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How Does the Implicit Awareness of Consumers Influence the Effectiveness of Public Service Announcements? A Functional Near-Infrared Spectroscopy Study


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A large number of scholars have conducted detailed studies on the effectiveness of commercial advertising by using neuroimaging methods, but only a few scholars have used this method to study the effectiveness of public service announcements (PSAs). To research the relationship between the effectiveness of PSAs and the audience’s implicit awareness, functional near-infrared spectroscopy (fNIRS) was employed to record the neural activity data of participants in this study. The results showed that there was a correlation between activation of dorsolateral prefrontal cortex (dlPFC) and the effectiveness of PSAs; The activation of the dlPFC could also be used as an indicator to represent the appeal of advertising content. The results means that neuroimaging tool can also be used to investigate the effectiveness of PSAs, not just commercial advertisements and a few PSAs study, and that neural activity can predict and improve the effectiveness of PSAs before they are released.
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Frontiers in Psychology | 1 March 2022 | Volume 13 | Article 825768
published: 14 March 2022
doi: 10.3389/fpsyg.2022.825768
Edited by:
Wuke Zhang,
Ningbo University, China
Reviewed by:
M. Raheel Bhutta,
Sejong University, South Korea
Dan-Cristian Dabija,
University, Romania
Arianna Trettel,
BrainSigns, Italy
Jialin Fu
Specialty section:
This article was submitted to
Decision Neuroscience,
a section of the journal
Frontiers in Psychology
Received: 30 November 2021
Accepted: 10 February 2022
Published: 14 March 2022
Fu J, Li X, Zhao X, Zhang K and
Cui N (2022) How Does the Implicit
Awareness of Consumers Inuence
the Effectiveness of Public Service
Announcements? A Functional Near-
Infrared Spectroscopy Study.
Front. Psychol. 13:825768.
doi: 10.3389/fpsyg.2022.825768
How Does the Implicit Awareness of
Consumers Inuence the
Effectiveness of Public Service
Announcements? A Functional
Near-Infrared Spectroscopy Study
*, XihangLi
1, XiZhao
1, KeyiZhang
1 and NanCui
1 College of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, China, 2 Economics and
Management School, Wuhan University, Wuhan, China
A large number of scholars have conducted detailed studies on the effectiveness of
commercial advertising by using neuroimaging methods, but only a few scholars have
used this method to study the effectiveness of public service announcements (PSAs). To
research the relationship between the effectiveness of PSAs and the audience’s implicit
awareness, functional near-infrared spectroscopy (fNIRS) was employed to record the
neural activity data of participants in this study. The results showed that there was a
correlation between activation of dorsolateral prefrontal cortex (dlPFC) and the effectiveness
of PSAs; The activation of the dlPFC could also beused as an indicator to represent the
appeal of advertising content. The results means that neuroimaging tool can also beused
to investigate the effectiveness of PSAs, not just commercial advertisements and a few
PSAs study, and that neural activity can predict and improve the effectiveness of PSAs
before they are released.
Keywords: neuromarketing, functional near-infrared spectroscopy (fNIRS), PSAs, dorsolateral prefrontal cortex
(dlPFC), implicit awareness, purchase decision
Advertising eectiveness is one of the most important indicators for advertisers. For all advertising
campaigns, consumers are the recipients of advertising, and the eectiveness of advertising is
ultimately reected by the behavior of consumers (Ramsoy, 2019). To obtain better advertising
outcomes, enterprises design dierent advertisements to promote new products and hire celebrities
to endorse their products at great cost (Clark et al., 2018). Some companies have established
a good brand image and gained good revenue through these methods, but there are also
some companies that have not met their expectations (Huang et al., 2018). In addition to
commercial advertisements, public service announcements (PSAs) focus on advertising eectiveness.
