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Persuasive interventions can lose their effectiveness when a person becomes reactant to the persuasive messages—a state identified by feelings of anger and perceived threat to freedom. A person will strive to reestablish their threatened freedom, which is characterized by motivational arousal. Research suggests that the motivational state of psychological reactance can be observed in physiology. Therefore, the assessment of physiological reactions might help to identify reactance to persuasive messages and, thereby, could be an objective approach to personalize persuasive technologies. The current study investigates peripheral psychophysiological reactivity in response to persuasive messages. To manipulate the strength of the reactant response either high- or low-controlling language messages were presented to discourage meat consumption. The high-controlling language condition indeed evoked more psychological reactance, and sympathetic arousal did increase during persuasive messaging in heart rate and heart rate variability, although no clear relationship between physiological reactivity and self-reported psychological reactance was found. However, the evaluation of multiple linear models revealed that variance in self-reported psychological reactance was best explained by initial intentions in combination with cardiovascular reactivity. To conclude, considering physiological reactivity in addition to motivational state can benefit our understanding of psychological reactance.
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Article
Psychophysiological Measures of Reactance to
Persuasive Messages Advocating Limited
Meat Consumption
Hanne Spelt 1, 2, * , Elisabeth Kersten-van Dijk 2, Jaap Ham 2, Joyce Westerink 1,2 and
Wijnand IJsselsteijn 2
1Philips Research, 5656 Eindhoven, The Netherlands; joyce.westerink@philips.com or
j.h.d.m.westerink@tue.nl
2Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology,
5612 AZ Eindhoven, The Netherlands; e.t.v.dijk@tue.nl (E.K.-v.D.); j.r.c.ham@tue.nl (J.H.);
w.a.ijsselsteijn@tue.nl (W.I.)
*Correspondence: hanne.spelt@philips.com or h.a.a.spelt@tue.nl; Tel.: +31-6-15134665
Received: 20 August 2019; Accepted: 16 October 2019; Published: 17 October 2019


Abstract:
Persuasive interventions can lose their eectiveness when a person becomes reactant to the
persuasive messages—a state identified by feelings of anger and perceived threat to freedom. A person
will strive to reestablish their threatened freedom, which is characterized by motivational arousal.
Research suggests that the motivational state of psychological reactance can be observed in physiology.
Therefore, the assessment of physiological reactions might help to identify reactance to persuasive
messages and, thereby, could be an objective approach to personalize persuasive technologies.
The current study investigates peripheral psychophysiological reactivity in response to persuasive
messages. To manipulate the strength of the reactant response either high- or low-controlling language
messages were presented to discourage meat consumption. The high-controlling language condition
indeed evoked more psychological reactance, and sympathetic arousal did increase during persuasive
messaging in heart rate and heart rate variability, although no clear relationship between physiological
reactivity and self-reported psychological reactance was found. However, the evaluation of multiple
linear models revealed that variance in self-reported psychological reactance was best explained by
initial intentions in combination with cardiovascular reactivity. To conclude, considering physiological
reactivity in addition to motivational state can benefit our understanding of psychological reactance.
Keywords:
psychophysiology; cardiovascular arousal; electrodermal arousal; persuasion profiling;
psychological reactance
1. Introduction
Persuasive technologies can help people to change their behavior to become healthier or
more pro-environmental by presenting persuasive information or indicating opportunities for
change. However, a persuasive message may also evoke psychological reactance. In that case
the user is motivated to reject the advocacy, thereby limiting the desired impact of the persuasive
technology on behavior [
1
]. The motivational state and the negatively valenced emotions associated
with psychological reactance are likely—as any emotions—to be reflected in psychophysiological
signals [
2
4
]. Physiological reactions might then be used to detect whether a persuasive message is
evoking resistance [
5
]. As such, physiology could be an objective measure of persuasion eectiveness.
Physiology-based selection of persuasive content would enable unobtrusive personalization of
persuasive technologies, minimizing the occurrence of reactance. In theory, such aective-loop
systems [
6
] facilitate user-specific tailoring and help to improve long-term behavior change interventions
Information 2019,10, 320; doi:10.3390/info10100320 www.mdpi.com/journal/information
Information 2019,10, 320 2 of 12
within and across individuals, contexts and time. Aective-loop systems could then contribute to the
field of personalized persuasive technologies. This study investigates the physiological patterns in the
cardiovascular and electrodermal systems that occur when people respond to persuasive messages
that can give rise to psychological reactance.
1.1. Psychological Reactance Is Situation Specific
Persuasive messages aim at convincing people to change their attitudes, intentions and
behaviors [
7
], but can also be perceived as a threat to or restriction of certain freedoms [
7
,
8
], e.g., due to
the use of controlling or forceful language [
5
]. In that case, people experience psychological reactance
in which a motivation is aroused to reject the advocacy and reestablish their threatened freedom [
3
].
Psychological reactance is a reactive phenomenon—it occurs when a person responds to a situation
containing a specific threat to a specific freedom and is best described as a mix of negative cognitions
and emotions towards this threat [
1
,
7
]. The negative emotions and cognitions aroused depend on these
situational characteristics [
7
]. To overcome feelings of reactance, a person may engage in freedom
restoration behaviors with a state of motivational arousal [1,3,9].
