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SamM7
SamM7
April 6, 2021, 5:14 AM
Right on man, looking great!
Kaizenshogun77
Kaizenshogun77
April 4, 2021, 4:49 PM
A review of previous behavioral theory-based interventions used in nutritional and/or health context is needed in order to choose a theoretical framework that can guide the design of an effective intervention capable of overcoming situational constraints.

Social norm theory; social norms are unwritten codes of conduct that are socially negotiated and understood through social interaction (Chung and Rimal, 2016). Social norms are the accepted or implied rules about how people should and do behave. These rules are generally accepted by a group and can guide the attitude, beliefs, and behavior of its members (Berger, 2016). An example is: when at someone else's home, ask permission to do things such as turning on the television or using the bathroom. This implies that the mere presence of others, or rather what is believed about their behavior, influences social behavior and can therefore affect performance (Berger, 2016). When used correctly Social Norms Theory can be very effective in changing individual behavior by focusing on changing misperceptions at the group level. Social norms interventions can be used alone or in conjunction with other types of intervention strategies. The most effective social norms interventions are those that have messages targeted to the at-risk population that are correct and influential. To target messages, a substantial amount of research and data collection has to be invested to understand the norms that exist in the group of interest. Social norms interventions are also most effective when presented in interactive formats that actively engage the target audience (Lamorte, 2018).


Social identity theory (Tajfel & Turner, 2004) further built on social norm theory by positing that group memberships inform one’s identity and that individuals strive to enhance their self-image through in-group bias that favors their social group. Social norms theory, which states that behavior is often influenced by incorrect perceptions about how one’s peers behave (Perkins & Wechsler, 1996), was first successfully introduced in the context of health education to address heavy alcohol use among American college students (Perkins & Berkowitz, 1986; Perkins, 1995). Since then, public health interventions have incorporated social norms to address a wide variety of health issues, including eating habits (Rah, Hasler, Painter, & ChapmanNovakofski, 2004), alcohol consumption (Campo, Cameron, Brossard & Frazzer, 2004), smoking (McMillan, Higgins, & Conner, 2005), drug use, exercise, seat belt use, drunk driving, safer sex practices, sexual assault prevention, and organ donation (Scholly, Katz, Gascoigne, & Holck, 2005). Such interventions attempt to correct misperceptions about unhealthy behaviors or emphasize the influence that people in one’s social environment can have on behavioral intentions. (Chung and Rimal, 2016).

Encompassed within social identity theory is self-categorization theory (Maines, 1989; Turner & Oakes, 1986), which describes how group identification influences behaviors associated with group membership, such as conformity, leadership, stereotyping, and ethnocentrism (Brown, 2000). When examining social norms within the context of nutrition, it may be necessary to consider that the effectiveness of social norms is tied to the relevance of reference group (Berger, 2016). The greater the degree of similarity concerning dimensions like age, gender and attitudes the higher the degree of adoption of certain actions like environmentally friendly behavior ( e.g. Goldstein, Cialdini, & Griskevicius, 2008). An example would be using social norm theory to reduce alcohol drinking in youth groups. Johnson, (2012) ‘s research demonstrated that providing social norms feedback changed perceived drinking norms and that changes in perceived norms were correlated with reduced drinking.

Social Cognitive Theory (SCT) is an interpersonal theory that is applied for surveying psychosocial effects on behavior as well as changing behavior. The theory focuses on mutual interactions of persons, behavior, and environment. A randomized controlled intervention conducted in Iran in 2011 aimed at promoting the intake of fruit and vegetables among students based on social cognitive theory concluded that intervention based on social cognitive theory led to increase in the consumption of fruits and vegetables among students, which confirmed the efficiency of social cognitive theory for such interventions ( Najimi & Ghaffari, 2013). Accordingly, access to Fruits &Vegetables among children depends on personality characteristics (e.g. preferences) and external factors (e.g. availability). SCT emphasizes that environmental and personal characteristics influence behavior, and so, this theory is one of the efficient theories for interventions aimed at promoting Fruit &Vegetable consumption.


Social marketing theory, which incorporates commercial marketing principles in the planning and execution of behavior change interventions takes into account: (1) exchange theory: consumers must perceive a benefit in exchange for their participation /purchase /behavior change; (2) audience segmentation: subgroups similar in some way related to the target behavior or may respond similarly to intervention; (3) marketing mix: a combination of price, product, place, and promotion; (4) customer orientation; and (5) continuous monitoring ( Ramirez et al , 2016). A 2006 Canadian intervention study evaluated innovative communication strategies promoting iron nutrition for infants at risk for iron deficiency anemia (IDA) in a northern Aboriginal community. The results were that multiple communication channels were associated with an increased awareness of IDA and an increased self-reported use of iron-rich infant food. Iron-rich infant food sales increased from pre- to post-intervention (p is greater than 0.05). Breadth of exposure to cooking activity was more limited; however, participants reported increased confidence in preparing
homemade baby food. The study concluded that social marketing communication strategies are a promising strategy for infant IDA prevention where appropriate food is available. (Verrall et al., 2006)

According to McKenzie‐Mohr (2000), Community-based social marketing is composed of four steps: uncovering barriers to behaviors and then, based upon this information, selecting whichbehavior to promote; designing a program to overcome the barriers to the selected behavior; piloting the program; and then evaluating it once it is broadly implemented (McKenzie-Mohr & Smith, 1999). Community-based social marketing merges knowledge from psychology with expertise from social marketing (Geller, 1989). In a case study from the province of Nova Scotia where municipalities throughout the province were developing initiatives to remove organics from the waste stream. Following the principles of community-based social marketing, they first conducted survey research to identify local barriers to backyard composting and determine present levels of backyard composting. This research identified that a surprisingly high number of residents (56%) were composting. Further, this research indicated that in comparison with composters, those who were not composting perceived it to be inconvenient and unpleasant, not the “right thing to do,” and lacked basic knowledge on how to compost. Planners reasoned that one explanation for the absence of community norms supporting backyard composting was the relative invisibility of composting compared to other activities, such as curbside recycling. Accordingly, those who composted were asked to commit to placing a decal on the side of their blue box or garbage container indicating that they composted and served to increase the likelihood that the household would compost more effectively, while at the same time fostering the development of descriptive social norms (Cialdini et al., 1990) in which composting is seen as appropriate behavior. Those who did not composted but said they were interested by it via phone communication were soon contacted and visited by a municipal employee who help them in overcoming their specific barriers. This case study revealed that 80% of those household residents who had expressed an interest in composting were found to be composting in a follow-up several months later (McKenzie-Mohr, 2000).