e existing studies of the eectiveness of PSAs are mostly focused on acquired immunodeciency
syndrome (AIDS) prevention (David and Cindy, 1996; Wang and Arpan, 2008), smoking
cessation (Shen, 2010; Wang et al., 2013), drug rehabilitation (Fishbein et al., 2002), trac
safety (Santa and Cochran, 2008), etc. All of these studies evaluate the eectiveness of PSAs
by understanding peoples views on PSAs through interviews, questionnaires, and other forms
Frontiers in Psychology | 2 March 2022 | Volume 13 | Article 825768
Fu et al. Improving PSAs Effectiveness With fNIRS
of self-report. However, self-repots sometimes do not reect
what people really think (Dmochowski etal., 2014). Evaluating
the eectiveness of PSAs solely on self-reports may lead to
wrong conclusion, which will greatly reduce the eectiveness
of them.
e emergence of neuromarketing oers a new approach
to the study of advertising eectiveness. Telpaz et al. (2015)
believe that people are oen reluctant to express themselves
or unable to express themselves correctly, but their neural
activity, heart rate, and other implicit awareness indicate what
they are truly thinking. Neuromarketing, unlike traditional
marketing approaches, employs neuroimaging tools to record
consumers’ neural responses to products, brands, and
advertisements and can be used to analyze neural data to
explain and predict consumers’ decisions (Lim, 2018; Hakim
and Levy, 2019). Several scholars have proved that neural
activity can provide higher prediction accuracy than self-report
(Dmochowski et al., 2014; Boksem and Smidts, 2015;
Telpaz etal., 2015; Barnett and Cerf, 2017; Chan etal., 2019).
Some researchers have introduced neuroimaging tools into
the study of PSAs. ey have studied the predictability of
advertising eect in PSAs (Falk et al., 2012), the relationship
among advertising eect, content, and neural activity (Wan g
et al., 2013), and the indicators that distinguish eective PSAs
from ineective PSAs by neural activity (Cartocci etal., 2018).
However, despite the abundance of previous studies, three
problems remain. First, most of the previous studies were
posterior and did not reveal indicators that could improve
eectiveness of PSAs; Second, almost all of previous studies
using neuroimaging tools were on anti-smoking PSAs, and
the applicability of the ndings to other types of PSAs remains
to be tested; ird, functional MRI (fMRI), the neuroimaging
machine used in the previous studies, is extremely expensive
and large, making it dicult to scale up widely.
erefore, in this study, functional near-infrared spectroscopy
(fNIRS), a new, cheaper and more portable neuroimaging tool,
was used to measure participants’ neural activity while viewing
PSAs, with the goal of nding indicators that could improve
the eectiveness of PSAs. An experiment on agricultural PSAs
was conducted to nd indicators of neural activity that would
improve the eectiveness of PSAs. In this paper, the progress
of related studies is summarized and hypotheses are presented
in the Literature Review. en the experimental design and
data processing are described in the Method. e results of
data analysis are shown in the Results. en aer that, the
ndings are discussed and compared with literature in the
Discussion. Finally, in the Conclusion, conclusions are stated
and possible topic selections for future research are suggested.
Advertising eect has received much attention in neuromarketing,
and numerous studies have investigated the relationship between
neural activity and advertising eect. Previous studies have
shown that neural activity is a better predictor of advertising
eect than self-report. By analyzing neural activity of the ventral
striatum, Berns and Moore (2012) found that the activation
within the ventral striatum was correlated with the sales of
music albums, while self-report was not. Not limited to music
albums, the advertising eect of printer poster can also
be accurately predicted. In analyzing the neural activity of
participants’ viewing advertising poster for chocolate bars at
dierent times, Kühn et al. (2016) assigned dierent weight
to dierent brain region and successfully predicted the sale
ranking of chocolate bars at dierent times, which was not
possible for self-report.