Dierences between people and/or the strength of threats can influence the level of the reactant
response. Individual dierences arise from the perceived importance of the freedoms that are
threatened [
9
]. The beliefs that shape perceived importance rely on underlying motivations, such as
social norms [
1
] or intentions [
5
,
10
]. A second determinant for the magnitude of reactance is the
nature and strength of the threat, which can depend on the content but also on the formulation of the
message [
8
,
11
,
12
]. Generally, high controlling language (HCL) is more likely to arouse reactance than
low controlling language (LCL): HCL has a powerful and directive nature due to the use of many
imperatives. It tends to be short, clear and ecient [
12
]. In LCL, the intentions of the sender are more
ambiguous. LCL emphasizes self-initiation and choice. Consequently, it is perceived to be more polite
and less forceful [
12
]. Usage of HCL increases the probability that the recipient perceives the messages
as a threat, will reject the message, and experiences psychological reactance [12].
1.2. Measuring the Psychophysiology of Reactant Responses
Earlier research indicates that it is dicult to measure the presence and intensity of reactant
responses and its eects and on people’s experiences [
1
,
8
]. Several surveys have been developed
for this purpose [
1
,
5
,
8
], but their validity is an ongoing debate [
5
,
8
]. Most surveys measure trait
characteristics of reactance, while reactance is a situational response [
1
]. Therefore, researchers have
proposed physiological measures as an additional measure of reactance accounting for direct aective
responses [
1
,
5
]. Physiological arousal can give information about the mental state of a person, and can
thereby function as an implicit measure of the mind [
13
,
14
]. Therefore, analyzing psychophysiological
responses might yield essential additional insights into psychological reactance.
For our argumentation, it is important to realize that the motivational state of reactance has
energizing properties, which can be reflected in the physiological system [
1
,
5
]. That is, cortical responses
reflecting the negative emotions and cognitions specific to reactant responses can influence peripheral
physiology as well [
2
]. Peripheral physiology is influenced by the sympathetic, ‘fight-or-flight’, and
parasympathetic, ‘rest-and-digest’, branches of the nervous system. These influences are measurable,
among others, using features of the cardiovascular and electrodermal system [
15
,
16
]. Thus, the
negative emotions and cognitions that arise in reactant responses might reflect in cardiovascular
and electrodermal arousal [
17
,
18
]. To draw psychophysiological inferences from cardiovascular and
electrodermal arousal we have to review the function of both systems.
The cardiovascular system is responsible for blood circulation and, thereby, transportation of
blood cells, oxygen, nutrients, waste, and hormones through the body [
16
]. Easily measurable features
of the cardiovascular system are heart rate (HR), i.e., the number of heart beats per minute, and heart
rate variability (HRV), i.e., the variability between those beats resulting from the interplay between
the sympathetic and parasympathetic nervous system [
19
]. Sympathetic influences increase HR and
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decrease HRV, and can hint at high arousal emotions, such as fear or joy, and increased cognitive
demands. HR decreases and HRV increases under parasympathetic control, often indicating resting
states or passive emotions [
2
,
20
]. Electrodermal activity, on the other hand, comprises sweat gland
activity and is under only sympathetic control. Electrodermal arousal can increase in actionable
emotional experiences and cognitive demands, such as decision-making. Measurable features of
electrodermal arousal are the tonic component, namely skin conductance level (SCL), and the number
of rapid phasic responses per minute, called skin conductance responses (SCRs) [21].
Results from several studies indeed indicated that psychological reactance can be seen as a
state with motivational, emotional and cognitive components [
3
,
5
,
8
,
22
,
23
], such as anger, which is
both motivational and aective [
5
], and negative cognitions [
8
]. Earlier research has shown that
reactant responses are indeed associated with heightened sympathetic arousal as reflected in elevated
epinephrine and norepinephrine neurotransmitter levels [
1
]. Only a few studies have linked peripheral
physiological arousal with psychological reactance [
3
,
5
,
23
]. These studies analyzed reactance in specific
contexts and only for heart rate and skin conductance levels. Other features of cardiovascular and
electrodermal arousal such as heart rate variability or skin conductance responses are even more
sensitive to sympathetic and parasympathetic changes [
16
], and, thereby, might reveal further insights
in psychological reactance. Evoking reactance in other contexts can also produce extra insights, as
situational aspects might determine psychophysiological arousal during reactance, for example, the
topic, the severity of the threat, the perceived importance of the freedom, or specific determinants
of freedom.
1.3. Study Aim and Hypotheses
This study investigates whether psychological reactance is reflected in peripheral physiology.
Additionally, we want to gain more insight in what predicts psychological reactance, especially the
potential role physiological arousal. We build on previous work on reactance to persuasion [
7
] by using
a similar experiment set-up with persuasive content diering in high or low controlling language and
self-report measures of reactance [
7
,
24
], but now also measure cardiovascular and electrodermal activity.
