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. 2025 May 2;20(1):nsaf044. doi: 10.1093/scan/nsaf044

Are older adults more deceived by false advertising? Evidence from intra- and inter-brain connectivity in the prefrontal cortex during face-to-face deceptive sales

Ying-Chen Liu 1, Zi-Han Xu 2, Zhi-Jun Zhan 3, Zi-Wei Liang 4, Xue-Rui Peng 5,6,7,*, Jing Yu 8,*
PMCID: PMC12201989  PMID: 40314103

Abstract

Financial fraud through false advertising has become increasingly prevalent among both younger and older adults, yet the neuropsychological mechanisms underlying real-time, face-to-face deceptive sales are unclear. In addition, the effects of guilt appeal as a marketing strategy, across age groups, remain unexplored. We used functional near-infrared spectroscopy hyperscanning to examine purchase decisions and neural mechanisms by age group and sales approach (guilt vs. control) in a face-to-face sale mimicking real-life scenarios. Older adults had higher purchase intentions for products promoted by false advertising across sales approaches compared to younger adults. However, younger adults were more likely to be influenced by guilt appeal. The neural results aligned with the behavioral finding that younger adults’ intra-brain functional connectivity and inter-brain synchronization values were greater in the guilt condition than in the control, whereas no difference between conditions was found for older adults. Using inter-subject representational similarity analyses, we identified distinct neuropsychological mechanisms between two age groups. Younger adults’ frontopolar activity was associated with the advertising credibility, whereas older adults’ frontopolar activity was associated with the trustworthiness of the salesperson during deceptive sales. These findings provide insights into age-specific vulnerabilities and may inform tailored consumer fraud prevention strategies targeting younger and older adults separately.

Keywords: false advertising, aging, guilt appeal, fNIRS hyperscanning, inter-brain synchronization

Introduction

Financial fraud refers to intentional deception that promises nonexistent, unnecessary, or materially inaccurate goods, services, or other benefits for financial gain (Titus et al. 1995). False advertisements are often used as a tool for financial fraud, a lucrative practice involving the dissemination of deceptive information, misleading claims, and dishonest statements to consumers (Hasan et al. 2011). The misleading content of such advertisements can influence the decision-making process of consumers, leading them to make unfavorable financial choices that ultimately result in fraud victimization (Anderson 2016, Nuseir 2018). According to the Federal Trade Commission’s most recent report on Frauds and Losses by Age, individuals aged 60–69 years experienced the highest percentage (∼18%) of financial losses of any age group (Federal Trade Commission 2024). Older consumers are particularly susceptible to persuasion through advertising (Phillips and Stanton 2004). Empirical evidence shows that, compared to younger adults, older adults are more likely to purchase products based on misleading or false advertising and are at greater risk of being scammed (Denburg et al. 2007, Anderson 2016, Koestner et al. 2016, Kircanski et al. 2018). Age-related susceptibility to scams can be investigated by assessing participants’ responses to false advertisements and corresponding brain activity (Koestner et al. 2016).

Among various advertising marketing approaches, emotional appeal is an effective advertising tactic that evokes emotional responses to capture customers’ attention and influence their purchasing behavior (Edell and Burke 1987, Olney et al. 1991). Guilt appeal, as one of them, has become a useful strategy by influencing consumers’ attention, attitudes toward products, and purchase intentions (Hibbert et al. 2007, Basil et al. 2008). Empirical evidence suggests that consumers exposed to guilt appeals in advertising are more likely to adopt the behaviors promoted in those advertisements (Ruth and Faber 1988). The underlying mechanism involves individuals’ tendency to reduce guilt-induced discomfort through compensatory behaviors, often manifested as ethical consumption (e.g. Chang 2014, Pounders et al. 2018, 2019, La Ferle et al. 2019, Chen and Moosmayer 2020, Coleman et al. 2020). In consumer decision-making, guilt appeals employed in false advertising could distract consumers’ attention from advertisement content, potentially making them overlook deceptive elements (McGuire 1969) and increasing their likelihood of purchasing the advertised product. To date, age differences in response to guilt appeals remain unclear. One possibility is that older adults may be more susceptible than younger adults to guilt appeals because they are generally more prosocial (Li et al. 2024, Pollerhoff et al. 2024). However, it is also possible that younger adults are more affected, as some evidence suggests a reduced influence of guilt appeals on older adults. Specifically, older adults are better at emotional regulation (Lang and Carstensen 2002, Löckenhoff and Carstensen 2004), which may reduce the impact of guilt-induced emotions on their purchasing behavior. For example, a recent study suggested that aging weakened the regulatory effect of emotions on social decision-making, with older adults showing less emotion-related generosity (Xu et al. 2024). Furthermore, age-related amygdala decline selectively reduces emotional arousal to negative stimuli, which potentially makes guilt appeals less effective (Cacioppo et al. 2011).

