What motivates German consumers to reduce their meat consumption? Identifying relevant beliefs

Abstract

High levels of meat consumption cause problems related to public health, the environment, and animal welfare. Therefore, it is crucial to improve our understanding of the drivers and barriers involved in reducing meat consumption. Using the Theory of Planned Behavior (TPB), we examined to what extent attitude, subjective norm, and perceived behavioral control (PBC) affect intention and willingness to reduce meat consumption. In line with the TPB and going beyond existing literature, we also explored which specific beliefs determine these three constructs. In 2021, we conducted an online survey with a sample representative of the German population (N = 1093). Hierarchical regression models revealed that after controlling for sociodemographic characteristics, the TPB constructs explained 55% of the variance in intention and 61% of the variance in willingness. Importantly, each of the three TPB constructs affected intention and willingness to reduce meat consumption, with attitude having the largest impact. Habit strength and past behavior in addition to the TPB constructs did not improve prediction. Multiple linear regression models showed that attitude was determined by the beliefs that reducing meat consumption leads to a healthier diet, a reduced risk of developing certain diseases, a more natural diet, and the feeling of missing meat. In contrast, environmental and animal welfare concerns showed no significant effect on attitude. Both family and friends contributed to the perceived social pressure. The beliefs of being able to prepare meat-free meals, having enough time to spend on one's diet, and being able to easily purchase meat substitutes led to higher PBC. Based on these findings, we provide recommendations for intervention strategies and derive implications for future research.

Full text

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 1
What motivates German consumers to reduce their meat consumption? Identifying relevant beliefs
Alice Elena Seffen a, b and Simone Dohle a, b
a University of Bonn, Germany
b University of Cologne, Germany
Manuscript accepted at Appetite
Author Note
Alice Elena Seffen, Institute of General Practice and Family Medicine, University Hospital Bonn,
University of Bonn, Bonn, Germany; Social Cognition Center Cologne, Department of Psychology,
University of Cologne, Germany, Email address: alice.seffen@ukbonn.de, ORCID: 0000-0003-0864-0814.
Simone Dohle, Institute of General Practice and Family Medicine, University Hospital Bonn,
University of Bonn, Bonn, Germany; Social Cognition Center Cologne, Department of Psychology,
University of Cologne, Germany, Email address: simone.dohle@ukbonn.de, ORCID: 0000-0003-1535-
5464.
Correspondence concerning this article should be addressed to Alice Elena Seffen, Institute of
General Practice and Family Medicine, University Hospital Bonn, University of Bonn, Bonn, Germany,
Email address: alice.seffen@ukbonn.de.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 2
Abstract
High levels of meat consumption cause problems related to public health, the environment, and
animal welfare. Therefore, it is crucial to improve our understanding of the drivers and barriers involved
in reducing meat consumption. Using the Theory of Planned Behavior (TPB), we examined to what
extent attitude, subjective norm, and perceived behavioral control (PBC) affect intention and willingness
to reduce meat consumption. In line with the TPB and going beyond existing literature, we also explored
which specific beliefs determine these three constructs. In 2021, we conducted an online survey with a
sample representative of the German population (N = 1093). Hierarchical regression models revealed
that after controlling for sociodemographic characteristics, the TPB constructs explained 55% of the
variance in intention and 61% of the variance in willingness. Importantly, each of the three TPB
constructs affected intention and willingness to reduce meat consumption, with attitude having the
largest impact. Habit strength and past behavior in addition to the TPB constructs did not improve
prediction. Multiple linear regression models showed that attitude was determined by the beliefs that
reducing meat consumption leads to a healthier diet, a reduced risk of developing certain diseases, a
more natural diet, and the feeling of missing meat. In contrast, environmental and animal welfare
concerns showed no significant effect on attitude. Both family and friends contributed to the perceived
social pressure. The beliefs of being able to prepare meat-free meals, having enough time to spend on
one’s diet, and being able to easily purchase meat substitutes led to higher PBC. Based on these
findings, we provide recommendations for intervention strategies and derive implications for future
research.
Keywords: Meat; Food choice; Theory of Planned Behavior; Intention; Attitude; Beliefs

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 3
1. Introduction
The Western diet is characterized by high levels of meat consumption which causes serious
problems related to public health, the environment, and animal welfare (Aiking & de Boer, 2020; Clark
et al., 2019; Springmann et al., 2016; Steinfeld et al., 2006; Tilman & Clark, 2014; Willett et al., 2019; Xu
et al., 2021). A dietary shift toward reduced meat consumption would result in major health benefits by
reducing the risks of non-communicable diseases (such as type 2 diabetes, cardiovascular diseases, and
some types of cancer) and by reducing overall mortality (Clark et al., 2019; Springmann et al., 2016;
Tilman & Clark, 2014; Willett et al., 2019). Furthermore, the food system is responsible for
approximately 35% of global greenhouse gas emissions (GHGs, e.g., CO2), thus contributing significantly
to climate change (Xu et al., 2021). Importantly, according to Xu and colleagues, animal-based foods
cause twice as much GHGs compared to plant-based foods. Livestock also contributes to biodiversity
loss, land degradation, and water depletion (Aiking & de Boer, 2020; Steinfeld et al., 2006). In addition,
Clark and colleagues (2019) showed that healthier foods (e.g., vegetables) tend to be more sustainable,
whereas unhealthy foods (e.g., red meat) tend to have high environmental impacts. To reach
international goals as defined in the Sustainable Development Goals (UN, 2015) and the Paris
Agreement (UNFCC, 2015), the EAT-Lancet commission strongly calls for dietary changes (Willett et al.,
2019). The commission proposes a Planetary Health Diet, which includes a significant increase in plant-
based foods and a reduction in meat consumption of more than 50% for countries that currently follow
a Western diet. To achieve such changes in meat consumption, a profound understanding of the drivers
and barriers involved in reducing meat consumption is required.
1.1 Determinants of meat consumption and the motivation to reduce it
Past research has identified multiple factors that influence meat consumption and the
motivation to reduce it (see Graça, Godinho, et al., 2019 and Stoll-Kleemann & Schmidt, 2017 for
reviews). Regarding sociodemographic factors, gender differences are particularly pronounced: males

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 4
consume approximately twice as much meat as females (Max Rubner-Institut, 2008), they are less likely
to be vegetarians/vegans (Paslakis et al., 2020), and show lower intention to reduce meat consumption
(e.g., Çoker & van der Linden, 2022). For the relationship between meat consumption and age, the
literature shows mixed findings (Graça, Godinho, et al., 2019). Meat consumption has also been linked
to socioeconomic status (SES). While eating large amounts of meat has long been a symbol of wealth
and luxury in many countries, individuals with high SES in Western societies are now more inclined to
reduce their meat consumption (Graça, Truninger, et al., 2019; Klink et al., 2022; van der Veen, 2003;
Vranken et al., 2014).
Looking at specific drivers of and barriers to reducing meat consumption, health, environmental,
and animal welfare concerns are important (Graça, Godinho, et al., 2019). Past research has shown that
people tend to believe that meat is a necessary component of a balanced diet and that abstaining from
meat could cause nutritional deficiencies, e.g., protein deficiency (Lea et al., 2006; Lea & Worsley, 2001;
Piazza et al., 2015; Povey et al., 2001). On the other hand, high agreement with health benefits of
reducing meat consumption, such as disease prevention, has been observed (Cheah et al., 2020; Lea et
al., 2006; Lea & Worsley, 2001). Lentz et al. (2018) point out that individuals who reduce their meat
consumption are primarily motivated by health benefits, whereas animal welfare and environmental
concerns appear to be most important for abstainers. Emerging scandals in the meat industry have also
raised public awareness of ethical concerns; in 2016, the vast majority of Europeans (82%) believed that
animal welfare needed improvement (European Commission, 2016). Some studies showed that climate
awareness is associated with the intention to reduce meat consumption (de Boer et al., 2014; Hielkema
& Lund, 2021; Tobler et al., 2011). However, two reviews - one looking at consumer perceptions
regarding sustainable protein consumption (Hartmann & Siegrist, 2017) and one at attitudes toward
meat consumption (Sanchez-Sabate & Sabaté, 2019) - have shown that public knowledge of the link