Theory of Planned Behavior (TPB) is an updated version of the Theory of Reasoned Action ( TRA). According to the theory of planned behavior, intention is the most proximal predictor of behavior. Intention in turn is predicted by three constructs, attitude (evaluation of the behavior and its expected outcomes), subjective norm (perceived social pressure to engage in the behavior), and perceived behavioral control (perceived ease or difficulty of engaging in the behavior). Kothe & Mullan (2014) designed and conducted a theory of planned behavior-based intervention called Fresh Facts. It was designed to promote fruit and vegetable consumption. They found that significant increases in attitude and subjective norm relative to control were found among Fresh Facts participants. However, intention, perceived behavioral control and fruit and vegetable consumption did not change as a result of the intervention. Changes in intention reported by each participant between baseline and follow-up were not correlated with corresponding changes in fruit and vegetable consumption. Fresh Facts was not successful in increasing fruit and vegetable consumption. This study ‘s results does not support the use of the theory of planned behavior in the design of interventions to increase fruit and vegetable intake in this population.
The Health Belief Model (HBM) was developed in the 1950's by social psychologists Hochbaum, Rosenstock and others, who were working in the U.S. Public Health Service to explain the failure of people participating in programs to prevent and detect disease. The HBM contains several constructs that are hypothesized to predict why people engage in prevention, screening, and/or controlling health conditions, e.g.; Personal characteristics, perceived susceptibility and severity of a health condition together, have been labeled as "perceived threat." Perceived benefits help reduce perceived threat about a health behavior. Perceived barriers impede health behaviors. Benefits minus barriers support health behavior change. Self-Efficacy influences perceived threat (perceived susceptibility and severity) and perceived benefits minus perceived barriers, which support initiation of health behavior change. Cues in the environment trigger action and act on individual perceptions, such as perceived benefits, and perceived susceptibility.
In 2013, Labrosse & Albrecht conducted a pilot study test the hypothesis that a learner-centered educational intervention based on the Health Belief Model (HBM) will successfully increase knowledge and consumption of folate-rich foods, while increasing positive beliefs about folate and health in adolescents. A two-group parallel control trial was conducted in two schools in Nebraska. Pre- and post-study questionnaires included a folate-based food frequency questionnaire, an HBM questionnaire and a folate knowledge test. Participants in the intervention group completed a post-study evaluation. The intervention consisted of three 30-min lessons followed by participant creation of podcasts. One podcast was viewed each week for 8 weeks following the lessons. Data were analysed using t-tests to measure simple effects within the intervention and control groups, and analysis of variance to measure within-subject effects between the groups. Folate consumption decreased in both the intervention and control groups, but these differences were not significant (P greater than 0.05). Significant increases (P=0.000) in folate knowledge occurred in the intervention group. This difference remained significant (P=0.001) when compared to the control group. Average HBM rankings significantly decreased (P smaller than 0.05) towards 'strongly agree' (Likert scale of 1-6) in the intervention group (P smaller than 0.05) for all constructs except cues to action. However, when compared to the control group, these differences were only significant for self-efficacy and perceived susceptibility. Creating and viewing podcasts may be helpful for the retention of knowledge over time but did not appear to be an effective cue to action for increased folate-rich foods in this pilot study.


The Integrated Behavioral Model is a combination of the two theories, the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB). The Theory of Reasoned Action used the behavior beliefs and the evaluation of behavior to determine one’s attitude about the behavior that normative beliefs and one’s motivation to comply. It also determines one’s perception of the subjective norms, i.e. subjective norms refer to perceptions about what important others expect one to do (Chung & Rimal, 2016). The Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) were created earlier than the Integrated Behavioral Model (IBM) (Guo, 2007). Fishbein and colleagues expanded the TRA and TPB to include components from other major behavioral theories (Montano & Kasprzyk, 2015). The Integrated Behavioral Model combines parts of the TRA/TPB. Fishbein described a model that would primarily focus on the determinants of behavioral motivation/ intention. The Integrated Behavioral Model is a general theory of behavioral predictions that is assumed to apply to any given situation.
The combination of attitudes and subjective norms is used to identify one’s intention to perform the act. This had the effect of being the most crucial determinant of behavior adoption (Montano and Kasprzyk, 2015). Also, included at the base of the framework are the external variables like demographics, personal traits, attitudes, and other individual norms. The Theory of Planned Behavior adds on with the addition of control as a determinant of behavior (the idea that one’s ability to control beliefs and perceived power determine their perceived authority of the situation). This, along with perceived control as well as attitude and subjective norms, are the constructs that one performs the behavior, and behavior itself. Without motivation/intention, an individual is less likely to carry out a behavior. An individual need to know the knowledge, as well as have the skills to act (Montano and Kasprzyk, 2015). The Integrated Behavioral Model has four additional factors that directly affect whether or not behavior can be carried out:1) Knowledge and skills to perform the behavior. 2) Salience of the behavior. 3) Environmental constraints. 4) Habits. All these factors should be considered for an intervention that is promoting behavior change.
In 2007, the Integrative Behavioral Prediction Model (IMB) provided guidelines for the development of successful HIV/STD interventions, yet few HIV prevention programs have identified which components of the IM have been associated with successful behavioral outcomes. Using structural equation modeling, this study examines in detail how components of the IM assessed prior to, and immediately after, the delivery of an intervention are associated with reported condom use 3 months later among participants in Project RESPECT, a multisite randomized controlled trial testing HIV/STD risk reduction strategies among clients attending public health clinics for sexually transmitted diseases. Overall, the IM predicted condom use at 3 months; there were, however, variations in the relative contribution of differing IM components as a function of gender and type of sexual partner as well as the type of intervention the participant had received (Rhodes et al., 2007).

Transtheoretical Model (TM) of behavior change. The TM consists of various stages of change, processes of change, self-efficacy, and decisional balance. As people change, the processes, self-efficacy, and decisional balance are employed uniquely at each stage (27). The stages of change, conceptualized as when one changes behavior, consist of five stages: precontemplation (not intending to make changes); contemplation (considering a change), preparation (making small changes), action (actively engaging in a new behavior), and maintenance (sustaining change over time). Processes of change are defined as overt and covert activities that individuals use to alter their experiences and environments to modify behavior (28,29). The 10 processes (defined in Table 1) are divided into two higher-order factors representing experiential (where relevant information is generated by an individual's own actions or experiences) and environmental (where the information is generated by environmental events) processes of change (NIGG &COURNEYA, 1998).