Within the eld of PSAs, several studies have focused on
investigating the relationship between anti-smoking PSAs
eectiveness and neural activity. One study found that neural
activity was also a much better predictor of PSAs than self-
report. Falk et al. (2012) found that medial prefrontal cortical
neural activity, while participants viewed anti-smoking PSAs
was associated with the number of calls to an anti-smoking
hotline. Previous studies have found that the content and format
inuence the eectiveness of PSAs (Dillard and Peck, 2000;
Santa and Cochran, 2008). Several scholars have studied how
content and format aect the eectiveness of PSAs through
neuroimaging tools. By comparing participants’ neural activity
and behavior aer viewing anti-smoking PSAs, Wang et al.
(2013) found that neural activity evoked by PSAs with dierent
content diered signicantly in the inferior frontal gyrus, the
precuneus and the dorsomedial prefrontal cortex (dmPFC),
and that neural activity in dmPFC could predict the urine
cotinine levels 1 month later, which reected participants’ smoking
intensity. rough measurement and analysis of multiple
instruments, Cartocci et al. (2018) found that eective ads
focused on visual elements while ineective ads focused on text.
Interestingly, the prefrontal cortex (PFC) has been frequently
mentioned in studies of PSAs eect. Functionally, the PFC
can bedivided into three parts, the orbitofrontal cortex (OFC),
ventral prefrontal cortex (vPFC), and the dorsal prefrontal
cortex (dPFC; Parnamets et al., 2020). e OFC is the brain
region associated with value assessment, the vPFC is the brain
region associated with emotions, and the dPFC is the brain
region associated with working memory and rational thinking
(Plassmann et al., 2015; Karmarkar and Plassmann, 2019).
Notably, the PFC is also the main area of interest for scholars
who have used fNIRS for advertising eect. Most of the existing
studies of advertising eects via fNIRS chose the dorsolateral
prefrontal cortex (dlPFC) as the observed brain region. Some
scholars have veried the reliability of fNIRS in advertising
eect research by repeating previous fMRI experiments (Krampe
et al., 2018; Gier etal., 2020; Meyerding and Mehlhose, 2020).
Gier et al. (2020) repeated Kühn et al. (2016) study on the
advertising eect of chocolate bars by measuring the neural
activity of dlPFC, and obtained a high accuracy. Some scholars
have also used fNIRS to measure neural activity in the dlPFC
to reveal a variety of factors that inuence the eectiveness
of advertising, such as gender dierences (Duan etal., 2021),
preference dierences (Qing et al., 2021), etc. However, fNIRS
also has disadvantages. Limited by the penetrating ability of
NIR light, fNIRS cannot measure neural activity in deep brain
regions, such as the ventral medial prefrontal cortex.
Fu et al. Improving PSAs Effectiveness With fNIRS
Frontiers in Psychology | 3 March 2022 | Volume 13 | Article 825768
erefore, in this study, the dlPFC was selected as the target
observation region to collect neural activity of participants
while viewing PSAs. e following hypothesis has been proposed
that the dlPFC activity can predict the eectiveness of PSAs
and help improve the advertising eect.
Fourteen males and 16 females participated in this experiment
(age M = 24.47, years, SD = 1.69). All participants attended
Zhengzhou Light Industry University, were right-handed, had
normal or corrected-to-normal vision, no brain injury, no
history of psychiatric disorders, no recent use of tranquilizers,
and no previous participation in neuroscience experiments.
e experiment was approved by the ethics committee of
the university.
e year 2021 is the rst year that China has declared that
everyone is free from poverty, and almost all Chinese people
have focused on the cause of poverty eradication. China Central
Television (CCTV) has released many PSAs to help poor regions
promote their special products and industries during the ght
against poverty. Since all Chinese people are aware of the
project of ghting poverty, wechose PSAs related to this project
as experimental materials. e PSAs released by CCTV contain
three themes: tourism, represented by landscapes, agricultural
products, represented by fruits, vegetables and meat, and
traditional handicras. Considering that the participants were
university students, fruit and milk ads were chosen as the
stimulus material for this experiment in order to be more
relevant to reality. Ten dierent ads were selected from the
agricultural PSAs released by CCTV from January 2020 to
December 20201, as shown in Tab le 1 .