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 5
between meat consumption and environmental consequences is rather low and that only a minority
reduces their meat consumption due to environmental concerns.
Prior research has shown that eating behavior is influenced by social norms (see Higgs, 2015 for
a review). Social eating norms can be defined as “perceived standards for what constitutes appropriate
consumption, whether that be amounts of foods or specific food choices, for members of a social group”
(Higgs, 2015, p. 39). Different levels of social groups can be important, for example, the national level
(e.g., Germans) and the peer group level including family and friends. Accordingly, Lea et al. (2006)
showed that one of the most frequently perceived barriers to following a low-meat diet are others
(family and friends) who are not willing to adopt this diet. Especially when people live in a shared
household, compromises regarding food must be found. However, family and friends can not only
hinder dietary change, but they can also encourage individuals to reduce their meat consumption
(Hielkema & Lund, 2021; Lea & Worsley, 2001).
Because eating behavior is repeated daily, often in the same places and at the same time, it is
also considered a routine and a highly habitualized behavior (see Riet et al., 2011). A habit can be
defined as a behavior that is based on a learned situation-behavior association and that “has been
repeated until it has become more or less automatic, enacted without purposeful thinking, largely
without any sense of awareness” (Nilsen et al., 2012, p.1). As habits are not guided by intentions but are
automatically evoked by situational cues (e.g., a lunch break at work), it requires a considerable amount
of effort to change them. Accordingly, eating habits have been shown to challenge reductions in meat
consumption (Hielkema & Lund, 2021; Lea et al., 2006; Rees et al., 2018; Saba & Di Natale, 1998; Zur &
Klöckner, 2014). That is, people who report high degrees of meat eating habits, are less inclined to
reduce their meat consumption.
Prior research has shown that cooking skills play a role in healthy food choices (Hartmann et al.,
2013). In line with this, a lack of cooking skills to prepare tasty meat-free dishes has been identified as a

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 6
practical barrier to reducing meat consumption (see Graça, Godinho, et al., 2019). Meat substitutes
could facilitate the preparation of meat-free dishes, but research has shown that they are rarely used
(de Boer et al., 2014; Hagmann et al., 2019; Hielkema & Lund, 2021; Hoek et al., 2011; Michel et al.,
2021). Furthermore, costs also play a role when individuals decide whether to reduce their meat
consumption (see Stoll-Kleemann & Schmidt, 2017). While some individuals seem to believe that a
meat-free or low-meat diet is more expensive and requires more time (e.g., to prepare meals), others
think that it leads to saving money and time (Kemper, 2020; Lea et al., 2006; Povey et al., 2001). Finally,
taste is a driver of meat consumption (Kemper, 2020; Michel et al., 2021; Piazza et al., 2015; Povey et
al., 2001). In a German sample, Michel et al. (2021) showed that “tasty” is the most common association
meat consumers have with meat. Individuals in New Zealand also described a craving for meat (Kemper,
2020). In addition, Graça et al. (2015) showed that meat attachment (reflecting a positive bond toward
meat) is negatively associated with willingness to reduce meat consumption. Piazza and colleagues’
(2015) research highlights that people commonly justify their meat consumption with four arguments:
that eating meat is nice (e.g., “It’s delicious”), natural (e.g., “It’s natural for humans to eat meat”),
necessary (e.g., “Humans need meat to survive”), and normal (e.g., “A lot of other people eat meat”)
(the “4Ns”). Individuals who supported the 4N beliefs consumed meat more frequently and showed
lower willingness to reduce their consumption.
When previous studies examined specific beliefs related to meat consumption reduction, it was
predominantly done without considering a theoretical framework (e.g., Lea et al., 2006; see Graça,
Godinho, et al., 2019). In this study, we used the Theory of Planned Behavior (TPB; Ajzen, 1991) to
examine how individuals’ motivation to reduce meat consumption is shaped. Since the motivation to
reduce consumption has been shown to be rather low among European adults (e.g., Çoker & van der
Linden, 2022; de Boer et al., 2013, 2014; Hielkema & Lund, 2021; Tobler et al., 2011), understanding this
motivation and how it can be changed is an important first step in achieving behavior change. The TPB is

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 7
particularly appropriate for this purpose because it makes detailed assumptions about the socio-
cognitive determinants of intention and allows us to embed specific beliefs into a theoretical
framework.
1.2 The TPB and reducing meat consumption
The TPB, proposed by Ajzen (1985; 1991), is based on the Theory of Reasoned Action (TRA; Ajzen
& Fishbein, 1980; Fishbein & Ajzen, 1975). The TRA proposes that behavior is best predicted by the
intention to perform the behavior in question. Intention reflects how much effort one is willing to invest
in a certain behavior. The TRA states that intention depends on two constructs: attitude (the degree of
favorable or unfavorable evaluation of the behavior) and subjective norm (the perceived social pressure
to perform the behavior). The TPB has extended this theory by the construct of perceived behavioral
control (PBC, the perceived level of difficulty to perform the behavior) to increase its applicability for
more complex behaviors (e.g., food choice). PBC plays a special role because it is expected to influence
both intention and behavior. Furthermore, the three constructs are each based on a set of salient
beliefs.
Because the TPB makes clear assumptions about intention and behavior formation that can be
used to predict any planned behavior, it has been applied to a wide range of domains, reaching from
purchasing behavior and voting decisions to public transportation use and food choice (see Fishbein &
Ajzen, 2010). Importantly, a substantial body of evidence supports the usefulness of the TPB in
predicting pro-environmental behaviors (Bamberg & Möser, 2007) and health behaviors (Conner &
Sparks, 2015). Also, some studies indicate that the TPB is a useful framework to predict meat
consumption and the intention to reduce it (Carfora et al., 2017, 2020; Çoker & van der Linden, 2022;
Povey et al., 2001; Rees et al., 2018). However, none of these studies has embedded specific beliefs into
the TPB.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 8
Çoker and van der Linden (2022) applied the TPB to study meat consumption reduction in the
UK. While some studies found that only attitude predicted the intention to reduce consumption (e.g.,
Lentz et al., 2018), Çoker and van der Linden found that attitude, subjective norm, and PBC each
significantly contributed to the intention to reduce meat consumption. Among the three TPB constructs,
attitude was the best predictor of the intention to reduce consumption. The TPB proved to be a useful
framework, explaining approximately 55% of the variance in intention and 30% of the variance in self-
reported meat consumption reduction (Çoker & van der Linden, 2022). Furthermore, the authors
extended the TPB with past behavior and habit strength. While other studies emphasized that habit is an
important factor beyond the TPB constructs (Rees et al., 2018; Saba & Di Natale, 1998; Zur & Klöckner,
2014), they found that habit neither explained additional variance in intention nor in behavior.
Previous studies that have applied the TPB missed examining which beliefs determine the TPB
constructs, so only general recommendations for increasing the intention to reduce meat consumption
could be offered, e.g., promoting a more positive attitude. While the three TPB constructs are typically
used to predict intention, examining their underlying beliefs is particularly useful to inform interventions
(Ajzen, 2020; Ajzen & Schmidt, 2020; Fishbein & Ajzen, 2010). Attitude is described to depend on
behavioral beliefs which reflect the outcome expectations of the behavior (a person might, for example,
expect that reducing meat consumption leads to a healthier diet). The subjective norm is based on
normative beliefs, that is, the extent to which an individual thinks that certain referents (“important
others”) expect them to perform the behavior. The amount of PBC depends on control beliefs, reflecting
to what extent an individual believes that factors which facilitate or hinder the behavior (i.e., relevant