Doing so, previously researched [
3
,
23
] and new features of the cardiovascular and electrodermal system
will be analyzed in relation to psychological reactance. To induce reactant responses, we will use the
issue of meat eating, because earlier research suggested people consume meat as a way to express
their identity [
25
] and that reactance occurs more easily for high involvement issues [
11
]. Based on
earlier research we expect that 1) the motivational arousal and negative feelings in reactance increase
sympathetic arousal, as reflected by HR acceleration, decreased HRV, elevated SCL and more SCRs
compared to rest state, 2) that this increased arousal positively correlates with self-report measures
of reactance, and 3) this psychophysiological relation adds insights to current means of predicting
relationship explains part of the reactant responses.
2. Method
2.1. Participants
We recruited participants using the University database, which contains mainly students and
a few adults. Fifty-nine people with a relatively high meat consumption (>5 times per week) and
without (a history of) cardiovascular diseases participated in this study. Sucient English language
skills and willingness to sign the informed consent were required. Participants received 10 euros or
student credits as compensation. Participants were divided into two manipulation groups (group 1:
N=31 (19 women), M
age
=23.3, SD
age
=5.5, and group 2: N =28 (16 women), M
age
=24.5, SD
age
=6.7.
The internal ethical board at the Eindhoven University of Technology reviewed and approved the study.
Information 2019,10, 320 4 of 12
2.2. Manipulation
This study had a between-subject repeated-measures design in which participants watched
a persuasive video advocating limited meat consumption in either high controlling (HCL) or low
controlling language (LCL) for group 1 and 2 respectively. Based on previous research [
7
,
24
], the video
consisted of a threat-to-health/environment component (202 words) and a recommendation for action
(Table 1, HCL: 226 words, LCL: 224 words). The first part emphasized the negative consequences of
behavior, whereas the second part regulated the strength of the threat. Both videos had comparable
content but diered in framing. Besides using more imperatives, the HCL video pressed participants
to do a certain action, i.e., become vegetarian, whereas the LCL video emphasized the choice for action.
Especially for the group that saw the HCL video, the intervention tried to evoke psychological reactance.
Table 1. A subset of sentences from the manipulation video advocating limited meat consumption.
Segment Example Sentences
Threat-to-health/environment
(202 words, presented to both
groups)
Eating meat has consequences for your health and the environment.
People who eat meat have a higher body mass index and blood pressure
than non-meat eaters. [ . . . ], eating meat increases your risk of heart
disease, diabetes and various types of cancer. [ . . . ], eating meat poses
several serious long-term risk to your health. [ . . . ]
Meat production uses up many of the earth’s resources. [ . . . ] About
15% of the global greenhouse gasses come from livestock production.
[. . . ] This makes livestock production a bigger contributor to global
greenhouse gasses than all the world’s planes, trains and automobiles
put together. [ . . . ] Around 70% of global freshwater consumption is
used in agriculture. [ . . . ]
Recommendation in HCL
(226 words, presented to group 1)
As any sensible person can see, there is really no choice when it comes to
consuming meat: you simply have to stop. [ . . . ]
The scientific evidence showing a link between cardiovascular risks and
meat consumption is so overwhelming that only a fool would possibly
argue with it. [ . . . ]
If you have been reducing your meat consumption, do it even more. [
. . .
] If you haven’t been reducing your meat consumption, right now is the
time to start. Today. [ . . . ]
Set a goal for yourself to stop and commit to it. Stop eating meat.
Recommendation in LCL
(224 words, presented to group 2)
Most people agree that reducing your meat consumption is a good idea;
nevertheless, the choice to do so is completely up to you. [ . . . ]
You are the boss of your own body and you make the rules. What you
consume is your own decision. [ . . . ]
If you have been reducing your meat consumption, we support your
decision. And if you haven’t been reducing your meat consumption, we
support your decision. [ . . . ]
You are free to do as you want.
2.3. Procedure
One week before the laboratory session, the participant completed an online pre-survey assessing
demographic information, meat consumption, and initial motivational state towards limited meat
consumption. The participant was instructed to refrain from caeinated drinks in the 2 hours preceding
the laboratory session. Prior to the experiment segments, the participant received a short introduction,
signed the informed consent and was attached to the physiological measurement equipment. Then,
the participant was seated in front of a computer screen to start the experiment. The computer asked
the participant to describe his/her favorite dish to increase awareness of their consumption freedom
(Figure 1). A baseline measurement of physiology was conducted twice while the participant viewed
3- and 5-minute sea-life movies [
26
]. A 4.5-minute factual video with neutral information about
Information 2019,10, 320 5 of 12
the consequences of meat consumption on the environment and health followed the first baseline.
The factual video ensured that all participants had similar topic-specific knowledge. After the second
baseline, the persuasive messages were presented. Both the HCL and LCL messages had a total
duration of 3 minutes. After the persuasive messages, participants had the opportunity to restore their
freedom by filling out questions in the post-survey while reflecting on the video. In this post-survey,
a reactance questionnaire as well as control questions were asked in addition to questions assessing
motivational state towards limited meat consumption.
Computers 2019, 8, x FOR PEER REVIEW 5 of 12
the participant viewed 3- and 5-minute sea-life movies [26]. A 4.5-minute factual video with neutral
information about the consequences of meat consumption on the environment and health followed
the first baseline. The factual video ensured that all participants had similar topic-specific knowledge.