Task Design
In this experiment, participants were told that purchasing the
products in PSAs was considered as a willingness to support
the anti-poverty project, and participants’ willingness to purchase
Experimental material source website:
the products in the PSAs was considered as an indicator of
advertising eect. To determine what factors can enhance
advertising eect, a control group containing price was added
into the experiment, which was designed whether people would
actually behave as expected in PSAs when they are in their
lives. Aer the experiment, participants in the experiment
group and control group were randomly invited to participate
in a telephone interview, with the aim of nding the reason
for the dierence in the result between two groups.
e group that did not include price was named group A
and the group that included price was named group B. Before
the experiment began, participants were randomly assigned to
group A and group B. Participants in group A were told that
they did not need to take price into account, and they could
make decisions based on their own preferences. In contrast,
participants in group B were told that the product price would
be displayed during the decision phase and that they should
make a decision choice based on their real needs.
e experiment consists of two parts, the rst part collected
neural data when participants were resting and the second
part collected neural data when participants were watching
the advertisement. In the rst part, a landscape picture that
lasted 60 s would appear on the screen, and participants simply
watched the picture without any reaction. Aer the picture
disappeared, the participants rested for 30 s and then entered
the second part. e second part consisted of 10 trials, each
of which containing an advertising video and a decision-making
session. e ads lasted 60 s, and the decision-making session
had no time limit until the participants made a choice. In
decision-making session, only product pictures in the ads
appeared in group A while product pictures and prices appeared
in group B. ere was a 30-s break at the end of the decision-
making session, and the experimental ow is shown in Figure1.
Data Acquisition and Processing
e portable fNIRS used in the experiments was Artinis Brite
24 (10 transmitters and eight receivers), which emits NIR light
at 762 and 841 nm and has a sampling rate of 10 Hz. Transmitter
and receiver were separated from each other by a distance of
3 cm in order to guarantee signal quality. ey were placed
with reference to the 10–20 standard EEG positions, centered
on F3 and F4 and symmetrically distributed along the central
sulcus, as shown in Figure2. E-Prime 3.0 was used to present
the experimental stimuli, and Oxyso (v3.2.72) was used as
data collection soware.
NIRS_KIT (Hou et al., 2021) was used to process the raw
data and analysis. e pre-processing of the raw data went
through the following steps: rst detrending of the raw data,
then Motion correction of the data by TDDR method, and
nally band-pass ltering of the data by IIR method at 0.01–0.1 Hz.
e preprocessed data were entered into the data analysis phase,
and as oxyhemoglobin (HbO) correlates more with cerebral
blood ow than deoxyhemoglobin (Hb; Strangman etal., 2002),
only HbO was focused on in the next analysis.
For every participant, a general linear model (GLM) was
set up to model neural activity during the experimental task.
e model contained 11 parameters, respectively, “rest” and
TABLE1 | Task materials.
Number Agricultural products Origin
v1 Carambola Fujian
v2 Red date Xinjiang
v3 Red kiwi Jiangxi
v4 Apple Sichuan
v5 Navel orange Chongqing
v6 Pomelo Fujian
v7 Passion fruit Fujian
v8 Milk Gansu
v9 Pitaya Guangxi
v10 Roxburgh rose Guizhou
Fu et al. Improving PSAs Effectiveness With fNIRS
Frontiers in Psychology | 4 March 2022 | Volume 13 | Article 825768
FIGURE1 | The top half of the picture “rest” is the rst part of the experiment, where participants view the picture for 60 s and then rest for 30 s before moving on
to the second part. The bottom half of the picture, “task,” shows the process of each trial in the second part, including an ad and a decision-making session.
FIGURE2 | The locations of the transmitters and receivers are shown in (A), with the yellow dot being the transmitter and the blue dot being the receiver. The
distribution of each channel is shown in (B), with channels 1–12 distributed in the right hemisphere and channels 13–24in the left hemisphere. Channels 4, 6, 7,
and 9 were selected as analysis channels for the right hemisphere, and channels 16, 18, 19, and 21 were selected as analysis channels for the left hemisphere.