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 9
resources, e.g., cooking skills) are present.
1
In this study, we aimed to identify such relevant beliefs to
derive more specific recommendations for interventions.
1.3 The present study
The main goal of this study was to contribute to a better understanding of which socio-cognitive
factors shape the motivation to reduce meat consumption using a sample of German adults. Past
research calls for focusing not only on differences between meat eaters and meat abstainers but also on
the variance in the amount of meat that different meat eaters consume (e.g., Cheah et al., 2020). Even
though the number of vegetarians/vegans in Germany is rising, these groups make up only a very small
part of the population overall, estimated at 5.4% (Paslakis et al., 2020). Therefore, we specifically
examined the intention to reduce meat consumption among meat consumers. German consumers
provide an interesting sample, as traditional German dishes are centered around meat and individuals
on average consume approximately 60 kg of meat per year, which clearly exceeds health
recommendations (German Nutrition Society, 2020).
First, we aimed at testing how effectively the TPB explains differences in the intention to reduce
meat consumption. Like Çoker and van der Linden (2022), we examined to what extent the three TPB
constructs contribute to intention after controlling for sociodemographic characteristics. We also tested
the predictive power of the TPB by adding past behavior and habit strength to the model. Some studies
have measured habit strength based on the past frequency of meat consumption (e.g., Graça et al.,
2015, 2016), but it has been argued that it is important to distinguish between the frequency and the
degree of automaticity of a behavior (Gardner, 2015). Based on previous literature (Conner & Sparks,
1
Based on an expectancy-value model (Fishbein & Ajzen, 1975), the TPB in addition states that each of these beliefs is
weighted. Each behavioral belief is therefore multiplied by the outcome evaluation, each normative belief is multiplied by the
motivation to comply, and each control belief is multiplied by the control factor’s power (see Ajzen, 1991). As we will explain in
section 2.3 Data analysis, this paper focuses on the behavioral, normative, and control beliefs without weighting them.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 10
2015; Graça et al., 2015, 2016; Rees et al., 2018; Saba & Di Natale, 1998; Zur & Klöckner, 2014), we
expected both variables to improve the predictive power of the model. Unlike Çoker and van der Linden
(2022), we assessed all TPB variables with multi-item measures to obtain more reliable measures.
Furthermore, we distinguished between the general willingness and the specific intention to
reduce meat consumption (see also Lentz et al., 2018). While the TPB does not differentiate between
willingness and intention (see Fishbein & Ajzen, 2010), stage theories do. Stage theories explain
behavior change by proposing that individuals go through qualitatively different stages within the
behavior change process (see Sutton, 2015). In this process, the formation of a general willingness
precedes the formation of a specific intention. Stage theories claim that interventions must be tailored
to individuals depending on the stage they are currently in. To examine the extent to which willingness
and intention differ and should be distinguished in future research and intervention designs, we added a
measure of willingness to the TPB. We hypothesized that the level of general willingness to reduce meat
consumption will be higher than the level of the specific intention to actually reduce consumption in the
near future.
Second, we aimed at identifying which beliefs determine attitude, subjective norm, and PBC to
provide more specific recommendations for interventions. To the best of our knowledge, this is the first
study to integrate specific beliefs in the TPB while examining the intention to reduce meat consumption.
According to Fishbein and Ajzen (2010), relevant beliefs can be derived from pilot studies. However, as
past research has already identified several drivers of and barriers to reducing meat consumption
(Cheah et al., 2020; de Boer et al., 2013, 2014; Graça et al., 2015; Graça, Truninger, et al., 2019;
Hagmann et al., 2019; Hielkema & Lund, 2021; Kemper, 2020; Lea et al., 2006; Lentz et al., 2018; Piazza
et al., 2015; Povey et al., 2001; Tobler et al., 2011), we aimed at integrating these findings into the
present research. Note that previous studies were predominantly conducted in Western societies, e.g.,

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 11
Switzerland (Tobler et al., 2011) or Australia (Lea et al., 2006); therefore, it seems reasonable to assume
that beliefs identified in previous research would be similarly important for the German population.
Based on the TPB and empirical findings presented above, we tested the following hypotheses:
H1: Females will show higher levels of intention and willingness to reduce meat consumption
than males.
H2: Attitude, subjective norm, and PBC will explain differences in intention and willingness to
reduce meat consumption after accounting for sociodemographic characteristics (i.e., gender,
age, household composition, and socioeconomic status).
H3: Past behavior and habit strength will contribute to intention and willingness over and above
sociodemographic characteristics and the TPB constructs.
H4: Willingness to reduce meat consumption will be more pronounced than intention to reduce
meat consumption.
H5a: Behavioral beliefs will predict attitude toward reducing meat consumption.
H5b: Normative beliefs will predict the subjective norm.
H5c: Control beliefs will predict the amount of PBC.
The preregistration, anonymized data, and analysis code can be found at
https://osf.io/typ96/?view_only=39d046444b4d4fb8b594ebfddf6daf84.
2. Method
2.1 Participants and procedure
To test these hypotheses, we conducted a cross-sectional online study in Germany. In October
2021, participants were recruited through an ISO-certified (ISO 20252:2019) internet panel provider
(Respondi AG, Germany). The sample was representative of the German population in terms of gender