After the second baseline, the persuasive messages were presented. Both the HCL and LCL messages
had a total duration of 3 minutes. After the persuasive messages, participants had the opportunity to
restore their freedom by filling out questions in the post-survey while reflecting on the video. In this
post-survey, a reactance questionnaire as well as control questions were asked in addition to
questions assessing motivational state towards limited meat consumption.
Figure 1. Experimental procedure during the laboratory experiment starting with a freedom exercise
followed by a baseline measurement of physiology in rest, a factual movie about the consequences of
meat consumption on health and environment, a second baseline, a persuasive message using high
or low controlling language and a post-survey.
2.4. Materials
2.4.1. Subjective Data
Self-report measures included demographic information such as age, gender and educational
level. The highest received degree determined educational level. Following the theory of planned
behavior [10,20], participants’ motivational state to limit meat consumption was asked using
questions about attitude towards and intention to perform the advocated behavior, as well as
subjective and injunctive norms. The five attitude items focused on the instrumental, e.g., worthless
valuable, and affective, e.g., goodbad, nature of limiting meat consumptions with scale end-points
counterbalanced. Intention was assessed using three items on intentional effort. Subjective norms
measured the perceived expectations of other people’s behavior (3 items), whereas injunctive norms
represented people’s ideas of the participants own behavior (3 items). These items used a 7-point
Likert scale ranging from ‘strongly disagree’ to ‘strongly agree’.
In the post-survey, four items per scale concerning feelings of anger and perceived threat to
freedom (PTTF) checked if participants were reactant towards the video. These questionnaires were
answered on 5-point Likert scales ranging from ‘completely disagree’ to ‘completely agree’ (Table 2) [7].
In addition, a control survey consisted of one question on the newness of the information and three
multiple-choice questions to test if participants paid attention to the video. The questions were
presented in English. With exception of the control questions, all questionnaires in this study were
validated in previous research and analyzed as instructed [7,10] using various packages in R studio
[2729].
Table 2. Items for both reactance scales.
Feelings of Anger
Perceived Threat to Freedom
1
I was irritated
The video tried to make a decision for me
2
I was angry
The video tried to manipulate me
3
I was annoyed
The video tried to pressure me
4
I was aggravated
The video threatened my freedom to choose
2.4.2. Physiological Data
Figure 1.
Experimental procedure during the laboratory experiment starting with a freedom exercise
followed by a baseline measurement of physiology in rest, a factual movie about the consequences of
meat consumption on health and environment, a second baseline, a persuasive message using high or
low controlling language and a post-survey.
2.4. Materials
2.4.1. Subjective Data
Self-report measures included demographic information such as age, gender and educational
level. The highest received degree determined educational level. Following the theory of planned
behavior [
10
,
20
], participants’ motivational state to limit meat consumption was asked using questions
about attitude towards and intention to perform the advocated behavior, as well as subjective and
injunctive norms. The five attitude items focused on the instrumental, e.g., worthlessvaluable, and
aective, e.g., goodbad, nature of limiting meat consumptions with scale end-points counterbalanced.
Intention was assessed using three items on intentional eort. Subjective norms measured the perceived
expectations of other people’s behavior (3 items), whereas injunctive norms represented people’s ideas
of the participants own behavior (3 items). These items used a 7-point Likert scale ranging from
‘strongly disagree’ to ‘strongly agree’.
In the post-survey, four items per scale concerning feelings of anger and perceived threat to freedom
(PTTF) checked if participants were reactant towards the video. These questionnaires were answered
on 5-point Likert scales ranging from ‘completely disagree’ to ‘completely agree’ (Table 2) [
7
]. In addition,
a control survey consisted of one question on the newness of the information and three multiple-choice
questions to test if participants paid attention to the video. The questions were presented in English.
With exception of the control questions, all questionnaires in this study were validated in previous
research and analyzed as instructed [7,10] using various packages in R studio [2729].
Table 2. Items for both reactance scales.
Feelings of Anger Perceived Threat to Freedom
1
I was irritated The video tried to make a decision for me
2
I was angry The video tried to manipulate me
3
I was annoyed The video tried to pressure me
4
I was aggravated The video threatened my freedom to choose
Information 2019,10, 320 6 of 12
2.4.2. Physiological Data
We used a Mobi physiology-recording device with gel electrodes in Lead II placement for
ECG measurement, and dry electrodes with Velcro straps on the fingertips for skin conductance
measurement [
21
], sampling at 1029.5 Hz. Physiological features were measured during the complete
laboratory experiment. In the ECG signal, we calculated inter-beat intervals (IBIs) and verified them by
manually checking the R-peaks. IBIs below 0.4 s or above 1.4 s were interpolated [
30
]. This procedure
was not seldom needed. From the filtered IBI data, mean heart rate (HR), standard deviation from
normal-to-normal peaks (SDNN), and root mean square of successive dierences (RMSSD) for the
middle three minutes of each experiment segment were calculated. Electrodermal activity (EDA) was
down-sampled to 2 Hz and filtered with a 0.5 Hz low-pass Butterworth filter. From the filtered EDA
signal, mean skin conductance level (SCL) and the number of skin conductance response peaks per
second (SCRs) were calculated for the middle 3 minutes of each experiment segment [
16
]. The dierence
between the physiological values during the factual video, persuasive messages, or survey and those
of the preceding baseline served as measure of physiological reactivity to each experiment segment,
e.g., reactivity
(messages)
=arousal
(messages)
arousal
(short baseline)
. Several R packages were used for the
preprocessing of physiological data [28,30,31].