From a neurobiological perspective, the prefrontal cortex (PFC) plays an important role in false advertising processing because it is involved in highly relevant cognitive functions such as information seeking and evaluation (Nakamura and Komatsu 2019), emotional processes (Dixon et al. 2017), and inhibitory control (Cohen 2005). However, the PFC is also one of the first brain regions to be affected by aging (Navakkode et al. 2018). Older adults experience functional declines in several areas of the PFC (Tisserand et al. 2002, Bergfield et al. 2010), which increases their susceptibility to deception (Ebner et al. 2023). For example, older adults with impairments in the ventral medial PFC are more likely to be persuaded by false advertising (Asp et al. 2012). Furthermore, functional connectivity (FC) within the PFC changes with aging (Jobson et al. 2021). Older adults show reduced intra-network FC during cognitive tasks compared to younger adults (Persson et al. 2007), which may impair their ability to effectively process complex information such as deceptive advertising. Additionally, inter-network FC between the PFC and other brain regions also changes as people age (Filippi et al. 2023). These changes in FC could make older adults more vulnerable to deceptive information, as they may struggle to recruit specialized neural systems for processing complex information, evaluating credibility, and making decisions (Geerligs et al. 2015, Yu et al. 2017).

Most existing studies have low ecological validity due to the lack of face-to-face interactions between salespersons and consumers (Arslan et al. 2017, Spreng et al. 2017, Wang et al. 2025). Dual-brain hyperscanning techniques, by capturing both the intra- and inter-brain exchanges during natural conversation, have provided new insights into consumer purchasing behavior (Zhang and Yartsev 2019, Zhang et al. 2023). Inter-brain synchrony (IBS) serves as a key neural indicator for understanding the neural mechanisms of social interactions (Dikker et al. 2017, Yang et al. 2020) and showing strong predictive power for decision-making tendencies (Kingsbury and Hong 2020). During face-to-face interactions, PFC activity is closely linked to deceptive behaviors, with synchronization observed between the brain activity of leaders and followers (Pinti et al. 2021). In the context of consumer decision-making, functional near-infrared spectroscopy (fNIRS) appears to be a promising tool for capturing PFC responses during purchase decisions (Krampe et al. 2018), and the IBS variations in shopping scenarios influence consumer purchasing decisions (Zhang et al. 2025).

The current study aims to investigate adult age differences in response to guilt appeal marketing through face-to-face false advertising and the underlying neural mechanisms. To this end, we used fNIRS hyperscanning to measure PFC activity in consumer–salesperson dyads during the sales interactions. First, we examined how younger and older adults differ in their purchase intentions for falsely advertised products and the influence of guilt appeal marketing elicited by the salesperson’s poor family background. We hypothesized that older adults are more susceptible to false advertisements than younger adults, and the susceptibility is moderated by guilt appeal. Second, we examined consumers’ prefrontal intra-brain FC during deceptive sales. Furthermore, we conducted an IBS analysis to investigate age-related differences in PFC neural synchronization during consumer–salesperson interactions and the effect of guilt. We expected to observe reduced intra-brain FC and IBS in older adults. Finally, we conducted inter-subject representational similarity analyses (IS-RSAs) to explore the underlying neuropsychological mechanisms that might be present during deceptive marketing for consumers in different age groups. In light of previous research suggesting that older adults often exhibit excessive trust, which significantly increases their susceptibility to fraud (Shao et al. 2019), we hypothesized that brain activity in older adults would be more related to the trustworthiness of salesperson. The current study advances our understanding of how aging affects vulnerability to deceptive marketing. The findings of the study also have important implications for developing consumer protection strategies to prevent financial fraud, especially for older adults who are at greater risk of financial exploitation.

Method

Participants

The sample size was determined through a priori power analysis conducted using G*Power (Faul et al. 2007), which suggested a minimum of 54 dyads to detect a reliable age × sales approach interaction effect (d = 0.25) with 95% power. 60 participants were recruited as potential consumers, and two older adults were excluded because they did not complete the entire experiment. The final consumer dataset consisted of 30 younger adults (aged 18–25 years) and 28 older adults (aged 65–83 years). The older adults had no cognitive impairment, with a Montreal Cognitive Assessment score ≥ 22 (Yu et al. 2012). Younger and older adults were matched for sex, susceptibility to deception as measured by the Susceptibility to Deception Scale (Shao et al. 2019), and social isolation as measured by the Lubben Social Network Scale-6 (Lubben et al. 2006). Detailed demographic and neuropsychological characteristics of the participants are shown in Supplementary Material (Table S1). In addition, four university students were recruited and trained as pseudo-salespersons. Their information can also be found in Supplementary Material (Text S1). Each consumer was paired with one salesperson in each condition, resulting in 58 dyads per condition for the subsequent analyses. All participants signed the informed consent form before starting the experiment and were compensated with 50 RMB for their participation.