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 12
(male and female) and age (18 to 69).
2
Individuals could only participate if they reported eating meat
(including cold cuts, excluding fish) at least once a week and if they did not follow a specific meal plan
(e.g., a medically prescribed meal plan). After giving informed consent, participants were provided with
all measures. The survey was hosted on Qualtrics and took approximately ten minutes to complete.
Participants received 0.65€ for compensation. This study was conducted consistent with the Declaration
of Helsinki. It was exempt from Institutional Review Board approval by guidelines of the German
Psychological Society DGPS (Deutsche Gesellschaft für Psychologie).
The initial sample consisted of 1388 individuals. Following our preregistration, we excluded
those who failed an attention check (“Please indicate ‘7’ here”, n = 202) and those who indicated that
we should not use their data for analyses (n = 18, see also below). In addition, 75 individuals did not
complete the survey. The final sample consisted of 1093 participants (Mage = 44.35, SDage = 14.51, 50.3%
male, see Table S2 in the Supplementary Material for further sample characteristics).
2.2 Materials and measures
The questionnaire was presented in German. To measure the TPB variables, we followed the
recommendations by Fishbein and Ajzen (2010) and Conner and Sparks (2015). For all TPB variables,
multi-item measures with 7-point Likert scales were assessed.
Intention and willingness to reduce meat consumption were each measured by three items. In
line with Çoker & van der Linden (2022), intention referred to the next four weeks (e.g., “I plan to
reduce my meat consumption within the next four weeks.”, α = .98, 1 = strongly disagree, 7 = strongly
agree), whereas willingness was not related to a specific point in time (e.g., “In general, I can imagine
reducing my meat consumption.”, α = .94, 1 = strongly disagree, 7 = strongly agree).
2
The quotas were based on the Eurostat database (https://ec.europa.eu/eurostat/databrowser/
view/demo_pjan/default/table). They are shown in Table S1 in the Supplementary Material.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 13
Attitude, subjective norm, and PBC each consist of two components (Fishbein & Ajzen, 2010;
Conner & Sparks, 2015): Attitude comprises a cognitive and an affective component, subjective norm is
made up of the injunctive norm (perceived expectations of important others) and the descriptive norm
(perceived behavior of important others) and PBC is a composite of self-efficacy and controllability. To
provide valid measures of the constructs, we assessed all components. Furthermore, based on the
principle of compatibility (see Fishbein & Ajzen, 2010), the three TPB constructs were assessed at the
same level of specificity as intention. To measure attitude, participants completed the sentence
“Reducing my meat consumption within the next four weeks would be…” with six semantic differentials
(α = .95). Three differentials measured the cognitive component of attitude (e.g., unimportant -
important) and three measured the affective component (e.g., unpleasant - pleasant). Four items were
used to assess the subjective norm (α = .84). Two of these captured the injunctive norm (e.g., “People
who are important to me want me to reduce my meat consumption within the next four weeks.”) and
two captured the descriptive norm (e.g., “People who are important to me reduce their meat
consumption.”). PBC was measured with four items (α = .71). Two of these measured self-efficacy (e.g.,
“I am confident that I could reduce my meat consumption within the next four weeks.”) and two
measured controllability (e.g., “It is up to me whether I reduce my meat consumption within the next
four weeks.”). Participants indicated their agreement on a 7-point Likert scale ranging from 1 (strongly
disagree) to 7 (strongly agree). We provide an overview of all items used to measure the TPB constructs
and willingness to reduce meat consumption in the Supplementary Material (Table S3).
In addition, behavioral beliefs, normative beliefs, and control beliefs were measured. In total,
we examined 18 behavioral beliefs. To assess the beliefs, participants indicated their agreement with 18
potential outcomes of meat consumption reduction (“Reducing my meat consumption would make
me…”). Six outcomes were related to health (adapted from Lea et al., 2006): control my weight, eat a
healthier diet, prevent diseases (e.g., a heart disease), eat a more natural diet, suffer a nutrient

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 14
deficiency (e.g., a lack of protein), and feel weaker. We developed four items referring to the
environment (mitigate climate change, protect the environment, eat a sustainable diet, and save CO2;
see e.g., de Boer et al., 2013) and two items referring to animal welfare (reduce animal suffering and
reduce animal slaughtering; see e.g., Tobler et al., 2011). In addition, two items measured the potential
costs of reducing meat consumption (spend more money and spend more time on nutrition; see e.g.,
Kemper, 2020; Lea et al., 2006; Povey et al., 2001). Other items measured the potential barriers of a
worse taste, less eating enjoyment, and the feeling of missing meat (see e.g., Graça et al., 2015; Lea et
al., 2006; Piazza et al., 2015). One additional item captured the symbolic meaning of meat by
investigating the potential barrier of less luxury (see e.g., Logue, 2014; van der Veen, 2003). We also
asked participants to evaluate each outcome (e.g., “Eating healthier would be [...].” 1 = slightly good, 7 =
extremely good).
Furthermore, four normative beliefs were examined. We considered family and friends as
referents (see also Lea et al., 2006; Povey et al., 2001) and measured the injunctive norm (e.g., “My
friends think I should reduce my meat consumption”, 1 = strongly disagree, 7 = strongly agree) and the
descriptive norm (e.g., “How many of your friends reduce their meat consumption?”, 1 = none, 7 = all).
For all four normative beliefs, we also assessed the motivation to comply (e.g., “Regarding my diet, I
want to do what my friends think I should.”, 1 = strongly disagree, 7 = strongly agree).
Moreover, we measured eight control beliefs. For this purpose, participants rated to what
extent the following control factors were present: knowledge about meat-free meals, the ability to
prepare meat-free meals, availability and liking of meat substitutes, knowledge about a healthy diet and
a sustainable diet, money, and time (see de Boer et al., 2014; Hielkema & Lund, 2021; Kemper, 2020;
Lea et al., 2006). We also asked participants to rate the perceived power of each control factor (e.g.,
“Having knowledge about meat-free meals makes reducing meat consumption […]”, 1 = less likely, 7 =
more likely). Table S4 in the Supplementary Material provides an overview of the assessed beliefs.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 15
Habit strength was measured using the four-item Self-Report Behavioural Automaticity Index
(e.g., “Eating meat is something I do without thinking“, α = .92, 1 = strongly disagree, 7 = strongly agree;
Gardner et al., 2012). Past behavior was assessed by a single item asking participants how many meals
with meat they eat per week (1 = 1, 14 = 14 or more).
In addition, sociodemographic characteristics were collected. These included gender, age,
income, education, occupation, and household composition (see Table S2 in the Supplementary Material
for the response options and their coding). The values of income, education, and occupation were
summed to yield an index of socioeconomic status (SES), ranging from 3 to 19 (Winkler-Index; Emrich et
al., 2018; Winkler & Stolzenberg, 2009). Missing values were replaced with the variable’s mean.
3
For
statistical analyses, household composition was divided into two categories: living alone and living in a
shared household.
At the end of the survey, we measured how conscientiously participants completed the
questionnaire by asking them how much effort they invested, how much attention they paid (1 = almost
no, 5 = very much, respectively), and if we should use their data for analyses (yes/no; items taken from
Meade & Craig, 2012). In line with our preregistration, participants who indicated that we should not
use their data for analyses were excluded from analyses.
2.3 Data analysis
Average scores were calculated for intention, willingness, attitude, subjective norm, PBC and
habit strength. Hypotheses 1, 2 and 3 were tested by means of two hierarchical regressions with the
identical three steps, one predicting intention and one predicting willingness to reduce meat
3
For income, data were missing for four participants, for education, data were missing for one participant, and for
occupation, data were missing for six participants (see also Table S2). Results did not change when cases with missing data were
excluded from the analyses. No data were missing for any other sociodemographic variable.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 16
consumption. In the first step, we included sociodemographic characteristics (age, gender, household
composition, and SES; H1). In the second step, the three TPB constructs were added (H2). Finally, we
entered habit strength and past behavior to explore whether it is useful to add these variables to the
model (H3). Mean values of intention and willingness were compared by computing a dependent
samples t-test (H4). Furthermore, we ran three multiple linear regressions to examine which beliefs best
predict attitude (H5a), subjective norm (H5b), and PBC (H5c).
4
None of the five regression models revealed problems with multicollinearity (VIF < 10, TOL >
.10), but all of them showed heteroscedasticity. Therefore, each regression was performed with the
method of weighted least squares. To account for alpha error accumulations, we deviated from the pre-
registered significance level of p < .05 and applied a Bonferroni correction for all regression models.
Therefore, the p-value of 0.05 was divided by the number of predictors for each regression model. All
statistical analyses were conducted with IBM SPSS Statistics (version 28.0).
3. Results
3.1 Descriptive statistics
On average, participants showed a rather positive attitude (M = 4.65, SD = 1.51), a low perceived
social pressure (M = 3.10, SD = 1.38), and a high amount of PBC (M = 5.13, SD = 1.21) regarding reducing
meat consumption within the next 4 weeks. Participants ate about six meals with meat per week (M =
6.04, SD = 3.49) and reported a medium degree of habit strength (M = 3.83, SD = 1.83). While the
4
The TPB originally states that each belief should be weighted, i.e., multiplied by another belief that evaluates the
outcome (see Ajzen, 1991). Based on the TPB, we pre-registered this multiplication and assessed the corresponding beliefs
(outcome evaluations, motivations to comply, and control factors’ power). However, after concerns raised by a reviewer and
careful reflection, we acknowledge that this may be problematic. For example, different scoring systems (unipolar vs. bipolar
scales) lead to different results, and there is no consensus on how to test the multiplicative linking of beliefs, limiting valid
conclusions (see French & Hankins, 2003 for an in-depth discussion). We, therefore, decided to analyze and interpret the
behavioral, normative, and control beliefs without weighting them (see also e.g. Chan et al., 2015). Note that the descriptive
statistics of outcome evaluations, motivations to comply, and control factors’ power as well as the results of the pre-registered
analyses with weighted beliefs can be found in the Supplementary Material (Table S5 and S6).