Carvalho de Menezes et al., 2014 conducted an intervention based on the Transtheoretical Model that aimed to change the anthropometric and dietetic profile among women in the Primary Health Care in Brazil. The intervention group participated in 10 workshops based on the Transtheoretical Model. Results: Participants in the intervention group showed an improved body perception, reduced weight and body mass index postintervention, and lower consumption of calories and foods high in fat. Significant weight reduction in the intervention group was associated with higher per capita income, reduced consumption of protein, reduced consumption of lipids, and the removal of visible fat from red meat and skin from chicken. Conclusion: The intervention based on the Transtheoretical Model promoted reduction in consumption of foods high in calories and fat, with positive effects on weight and body perception. These results provide evidence of the applicability and benefit of the Transtheoretical Model within primary care.

An updated version of the Health Belief Model was named Health Action Process Approach (HAPA) suggests that the adoption, initiation, and maintenance of health behaviors must be explicitly conceived as a process that consists of at least a motivation phase and a volition phase. The latter might be further subdivided into a planning phase, action phase, and maintenance phase. It is claimed that perceived self-efficacy plays a crucial role at all stages along with other cognitions (Bandura, 1997). For example, risk perceptions serve predominantly to set the stage for a contemplation process early in the motivation phase but do not extend beyond. Similarly, outcome expectancies are chiefly important in the motivation phase when individuals balance the pros and cons of certain consequences of behaviors, but they lose their predictive power after a personal decision has been made. However, if one does not believe in one's capability to perform a desired action, one will fail to adopt, initiate and maintain it. It also bridges the gap between intentions and behavior by considering planning as a construct which has been found to mediate the intention-behavior relation.


So, we can use the 4 knowledge domains of sustainability for transformative action to create an educational tool based on social theories such as Community based social marketing. However, what if people do not want to use it, or quickly stop using it? We must then, design the educational tool to be engaging. According to Stephen Wendel behavioral science researcher and author of the book:” Designing for behavior change, 2013”; (which is based amongst others on BJ Fogg behavior change model, and theory of behavioral economics), explains: “ We designed features on the cutting edge of academic knowledge, with all the indication that if people use those features, we would transform their lives. Well, we found that people just did not use those features. A product that could change behavior is useless if no one wants to use it.” In an given an ideal world, everyone would engage in activities that promote good health and would work to prevent the onset of deleterious health conditions and diseases (Lindsay. J. Della et al, 2008). “You need product and design expertise to build something that people will actually like” (Wendel, 2013). Wendel points to the fact that a product can be effective at teaching but is rendered useless if its usage is unappealing to its potential users. In order to become user efficient, the product or service needs to be designed to overcome the attitude behavior gap by generating motivation and engagement in its users.



Gamification is a relatively new trend that focuses on applying game mechanics to non-game contexts in order to engage audiences and to inject a little fun into mundane activities besides generating motivational and cognitive benefits. Deterding et al. (2011) who identify gamification as “… the use of design elements characteristic for games in a non-game context” That approach presents a more systemic view of the term, pointing out the process of decomposing games into building blocks and introducing them into areas that can benefit and didn’t previously employ such techniques. A different view of gamification presented by Zichermann and Cunningham (2011) endorses gamification as a “process of game-thinking and game mechanics to engage users and solve problems” (Stavros L, 2013). While many fields such as Business, Marketing and e-Learning have taken advantage of the potential of gamification, the digital healthcare domain has also started to exploit this emerging trend. Sardi (2017) conducted a systematic literature review to explore the various gamification strategies employed in e-Health and to address the benefits and the pitfalls of this emerging discipline. A total of 46 studies from multiple sources were then considered and thoroughly investigated. The results show that the majority of the papers selected reported gamification and serious gaming in health and wellness contexts related specifically to chronic disease rehabilitation, physical activity and mental health. Although gamification in e-Health has attracted a great deal of attention during the last few years, there is still a dearth of valid empirical evidence in this field. Moreover, most of the e-Health applications and serious games investigated have been proven to yield solely short-term engagement through extrinsic rewards. For gamification to reach its full potential, it is therefore necessary to build e-Health solutions on well-founded theories that exploit the core experience and psychological effects of game mechanics (Sardi, 2017).

Incorporating the power of social mechanisms might therefore be a promising way to foster SNB in overcoming at least some environmental and health-related challenges.
Gamification is a concept that makes use of social mechanisms such as social influence or interaction by applying game mechanics. In this connection, concepts closely related to self-efficacy are included in the self-determination theory (SDT), which addresses both intrinsic and extrinsic motives for action (Berger & Schrader, 2016). According to Ryan & Deci (2000), intrinsic motivation, refers to doing something because it is inherently interesting or enjoyable, and extrinsic motivation, refers to doing something because it leads to a separable outcome.

The SDT theory is based on three psychological needs: autonomy, competence and relatedness, which can be addressed by gamified interventions contributing to enjoyment, regardless of the specific content, complexity, or genre of games (Przybylski et al., 2010). Game design elements such as feedback and rewards for tasks can foster the feeling of competence in the same way as self-efficacy. This is especially important in motivating people with low initial self-efficacy. At the same time, people with high self-efficacy must also be kept at a task by experiencing satisfaction of the need for competence as well as having the autonomy to maintain or enhance intrinsic motivation (Berger & Schrader, 2016). Through gameplay, we expect to foster the habit of reading ingredients lists, encouraging users to better inform themselves about what they eat and drink. (Spitz, R et al., 2018). Gamification could be used as a behavior change tool that can increase user engagement and retention. Gamification may be a way to meet the need for effective, behavior-specific intervention by turning an intention to eat more sustainably into action (Berger, 2016).


Many authors have reported success examples of gamification as an effective strategy to improve people’s motivation and performance in areas such as education, entertainment,
health and business. Hervas et al., (2017) reviewed the literature on the use of gamification for health, specifically for the promotion of behavioral changes. Their paper describes a systematic review conducted to identify in the literature the gamification elements that are being efficiently used to promote behavioral change. The results of this systematic review evidence the broad terminology related to gamification elements, with different perspectives and levels of abstraction. Based on these results, a taxonomy has been proposed, it identifies and classifies the most common gamification mechanics and relates them with psychological fundamentals on behavioral changes (Hervas et al., 2017). According to the results those gamification mechanisms are: GOALS (Main reasons and way of acting based on users’ ambitions and efforts. STATUS (Set of characteristics of a user that differentiate from the rest). RANDOMNESS (Characteristic of the game that makes it seem unpredictable). APPOINTMENT (Dynamics in which at predetermined time a user must log-in or participate). SCORING (Is the way to feedback the user for his work). And finally, INMERSION (Deep mental involvement in something in the gamified context.)


