in loss-framed health communication. The fNIRS results further revealed that watching gain-framed messages evoked significant positive activity in the left mPFC for the low PA group. In the high PA group, watching loss-framed messages evoked significant activity in the right dlPFC. We also found a correlation between the right dlPFC and message framing effects during loss-framed.

This study validates the use of knowledge, attitude, and intention as key indicators of persuasive effectiveness in health communication, aligning with previous research [45]. Our findings underscore that message framing significantly influences physical activity-related outcomes, with differential effects observed across participants of varying physical activity levels. Specifically, both gain- and loss-framed messages not only enhanced knowledge about physical activity promotion in both high and low PA groups but also substantially improved positive attitudes and intentions toward physical activity, particularly among participants in the low PA group. This pattern is powerfully explained by Prospect Theory [1], which highlights how the framing of information critically affects its impact [46]. The observed matching effect [47], where message framing congruent with an individual’s orientation facilitates easier processing and leads to greater effectiveness, appears particularly salient for individuals with lower levels of current physical activity. This suggests that strategically framed health messages can amplify message reception and serve as crucial precursors to sustained behavioral change in physical activity for this population.

The positive contribution of enhanced knowledge to engagement with health promotion programs is well-established [48]. While previous interventions to increase physical activity among adolescents (15–32 years) have employed various strategies [49], and a single strategy focused solely on knowledge may not be sufficient for behavioral change [50], improving an individual’s knowledge through effective health communication remains a crucial step towards promoting healthier behaviors.

Furthermore, the observed changes in attitude and intention are important indicators of an individual’s receptiveness to health information [51]. Shifts in these cognitive and affective domains are essential for increasing adherence to recommended physical activity guidelines [19]. While some studies have reported variability in the impact of message framing on attitude and intention, with some finding changes in attitude but not intention [52], our study demonstrates a consistent positive effect of congruent framing on both attitude and intention, particularly for the low PA group. This suggests that tailored message framing can be a powerful tool for motivating individuals with lower levels of physical activity.

In this study, we found that knowledge enhancement was significantly higher in the low PA group than in the high PA group. fNIRS results further revealed significant activation of mPFC with a higher activation level in the low PA group than in the high PA group. Studies have shown that mPFC is highly correlated with memory consolidation and extraction [53, 54]. Over the past decade or so, studies have established that the mPFC is a central predictor of whether persuasive information is successful in changing behavior [41], and that activation of the mPFC is significantly correlated with information-concordant behavioral change, even more so than self-intentional reports [55]. General mPFC behavioral effects have been observed many times [56], but are still novel for simultaneous mPFC effects in a gain- and loss-framed. Thus, these findings suggest that the use of a message framing leads to more knowledge enhancement in the low PA group than in the high PA group, thus increasing the effectiveness of health communication.

Our study explored the differential roles of gain- and loss-framed messages, finding that loss-framed messages generally yielded greater persuasiveness in terms of knowledge, attitude, and intention compared to gain-framed messages. While this main effect suggests a broad advantage for loss framing, the absence of a significant interaction effect implies that this advantage may not be universally moderated as anticipated, or that further investigation into the underlying mechanisms is needed. The mixed findings in the literature regarding the superiority of gain- versus loss-framed messages [57–60] and the conditional effectiveness based on perceived risk [61] highlight the nuanced nature of message framing. We propose that physical activity, while often perceived as low-risk, may be subject to variable risk perceptions depending on the context. As demonstrated by Francis and West [8], the effectiveness of framing for physical activity motivation can shift with situational factors, such as the COVID-19 pandemic. This suggests that beyond intrinsic risk, contextual influences and individual perceptions play a critical role in determining the optimal message framing for promoting physical activity.