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 17
general willingness to reduce meat consumption was rather high (M = 4.68, SD = 1.83, Mod = 7.0), the
specific intention to do so within the next 4 weeks was rather low (M = 3.54, SD = 2.01, Mod = 1.0). This
difference was statistically significant, t(1092) = 29.58, p < .001 (one-tailed), d = 0.90, 95% CI [0.82, 0.97].
The bivariate correlations between these variables were all significant (all ps < .001), except for
the relationship between the subjective norm and habit strength (see Table 1). Intention and willingness
to reduce meat consumption were highly correlated (r = .78). The correlations between the three TPB
constructs and the two criterion variables are considered to be medium to high (Cohen, 1988).
[Table 1]
3.2 Predicting intention and willingness to reduce meat consumption
The results of the hierarchical regression models are summarized in Table 2. Step 1 revealed
that gender was a significant predictor for both intention (β = .17, p < .001) and willingness (β = .18, p <
.001), so that females showed higher levels of intention and willingness to reduce meat consumption
than males. Overall, sociodemographic characteristics explained only small amounts of variance in
intention and willingness (R² = .03, p < .001 and R² = .04, p < .001, respectively). The second step showed
that the TPB constructs explained a substantial amount of variance in intention and willingness over and
above sociodemographic characteristics (ΔR² = .55, p < .001 and ΔR² = .61, p < .001, respectively). All
three TPB constructs had significant effects on both intention and willingness (all ps < .001). Intention
was best predicted by attitude (β = .50), followed by subjective norm (β = .30) and PBC (β = .12). Attitude
was also the best predictor for willingness (β = .65), followed by PBC (β = .18) and subjective norm (β =
.11). Interestingly, gender was no longer a significant predictor in these second models, indicating a full
mediation through the TPB constructs. Step 3 showed that neither past behavior nor habit strength
explained additional variance in willingness (ΔR² = .00, p = .478). Past behavior (β = -.10, p < .001) but

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 18
not habit strength (β = .03, p = .116) contributed additionally to intention and explained an additional
1% of the variance (ΔR² = .01, p < .001).
[Table 2]
3.3 Which beliefs determine attitude, subjective norm, and PBC related to reducing meat
consumption?
The results of the three linear regression models are shown in Table 3. Behavioral beliefs
explained 65% of the variance in attitude (p < .001). Four behavioral beliefs significantly contributed to
attitude. Believing that a reduction in meat consumption will result in a healthier diet (β = .18, p < .001)
and a more natural diet (β = .12, p < .001), and will reduce the risk of certain diseases (β = .11, p < .003)
showed positive effects on attitude. Furthermore, the assumption that one will miss meat (β = -.12, p <
.001) when reducing meat consumption had a negative effect on attitude. Overall, the expectation of a
healthier diet was most relevant. It is worth noting that none of the beliefs referring to the environment
and animal welfare showed a significant impact on attitude.
Normative beliefs significantly predicted the subjective norm (R² = .52, p < .001). Family
members’ meat consumption and their expectations as well as friends’ meat consumption showed
positive effects on subjective norm (all ps < .001). In contrast, friends’ expectations showed no effect (β
= .03, p = .391).
Furthermore, control beliefs significantly explained differences in PBC (R² = .28, p < .001). Three
control beliefs showed a significant impact. The beliefs of being able to prepare meat-free meals (β =
.26, p < .001), having enough time to spend on one’s diet (β = .16, p < .001), and being able to easily
purchase meat substitutes nearby (β = .13, p < .001) had positive effects on PBC.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 19
[Table 3]
4. Discussion
Most studies examining the drivers and barriers involved in meat consumption reduction do not
consider a theoretical framework. In this study, we used the TPB and examined not only to what extent
attitude, subjective norm, and PBC predict intention and willingness to reduce meat consumption, but
also which beliefs are central to these three constructs. The results provide insights into which beliefs
might best be addressed by interventions to increase the motivation to reduce meat consumption.
4.1 Willingness and intention to reduce meat consumption
In line with Hypothesis 1, we confirmed the well-established gender effect: females showed
higher levels of intention and willingness to reduce meat consumption than males. Interestingly, the TPB
constructs fully mediated the gender effect (see also Çoker & van der Linden, 2022). This is in line with
the TPB assuming that sociodemographic variables are background factors whose impact on intention
and behavior can be explained by differences in the TPB constructs (see Fishbein & Ajzen, 2010).
Supporting Hypothesis 2, the TPB constructs explained a large amount of variance in intention and
willingness to reduce meat consumption after controlling for sociodemographic characteristics (an
additional 55% and 61%, respectively). Importantly, attitude, subjective norm, and PBC all showed
significant effects on intention and willingness to reduce meat consumption. Consistent with previous
findings (Çoker & van der Linden, 2022; Lentz et al., 2018; Rees et al., 2018; Wolstenholme et al., 2021),
attitude had the largest impact.
Moreover, we found no additional predictive power of habit strength and only a small additional
predictive power of past behavior in explaining intention (an additional 1%). This provides only partial
evidence for our third hypothesis, but it replicates the findings from Çoker and van der Linden (2022).
Our results indicate that the TPB constructs are sufficient and do not need to be extended by past