Experimental design and procedure

The deceptive sales scenarios in this study were conducted using false advertising, such as “100% bacteria elimination rate” and “…cures cardiovascular disease.” Details of the false advertising for each product can be found in Supplementary Material (Table S2). The deceptive sales task consisted of two blocks, guilt condition and control condition, with the order counterbalanced across participants. In the guilt condition, the salesperson described a difficult life situation with a poor family background before proceeding with the false sales pitch, while in the control condition, the salesperson described an average family background. Detailed information on the salespersons’ backgrounds can be found in Supplementary Material (Figure S1).

During the task, the brain activation of the salesperson and the consumer was simultaneously recorded using fNIRS-based hyperscanning in the prefrontal region. The salesperson and consumer were required to sit face-to-face and 120 cm apart to control the social space for the interaction with strangers (Hall 1966). Each block consisted of a 3-minute resting state, a salesperson introduction, and a four-product sales phase. Consumers were presented with the salesperson’s background materials before the introduction. During the sales phase, the salesperson attempted to sell four products to the consumer, showing pictures of each product and delivering a pre-rehearsed script with consistent lines and tone of voice. After each pitch, the consumer was asked to rate purchase intention and advertising credibility for that product. After each block, trustworthiness of the salesperson, perceived manipulative intent (Campbell 1995), and perceived guilt (Bozinoff and Ghingold 1983, Cotte et al. 2005) were assessed. The experimental design and procedure are shown in Fig. 1a.

Figure 1.

Figure 1.

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Schematic experimental procedure and data analysis. (a) Experimental design and procedure. (b) Optode probe placement layout. (c) fNIRS data preprocessing and inter-brain synchronization calculation. (d) Intra-brain FC maps of consumers in different age groups and different conditions. (e) Frequency bands of interest (highlighted in the red box) used for WTC calculation. (f) IS-RSA procedure. The behavioral and neural dissimilarity matrices were constructed by calculating the Euclidean distance between all pairs of subjects. Spearman’s correlation was used to calculate the correlation between these two matrices.

Behavioral data analysis

We first used repeated-measures analyses of variance (ANOVAs) to assess the effectiveness of the experimental manipulations on perceived manipulative intent and perceived guilt. Age group (younger vs. older adults) served as the between-subjects factor, and sales approach (guilt vs. control) as the within-subjects factor. Significant age differences were found in perceived manipulative intent. Main analyses examined purchase intention, advertising credibility, and salesperson trustworthiness using the same ANOVA model, with perceived manipulative intent included as a covariate. Correlational analyses explored relationships among these variables. Behavioral data were analyzed using SPSS (version 21.0, IBM Corporation, Somers, NY, USA).

Functional near-infrared spectroscopy data acquisition and preprocessing

A Shimadzu multichannel high-speed continuous wave system (fore3000, Shimadzu, Kyoto, Japan) with three wavelengths of 780, 805, and 830 nm was used to record the hemodynamic signals of each dyad at a sampling rate of 7.69 Hz. The optodes were placed to optimize coverage of the PFC, as previous work has implicated the role of this region in consumption decisions (Spreng et al. 2017, Çakir et al. 2018). The PFC was covered by a 3 × 5 photoprobe set consisting of 8 emitters and 7 detectors spaced 30 mm apart, resulting in 22 measurement channels (CHs; see Fig. 1b). The optode probes were placed according to the international 10–20 system (Okamoto et al. 2004), with Fpz as the reference point. The correspondence between channels and cortical locations was determined using the virtual registration method (FASTRAK; Polhemus, USA; for detailed MNI coordinates see Supplementary Material Table S3).

The collected data were preprocessed in MATLAB (Version 2022b; Mathworks, Natick, MA, USA) using the NIRS-KIT. The correlation-based signal improvement method was used to reduce motion artifacts (Cui et al. 2010). Band-pass filtering (0.01–0.50 Hz) was performed to remove the high- and low-frequency noises (Zhou et al. 2023). We focused on the oxyhemoglobin (HbO) concentrations due to its better signal-to-noise ratio than deoxyhemoglobin (HbR) and total hemoglobin (HbT) (Mahmoudzadeh et al. 2013) and stronger signal amplitude (Strangman et al. 2002, Duan et al. 2012). The preprocessing procedure is illustrated in Fig. 1c.

Intra-brain functional connectivity in consumers

The Pearson correlation coefficient was used to calculate FC between different channels in the consumer’s PFC (Preti et al. 2017). The FC between channels is defined as:

graphic file with name UM0001-Latex.gif

where Inline graphic and Inline graphic were the observed HbO concentrations of the two different channels at the ith time point (translated by the ith sampling point).Inline graphic and Inline graphic were the mean HbO concentrations for each channel, and n was the total number of time points. We only included the time points in the sales process for each dyad to calculate the FC. The calculations were performed using the corrcoef function in MATLAB. The P-values were then corrected for multiple comparisons using the false discovery rate (FDR) method with the Benjamini–Hochberg procedure. We calculated FC strengths separately for both guilt and control conditions for each participant and generated the FC maps for each age group in the two conditions using the group-level mean value of FC (See Fig. 1d). Subsequently, repeated-measures ANOVAs were conducted for FC of each channel pairs, with age group (younger vs. older adults) as the between-subjects factor and sales approach (guilt vs. control) as the within-subjects factor.