Fu et al. Improving PSAs Effectiveness With fNIRS
Frontiers in Psychology | 5 March 2022 | Volume 13 | Article 825768
v1–v10. Next, for each participants neural data, v1–v10 was
compared with “rest” to calculate the beta value, which was
named condition 1–condition 10, respectively. Finally, in order
to investigate the dlPFC activation induced by ads at the group
level, one-sample t-test was performed for all participants’ beta
values in condition 1–condition 10. Bonferroni correction was
used to correct the t-test results. e ranking method of
activation results refers to Kühn et al. (2016) and Gier et al.
(2020). Channel 4, 6, 7, 9, 16, 18, 19, and 21 were selected
as the comparison channels, and the highest value of
corresponding t-value of the channels was selected as the
ranking basis.
Behavioral Results
e decision-making session result data for each group was
extracted from E-Prime 3 keylog (M = 9.30, SD = 5.17 for group
A and M = 7.8, SD = 4.13 for group B), the results of which
are shown in Figure3. e various purchases of each product
were ranked according to their purchase volume and ranked
as follows: group A was v2, v10, v1, v9, v7, v6, v5, v8, v3,
and v4; group B was v2, v9, v7, v6, v10, v5, v8, v3, v1, and
v4. Independent samples t-test conducted with SPSS 20 was
used to measure the dierence between the groups. ere
was no signicant dierence in purchase volume between
the two groups [t(18) = 0.253, p > 0.05], but there was a large
dierence in purchase volume between the two groups for
v1 and v10.
fNIRS Results
e peak t-values in the selected channels were used as the
basis for ranking the degree of dlPFC activation, as shown in
Table 2 . e t-contrast activity map of each ad was sorted
according to the peak value of the selected channel, as shown
in Figure 4.
It is worth noting that while most of the ads in the behavioral
and fNIRS results are largely consistent in rankings, there are
still some dierences. v1 and v10 ranked 3rd and 2nd in the
behavioral results of Group A, but 8th and 3rd in the fNIRS
results. While v1 and v10 ranked 9th and 5th in the behavioral
results of Group B, and 10th and 7th in the fNIRS results,
the rankings of the two results are closer. To nd the reason
for this phenomenon, 10 participants were randomly selected
to be interviewed.
Interview Results
Compiling the interview transcripts revealed that almost all
interviewees felt they were not familiar with the fruits introduced
by v1 and v10. e origin of the carambola introduced in v1
and the roxburgh rose introduced in v10 are both very distant
from the location of this experiment, and both fruits are very
rare in the experimental location.
Interviewees felt they were more concerned about the taste
of the fruits than the environment in which they were grown.
In the ads, v10 introduced more about the taste of roxburgh
rose, the way to consume and the deep processing products,
while v1 focused more on the growing environment and the
appearance of carambola. Moreover, because group A did not
need to consider price when making decisions, almost all
FIGURE3 | Purchase data for each group.
Fu et al. Improving PSAs Effectiveness With fNIRS
Frontiers in Psychology | 6 March 2022 | Volume 13 | Article 825768
participants chose to try unfamiliar products; in contrast, group
B needed to consider price when making decisions, so most
participants made choices based on their preferences. us,
the situation emerged that v1 and v10 diered in the ranking
of behavioral and neural outcomes in group A, while they
were more similar in group B.
e purpose of this study was to investigate whether consumers’
implicit awareness can predict the eectiveness of PSAs and
help improve the eectiveness of PSAs. According to results,
the neural activity collected by portable fNIRS accurately predicts
the participants’ decision-making behavior aer they viewed
the PSAs. At the group level, the higher the participants’ dlPFC
activation, the greater their purchase volume. is implies that
activation of the dlPFC predicts the advertising eect of PSAs.
is nding is consistent with the results of previous fMRI
studies (Falk etal., 2012) and fNIRS studies (Gier etal., 2020).
is means that the neuroimaging tool is not limited to anti-
smoking PSAs, but can also beapplied to other types of PSAs.