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 20
behavior or habit strength to predict intention and willingness to reduce meat consumption. This seems
to contradict past research which suggests that habit is one of the most important predictors of eating
behavior (Riet et al., 2011) and of meat consumption in particular (e.g., Rees et al., 2018; Saba & Di
Natale, 1998; Zur & Klöckner, 2014). One possible explanation for these conflicting results is that Saba
and Di Natale (1998) measured the intention to consume meat (a habit-congruent intention), whereas
we measured the intention to reduce meat consumption (a counter-habitual intention). Richetin et al.
(2011) showed that the intention to consume meat and the intention to reduce meat consumption are
independent predictors of meat consumption. Therefore, the authors emphasized that these two
intentions should not be considered simply as opposites. Furthermore, they likely depend on different,
not opposing, variables: for example, the prevention of animal suffering may be a motive for reducing
meat consumption, but causing animal suffering is very unlikely a motive for meat consumption
(Richetin et al., 2011). Possibly, habit strength has a relevant impact on the intention to consume meat
but not on the intention to reduce meat consumption. Furthermore, habit strength as an additional
variable to the TPB has predominantly been studied as a direct predictor of behavior (e.g., Rees et al.,
2018; for a review see Gardner, 2015). In two studies, Rees and colleagues (2018) showed that habit
strength was the best predictor of meat consumption compared to the TPB variables (intention and
PBC). In an additional experimental study, the authors examined how to change the habitualized
behavior. Implementation intentions (e.g., “If I visit the university cafeteria for lunch tomorrow, then I
will choose one of the vegetarian meals”) were an effective strategy to enable individuals with the
intention to reduce meat consumption to actually do so (Rees et al., 2018). We conclude that habit
strength (the automaticity of meat consumption) is of little relevance when it comes to forming the
intention to reduce meat consumption but is indeed an important barrier when it comes to translating
this intention into actual behavior (see also Hielkema & Lund, 2021).

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 21
In this study, we focused on the motivational phase of behavior change and investigated, among
other aspects, the extent to which willingness and intention to reduce meat consumption differ. While
willingness and intention were highly correlated, their mean values differed significantly. In line with
Hypothesis 4, willingness was more pronounced than intention to reduce meat consumption. The results
suggest that meat consumers in Germany are in general rather open to the idea of reducing their meat
consumption, but predominantly do not plan to do so within the next weeks. Overall, the results of the
hierarchical regression models were similar for willingness and intention, but the relative impact of the
three TPB constructs was different. The perceived social pressure seems to be especially important for
developing the specific intention to reduce consumption. Our results indicate that it might be useful to
consider willingness and intention as different stages in the behavior change process.
Taken together, we replicated the findings from Çoker and van der Linden (2022) related to the
intention to reduce meat consumption by using multi-item measures and examining a quota-based
sample of the German population. Our results provide further evidence for the usefulness of the TPB to
explain intention and willingness to reduce meat consumption. Most importantly, attitude, subjective
norm, and PBC all showed significant effects on intention and willingness, indicating that changing each
of the three constructs is a promising strategy to increase the motivation to reduce meat consumption.
4.2 Beliefs, practical implications, and recommendations
Hypotheses 5a, b, and c are supported by the results of the three linear regression models
showing that behavioral beliefs explain 65% of the variance in attitude, normative beliefs explain 52% of
the variance in the subjective norm, and control beliefs explain 24% of the variance in PBC. According to
the TPB, interventions are effective in changing intention and behavior by changing the relevant
behavioral, normative, and control beliefs (Ajzen & Schmidt, 2020). An intervention likely needs to
change more than one belief to show noticeable effects on intention and behavior. In the following

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 22
sections, we therefore discuss which beliefs are most relevant and how interventions could address
those.
4.2.1 Attitude
As attitude showed the strongest effect on intention and willingness, we conclude that
addressing attitude toward reducing meat consumption is most promising to increase the motivation to
reduce meat consumption. Attitude was best predicted by the belief that reducing meat consumption
will lead to a healthier diet. The associated belief that meat reduction will reduce the risk of developing
certain diseases (e.g., a heart disease) was also relevant. This is in line with previous research showing
that health benefits are one of the most important drivers for reducing meat consumption (Cheah et al.,
2020; De Backer & Hudders, 2014; Lea et al., 2006; Lentz et al., 2018; Malek & Umberger, 2021; Marcus
et al., 2022; Tobler et al., 2011). Expecting a more natural diet when reducing meat consumption also
revealed a positive effect on attitude. As we did not define a “natural diet”, it is not clear which aspects
individuals were considering when answering this item. Based on previous research, we assume that
aspects such as the absence of pharmaceuticals (e.g., antibiotics), minimal processing, and positive
attributes like freshness contributed to naturalness (see Román et al., 2017). Based on these findings,
we recommend interventions to communicate that reducing meat consumption (a) leads to a healthier
diet, especially highlighting the preventive function with regard to non-communicable diseases and (b)
leads to a more natural diet.
As none of the beliefs referring to the environment and animal welfare showed a significant
impact on attitude, we assume that providing information about the environmental and animal welfare
related benefits of reducing meat consumption is a less promising approach. One explanation for this
could be that the positive health outcomes that relate to oneself are closer and more under one’s
control compared to the positive effects on animal welfare and the environment, which are more
distant and also depend on the behavior of others. Consistently, two experimental studies showed that

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 23
information about health is more effective than information about the environment in changing
willingness to reduce meat consumption (Cordts et al., 2014) and self-reported meat consumption
(Dijkstra & Rotelli, 2022; but see also Grundy et al., 2022). Informing the public about the environmental
consequences of meat consumption is nevertheless relevant, especially as public awareness in this
regard seems to be low (see Hartmann & Siegrist, 2017; Sanchez-Sabate & Sabaté, 2019). Regarding
animal welfare, a recent meta-analysis showed that interventions strengthening the meat-animal
association can effectively reduce meat consumption, at least for the short term (Marthur et al., 2021).
Based on our results, we suggest that interventions should predominantly provide health information
and that information about the environment and animal welfare should rather be combined with health
information. However, the most suitable information likely varies between consumer segments (see
e.g., Kwasny et al., 2022; Malek & Umberger, 2021; Verain et al., 2022). This needs to be further
investigated in experimental studies.
Furthermore, the expectation that one will miss meat when reducing meat consumption
showed a negative impact on attitude. To counter this belief, it might be helpful to provide a variety of
different meat-free recipes to show that a wide range of dishes can be covered without meat. In
addition, meat substitutes or innovations such as in-vitro meat could be useful to maintain familiar
dishes and similar flavors. Policymakers could expand the opportunities which allow individuals to have
positive experiences with meat-free dishes. This could be achieved, for example, by offering more meat-
free meals in canteens and providing them as default option (Harguess et al., 2020; Kwasny et al., 2022).
Another option could be to offer cooking classes as involvement in meal preparation can increase liking
of foods (Dohle et al., 2014, 2016).
4.2.2 Subjective norm
Believing that family members and friends reduce their meat consumption and that family
members expect one to do so increased the perceived social pressure to reduce meat consumption,