Gamification and exergames (e.g. the activity of playing video games that involve physical effort and are thought of as a form of exercise) in particular have been broadly employed in health and fitness as an attempt to promote exercise and more active life styles. Motivated by popularity and availability of wearable activity trackers, Zhao et Al (2017) presented the design and findings of a study on the motivational effects of using activity tracker-based games to promote daily exercise. Furthermore, they have investigated user behaviors, usage patterns, engagement, and parameters that affect them. An exergame was developed with an accompanying wearable device, for which different variations of application updates were pushed out periodically over a 70-day period. The results of this long-term study show that the usage of wearable activity trackers during exercise, even when gamified for increased entertainment, sees a consistent decline over time. This decline, however, is observed to be reversible with periodic updates to the game. This work, they believe, can make a significant contribution to solving the user retention problem of gamified health applications.


There have been successful interventions developed to optimize nutritional behavior change through gamification. The FIT Game was a preliminary evaluation of a gamification approach to increasing fruit and vegetable consumption in school developed by Jones et al., (2014). Their objective was to create an incentive-based intervention designed to increase fruit and vegetable consumption tend to yield positive, short-term outcomes. An alternating-treatments design was used to evaluate the effects of the FIT Game on objectively measured fruit and vegetable consumption in one elementary school (n = 251) in Utah. During the Fall 2013 semester, game-based rewards were provided to heroic characters within a fictional narrative read by teachers on days when the school, as a whole, met a fruit or vegetable consumption goal in accord with the alternating treatments design. The results were that, on intervention days, fruit and vegetable consumption increased by 39% and 33%, (p b 0.01, p b 0.05; binomial tests), respectively. Teacher surveys indicated that students enjoyed the game and grade 1–3 teachers recommended its use in other schools. The authors’ conclusion was that this game-based intervention provides a promising step towards developing a low-cost, effective, and sustainable nutritional intervention that schools can implement without outside assistance.

The framework developed by Frisk et al, can thus be used in a gamified educational tool that targets social norms belonging to different reference groups and tailors its gamified mechanisms and educational content according to social norm and identity in order to optimize behavior change. Various industry sectors have identified the potential for increment in consumer interactions and have started implementing gamification mechanism within their strategies; e.g., retailers in India have identified it as an upcoming trend of social media marketing and their customer centric initiatives include gamification in their core process in order to “drive engagement and participation” (Archana, 2012). In Education, gamification has been found to have great potential to motivate students (Lee & Hammer, 2011; Simõesa, Díaz Redondob, & Fernández Vilasb, 2012). In the sustainability sector in particular, research conducted by Kuntz et al. (2012) resulted in the introduction of gamification in the sustainability awareness and efforts of individuals had positive outcome in saving energy, water and reducing gasoline use. (Stavros L, 2013). A recent literature review shows that the majority of the studies yielded positive effects of gamification on engagement, increased motivation and enjoyment (Hamari et al., 2014), but no study was found that examined gamification in the context of behavior change and sustainable food behavior. (Berger. E et al, 2014).

After conducting in-depth interviews with participants regarding a gamified shopping process aimed at motivating ecologically conscious consumption, Lounis et al., (2013) concluded that not all consumers respond / endorse all aspects of gamification in the same degree and different gamification dimensions, result in different outcomes in terms of engagement / stated intention to participate. Hence, the need for personalization. The ability of the proposed gamification scheme to be customizable and personalized should span throughout the entirety of the selected and implemented processes to become efficient. According to Manning (2009), “We humans are hard-wired to take special interest in anything that is related to our own selves. Again, our very survival has historically depended on it. Messages that people perceive to be personally relevant receive significantly more attention and are thus more likely to prompt deeper, deliberate processing.”

Psychographic and demographic data combined should be used to customize content according to segmented reference group, it will improve the relevance of the educational content and also enhance the degree of behavior change. Verain et al., conducted a segmentation study in 2017 aimed at testing whether communication is most effective at changing dietary intentions when tailored to specific consumer segment. Their results outline the importance of segmentation research in the development of dietary messages. In addition, the findings show the importance of taking product category differences into account in studying consumer food motivations and intentions (Verain et al., 2017). From a practical perspective, socio-demographics is often the best way to start segmentation studies because a lot of published information is available and easily obtainable. (Moreover, demographics are often used to enhance the accessibility of segments for subsequent profiling and targeting strategies, since the corresponding media usage profiles are usually available (Wedel and Kamakura, 2000). However, according to Gupta & Odgen (2009), even though socio-demographics are associated with environmental consciousness, their explanatory power is weak. (Gupta and Ogden, 2009) Therefore demographic is insufficient at explaining and predicting environmental awareness and behaviors.

Psychographics or lifestyle segmentation targets customer hobbies and interests. This segmentation strategy caters to the most niche markets, where attractiveness, quality and brand recognition are more important than price. Findings further reveal that social and reference groups, especially peers and other individuals with close proximity to consumers have a stronger influence on consumers’ green purchase decision-making process (Lee, 2010; Salazar et al., 2013; Tsarenko et al., 2013). The more individuals identify with a norm reference group, the more likely they are to follow a norm associated with it (Berger, 2016). Therefore, the more an individual share similar hobbies and interests with a reference group, the more they will identify to the norms the group has adopted as part of their lifestyle.

In the context of comparison with their close friends in the form of ranking, 67% of the sample stated that they would like to know their own environmental consumption (past, current and evolution of) as individuals as well as where they rank amongst their friends (Lounis, 2013).( Gamification elements, leaderboards) To summarize, it can be said that subjective or social norm and reference groups have a positive relationship with consumer green purchase behaviour. (Yatish Joshi and Zillur Rahman, 2015). Padel & Foster, (2005) claim that future research should consider tradeoffs that consumers make between values and product as well as consumer segmentation

Audience segmentation and targeted messaging are potentially valuable tools for enhancing climate change communication. (Donald W Hine et al., 2014). Interventions should be all the more effective the better they are tailored to homogeneous target groups (R. Schwarzer et al., 2014). Knowledge on food ingredients and artificial additives should not only be accessible and legible, but also intelligible and personally meaningful to citizens. (Spitz, R et al., 2018) Audience segmentation research and traditional health behavior theory research can be successfully integrated to yield strong health marketing and communication ideas.

Psychographics and demographics are thus relevant in segmentation strategy for nutritional products. Lindsay J. Della et al., (2008) concluded from her study that psychographic audience segmentations can be valuable tools for developing and designing lifestyle-based primary prevention campaigns. Moreover, combining psychographic and demographic data will further segment the reference group the participants belong to according to social norm theory. We can therefore study the gap between knowledge and behavior according to groups with different social norm and identity to find a pattern.