Activation of the dlPFC means that neural activity was
signicantly higher when participants viewed the PSAs compared
to when they did not, implying that the PSAs had a signicant
eect on participants’ decision-making processes. e dlPFC
is the brain area associated with working memory, value
assessment, willingness to pay, and decision-making (Karmarkar
and Plassmann, 2019). Previous research has suggested that
the more attractive the stimulus is to the participant, the higher
the activation of dlPFC in their decision-making process
(Meyerding and Mehlhose, 2020). In the present study, higher
activation in the dlPFC meant that the PSAs had a greater
impact on the participants and the ads were more eective.
erefore, we believe that the neural activity of dlPFC can
predict the eectiveness of PSAs.
e products involved in v1 and v10 showed dierences
in the behavioral results of participants in group A and group
B. is can be interpreted as viewers agreeing with the PSAs
in their thoughts but not acting on them, consistent with the
phenomenon mentioned by Kang etal. (2009). Combined with
the interview results, we learned that this dierence stems
from the dierent content of the ads, which is consistent with
the fact that ad content aects dlPFC activation (Wang et al.,
2013). e dierent focus and presentation in the v1 and v10
resulted in dierent appeal of the ad content to participants,
consistent with the ndings of Shen (2015) on the eectiveness
of sympathy appeals and fear appeals for anti-smoking ads.
When people make decisions, they tend to value stimuli by
using experiences and preferences as reference, showing activation
of the dlPFC (Parnamets et al., 2020). From the interviews,
we learned that the participants obtained some content of
interest to them from v10, but did not obtain that from v1.
Although the participants were unfamiliar with the fruits
introduced by both v1 and v10, they had a reference in their
value assessment because they got the information of interest
from v10, as shown by the activation of the dlPFC, which
was not the case with v1. It is noteworthy and interesting to
note that most of the participants in group A bought the
fruits presented in v1 and v10 out of curiosity and sympathy,
because the anti-poverty project is a dicult and well-known
project in China and most Chinese want to contribute to it.
On advertising content alone, we believe that the activation
of the dlPFC can be used as an indicator of the attractiveness
of PSA content to enhance the advertising eect.
Although the results of this experiment are satisfactory, the
shortcomings of this experiment still need to be addressed.
e prediction method adopted in this experiment was within-
sample prediction, and whether the experimental results can
be applied to the overall population cannot be determined
and still needs to be veried in future studies. Furthermore,
although, we found that activation of the dlPFC can be used
as an indicator of the eect of advertising, there are still some
brain areas that we have not studied. McClure et al. (2004)
suggested that vmPFC would assume a major role in decision-
making and show greater activation when the decision is based
on perception only; dlPFC would be more active when the
information is more comprehensive. Wang et al. (2013) also
suggested that dierence in PSAs content can cause activation
of the inferior frontal gyrus and precuneus. However, due to
the limitation of the fNIRS observation range, we could not
observe the neural activity of vmPFC, inferior frontal gyrus
and precuneus. Whether advertising content aects emotion,
whether emotion aects the decision-making process, and
TABLE2 | The peak t-values of the selected channels.
Videos Group A Group B
TpChannel T pChannel
v1 3.15 p < 0.01 21 1.09 p > 0.05 6
v2 7.67 p < 0.01 16 8.32 p < 0.01 21
v3 2.57 p < 0.05 16 1.73 p > 0.05 18
v4 1.63 p > 0.05 18 1.46 p > 0.05 19
v5 5.87 p < 0.01 16 6.39 p < 0.01 18
v6 6.33 p < 0.01 16 6.69 p < 0.01 16
v7 6.47 p < 0.01 18 7.27 p < 0.01 21
v8 5.54 p < 0.01 16 4.97 p < 0.01 16
v9 6.71 p < 0.01 16 8.32 p < 0.01 19
v10 6.62 p < 0.01 21 2.63 p < 0.05 6
Fu et al. Improving PSAs Effectiveness With fNIRS
Frontiers in Psychology | 7 March 2022 | Volume 13 | Article 825768
whether advertising content can be better improved through
other brain regions need to be investigated further in
future research.