Inter-brain synchronization between the salesperson and the consumer

Wavelet transform coherence (WTC) analysis was used to calculate the interpersonal brain synchrony between the salesperson and the consumer (Zhang et al. 2023). The WTC of the HbO time series i (m) and j (m) with the wavelet scales was denoted below (Nozawa et al. 2016).

graphic file with name UM0002-Latex.gif

We utilized the MATLAB wcoherence function to identify wavelet coherence values. Next, a series of paired samples t-tests were performed to compare whether the IBS was increased during the sales task compared to the resting state, and the frequency range of interest (FOI) was identified as 0.18–0.23 Hz (Fig. 1e). Within this FOI, the IBS for the task and resting phases were averaged across time and the frequency band (Zhao et al. 2022). Task-related IBS was defined as the brain synchrony during the task phase minus that during the resting phase and was then Fisher-Z transformed. Repeated-measures ANOVAs were performed on each task-related IBS with age group as a between-subjects factor and sales approach as a within-subjects factor, P-values were FDR-corrected using the Benjamini–Hochberg procedure.

Inter-subject representational similarity analysis in consumers

Previous studies have suggested that there are age-related differences in consumer decision-making (Yoon et al. 2009, Peng et al. 2016). To address this, IS-RSA was used to examine the association between purchase decision-related behavioral ratings (advertising credibility and trustworthiness of the salesperson) and HbO signals during the sales phase of consumers. The resulting IS-RSA r-values reflect the extent to which similarities in the behavioral index correspond to similarities in neural responses to the sales process.

The analysis proceeded in three steps. First, we constructed representational dissimilarity matrices (RDMs) separately for behavioral and neural data within each sales approach (guilt vs. control) and age group (younger vs. older). Behavioral RDMs were created for both advertising credibility and trustworthiness of the salesperson by computing unique pairwise Euclidean distances between all participants’ ratings (where each element represented the dissimilarity between two participants), with larger distances indicating greater dissimilarity (Zhang et al. 2024). For the neural data, corresponding RDMs were generated for each of the 22 channels, capturing pattern dissimilarities in hemodynamic responses across participants. Specifically, the pre-processed HbO signals were fast Fourier-transformed to obtain power spectrum, and the square root of each power spectrum (representing signal fluctuation amplitude) was averaged over the frequency range of 0.01–0.50 Hz (Zhang et al. 2023). These neural features were extracted from the advertising listening phase. For each of the 22 channels, we computed the Euclidean distance between the processed neural data for each pair of participants, where larger distances indicate the more dissimilar temporal dynamics of neural activation between pairs of consumers on the corresponding channel (Lyu et al. 2024). Second, we computed Spearman’s rank correlation between the lower triangular matrix of each neural RDM and the behavioral RDM separately from each age group and condition. Finally, the statistical significance of the correlation was assessed using Mantel tests (Kriegeskorte et al. 2008; Mantel 1967) with 1000 iterations. For each iteration, rows and columns of the neural RDM were randomly shuffled. We then calculated the Spearman’s rank correlation between the shuffled neural RDM and original behavioral RDM. This procedure was repeated 1000 times to generate the null distributions of the correlation coefficients for each channel. The P-value was calculated as the proportion of correlation values in the null distribution that exceeded the empirical r-value (two-tailed, P < .05). The analysis process is shown in Fig. 1f.

Results

Behavioral results

We first assessed the effectiveness of our experimental manipulations. As expected, the salesperson’s poor family background successfully induced increased perceived guilt in both age groups (ps < .01, see Supplementary Text S3 and Figure S2b for details) and stronger negative emotions in the post-test (P < .001, see Supplementary Text S4 and Figure S2c). However, we observed a significant age × sales approach interaction in perceived manipulative intent, with younger adults perceiving stronger manipulative intent in the guilt condition (P < .001), whereas older adults showed no difference between conditions (see Supplementary Text S2 and Figure S2a). Therefore, we included perceived manipulative intent as a covariate in the main analyses to control its effect on consumers’ purchase-related behavioral ratings.

Purchase intention showed an interaction effect of age × sales approach (F(1,54) = 11.78, P < .005, ηp2 = 0.18; Fig. 2a). The subsequent simple effects analysis revealed that younger adults’ purchase intentions were higher in the guilt condition than in the control condition (t(29) = 6.23, P < .001, Cohen’s d = 1.00), whereas there was no significant difference between the two conditions for older adults (t(27) = 1.04, P = .31, Cohen’s d = 0.17). The main effect of age was significant (F(1,54) = 4.42, P = .04, ηp2 = 0.08), with older adults’ purchase intention higher than that of younger adults (t(54) = 2.10, P = .04, Cohen’s d = 0.40). In summary, older adults generally had higher purchase intent, while younger adults were more influenced by guilt appeals.

Figure 2.

Figure 2.