To design an intervention (gamified nutritional program) that promotes sustainable nutrition behavior, it is important to understand how social norms (descriptive and injunctive) differ regarding their effectiveness and how the reference group has to be designed to achieve maximum effects (Berger et al, 2014) The framework developed by Frisk et al, can thus be used in a gamified educational tool that targets social norms belonging to different reference groups and tailors its gamified mechanisms and educational content according to social norm and identity in order to optimize behavior change.

In order to investigate the effectiveness of gamification in a context as realistic as possible, we have to figure out the best medium (e.g. website, application for smartphone) for implementing our study. People who have a passion for gaming or individuals who grew up with the internet, the use of smartphones and social media (i.e., digital natives) will probably respond differently to gamified interventions. According to Prenzy (2001), digital natives are the native speakers of the digital language of computers, video games and the Internet. On the other hand, those of us who were not born into the digital world but have, at some later point in our lives, adopted many or most aspects of the new technology are digital immigrant. Effective approaches to sensitize consumers and initiate change with regard to SNB are still scarce, not least because nutritional behavior is a complex issue influenced by many factors ranging from the biological and psychological to lifestyle issues
(Berger & Schrader, 2016)

This means that the attitude towards such gamified systems have to also be considered when investigating the effect of gamification on behavior change. We also anticipate different effects according to lifestyle (nutrition habits) and socio demographics (age, income) (Berger. E, 2014). According to Karen Glanz, “The emergence of information technology tools such as the internet, wireless technology, and personal digital assistants have expanded the range of theory-based strategies available for effective behavior change in health care and community settings. Behavioral interventions should be sensitive to audience and contextual factors, and recognize that most behavior change is incremental and that maintenance of change usually requires continued and focused efforts.”

Thus, this segmentation study aims to evaluate how social norms and social identity characteristics are interrelated to gamification and sustainable nutrition awareness and behaviors, the results will help assess how a certain reference group segment should be targeted with gamified educational content for effective behavior change.

Kaizenshogun77
Kaizenshogun77
March 29, 2021, 7:47 PM

I apologize for the organization of things, I have been sending material not in the order it will be presented, which makes it harder for you to understand.


In 1972, the United Nations held a conference in Stockholm on the human environment. This international conference was the first one in history to officially recognize the damaging impact human development has had on the earth’s natural environment (Brisman 2011). In 1984, another UN conference gave rise to a report titled: ‘Our common future’ which introduced a global plan that would provide “the security, wellbeing, and very survival of the planet” (WCED, 1987). This report is more commonly referred to as the Brundtland report, named after the former Norwegian Prime Minister, who in 1984, presided as chairman of the World Commission on Environment and Development. The Brundtland report is established to be of immense historical significance, and one reason that explains its importance is that the concept of ‘sustainable development’ was first introduced to the entire world in this report (Sneddon et al., 2006). Sustainable development was then described as “the ability to make development sustainable, to ensure that it meets the needs of the present without compromising the ability of future generations to meet their own needs” (WCED, 1987). This definition has passed the test of time and has since become the most widely used description of sustainability (Kates et al., 2016).

Academics have yet to reach an agreement on whether the terms ‘sustainable development’ and ‘sustainability’ diverge slightly in their meaning, or whether they are synonymous (Eweje and Bathurst, 2019). For instance multiple scholars regard ‘sustainability’ as the objective ( i.e. the finish line), and ‘sustainable development’ to be the process required to attain such objective (Mancebo 2013; McKeown 2013). This paper judges that the two terms are similar enough in terms of denotation, as well as sufficiently related in terms of content, that they can be used interchangeably. No matter what term you choose to use, the Brundtland report has established 4 central goals at its core: 1) safeguarding long-term ecological sustainability, 2) satisfying basic human needs, 3) and promoting intragenerational and 4) intergenerational equity (WCED, 1987). Those goals are fundamentals and non-negotiables parts of the sustainability movement (Daly, 2007). The Brundtland report provides its audience with an extensive list of suggested legal changes to be implemented by all governments to reach a state of sustainability (e.g., reform of national policies to reach sustainability goals; fortify the power of environmental bureaucracies; increase funding towards environmental restoration, etc) (WCED, 1987).

Since 1987, sustainable development goals have gained an increased importance in national, international and corporate policies (Mebratu, 1998), however, very few reforms have been successfully implemented (Sneddon et al., 2006). For example, a 2014 study measured whether 167 different countries met the level of sustainable development required at the time based on key indicators and threshold values. The study found that not a single country met the required level in the four fundamental dimensions of sustainable development mentioned above, and that some governments were alarmingly far from reaching them (Holden, Linnerud, and Banister, 2014). This can be explained by the fact that sustainability as a concept is both abstract and complex (Eagle et al. 2019; Kates, Parris, and Leiserowitz, 2016), therefore it makes it difficult for anyone to implement procedures aimed at accomplishing such a conceptual goal (Aleixo et al., 2018). Moreover, studies have revealed that not only do governments prioritize sustainable goals to a different extent, but they also understand and interpret those goals quite differently from one another (Lafferty and Meadowcroft, 2000; Mebratu, 1998).

Despite the fact that politicians and scientists have yet to reach an agreement on the exact definition of sustainability, the idea has stayed an ideal political concept throughout several decades (Holden, Linnerud, and Banister 2014; Kates, Parris, and Leiserowitz, 2016). For instance, sustainability has been at the forefront of international preoccupations, as demonstrated in the 2012 Sustainable Development Conference in Rio de Janeiro, as well as the 2015 Paris agreement. Sustainability, as (Lafferty, 2004) phrases it “ is now like ‘democracy’: it is universally desired, diversely understood, extremely difficult to achieve, and won’t go away.” Not only will the sustainability movement not go away, but this it is now more wanted and essential than ever.

Besides policies, education is advocated as a way to reach the reconciliation our economic development with our environment by both the 1976 and 1984 Conferences previously mentioned in this paper. For instance, the Brundtland report stipulates “changes in attitudes, in social values, and in aspirations that the report urges will depend on vast campaigns of education, debate and public participation” (WCED, 1987). Moreover the 1976 report states that: “Governments and policy makers can order changes, and new development approaches can begin to improve the world’s condition; but all of these are no more than short-term solutions, unless the youth of the world receive a new kind of education.” (Fensham, 1976) (Brisman 2011). After measuring the sustainability progress of the 167 countries, (Holden, Linnerud, and Banister, 2014) concluded that implementation issues should be corrected by increasing the public’ acceptance, and participation. According to an edict of the Belgrade conference (Fensham, 1976), the goal of environmental education is: 'To develop a world population that is aware of, and concerned about, the environment and its associated problems, and which has the knowledge, skills, attitudes, motivations, and commitment, to work individually and collectively towards solutions of current problems and the prevention of new ones.' (Robottom 1987). Therefore this paper focuses on the research of how to increase the effectiveness of sustainability education in order to promote sustainable behaviors.