2.5. Analyses
First, we verified if the two groups were statistically similar with respect to demographic
information and motivational state using an independent t-test. As manipulation check, an
independent t-test was applied to check whether HCL evoked more reactance than LCL. Additionally,
a within-between MANOVA on attitudes and intentions checked whether the video was persuasive.
To answer hypothesis 1, a linear mixed model was applied for each physiological reactivity
variable with experimental segment and manipulation condition as fixed and subject as random eects.
In linear mixed models, fixed eects are variables constant over measurements, while random eects
can vary per measurements. This approach enabled the analysis of physiological reactivity during
dierent experiment segments, while accounting for individual dierences and missing data [32].
To answer hypotheses 2 and 3, we evaluated the fit of multiple linear models with psychological
reactance as dependent variable. To yield only one dependent variable, reactance was calculated
by adding anger and PTTF scores. The best predictors of variance in psychological reactance were
established by evaluating four models: (1) a null model, (2) a state model, (3) a message-reactivity
model, and (4) a full model. The null model included no predictors. The state model evaluated all
self-reported scores that determined initial motivational state to limit meat consumptions; attitude,
intention, subjective and injunctive norms before the manipulation. The message-reactivity model
evaluated HR, SDNN, RMSSD, SCL and SCRs reactivity to the persuasive messages—that is the rise in
physiological arousal from the short baseline to the persuasive messages for each parameter. Lastly,
the full model evaluated all physiological reactivity and initial motivational state variables. Only
significant models were presented and only including those variables that improved predictive power
of the model by explaining extra variance in reactance based on AIC weights [
33
]. Eventually, the fit of
the four models was evaluated using Akaike Information Criterion [
33
]. This evaluation reveals which
combination of predictor variables predicts variance in psychological reactance best. In these relational
analyses, the eect of manipulation was not considered relevant. Analyses were carried out using
several R Studio packages [2729,34].
3. Results
The final data set contained subjective and physiological data of 56 participants. Three datasets
had to be excluded due to incompleteness. Data for intention, descriptive norms, and PTTF were not
normally distributed and transformation did not eectuate normal distribution, i.e., log, log+1, Tukey’s
Ladder of Powers, Cube root nor square root transformation. There were no significant dierences
Information 2019,10, 320 7 of 12
between the demographic characteristics or initial motivational state of the two groups, e.g., attitudes,
intention, subjective norms and descriptive norms.
As a persuasion check, a within-between MANOVA with Bonferroni–Holm correction was
conducted to compare the main eects of condition and time, and the interaction eect between
manipulation and time on attitudes and intentions towards limited meat consumption. Both the main
and the interaction eects were not significant; attitudes and intentions did not change over the course
of the experiment in either condition.
As a manipulation check, an independent sample one-tailed Mann–Whitney U t-test with
Bonferroni–Holm correction revealed that the HCL condition indeed evoked significantly more anger
and perceived threat to freedom than the LCL persuasive messages (Table 3).
Table 3.
Descriptive statistics of both reactance scales and results of a one-tailed Mann–Whitney U test
comparing the two conditions (high controlling language (HCL) >low controlling language (LCL)).
Condition HCL LCL
Scale αm s.d. m s.d. U p
Anger 0.91 3.45 1.35 2.84 1.12 280 0.034
PTTF 0.92 4.20 1.43 2.70 1.45 164 0.002
The results of multiple linear mixed models with experiment segment and manipulation condition
as fixed eects and subject as random eect showed physiological reactivity diered significantly
between experimental segments for HR, SDNN, and RMSSD (Table 4). On average, SDNN and RMSSD
were 89 and 36 ms lower, and HR 1.30 bpm higher during the persuasive messages compared to the
short baseline. During the factual video, HR reactivity was 1.03 bpm lower than during the persuasive
messages, whereas SDNN reactivity was 54 ms higher (see also Figure 2). With the exception of number
of skin conductance peaks, the dierence in experiment segments explains between 32.7% and 44.9%
of the variance in physiological reactivity based on the conditional R
2
, i.e., based on both fixed and
random eects [34]. There was no significant eect of manipulation on physiological reactivity.
Table 4.
Summary results of the mixed linear models for reactivity of Heart Rate (HR), Heart
Rate Variability (standard deviation from normal-to-normal peaks (SDNN) and root mean square of
successive dierences (RMSSD)) and Electrodermal (skin conductance level (SCL) and skin conductance
responses (SCRs)) per segment.
HR SDNN·102RMSSD·102SCL SCRs
Predictors
Est.