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 24
whereas friends’ expectations showed no effect. Overall, the results suggest that family members and
friends are important referents that could increase the motivation to reduce meat consumption (see
also Hielkema & Lund, 2021; Lea & Worsley, 2001; Sharps et al., 2021). Thus, interventions are expected
to be especially effective when they consider a person’s social environment.
On average, the perceived social pressure to reduce meat consumption was rather low (see also
Rees et al., 2018). This is not surprising given that most German citizens do not reduce their meat
consumption. Experimental studies have shown that, in general, information about the eating habits of
others significantly influences food choices (Robinson et al., 2014). In the case of reducing meat
consumption, Sparkman and Walton (2017) found that information about the dynamic norm (how many
people recently started to reduce their meat consumption) can be effective. Because recent studies
failed to replicate this finding (e.g., Aldoh et al., 2020; Çoker et al., 2022), further investigations are
needed to explore how a dynamic norm message can be an effective intervention to reduce meat
consumption. Social norms can also be shifted in other ways; for example, role models, such as
celebrities who advocate a low-meat diet, may drive such social change (Stoll-Kleemann & Schmidt,
2017). Also, changes in the environment, e.g., offering more meat-free dishes in canteens, hospitals,
schools, and restaurants could normalize a low-meat diet.
4.2.3 Perceived behavioral control
PBC was higher for participants who stated that they are able to prepare meat-free meals, that
they have enough time to spend on their diet, and that they can easily purchase meat substitutes
nearby. Based on the TPB, we expect that cooking skills, time, and the availability of meat substitutes do
not only impact the intention to reduce meat consumption but also enable individuals to implement this
intention.
The ability to prepare meat-free meals was most relevant for PBC. Therefore, improving cooking
skills seems an important strategy to enhance PBC. This is in line with prior research showing that

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 25
cooking skills contribute to healthy food choices (Hartmann et al., 2013). Several experimental studies
have shown that cooking classes can effectively reduce meat consumption and increase the intake of
plant-based foods (Kwasny et al., 2022). However, it is worth noting that these studies predominantly
examined specific groups, e.g. people with illnesses (Carmody et al., 2008) or with low SES (Flynn et al.,
2013). On average, the ability to prepare meat-free meals was rather high in our representative German
sample (M = 6.26, SD = 1.35, see Table S4). Therefore, it seems reasonable that cooking classes may be
especially effective for specific groups which show low cooking skills. Suitable target groups and
contexts remain to be explored. Schools, for example, could be a particularly important context for
targeting individuals with different backgrounds and establishing healthy eating habits at young age.
Reporting to have enough time to spend on one’s nutrition was associated with higher levels of
PBC. People who are busy, for example because they have many family and work obligations, may find it
particularly difficult to change their diet. It is therefore important to communicate that there is a wide
variety of vegetarian dishes, including those that can be prepared very quickly and easily. In addition,
interventions could emphasize the importance of being mindful of one's diet and setting aside time to
prepare and eat meals.
Furthermore, the possibility to easily purchase meat substitutes nearby led to higher PBC. This
implies an intervention that alters environmental conditions, i.e., increases the availability of meat
substitutes. Given that meat substitutes are in general rarely used (see e.g., Michel et al., 2021), it is
possible that some participants did not even know where to purchase meat substitutes or what exactly
is meant by the term. Therefore, to increase PBC, interventions could expand the availability of meat
substitutes and attempt to increase their popularity and acceptance.
4.3 Limitations and future research
This study is not without limitations. First, we assessed intention and willingness to reduce meat
consumption, but we did not assess the subsequent behavior, namely meat consumption. While

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 26
intention has been shown to be a good predictor of behavior (Armitage & Conner, 2001), research has
consistently shown an intention-behavior gap, indicating that high levels of intention do not necessarily
lead to the intended behavior. The drivers and barriers identified in this study, along with the
interventions we propose, are mainly relevant for individuals in the motivational phase of behavior
change. If individuals with high levels of intention try to reduce their meat consumption, other factors
(e.g., habit strength) are expected to be relevant and therefore also other behavior change strategies
(e.g., implementation intentions) are required (see Hielkema & Lund, 2021; Rees et al., 2018). Future
research thus also needs to carefully look at the transition from intention to behavior.
Second, we studied a sample representative of the German population, and it is not clear to
what extent our results can be generalized to other (Western) countries. Future research could
investigate how and why (Western) societies differ in their determinants of meat consumption
reduction (see e.g., Wolstenholme et al., 2021). In addition, we want to emphasize that future studies
that aim to investigate the beliefs underlying the TPB constructs should be aware of the problems
associated with the proposed expectancy-value model (see French & Hankins, 2003). Accordingly, we
recommend carefully planning in advance how beliefs will be assessed and analyzed. In examining
relevant beliefs, future research could also differentiate between consumer segments to develop more
tailored interventions.
Another limitation arises from the cross-sectional design of this study: as all results were
correlative, no conclusions about causality can be drawn. However, our results provide interesting
starting points for experimental studies. These could investigate how the beliefs identified in this study
can be changed and how this affects the three TPB constructs, the intention to reduce meat
consumption and actual meat consumption. Interesting questions in this context include how
information (e.g., about health benefits) might best be framed, combined, and tailored (Harguess et al.,

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 27
2020; Kwasny et al., 2022). In addition, more field studies are needed to evaluate the practical
implementation of the proposed interventions (see e.g., Weingarten et al., 2022).
5. Conclusion
The TPB is a useful framework to predict and explain the motivation to reduce meat consumption.
Attitude, subjective norm, and PBC explained substantial amounts of the variance in intention and
willingness to reduce meat consumption after controlling for sociodemographic characteristics. Extending
the TPB with past behavior and habit strength did not improve the model’s predictive power. Examining
the underlying beliefs of the three TPB constructs revealed that attitude was predicted by the beliefs that
reducing meat consumption leads to a healthier diet, a reduction in the risk of developing certain diseases,
a more natural diet, and the feeling of missing meat. Family and friends both contributed to the perceived
social pressure. The beliefs of being able to prepare meat-free meals, having enough time to spend on
one’s diet, and being able to easily purchase meat substitutes showed positive effects on PBC. How these
beliefs can be changed and to what extent this increases the motivation to reduce meat consumption and
consequently reduces meat intake needs to be examined in future research, especially by using
experimental and longitudinal study designs.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 28
CRediT author statement
Alice E. Seffen: Conceptualization, Data curation, Formal analysis, Investigation, Methodology,
Resources, Writing - original draft, Writing - review & editing. Simone Dohle: Conceptualization, Data
curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision,
Writing - review & editing. Both authors have seen and approved the final, submitted version of this
manuscript.
Ethical statement
The study was conducted consistent with the Declaration of Helsinki. The study is exempt from
Institutional Review Board approval by guidelines of the German Psychological Society DGPS (Deutsche
Gesellschaft für Psychologie).
Funding
This research did not receive any specific grant from funding agencies in the public, commercial,
or not-for-profit sectors.
Declaration of interest
None.
Data availability
Anonymized data, analysis code and the preregistration can be found at
https://osf.io/typ96/?view_only=39d046444b4d4fb8b594ebfddf6daf84.
Acknowledgements
We thank Julia Meis-Harris for proofreading the manuscript. In addition, we thank Antonia
Dörnemann for her help with the tables.