The fNIRS results further revealed that the right dlPFC may be a sensitive region for loss-framed. Specifically, the present study not only found that the right dlPFC was significantly higher in the high PA group than in the low PA group under loss-framed conditions, consistent with the self-reported outcomes, but also found a significant positive correlation between activation of the right dlPFC and message framing effects under loss-framed. Previous studies have highlighted the crucial role of the dorsolateral prefrontal cortex (dlPFC) in cognitive control, encompassing the reception of conflicting signals, regulation and reallocation of cognitive resources, attentional control, and conflict resolution [62, 63]. The dlPFC is also implicated in processing persuasive message counterarguments [41]. Specifically, research suggests that activity in the right dlPFC can influence decision-making behavior by modulating neural responses to stimuli [64]. Importantly, the right hemisphere, and particularly the right dlPFC, appears to be involved in risk assessment and the processing of negative affect and threat detection, which are characteristic of loss-framed messages [65]. Loss-framed messages, by emphasizing potential losses and disadvantages, tend to elicit stronger negative emotions and a heightened sense of threat. This may engage neural circuits associated with vigilance and the cognitive control required to evaluate potential negative outcomes and consider counterfactuals, processes that the right dlPFC is known to support. Therefore, our finding that the right dlPFC may be a sensitive area for loss-framed messages is consistent with these roles, suggesting a potential unilateralization of brain hemispheric function in message framing effects.

Overall, the results of the present study suggest a situation where the loss-framed is more effective than the gain-framed in terms of individual knowledge, attitude, and intention to change, especially for groups with low level of physical activity, despite the fact that physical activity facilitates the transmission of essentially the same message. The findings of this study on mPFC and dlPFC activation due to health communication in the gain- and loss-framed are equally revealing.

In summary, our findings suggest three key directions for future research. First, a deeper examination of the differential responses between high and low physical activity (PA) groups when encountering loss-framed health messages is warranted. The observed behavioral divergence between these groups suggests a potential interaction effect that warrants further investigation. Second, in-depth studies are needed to elucidate the mediating factors that may influence the effect of message framing on preventive behaviors. Specifically, exploring constructs such as self-efficacy, social norms, outcome expectations, and emotional responses could provide crucial insights into the underlying psychological mechanisms. Third, further research should delve into the neural mechanisms by which internal processes during health communication establish and modulate activity in the medial prefrontal cortex (mPFC) and dorsolateral prefrontal cortex (dlPFC).

Building upon these directions, certain aspects of our methodology warrant consideration for future refinement. Firstly, while our carefully selected single-item measures for knowledge, attitude, and intention were designed to capture core constructs and were pre-tested, future investigations could enhance the robustness and dimensionality of these assessments by employing multi-item scales. Such an approach would offer a more comprehensive representation of these complex psychological constructs, potentially revealing more nuanced effects of message framing and further validating our observed relationships. Secondly, to further strengthen the ecological validity and precision of our findings, future research could incorporate objective measurement methods for physical activity and sedentary behavior. While self-report measures like the IPAQ are valuable, the use of objective tools such as accelerometers or heart rate monitors can provide a more accurate estimation of PA intensity and duration, thereby offering higher fidelity data. Integrating these objective measures alongside sophisticated message designs tailored to address the distinct yet related constructs of physical activity and sedentary behavior would be instrumental in comprehensively verifying our results and advancing the field.

Conclusion

In the present study, drawing on the message framing effects in health communication and the work of neuroscience in persuasive communication, we utilized fNIRS to track participants’ neural activation and changes in knowledge, attitude, and intention while they were exposed to two message framing models. Our findings indicate that loss-framed messages appear to be more effective than gain-framed messages in enhancing knowledge, attitude, and intention regarding physical activity promotion. Furthermore, we observed an interaction effect between physical activity levels and message framing, particularly on knowledge, where health communication effectiveness was greatest for participants with low levels of physical activity when presented with loss-framed messages. Neuroimaging results revealed that the prefrontal cortex, specifically the mPFC and dlPFC regions, is involved in the cognitive processing of health communication. Notably, the right dlPFC may serve as a sensitive area for processing loss-framed messages, showing a correlation with the persuasiveness of health messages. Collectively, these findings provide novel insights into the differential effectiveness of message framing, the role of individual physical activity levels, and the neural underpinnings of persuasive health communication.

Authors’ contributions

JG contributed to the design and conduct of the study, was primarily responsible for data analysis and drafting part of the manuscript, critically reviewed the manuscript, and approved its final form. ZD contributed to the design of the study, critically revised the manuscript. JX and KW revised the manuscript. ZC assisted in the critical revision of the manuscript, and approved the final manuscript. All authors contributed to the article and approved the version submitted for publication.

Funding

None.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The experimental procedure of the study was reviewed and approved by the Commission of Investigation and Ethical Protocol of Shanghai Jiao Tong University (Approval number: H2020042I). The participants provided their written informed consent to participate in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.