1p Est. p Est. p Est. p Est. p
Persuasive messages
(Intercept) 1.30 0.001
0.89
<0.001
0.36
0.040 0.06 0.294
4.56
0.190
Factual video
1.03
0.018 0.54 0.038 0.04 0.829
0.06
0.317
0.32
0.948
Survey
0.60
0.165 0.50 0.058 0.13 0.519 0.10 0.112 4.74 0.330
Random Eects
σ25.25 2.26 1.10 0.11 639.99
ICC 0.43 0.37 0.33 0.31 0.03
Obs. 171 171 171 164 165
R2/Cond. R20.025 /0.449 0.010 /0.376 0.001 /0.336 0.028 /0.327 0.008 /0.040
AIC 847.072 692.645 563.667 163.913 1549.650
1
Est. =estimated dierence in units of the physiological parameters, p =p-value (presented in bold if
significant),
σ
2=subject variance, ICC =intra-class correlation coecient, R
2
=Marginal r-squared statistics, Cond.
R2=conditional r-squared statistics, Obs. =number of observations, AIC =Akaike Information Criterion
Information 2019,10, 320 8 of 12
Computers 2019, 8, x FOR PEER REVIEW 8 of 12
Figure 2. Average physiological reactivity per segment for each experimental group with error bars
representing standard errors of the mean. Red = group that received HCL, blue = group that received
LCL.
Results of various linear models with reactance as dependent variable and physiological
reactivity and/or initial motivational state as predictor variables for the main analysis are presented
in Table 5. Out of the four possible models (Section 2.5) only three models had a significant fit; the
null, state, and full model. The null model includes no predictors and the significant intercept reveals
that on average the participants experienced reactance. Results from the state model reveal that from
all initial motivational state factors, e.g., attitude, injunctive and subjective norms, only intention to
limit meat consumption explains variance in reactance; reported reactance drops 0.54 on a 114 point
scale with each unit rise of initial intention. We did not find a significant fit for the message-reactivity
model, suggesting a minor role of the physiological reactivity variables in explaining variance in
reactance. However, the full model was significant, not only including a relationship between
reactance and initial motivational state, but also with physiological reactivity. Results of the full
model reveal that on average people report 8.73 experienced reactance on a 114 scale. Higher initial
intentions to limit meat consumption lower the reported reactance by 0.58 per step on the intention
scale. Although the physiological reactivity variables were non-significant on their own, they did
yield a model with higher predictive power when combined with intention than the state model.
Physiological reactivity to the persuasive messages also lowers reactance by 0.23 and 0.52 for each
bpm rise in HR and millisecond rise in RMSSD, respectively. In comparison to the null and state
models, the full model has the best fit based upon the lowest AIC. The full model explains around
20.1% of variance in self-reported reactance in our sample based on R2.
Table 5. Results of three linear models explaining variance in reactance.
Null Model
State Model
Full Model
Predictors
Est. 1
p
Est.
p
Est.
P
(Intercept)
6.63
<0.001
8.47
<0.001
8.73
<0.001
Intention to limit meat consumption
0.54
0.012
0.58
0.006
HR reactivity to persuasive messages
0.23
0.056
RMSSD reactivity to persuasive
messages
0.52
0.055
Obs.
56
56
56
R2 / Adj. R2
0.000 / 0.000
0.112 / 0.095
0.201 / 0.155
AIC
262.250
257.627
255.693
1 Est. = estimated difference in units of the physiological parameters, p = p-value (presented in bold if
significant), R2 = r-squared statistics, Adj. R2 = r-squared statistics adjusted for number of parameters,
Obs. = number of observations, AIC = Akaike Information Criterion
4. Discussion
Use of psychophysiological reactions could be an objective approach to personalize persuasive
interventions, e.g., trying to avoid reactance. Therefore, we studied psychophysiological reactance to
Figure 2.
Average physiological reactivity per segment for each experimental group with error
bars representing standard errors of the mean. Red =group that received HCL, blue =group that
received LCL.
Results of various linear models with reactance as dependent variable and physiological reactivity
and/or initial motivational state as predictor variables for the main analysis are presented in Table 5.
Out of the four possible models (Section 2.5) only three models had a significant fit; the null, state,
and full model. The null model includes no predictors and the significant intercept reveals that on
average the participants experienced reactance. Results from the state model reveal that from all initial
motivational state factors, e.g., attitude, injunctive and subjective norms, only intention to limit meat
consumption explains variance in reactance; reported reactance drops 0.54 on a 1–14 point scale with
each unit rise of initial intention. We did not find a significant fit for the message-reactivity model,
suggesting a minor role of the physiological reactivity variables in explaining variance in reactance.
However, the full model was significant, not only including a relationship between reactance and
initial motivational state, but also with physiological reactivity. Results of the full model reveal that on
average people report 8.73 experienced reactance on a 1–14 scale. Higher initial intentions to limit
meat consumption lower the reported reactance by 0.58 per step on the intention scale. Although the
physiological reactivity variables were non-significant on their own, they did yield a model with higher
predictive power when combined with intention than the state model. Physiological reactivity to the
persuasive messages also lowers reactance by 0.23 and 0.52 for each bpm rise in HR and millisecond
rise in RMSSD, respectively. In comparison to the null and state models, the full model has the best
fit based upon the lowest AIC. The full model explains around 20.1% of variance in self-reported
reactance in our sample based on R2.