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Purchase intention and its relationship with advertising credibility and trustworthiness of the salesperson by age groups. (a) Difference in purchase intention between guilt and control conditions in younger and older adults. (b) The correlation between purchase intention and advertising credibility by age group. (c) The correlation between purchase intention and trustworthiness of the salesperson by age group.

Note. Perceived manipulative intent was controlled as a covariate; YA = younger adults, OA = older adults. ***P < .001; ns, not significant.

For advertising credibility and the trustworthiness of the salesperson, only significant age effect was found (advertising credibility: F(1,54) = 38.06, P < .001, ηp2 = 0.41; trustworthiness of the salesperson: F(1,54) = 21.87, P < .001, ηp2 = 0.29), with older adults exhibited higher advertising credibility (t(54) = 6.18, P < .001, Cohen’s d = 1.18) and trustworthiness of the salesperson (t(54) = 4.67, P < .001, Cohen’s d = 0.90) than younger adults. In addition, a significant positive correlation was found between purchase intention and advertising credibility for both younger (r = 0.53, P < .001) and older adults (r = 0.54, P < .001; Fig. 2b), as well as the correlation between purchase intention and trustworthiness of the salesperson for both younger (r = 0.38, P = .003) and older adults (r = 0.60, P < .001; Fig. 2c).

Intra-brain functional connectivity in consumers

Consumers’ FC during the sales process was calculated across brain regions of the PFC, and repeated-measures ANOVAs by age and sales approach were conducted (Fig. 3a). The results showed significant interaction effects of age × sales approach in intra-brain FC between CH9 and CH20 (Broca’s area–frontopolar; F(1,56) = 7.19, P = .01, ηp2 = 0.11), CH6 and CH15 (DLPFC–frontopolar; F(1,56) = 6.95, P = .01, ηp2 = 0.11), CH15 and CH18 (frontopolar–DLPFC; F(1,56) = 5.09, P = .03, ηp2 = 0.08), and CH14 and CH19 (DLPFC–frontopolar; F(1,56) = 4.31, P = .04, ηp2 = 0.07). Simple effects analysis revealed significantly stronger intra-brain FC in younger adults in the guilt condition compared to the control condition for both CH9–CH20 (t(29) = 2.14, P = .04, Cohen’s d = 0.43) and CH6–CH15 (t(29) = 2.92, P = .007, Cohen’s d = 0.33; Fig. 3b and c), whereas no significant differences were found for older adults. Simple effects analysis in CH15–CH18 and CH14–CH19 showed no significant difference between sales conditions for both younger and older adults (ps > .05). In addition, we found significant main effects of sales approach between CH1 and CH9, CH1 and CH18, CH9 and CH10, with stronger FC in the guilt condition than in the control (all ps < .05). Significant main effects of age were also found between CH8 and CH15, CH8 and CH19, CH8 and CH20, CH1 and CH16, CH5 and CH16, and CH21 and CH14, with younger adults showing stronger FC (all ps < .05; see Supplementary Table S4 for the specific statistics values).

Figure 3.

Figure 3.

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Intra-brain FC by age groups and sales approach. (a) Statistical F-value maps of the main effects of age and sales approach, and their interaction effects. Channels with significant effects (P < .05) are colored and the rest are gray. (b) FC difference of younger and older adults between CH9 (Broca’s area) and CH20 (frontopolar), and (c) CH6 (DLPFC) and CH15 (frontopolar) in the guilt and control conditions.

Note. *P < .05; **P < .01; ns, not significant. YA = younger adults, OA = older adults.

Inter-brain synchrony of salesperson–consumer dyads

Significant interaction effects of age × sales approach in IBS were found between CH5 and CH6 (Broca’s area–DLPFC; F(1,56) = 5.35, P = .02, ηp2 = 0.09; Fig. 4a) and between CH5 and CH15 (Broca’s area–frontopolar; F(1,56) = 5.59, P = .02, ηp2 = 0.09; Fig. 4b). The simple effect analysis in CH5–CH6 revealed that salesperson–younger consumer dyads had significantly higher IBS in the guilt condition than in the control (t(29) = 2.28, P = .03, Cohen’s d = 0.53), whereas salesperson–older consumer dyads had no difference between the two (t(27) = −1.14, P = .26, Cohen’s d = 0.33). As for IBS between CH5 and CH15, we found the same pattern.

Figure 4.

Figure 4.

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IBS in salesperson-consumer by age groups and sales approach. (a) IBS difference in CH5–CH6 (Broca’s area–DLPFC) by age and sales approach. (b) IBS in CH5–CH15 (Broca’s area–frontopolar) by age and sales approach.

Note. *P < .05, **P < .01; ns, not significant. YA = younger adults, OA = older adults.