“Achieving sustainability will depend ultimately on changes in behavior and lifestyles, changes which will need to be motivated by a shift in values and rooted in the cultural and moral precepts upon which behavior is predicated” (UNESCO, 1997, p.34).

Education is a necessary component for behavior change (Arlinghaus and Johnston, 2017). Education is defined by the Oxford dictionary as “the process of receiving or giving systematic instruction”; whereas knowledge is defined as “facts, information, and skills acquired by a person through experience or education.” According to Arlinghaus & Johnston: “knowledge is important. It is critical to explain to patients why behavioral changes need to be made.” For example, understanding the health risks associated with smoking is essential in order to make a decision about quitting. Therefore, behavior change cannot occur unless we have the relevant knowledge to understand why a specific behavior should change in the first place.

Most current environmental curriculums teach ecological knowledge. Those educative programs could be summarized in a statement by ecologist Babia Dioum Senegalese: “In the end, we will conserve only what we love. We only love what we understand. We only understand what we are taught” (Purrenhage, 2010; Donahue, 2008, K-12 and Community Programs section). In other words, in order to be able to solve any environmental problem, it is essential to first and foremost understand its roots and the entirety of the system affected by the problem. If we are to transition to a more sustainable society, we must continue teaching ecological knowledge describing how environmental systems function in technical, mechanical and biophysical terms. Current environmental education programs are therefore teaching ecological knowledge to their students as part of their curriculum. However, in spite of this worthy goal, substantial research illustrates how programs have failed to achieve transformative change (Ramsey, 1993). So why are the environmental programs inadequate to produce sustainable behaviors despite sharing ecological knowledge?

Past educational programs have failed because there is a gap between an individual’s thinking and actual actions (Chen and Chai, 2010; Wheale and Hinton, 2007). There can be a discrepancy between someone’s values, beliefs and attitudes towards a subject and the actual behavior performed regarding the subject. While many consumers showed a positive attitude towards purchases of organic food products (67%), only a small number of consumers (4%) actually purchased those product s (Joshi and Rahman, 2015). As Dr. Harold Hungerford, a well-respected environmental educator, stated: “Environmental educators still believe—so very strongly—in the knowledge; attitude; behavior model of learning when, at the same time, we know how desperately inadequate this is when it comes to changing the citizenship behaviors of large numbers of learners over long periods of time” (Simmons & Volk, 2002, p. 7). This indicates that the question of what shapes pro-environmental behavior is such a complex one that it cannot be visualized through one single framework or diagram (Kollmuss and Agyeman, 2002). It is thus clear that previous research has not been able to recognize why a positive consumer attitude fails to convert into a green purchase (Gupta and Ogden, 2009). According to Kollmuss & Agyeman, although many hundreds of studies have been done and numerous theoretical frameworks have been developed to explain the gap between the possession of environmental knowledge and environmental awareness, and displaying pro-environmental behavior, no definitive answers have been found.

The failure of environmental education to broadly change individual behaviors and collective action is primarily due to unsubstantiated assumptions about the relationship between knowledge and behavior (Finger, 2010; Simmons & Volk, 2002; McKenzie-Mohr, 2000; Ramsey, 1993). Knowledge is not enough to change behavior. If it was, no one would smoke or overeat to the point of becoming obese, and everyone would wear seatbelts and exercise (Arlinghaus and Johnston, 2017). Current education systems are inadequate to generate substantial changes in human behavior because they assume that teaching declarative knowledge, on its own, is sufficient to generate behavior change. Declarative knowledge can be defined as factual, technical socio-ecological information (Redman and Redman, 2014). Declarative knowledge usually contains answers to the question of how environmental systems work (Schahn, 1996), for example, knowledge of the side effects of chlorofluorocarbons (CFCs) in the atmosphere (Kaiser and Fuhrer, 2003). The focus on declarative environmental information as the means for targeting behaviors has been termed the Information-Deficit Model (e.g., students just need to understand the environment and then they will behave in a pro-environmental manner) (Redman and Redman, 2014). This simplistic, linear approach to behavior change has been found to be inadequate in addressing the motivators and impediments to changing behaviors (Kollmuss and Agyeman, 2002; Monroe, 2003; Pooley and O’Connor, 2000). The lack of efficacy in sustainability-related educational programs is at least partly due to faulty assumptions about knowledge automatically leading to action, and by extension, the information-intensive methods that focus largely on declarative knowledge regarding how environmental systems work (Frisk et al., 2011).

In order to move away from the Information-Deficit Model of behavior change, sustainability education must incorporate several categories of knowledge based on behavioral theories in order to inform the relationship between education and action (Redman & Redman, 2014). There are actually four distinct types of knowledge: declarative, procedural, effectiveness and social (Kaiser & Fuhrer 2003). Frisk et al., (2011) described the different forms of knowledge using food choices as an example. (1) life cycle analysis, or the human-ecosystem processes by which products are produced, consumed, and decomposed (declarative knowledge); (2) how to read labels and understand the meaning of different certifications, such as organic and fair trade (procedural knowledge); (3) the broader impacts of switching to a more sustainable diet, for instance, how fair trade affects the livelihoods of farmers or how organic farming minimizes pollution while maintaining soil fertility (effectiveness); and, (4) the social desirability of individual decisions and underlying reasons for cultural norms, such as high-meat diets in the U.S. (social knowledge). An educational program embodying all forms of knowledge converging towards a common ecological goal, will encourage ecological behavior more significantly that any exclusive form of knowledge alone (Kaiser & Fuhrer, 2003). Therefore, if current education systems are to create substantial changes in human environmental behavior, then they must incorporate categories of knowledge grounded on behavior theories.

The failure to incorporate behavioral sciences into educational philosophies and practice has resulted in a fundamental inability to promote transformative action, despite the fact that behavior change is often a stated goal of educational programs (Frisk et al., 2011).
Educating for conscious consumerism is a critical part of creating changes in production, consumption and disposal systems, but our current education system and approaches often reinforce unsustainable practices that neglect subjective ways of knowing as well as action and change (Redman & Redman, 2014). The approach to the knowledge domains taken by Kaiser & Furher in 2003 expands beyond the traditional views of knowledge in order to include the subjective and dynamic processing of our environment as a form of knowledge. Kaiser & Furher’s approach of knowledge convergence integrates concepts about values, norms, attitudes and beliefs developed by other behavioral scholars into the domain constructs (Ajzen, 1985; Cialdini et al., 1990; Stern, 2000). The framework developed by Frisk et al in 2014, which is based on Kaiser & Fuhrer ‘s work, serves as a predictor of behavior and can be used to fill the gaps of the different knowledge types necessary to educate for sustainable behavior change; however even the authors of the framework acknowledge that “many other factors, beyond knowledge, influence behaviors and habits”.