Table 5. Results of three linear models explaining variance in reactance.
Null Model State Model Full Model
Predictors Est.1p Est. p Est. P
(Intercept) 6.63 <0.001 8.47 <0.001 8.73 <0.001
Intention to limit meat consumption 0.54 0.012 0.58 0.006
HR reactivity to persuasive messages 0.23 0.056
RMSSD reactivity to persuasive messages 0.52 0.055
Obs. 56 56 56
R2/Adj. R20.000 /0.000 0.112 /0.095 0.201 /0.155
AIC 262.250 257.627 255.693
1
Est. =estimated dierence in units of the physiological parameters, p =p-value (presented in bold if significant),
R
2
=r-squared statistics, Adj. R
2
=r-squared statistics adjusted for number of parameters, Obs. =number of
observations, AIC =Akaike Information Criterion.
4. Discussion
Use of psychophysiological reactions could be an objective approach to personalize persuasive
interventions, e.g., trying to avoid reactance. Therefore, we studied psychophysiological reactance to
persuasive messages that used high controlling (HCL) or low controlling language (LCL). The messages
Information 2019,10, 320 9 of 12
tried to persuade people with a high meat consumption, e.g., >5 days per week, towards a more
vegetarian diet. Psychological reactance to these messages was assessed with self-reported feelings of
anger and perceived threat to freedom (PTTF). A factual video preceding the messages ensured that all
participants had akin topic-specific knowledge. Motivations to limit meat consumption were measured
one week before and immediately after the experiment. Physiological reactivity was measured during
the factual video, the persuasive messages, and the closing survey, using features of the cardiovascular
and electrodermal system.
We found that neither the HCL nor LCL messages persuaded participants to (further) limit their
meat consumption, as indicated by equal attitude and intention levels before and after the experiment.
While for the HCL condition this finding was in line with our expectations, we expected the LCL
messages to increase motivations to limit meat consumption. As both groups report some level of
reactance (at least 2.7 PTTF on a 7-point scale), this might have limited the persuasiveness of the
messages. Importantly, participants were more reactant in the HCL condition by experiencing higher
feelings of anger and greater perceived threat to freedom compared to participants that received the
LCL condition. Therefore, we can assume that, despite the lack of attitude change, our manipulation
was successful.
During the persuasive messages, participants had heightened sympathetic physiological arousal
as indicated by cardiovascular arousal compared to activity during rest state, i.e., the short baseline.
On the other hand, during the factual video, we found decreased heart rate and increased heart rate
variability. Because the action performed by the participant was similar during the factual video and
the persuasive messages, namely watching an informative video, this finding cannot be attributed to
a dierence in general information processing or attention. In addition, both the factual video and
the persuasive messages were concerned with the context of meat consumption. Generally heart rate
decelerates with increased attention [
16
], whereas during our persuasive messages the opposite occurs.
This finding, therefore, seems to suggest that elevated cardiovascular reactivity is indeed caused by the
content of the persuasive messages. We did not find a dierent eect of the HCL and LCL framing on
cardiovascular or electrodermal reactivity. One reason for the lack of this finding could be that the
manipulation conditions were not distinct enough in their psychological eects; both conditions were
not persuasive and both evoked some level of reactance.
Further analyses reveal a relationship between psychological reactance and initial motivations to
limit meat consumption; people with higher intention to limit their meat consumption experienced
lower reactance. This finding is not surprising. As the intentions of these people were in line with the
advocated appeal, the messages were probably less threatening to them and, thus, evoked lower levels
of reactance. Interestingly, adding cardiovascular measures significantly improved this explanatory
model. Both an increase in HR and SDNN reactivity appear to lower the reported reactance in this study.
These findings are somewhat surprising as increased HR indicates arousal, whereas increased SDNN
indicates relaxation. As this is contradictory, future research is needed to replicate this cardiovascular
relation. Despite this ambiguity, the combination of initial intention with cardiovascular measures
did explain almost twice as much variance in reactance than initial intentions alone, i.e., 20.1% versus
11.2% as indicated by the R
2
in Table 5. This underlines our idea that psychological reactance might
have a psychophysiological nature. It surely invites the combination of subjective self-report with
objective physiological measures in future reactance research.
This study has an explorative nature and, thereby, comes with limitations. Since the study
was limited to the context of meat consumption and concerns only people that have a high meat
consumption patterns (>5 days per week), the findings cannot be generalized. Eating animals is
seen as a moral dilemma between the aversion to animal suering and the desire to eat meat [
25
].
The moralization of vegetarianism is driven by strong aective responses, such as disgust and guilt [
35
].
Additionally, the formation of these beliefs depend on other attributes, i.e., experiences, characteristics,
objects, than health behaviors. [36]. Thus, the psychology of morality is wired dierently than health
beliefs. Therefore, it could be that similarly framed persuasive messages concerning other contexts
Information 2019,10, 320 10 of 12
produce dierent or no physiological markers. Further work is required to establish if this relation also
holds in other contexts, e.g., climate change, energy saving.