Moreover, we found significant main effects of sales approach between CH3 and CH10 (F(1,56) = 4.41, P = .04, ηp2 = 0.07), CH5 and CH3 (F(1,56) = 4.88, P = .03, ηp2 = 0.80), with higher IBS value in the guilt condition than in the control (ps < .05). Significant main effects of age were also found between CH3 and CH10 (F(1,56) = 5.67, P = .02, ηp2 = 0.09), CH9 and CH15 (F(1,56) = 7.90, P = .01, ηp2 = 0.12), with higher IBS in salesperson–younger consumer dyad than in salesperson–older consumer dyad (ps < .05).

Representational similarity between brain and behavior

IS-RSA revealed the relationship between behavioral and neural RDMs (Fig. 5a–d). For younger consumers, we found that in the frontopolar area (CH11, CH12, CH15, CH20, and CH22), their neural RDMs were significantly correlated with advertising credibility RDM in both guilt and control conditions (ps < .05; see Supplementary Figure S3 for the visualized Mantel test results and values of the statistics). However, no significant correlation was found with the trustworthiness of the salesperson RDM (all ps > .05). This suggests that when younger adults had similar judgments about the credibility of advertising, but not the trustworthiness of the salesperson, their brain activation patterns were also more convergent.

Figure 5.

Figure 5.

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The results of neural-behavioral IS-RSA by age groups and sales approach. (a–d) The IS-RSAs are shown by age and sales approach. (a) Younger adults’ CH12 neural dissimilarity matrix (bottom left) and advertising credibility dissimilarity matrix (top right) in the guilt condition. (b) Younger adults’ CH12 neural dissimilarity matrix (bottom left) and advertising credibility dissimilarity matrix (top right) in the control condition. (c) Older adults’ CH12 neural dissimilarity matrix (bottom left) and trustworthiness of the salesperson dissimilarity matrix (top right) in the guilt condition. (d) Older adults’ CH12 neural dissimilarity matrix (bottom left) and trustworthiness of the salesperson dissimilarity matrix (top right) in the control condition. (e) The Mantel test results of IS-RSA between trustworthiness of the salesperson and neural RDM of CH12. The violin shape indicates null distribution. The black horizontal bars indicate the two-sided, 5% positions. The red horizontal bars indicate the true r-value between the matrices. (f) The Mantel test results of IS-RSA between advertising credibility and neural RDM of CH12.

Note. *P < .05, **P < .01, ***P < .001. YA = younger adults, OA = older adults.

For older consumers, however, in the frontopolar area (CH12, CH16, and CH21), their neural dissimilarity matrices were significantly correlated with trustworthiness of the salesperson RDM in both guilt and control conditions (ps < .01), but only correlated with advertising credibility RDM in the control condition (ps < .05). See Supplementary Figure S4 for the visualized Mantel test results and statistical values. The results indicated that when older adults perceived similar levels of trust in salespeople, their brain activation patterns were also more aligned.

Together, IS-RSA analyses showed that during the sales process, frontopolar activity consistency in young consumers is associated with consistency in advertising credibility ratings, whereas in older consumers it was more related to consistency in trustworthiness ratings of the salesperson. The age-related difference IS-RSA pattern was presented in Fig. 5e and f using CH12 as an example, see Supplementary Figs S3 and S4 for all remaining CHs.

Additionally, we conducted IS-RSA analysis to examine correlations between neural activity and purchase intentions. This analysis revealed significant correlations in the frontopolar (Brodmann’s Area 10) in both age groups, suggesting the critical role of this region in purchase decisions (see Supplementary Figs S5 and S6 for the results).

Discussion

The present study investigated adults’ age differences in purchase decisions and underlying neural mechanisms in face-to-face false advertising and the role of guilt appeal as a marketing tactic. Using fNIRS-based hyperscanning, we simultaneously recorded neural activity from consumer–salesperson dyads and analyzed consumers’ intra-brain FC and consumer–salespersons’ inter-brain synchronization. As expected, we observed that older adults showed significantly higher purchase intentions in the context of false advertising compared to younger adults. However, guilt appeal increased purchase intentions in younger adults but not in older adults. Our neural findings aligned with the behavioral patterns. Specifically, younger consumers showed significantly increased intra-brain FC in Broca’s area–frontopolar and DLPFC–frontopolar in the guilt condition compared to the control, whereas no condition difference was observed in older adults. Similarly, inter-brain synchronization of the salesperson–younger consumer dyad was significantly higher in the guilt condition than in the control condition, whereas no difference was found for the salesperson–older consumer dyad. Furthermore, using IS-RSA, we investigated the neuropsychological mechanism underlying deceptive sales processing and found that neural activity during the sales process was correlated with the advertising credibility in younger adults, whereas it was correlated with the trustworthiness of the salesperson in older adults.

Older adults are more susceptible to false advertising

Consistent with previous empirical findings that older adults are more vulnerable to consumer fraud (James et al. 2014), older adults in the present study had higher purchase intentions for falsely advertised products across sales approaches. These findings suggest older adults are more inclined to accept deceptive claims in face-to-face sales scenarios, potentially due to their positive bias in information processing (Castle et al. 2012). This bias may be particularly influential when false advertisements use positive phrasing to emphasize or exaggerate product efficacy (e.g. “It can provide 100% of the body’s daily vitamin needs, boost immunity”), which may also contribute to the observed age-related differences in susceptibility.