Studies have shown that most consumer purchases are impulsive,
that 70% of purchases occur within 60 s (Rook and Fisher,
1995), and that better planning of advertising content to
inuence consumer decisions is the key to improving advertising
eectiveness (Fisher et al., 2010). e same eect is true for
PSAs. e more appealing the content of a PSA, the higher
the likelihood that it will inuence people. Nowadays, there
are many types of PSAs, anti-gambling ads (Shead et al.,
2011), and healthy diet ads (Phua, 2014). e method used
by these studies is still to evaluate the eectiveness of PSAs
based on the people’s self-report. According to the results of
this study, people’s neural activity can predict the eectiveness
of PSAs more accurately than self-report, and the rational
use of neuroimaging tools can better inuence people’s behavior.
e results of this study may provide a new approach for
subsequent PSAs research to improve the eectiveness
of advertising.
To change the bad social phenomenon and guide people’s
behavior, the preparation of PSAs needs to speed lots of time
and money. Ineective PSAs cannot achieve their purpose,
can only waste a lot of resources. e results of this study
provide a method to predict the eectiveness of PSAs before
they are released. Meanwhile, the appeal of content can
be adjusted according to the neural activity of viewers, so as
to improve their inuence and avoid the waste of social resources.
is study found that there was a positive correlation between
the activation of dlPFC and the eectiveness of PSAs; e
activation of dlPFC can also be used as an indicator of the
attractiveness of the advertising content and help improve the
eectiveness of PSAs. ese ndings imply that neuroimaging
tools can beused not only in commercial advertising eectiveness
and some PSA eectiveness studies, but also in PSA eectiveness
studies in the remaining elds. Meanwhile, the ndings of
this study can serve as a primer for subsequent studies on
the relationship between PSA eectiveness and neural activity.
Before the PSAs are released, advertisers can predict the eect
of the ads based on the audiences dlPFC neural activation,
determine the content of the ads that can better inuence the
audience, improve the eectiveness of the ads, and avoid
wasting resources.
In this study, only dlPFC was investigated as an observed
brain region, but there are many other brain regions associated
with advertising eects, such as vmPFC and insula, according
to previous studies. Limited by the measurement depth of
fNIRS, we were unable to measure these brain regions, which
may also have indicators related to advertising eects. Future
research could start with two aspects: rst, whether the brain
regions that were not observed in this study are related to
improving the eectiveness of PSAs; and second, the neural
mechanisms by which emotions inuence audience behavior
and how emotions aect PSA eectiveness.
e datasets presented in this article are not readily available
because it was ensured to the participants that their data is
FIGURE4 | v1–v10 are ranked according to the peak t-value of the selected
channel, with red representing the activation of dorsolateral prefrontal cortex
(dlPFC) compared to the resting state. Compared to the resting state, v4in
group A and v3, v4, and v1in group B were insignicant.
Fu et al. Improving PSAs Effectiveness With fNIRS
Frontiers in Psychology | 8 March 2022 | Volume 13 | Article 825768
not available for third parties and it was guaranteed that
participants can request the complete deletion of their datasets
at any time. Requests to access the datasets should be directed
e studies involving human participants were reviewed and
approved by College of Economics and Management Ethics
Committee, Zhengzhou University of Light Industry. e patients/
participants provided their written informed consent to
participate in this study.
All authors listed have made a substantial, direct, and intellectual
contribution to the work and approved it for publication.
is study was supported by Science and Technology Project
of Science and Technology Department of Henan Province
(202102310305); Graduate Education Reform and Quality
Improvement Project of Henan Province (HNYJS2020JD04);
and General Project of So Science Research of Henan Province
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