We should understand what motivates or constrains individual behaviors and create programs that move beyond information in order to target the predictors of behavior (Redman et al., 2014). Situational factors can hamper environmentally responsible purchasing and lessen the influence of a positive environmental attitude. (Yatish Joshi, and Zillur Rahman, 2015) There seem to be many more factors that influence pro-environmental behavior. Hines et al. (1986–87) called these ‘situational factors’ which include economic constraints, social pressures, and opportunities to choose different actions. Situational factors include: price, product availability, subjective norm/social norm and reference group; Product attributes and quality; Store related attributes; Brand image; Eco labelling and certification; Media exposure. The attitude-intention–behaviour models also ignore external effects of the environmental and situational factors on consumer purchase behaviour. (Carrington et al., 2010; Foxall, 1993). At least 80% of the motives for pro-environmental or non- environmental behavior seem to be situational factors and other internal factors (Fliegenschnee & Schelakovsky, 1998).


Coming up next week: Review of behavior change theories for sustainable beh
Kaizenshogun77
Kaizenshogun77
March 23, 2021, 3:46 AM
POST #2:

Gamification LIT :

Therefore, understanding how to reward users adequately in order to keep them engaged with a dietary mobile application in order to promote, facilitate and maintain sustainable food purchase is needed. I propose that an effective digital intervention promoting sustainable food purchase should combine social norm feedbacks with gamification techniques to reward users adequately and keep them engaged long enough to produce the desired habitual behavior.

Gamification was born in the digital media industry (Berger and Schrader, 2016) and became a worldwide trend around 2010 (Dicheva et al, 2015). Gamification is most commonly defined as “the use of game design elements in a non-game context” (Deterding et al, 2011), and has been established as an effective instrument for engagement and behavior change (Johnson et al., 2016). It is now recognized as a proven technique in the field of Human Computer Interaction (Rapp et al. 2019). Gamification has been widely used in numerous and diverse areas (Sardi et al., 2017), such as education (e.g. to foster the engagement of students) (Dreimane, 2019; Barata et al., 2013), human resource management (e.g. to increase employees’ productivity) (Prasad, M, and Vaidya n.d.; Aziz, Mushtaq, and Anwar 2017), digital marketing (e.g. increase customers loyalty and engagement (Noorbehbahani et al., 2019) health (e.g. to increase physical activity) (Guarneri and Andreoni, 2014; Hagberg et al., 2009; Lindberg et al., 2016), crowdsourcing systems ( e.g. to increase participation and the quality of the crowdsourced work) (Morschheuser et al. 2017), and also environmental sustainability (e.g. to help people conserve more energy and water) (Albertarelli et al., 2018; Ro et al., 2017). Similar concepts have been referred to as: ‘Pervasive games’, ‘Serious-games’ and ‘Game-based technologies’ (Deterding et al, 2011). A more descriptive and recent definition of gamification is “using game-design elements in any non-game system context to increase users’ intrinsic and extrinsic motivation, help them to process information, help them to better achieve goals, and/or help them to change their behavior”(Treiblmaier et al., 2018). Essentially, the goal of gamification research is twofold: to understand how games generate the ability to keep someone’s attention and maintain their engagement level in a given task, and to learn how to apply this knowledge to non-game activities (Rutledge et al., 2018; Deterding et al., 2011).

Unfortunately, even though gamification has positive effects such as increasing user engagement and motivation (Dicheva et al., 2015), the results about its effectiveness can be quite inconsistent (Seaborn and Fels, 2015; Koivisto and Hamari, 2019). On one hand, a paper reviewing whether gamification is effective to increase engagement in online programs found that gamification has substantial positive impacts. More specifically, the online educational programs that used gamification had more visits, more participation in quizzes and discussions, and furthermore more time spent by participants on the gamified programs than their non-gamified counterparts (Looyestyn et al. 2017). On the other hand, while the implementation in education is still fast-growing, there is also a rising number of studies revealing inconclusive and even negative results from implementing gamification in education (Dicheva and Dichev, 2015). For example, a 16 week longitudinal study that divided 71 students in two groups (one gamified class and one non-gamified), demonstrated that students in the gamified course actually ended up less motivated, which caused a them to have lower final exam grade than the non-gamified students (Hanus and Fox 2015). So how can gamification be so successful and such a counterproductive tool within the same context of gamification?


In 2012 Gartner famously predicted that: by 2014, 80% of all gamification intervention will fail to meet their objective largely due to inadequate design. Game systems are so intricate that the slightest flaw or tiniest change in design can have enormous repercussion on the overall experience of the user (Hunicke et al., 2004). For example, a gamified task manager named ‘Habitica’ that aims to help its user be more productive and feel more motivated has actually been found to have the reverse effect due to an inappropriate design of the reward system (Diefenbach and Müssig, 2018). One of the reason ‘Habitica’ failed in its gamification design is the same reason many gamification interventions also fail to have consistent results, they did not understand how to satisfy their users’ psychological needs within the context of a task management application (van Roy and Zaman 2017).

A review of gamification interventions demonstrated that the success rate of gamified interventions is immensely dependent on the context being gamified and, on the user, (Hamari et al., 2014). It was found by multiple academics and researchers that not all context are equally fit to be successfully gamified (Nacke and Deterding, 2017). For example, the library experience was found to be one of the context not fit to be gamified (Kim 2012). Moreover, personality types (e.g. introvert vs extrovert) can influence each individual ‘ learning style and gaming preferences (Codish and Ravid, 2014). For example it was found that: “extraverts tend to be motivated by Points, Levels, and Leaderboards; and people with high levels of imagination/openness are less likely to be motivated by Avatars”(Jia et al. 2016). Therefore, there is a need to know the design guidelines that gamification interventions have learnt to always be reliable throughout every contexts and users.

There are agreements amongst gamification experts and existing studies on what an effective gamification framework must include in order to be effective. For instance, a systematic review on gamification design frameworks used in higher education proved that despite existing differences amongst all existing gamification frameworks, there is a growing consensus on three guidelines: 1; the targeted behaviour (e.g. increased purchases of sustainable foods) must be clearly defined, 2; it is important to analyze the target users and identify player types ( e.g. socialisers, killers, achiever, explorers) (Bartle, 1996), and 3; it must employ the appropriate game design principles based on the player types of the users (Mora et al., 2017). For example, a framework for guiding gamification design, called “activity-challenge-motivation triplets” (Deterding, 2015) has been extensively cited in numerous studies investigating how to effectively and systematically apply gamification for behavior change (Hansen, 2017; Knutas et al., 2019; Morschheuser et al., 2017; Li, 2017). Deterding’s personalized gamification model focuses on combining the examination of both the user and the context being gamified together (Deterding, 2015). Therefore, there is a need to determine a specific context that would be fit to gamification design implementation.