From a neurological perspective, older adults show reduced within-network FC in the PFC during deceptive sales compared to younger adults. Previous studies have identified that older adults had weaker intrinsic connectivity during cognitive tasks (Grady et al. 2010, Hughes et al. 2019), because aging may disproportionately affect FC in specific task state, disrupting the interactions between brain networks in a cognitively detrimental manner (Hughes et al. 2020). Such changes may be related to the reduced efficiency of regional and global brain connectivity with age, which increases the cost of information transfer (Meunier et al. 2009). Notably, frontal lobe recruitment is less distinctive across cognitive tasks in older adults compared to younger adults (Goh 2011). The decreased distinctiveness might be due to less efficient organization of the brain’s baseline functional architecture in responding to task demands. This might explain the lack of FC differences between sales conditions in older adults and points to age-related impairments in specialized neural functions supporting verbal working memory and executive control (Caspers et al. 2014, Jockwitz et al. 2017)—processes crucial for advertising information processing and rational decision-making.

Guilt appeal influences younger but not older adults

Guilt, as an adaptive emotion, could influence behavior by generating emotional discomfort that prompts individuals to engage in reparative actions to alleviate the negative feelings (Chang 2014). Although the salesperson’s poor family background effectively induced guilt in both age groups, only younger adults showed increased purchase intentions in the guilt condition. The guilt regulation process may be at the expense of the evaluation process (Ariely et al. 2009), leading younger adults more susceptible to false advertising under guilt. For older adults, guilt appeal did not influence their subsequent purchasing decisions, which may be because older adults are more effective at regulating negative emotions than younger adults (Kryla-Lighthall and Mather 2009). Supporting this age-related difference in emotional processing, a previous study found negative emotional content in television advertisements influenced younger adults’ attitudes but not older adults’ responses (Droulers et al. 2015).

Consistent with the behavioral findings, our intra-brain analyses of consumers revealed significant age × sales approach interactions in FC between subregions within the PFC. Specifically, younger adults showed increased FC in guilt conditions, while older adults did not. FC refers to the coordinated activity between different brain regions, which reflects their functional coordination during cognitive tasks (Fingelkurts et al. 2005). In younger consumers, guilt appeal significantly increased FC between the Broca’s area (CH9)–frontopolar (CH20), and the DLPFC (CH6)–frontopolar (CH15). Previous studies suggest that the DLPFC modulates value computations during decision-making (Camus et al. 2008, Panidi et al. 2022), the frontopolar cortex facilitates complex decision-making by integrating multiple variables and monitors subgoals (Laureiro-Martínez et al. 2014, Law et al. 2023), and Broca’s area supports language processing (Novick et al. 2010). The increased FC may indicate enhanced integration of emotional, cognitive, and linguistic processes during sales interactions under guilt appeals. Although our sales pitch itself does not contain guilt-inducing content, the guilt arising from learning about the salesperson’s poor family background influenced how younger consumers process subsequent product information and neural activity. In contrast, older consumers did not show significant differences in FC between the guilt and control conditions, which aligns with their unchanged purchase intentions across conditions. One possible explanation is that older adults tend to ignore or downregulate negative emotions more effectively than younger adults (Mather, 2012). This age-related difference in emotion regulation could explain why guilt, as a negative emotional appeal, fails to influence their behavior and prefrontal FC patterns and purchase intentions, despite their overall higher susceptibility to false advertising.

Further supporting this age-related difference, our IBS analysis revealed that, in younger consumer–salesperson dyads, IBS was influenced by the sales approach, with higher IBS in the guilt condition than in the control condition, whereas no significant condition differences were found in older adults. Increased synchronization was particularly observed between the younger consumer’s Broca’s area (CH5) and the salesperson’s frontopolar (CH15) and DLPFC (CH6). Brain synchronization is commonly referred to as a set of transfer properties of brain-to-speech synchronization shared by both the narrator and the listener (Pérez et al. 2017). Broca’s area is particularly involved in language comprehension, especially in interpreting emotional context (Fadiga et al. 2009). Therefore, the higher IBS may reflect the younger consumers’ higher engagement with the salesperson’s narrative under guilt appeal, even though the sales pitch did not contain emotional content. From the salesperson’s perspective, deceptive selling involves both the inhibition of truth-telling tendencies and theory of mind (ToM) processes (Sip et al. 2008). The inhibitory control required for suppressing truth-telling is associated with the lateral PFC, particularly the frontopolar area (Abe et al. 2006, 2007, Sip et al. 2008, Ganis et al. 2009). In addition, ToM has been shown to engage multiple frontal regions, including both medial and lateral PFC (Kobayashi et al. 2007, Carrington and Bailey 2009). These findings align with our observation of increased activity in the frontopolar area (CH15) and DLPFC (CH6) in salespersons during deceptive sales interactions. Guilt has been considered an effective persuasive technique (O’Keefe 2000, Peng et al. 2023). Persuasive messages are thought to resonate with the target audience, promoting synchronization of brain activation and enhancing neural coupling (Dmochowski et al. 2014). During successful persuasion, significant increases in neural synchronization between persuaders and persuadees have been observed, which can predict persuasion outcomes (Li et al. 2023).