Another limitation might come from the manipulation not being strong enough, explaining
the similar eects of both conditions. Although the spread in reactance scores enabled correlational
analyses, it could be that too little people experienced high enough levels of reactance to evoke
physiological reactivity. Previous research [
7
] reported anger and PTTF scores between 0.45–1.44
and 2.31–3.11 on a 0–4 scale, while we found an average anger score of 3.45 and PTTF score of 4.20
on a 1–7 scale in the HCL condition. The scores are relatively high, but not extreme. This could be
one reason for not finding a stronger psychophysiological relationship in reactance. Future research
should find out whether higher levels of reactance do reflect in physiology or whether such a robust
relationship does not exist at all.
Lastly, personality traits were not considered in this study, while they might have explained
some of our results. As mentioned in the introduction, reactant responses are determined by the
perceived importance of the freedoms that are threatened [
9
]. These perceptions may dier based on
personality traits. These traits can therefore mediate the reactance response, but they can also influence
the physiological response. For example, trait characteristics such as approach-avoidance motivation
are associated with other nervous system activity patterns [
37
], novelty seeking correlates negatively
with low frequency HRV and LF/HF ratio [
38
] and cardiovascular arousal relates to neuroticism
and agreeableness [
39
]. As our main finding indicates that HRV parameters explain variability in
self-reported reactance, personality traits should also be considered in future research.
Despite its limitations, the study adds to our understanding of persuasive messages and their
eects on physiology. Future research should try to replicate and extend these findings to dierent
contexts, types of communication, and people. If an evident physiological marker for psychological
reactance is found, it could have considerable implications for personalized persuasive technologies,
i.e., indicating which messages are (not) eective for the user. It could set up the use of built-in
aective loops regulated by physiological, aective, and behavioral interactions in human–technology
interaction. Thereby, it would enable physiology-based tailoring as a personalization technique for
persuasive technology.
5. Conclusions
We did not find clear psychophysiological responses related to reactance. Nevertheless, the results
do encourage further research because the present findings indicate more cardiovascular arousal
during persuasive messages—although most likely not linked to reactance or attitude change. Further
research should not only consider the strategy to evoke reactance but also types of freedom and
underlying psychological processes that are targeted.
Author Contributions:
conceptualization, E.K.-v.D., J.W., W.I., J.H., H.S.; data curation, H.S.; formal analysis, H.S.;
funding acquisition, J.W.; investigation, H.S.; methodology, E.K.-v.D, H.S., J.W.; project administration, E.K.-v.D.,
H.S.; software, H.S.; supervision, E.K.-v.D., J.W.; validation, H.S.; visualization, H.S.; writing—original draft, H.S.;
writing—review and editing, J.W., J.H., H.S.
Funding: This research was funded by the H2020 INHERIT project, grant number 667364.
Acknowledgments:
We thank all volunteers and the Human–Technology Interaction Group at the
Eindhoven University of Technology. Special thanks to Shutong Liu, Tim van den Driesschen and Anisa
Fardhani Prasetyaningtyas.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to
publish the results.
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2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
... The variability in time between heartbeats is caused by an interplay between the sympathetic and parasympathetic nervous system [69]. It is the most commonly used measure to detect flow states [183] and was used previously to investigate the persuasiveness of messages [323,324] or assess arousal and affective responses in game-related contexts [351]. It was shown that increases in workload or arousal are associated with decreases in HRV [173]. ...
... For this, participants were asked to relax while watching a 5-minute video of sea life [263], in the absence of any discrete environmental event/external stimulus. This video has been successfully used in previous research for the purpose of getting baseline measurements of physiology [263,323]. While participants were watching the video, we prepared the Tailored Gamification and the Contra-Tailored Gamification conditions based on the results of the Hexad user types questionnaire by activating suitable and unsuitable gameful design elements on the study platform. ...
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... Results from earlier research indeed hint at the presence of a psychophysiological relationship in persuasion [1], [3], [5], [9]- [11], but a firm link has not yet been established. This paper seeks to extend the body of knowledge, and begins by describing (differences in) the processing of persuasive information. ...
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... The literature of psychological reactance might help to explain these findings. Spelt et al. (2019) have found that highly controlling language in meat reduction appeals is associated with increased psychological reactance, as measured by scales of anger and perceived threat to freedom, relative to low controlling language. Thus, vegan advocacy that is extreme and unforgiving may be damaging to the progression of the movement insofar as reactance may a barrier to message receptivity. ...
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... Reactance can occur either at the cognitive (e.g., counter-arguments, justifications, narratives) or at the emotional level (e.g., anger, irritation; Dillard and Shen, 2005). In a different setting, Spelt et al. (2019) find similar results as ours: moderate and more-demanding messages advocating limited meat consumption are associated with higher reactance. Unlike their study, we seek here to distinguish between cognitive and emotional reactance. ...
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Since Brehm first proposed reactance theory in 1966, many studies have explored the remarkable psychological phenomenon of reactance, which Miron and Brehm reviewed in 2006. We present an overview of research that has been done since then. A variety of studies have provided interesting new insights into the theory, adding to what is known about the phenomenon of reactance and the processes activated when people are confronted with threats to their freedom. Nevertheless, many issues that have not been clarified remain to be examined. We therefore close with proposing some suggestions for future research.
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