Gamification can be previosuly successfully used in the context of altering nutritional behaviors. For instance, it has been used to decrease the intake of unhealthy foods (Majumdar et al., 2015; Majumdar et al., 2013), teaching food literacy while shopping (Bomfim and Wallace, 2018; Bomfim et al., 2020), promoting fruits and vegetables intake in adolescents (Yoshida et al., 2020), and promoting healthy breakfasts intake (Luhanga et al., 2016). Gamification is perfectly adapted to change food behaviors because games typically have feedback and social comparaison as part of their core features (Webb, 2013). It has been previously established in this paper that food behaviors are habitual and therefore require immediate situational feedback to be altered (Wendel, 2013). It has also been established that food behaviors can be efficiently influenced by manipulating signals found in the social environment (Higgs, 2015). Digital gamification therefore has the potential to increase low impact food choice because it can use the power of social interactions to promote behavior change (Hamari and Koivisto, 2013; Koivisto and Hamari 2019; Hamari and Koivisto, 2015) through game design elements (e.g. points, badges, leaderboards, narratives, customization tools, levels, notifications, progress bars, and time constraints) that can be communicated instantaneously, therefore providing immediate feedback based on certain activities (McGonigal, 2011).

The effective gamification of food behaviors can be successfully implemented within a digital environment. For example, academics at Cornell University researched and developed the use of mobile games that motivate adolescents to eat more healthy breakfasts by providing them with instant feedback through virtual pets (Byrne et al. 2012; Pollak et al. 2010). Moreover a computer based educational game for children at school named “ Quest to Lava Mountain” was shown to help decrease sugar consumption and increase positive attitudes towards physical activity (Beasley et al. 2012; Sharma et al. 2015). Digitally gamified interventions also had success in increasing the time participants were engaged in interventions designed to promote sustainable behaviors, like reducing energy use (Oppong-Tawiah et al., 2020) and increasing sustainable travel (Wells et al., 2014).

The potential of gamification has been identified for the promotion of sustainable nutrition behaviors (Berger et al., 2014; Berger and Schrader, 2016; Kronisch, 2019; Vermeir et al., 2020) and even more specifically in promoting eco-friendly shopping (Lounis et al., 2013). For example, Berger (2019) conducted an experiment in which an online shop was designed to resemble a real shopping environment. Online shoppers were given different types of immediate social norm-based feedbacks adapted to their purchase. She found that using social norms feedbacks with gamification elements was effective at increasing the number of eco-friendly foods the participants would place in their online baskets. Berger, (2019) accomplished this by providing a green meter that indicated the level of eco-friendliness of products accompanied by social norm information as soon as a participant placed a product in their online basket.

The personalized gamification model requires a user analysis that involves defining the target users by examining relevant information such as socio-demographics information, as well as the needs, motivations and hurdles the users have within a specific context (Deterding, 2015; Morschheuser et al., 2017). For example, a meta-analysis review of 54 games for health concluded that personalization should be used according to the behavior change needs and demographics of the users (DeSmet et al., 2014). Multiple gamification researchers suggest that in order to reach a maximum level of efficiency, a gamified systems should be personalized based on who the user is (Hakulinen et al., 2015; Carreño, 2018; Mora et al., 2018; Monterrat et al., 2015). Different frameworks such as Personas, or Player types are then typically used to categorize the target users into different groups, segments or clusters in order to inform the design of the personalized gamification (Morschheuser et al., 2017; Knutas et al., 2019; Monterrat et al., 2015; Orji et al., 2018). There is a need to segment and personalize the gamification design based on the users within a certain context because it was demonstrated that different users understand and react differently to the same game element (i.e. badges) and that the context in which the badge is presented influences how user interpret the meaning of the badge (Antin and Churchill., 2011). Essentially, gamification researchers have learnt that a game that motivates a given individual can discourage another one (Dale, 2014; Monterrat et al., 2014; Orji et al., 2013). Therefore, the design of a gamified intervention promoting and facilitating sustainable food procurement should be based on a segmentation and in-depth analysis of its potential users within the context of sustainable food purchase.


Previous studies researching how to understand and change sustainable food choice state that future researchers should segment the consumers. For example, based on the findings of their survey investigating the influences of environmentally friendly product choice, Dahlstrand and Biel (1997) suggested a behavioral change model that would segment users by the strength of their behavioral habit. Next, after reviewing 53 empirical articles that studied what influences consumers purchasing environmentally friendly products, Joshi & Rahman (2015) ask future researchers to consider consumer segmentation. Moreover, after studying what determines organic food consumption, (Aertsens et al., 2009) state that future research should analyze the motivations and barriers of different user segments based on their organic food behaviors (e.g. non-, light-, medium- and heavy organic food users). This is because an intervention application that can adapt to the user specific situation (e.g. social and environmental context) can improve the effectiveness of the digital intervention (Sucala et al., 2019). Professor B.J. Fogg at the University of Stanford explains in his book ‘Persuasive technology’ (2003) how new technology offers behavior change proponents the advantage of tailor content towards individual needs, interests, personality characteristics, and contexts. Therefore, the design of a gamified intervention promoting and facilitating sustainable food procurement should be based on a segmentation of its potential users and adapted to the context of sustainable food purchase.

Previous studies researching how to understand and change food behaviors using gamification techniques state that future research should segment the users as well. A systematic review of gamification interventions promoting fruits and vegetables intake (Yoshida et al., 2020) asks future researchers to adapt gameful design elements according to population subgroups (i.e. segments). More recently, after experimenting with social norm-based feedback in a gamified online shopping environment, Berger (2019) stated that future studies should consider “elaborate, phase specific, target group specific gamification interventions”. A user segmentation is relevant in the context of sustainable food purchasing since interviews with participants demonstrated that people react very differently to the same aspects of gamification within the same gamified shopping context aimed at promoting eco-friendly purchases (Lounis et al., 2013).

Consequently, the purpose of this study is to conduct a consumer segmentation study aimed at informing the design of an effective digital intervention promoting and facilitating sustainable food behaviors. To the best of my knowledge, no previous research has ever segmented a population in order to inform the design of gamified interventions aimed at promoting sustainable food purchasing.
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