Different neural psychological mechanism in younger and older adults

The result of the channel-wise IS-RSAs suggests age-related differences in information processing preferences in consumption: younger adults prioritize the credibility of advertising, while older adults focus more on social trust, particularly the trustworthiness of the salesperson. This is consistent with previous research suggesting that older adults make suboptimal purchase decisions due to excessive trust in salespeople (Titus and Gover 2001), and are more likely to perceive trustees as more trustworthy and thus invest their money in trustees more than younger participants (Bailey et al. 2015). The frontopolar has been implicated in the decomposition, extraction, and integration of relevant information for decision-making (Law et al. 2023). Our results provide insight into the question of which psychological indicators are reflected in the brain signals of different ages during face-to-face deceptive sales. The results are concentrated in the frontopolar region, consistent with previous findings that purchase decisions are positively correlated with frontopolar activation, and that frontopolar neural activation can decode the buy or pass decisions with 85% accuracy (Çakir et al. 2018).

Our findings have important practical implications for protecting vulnerable populations from deceptive advertising. For older adults, fraud prevention programs should emphasize critically evaluating advertising claims rather than relying on the perceived trustworthiness of salespeople. For younger adults, interventions should focus on recognizing emotional manipulation through guilt appeals. Both older and younger adults would benefit from learning financial literacy and staying informed about evolving fraudulent schemes. These age-specific approaches are necessary, as our neural findings show different processing mechanisms between age groups when encountering deceptive sales practices.

Limitation

While our findings provide new insights into age differences in the neuropsychological mechanisms underlying deception by false advertising in the face-to-face sales scenario, several limitations of this study must be noted. First, the laboratory setting may reduce people’s vigilance to deceptive information (Plebani et al. 2021), limiting the generalizability of the findings to real-world sales. Future research could use portable fNIRS devices in real-world settings (e.g. shopping malls) to further enhance ecological validity. Second, due to the limited number of channels, brain regions such as the right temporo-parietal junction, which is implicated in reasoning and understanding others’ mental states (Saxe and Wexler 2005), were not captured. Future studies could expand the montage coverage to broader brain regions to gain a more comprehensive understanding of the neural mechanisms underlying deceptive sales in false advertising.

Conclusion

Going beyond existing studies, we used fNIRS hyperscanning to detect and examine purchase decisions and cortical responses of younger and older adults during real-time face-to-face deceptive sales. Older adults were more likely to purchase products promoted by false advertising, whereas younger adults were influenced by guilt appeals but not older adults. Younger and older adults exhibit heterogeneity in the neuropsychological mechanisms underlying the process of deceptive sales, with younger adults relying more on the advertising credibility and older adults relying more on the trustworthiness of the salesperson. These findings may contribute to targeted consumer fraud prevention for younger and older adults, respectively.

Supplementary Material

nsaf044_Supp
nsaf044_supp.zip (2.1MB, zip)

Contributor Information

Ying-Chen Liu, Faculty of Psychology, Southwest University, Chongqing 400715, China.

Zi-Han Xu, Faculty of Psychology, Southwest University, Chongqing 400715, China.

Zhi-Jun Zhan, Faculty of Psychology, Southwest University, Chongqing 400715, China.

Zi-Wei Liang, Faculty of Psychology, Southwest University, Chongqing 400715, China.

Xue-Rui Peng, Faculty of Psycholog, Technische Universität Dresden, Dresden 01062, Germany; Centre for Tactile Internet with Human-in-the-Loop, Technische Universität Dresden, Dresden 01062, Germany; International Max Planck Research School on Cognitive NeuroImaging (IMPRS CoNI), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany.

Jing Yu, Faculty of Psychology, Southwest University, Chongqing 400715, China.

Supplementary data

Supplementary data is available at SCAN online.

Conflict of interest:

None declared.

Funding

This work was supported by the National Natural Science Foundation of China (32371109 and 71942004).

Data availability and pre-registration

All the processed data and analysis scripts are available at https://osf.io/tk32p/ and pre-registered with AsPredicted at https://aspredicted.org/5qk3-nqnb.pdf.

Ethics approval

All participants provided written informed consent prior to the experiment, and the experimental procedures were approved by the Ethics Committee of Southwest University to be in accordance with the Declaration of Helsinki (No. H23146).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

nsaf044_Supp
nsaf044_supp.zip (2.1MB, zip)

Data Availability Statement

All the processed data and analysis scripts are available at https://osf.io/tk32p/ and pre-registered with AsPredicted at https://aspredicted.org/5qk3-nqnb.pdf.

Articles from Social Cognitive and Affective Neuroscience are provided here courtesy of Oxford University Press

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