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 29
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GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 40
Table 1
Means, standard deviations, reliabilities, and correlation matrix.
Note. Variables were measured on 7-point Likert scales, except for past behavior which assessed the
number of meals with meat per week (1 = 1, 14 = 14 or more).
a α = Cronbach‘s alpha. b PBC = perceived behavioral control. c No reliability was calculated due to the
single-item measure.
*p < .001.
Variable
M
SD
αa
1
2
3
4
5
6
Attitude
4.65
1.51
.95
Subjective norm
3.10
1.38
.84
.53*
PBCb
5.13
1.21
.71
.37*
.19*
Habit strength
3.83
1.83
.92
-.16*
-.06
-.35*
Past behavior
6.04
3.49
---c
-.35*
-.21*
-.32*
.32*
Intention
3.54
2.01
.98
.71*
.59*
.36*
-.13*
-.35*
Willingness
4.68
1.83
.94
.79*
.51*
.42*
-.14*
-.33*
.78*

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 41
Table 2
Hierarchical regression models predicting intention and willingness to reduce meat consumption.
Note. Both regressions were conducted with weighted least squares.
B (95%CI) = unstandardized regression coefficient and its 95% confidence interval. SE B = standard error
of the unstandardized regression coefficient. β = standardized regression coefficient.
a 0 = male, 1 = female. b 0 = single-household, 1 = shared-household. c SES = socioeconomic status.
d PBC = perceived behavioral control.
*Significant after Bonferroni correction (p < .006)
Step and predictor
Intention
Willingness
B (95%CI)
SE B
β
R²
∆R²
B (95%CI)
SE B
β
R²
∆R²
Step 1
.03*
.03*
.04*
.04*
Age
.00 (-.01, .01)
.00
-.02
-.01 (-.01, .00)
.00
-.06
Gendera
.67 (.44, .91)
.12
.17*
.62 (.41, .82)
.10
.18*
Householdb
.20 (-.06, .46)
.13
.05
.32 (.10, .55)
.12
.09
SESc
.01 (-.02, .04)
.02
.02
.01 (-.02, .04)
.01
.02
Step 2
.58*
.55*
.65*
.61*
Age
.00 (-.01, .01)
.00
.01
-.01 (-.01, -.01)
.00
-.08*
Gendera
.11 (-.05, .27)
.08
.03
.05 (-.08, .18)
.06
.02
Householdb
.08 (-.09, .25)
.09
.02
.24 (.10, .38)
.07
.07*
SESc
-.02 (-.05, -.00)
.01
-.05
-.02 (-.04, .00)
.01
-.04
Attitude
.66 (.59, .72)
.03
.50*
.78 (.73, .83)
.03
.65*
Subjective norm
.44 (.37, 51)
.04
.30*
.14 (.09, .18)
.03
.11*
PBCd
.19 (.12, .26)
.04
.12*
.25 (.20, .31)
.03
.18*
Step 3
.59*
.01*
.65*
.00
Age
.00 (-.00, .01)
.00
.02
-.01 (-.01, -.01)
.00
-.08*
Gendera
.07 (-.10, .23)
.08
.02
.05 (-.08, .18)
.07
.01
Householdb
.08 (-.09, .25)
.09
.02
.24 (.10, .38)
.07
.07*
SESc
-.02 (-.04, -.00)
.01
-.04
-.02 (-.03, .00)
.01
-.04
Attitude
.63 (.56, .69)
.03
.48*
.77 (.72, 83)
.03
.65*
Subjective norm
.43 (.37, .50)
.03
.30*
.13 (.08, .19)
.03
.11*
PBCd
.17 (.10, .25)
.04
.11*
.26 (.20, .32)
.03
.18*
Habit strength
.04 (-.01, .08)
.02
.03
.02 (-.02, .05)
.02
.02
Past behavior
-.06 (-.08, -.03)
.01
-.10*
-.01 (-.03, .01)
.01
-.02

GERMAN CONSUMERS’ MOTIVES TO REDUCE MEAT CONSUMPTION 42
Table 3
Multiple linear regression models: beliefs predicting attitude, subjective norm and PBC.
Note. All regressions were conducted with weighted least squares.
B (95%CI) = unstandardized regression coefficient and its 95% confidence interval. SE B = standard error
of the unstandardized regression coefficient. β = standardized regression coefficient.
a Items marked with a minus “(-)” were expected to be negatively correlated with attitude. b PBC =
perceived behavioral control.
*Significant after Bonferroni correction (p < .003 for Regression 1, p < .013 for Regression 2, p < .006 for
Regression 3).
Predictor variable
B (95%CI)
SE B
β
R²
Regression 1: Behavioral beliefs predicting attitude
.65*
Health
Control weight
.02 (-.01, .06)
.02
.03
Eat a healthier diet
.15 (.08, .22)
.03
.18*
Reduce the risk of diseases
.09 (.03, .15)
.03
.11*
Eat a more natural diet
.11 (.06, .16)
.03
.12*
Develop a nutrition deficiency (-)a
-.03 (-.06, .00)
.02
-.04
Feel weaker (-)
-.03 (-.08, .01)
.02
-.04
Environment
Mitigate climate change
.06 (-.01, .13)
.04
.08
Protect the environment
.08 (-.00, .16)
.04
.10
Eat a sustainable diet
.02 (-.05, .09)
.03
.02
Save CO2
-.05 (-.12, .02)
.04
-.06
Animal welfare
Reduce animal suffering
.05 (-.02, .11)
.03
.05
Reduce animal slaughtering
.08 (.02, .14)
.03
.09
Costs
Spend more money (-)
.02 (-.02, .05)
.02
.02
Spend more time (-)
.02 (-.02, .05)
.02
.02
Other
Less eating enjoyment (-)
-.10 (-.17, -.03)
.04
-.13
Worse taste (-)
-.06 (-.14, .01)
.04
-.08
Miss meat (-)
-.09 (-.14, -.05)
.02
-.12*
Less luxury (-)
-.02 (-.06, .02)
.02
-.03
Regression 2: Normative beliefs predicting subjective norm
.52*
Friends’ expectations
.03 (-.04, .10)
.04
.03
Friends’ behavior
.30 (.24, .36)
.03
.32*
Family expectations
.20 (.14, .27)
.04
.23*
Family behavior
.24 (.18, .29)
.03
.27*
Regression 3: Control beliefs predicting PBCb
.28*
Knowing meat-free meals
.03 (-.04, .10)
.04
.04
Ability to prepare meat-free meals
.22 (.15, .29)
.03
.26*
Availability of meat substitutes
.09 (.05, .13)
.02
.13*
Liking meat substitutes
.02 (-.02, .05)
.02
.03
Knowledge about a healthy diet
.07 (.01, .14)
.03
.09
Knowledge about a sustainable diet
.00 (-.06, .07)
.03
.00
Money
.04 (.00, .08)
.02
.06
Time
.11 (.06, .15)
.02
.16*