Different Types of Behavioural Change Model

Subject: Psychology
Pages: 12
Words: 3324
Reading time:
15 min
Study level: Undergraduate

Introduction

The actions of a person are, as a rule, determined by the patterns of behavior that are familiar to him or her. In an unusual situation or before the need to choose, he or she can take a completely unexpected step or follow one of the previously tested strategies. People with a diverse set of communicative strategies are easier to adapt in non-standard situations as they are more likely to make informed and responsible decisions (Sallis, Owen, & Fisher, 2015). While planning an innovation introduction and preparing policies, companies and the government need to take into account that some resistance may occur in response to new ideas (Lokhorst, Werner, Staats, van Dijk, & Gale, 2013). In order to facilitate their acceptance, it is important to apply one or several behavior change models to anticipate reactions and prevent misunderstanding. This section aims at providing a robust literature review on the contemporary models of behavior change applied in social sciences.

Transtheoretical Change Model

In 1982, James Prochaska and Carlo Di Clemente developed an original model of behavior change. According to this model, changes in behavior are a sequence of several stages, each of which requires growing changes in the views of an individual (Clark, 2013). In terms of the transtheoretical model (TTM), the process of behavior alteration consists of two components as reflections and actions. To guide individuals, there are five key stages in the following sequence: pre-contemplation, contemplation, preparation to act, action, and preservation. At the stage of pre-contemplation, a person does not yet have a serious intention to change his or her behavior at least in the next six months (Clark, 2013). This period was chosen as a criterion since it seems to be the maximum for planning some changes in behavior in the future. The process of contemplation is the period when a person begins to consider the possibility of changing his or her harmful behavior by evaluating both advantages and disadvantages of the current lifestyle.

The preparation stage begins when a person intends to change his or her behavior in a short period of time. Usually, during the year before this, some attempts have already been made, and now there may be small but essential steps through new efforts (Kowalski, Jeznach, & Tuokko, 2014). In terms of the balance of decisions, benefits are outweighed by pitfalls, although both are still critical. The action stage follows a drastic change in a lifestyle and is characterized by the stable preservation of the new behavior, while potential problems may be associated with avoidance of relapse. At the stage of action, behavioral processes of change are most active, and the degree of temptation decreases rapidly. Ultimately, the maintenance stage includes the period after the expiration of six months from the moment of obvious behavioral change until the time when the unwanted behavior is finally overcome.

It is important to note that this model reflects the process of deliberate behavior change when a person thinks about this and controls what happens. Even though TTM is largely used in healthcare to assist patients with alcohol abuse, obesity, and depression prevention, the recent trend is the focus on travel research. Friman, Huck, and Olsson (2017) conducted the literature review and found that the implementation of TTM leads to positive behavioral changes. In their turn, Diniz, Duarte, Peres, de Oliveira, and Berndt (2015) researched the role of education in promoting bicycle use and concluded that the intervention was effective. These studies show the great potential of TTM and the possibility to use it alone or in combination with other change models.

Self-Efficacy Model

As a part of the social cognitive theory (SCT), self-efficacy may be understood as an individual’s conviction in his or her abilities to handle difficult situations based on personal behavioral competence (Glanz, 2015). Those who perceive themselves as self-efficient are likely to make more efforts to resolve complex problems compared to those who have doubts about their capabilities. Albert Bandura, the founder of the self-efficacy model, believes that reward and punishment are insufficient to teach a new behavior, while imitation models compose the key to change (Mazur, 2016). One of the manifestations of imitation is the process of identification in which a person borrows thoughts, feelings, and ideas. Mazur (2016) states that Bandura understands belief in one’s own strength as confidence in planning and implementing target actions in order to accomplish the preferred outcome. A belief in one’s strength develops based on a comparison of one’s achievements with the successes of other people. It controls the level of human activity and, accordingly, the entire development.

It is rather significant to emphasize that the immediate environment of a person provides feasible tasks that stimulate him or her to further activity. For example, if a young girl is afraid of a threatening situation, then she may experience two forms of behavior such as avoiding or overcoming it. The latter is possible only if she is confident that he will cope with it. The most important factor affecting the feeling of self-confidence is an example of a positive experience of success (Faqih, 2013; Lent & Brown, 2013). In other words, her willingness to overcome a frightening situation will be higher if she can observe how other people or her family members handle it.

In his interpretation of the self-efficiency phenomenon, Bandura proceeds from the wide use of symbolic representations of events in the environment by people. Without recognition of such a symbolic activity, it is extremely difficult to explain the incredible flexibility of human behavior (Bullough, Renko, & Myatt, 2014). The mentioned scholar formulates the thesis that changes in behavior caused as a result of classical and operant conditioning as well as extinction and punishment are actively mediated by cognition. In the context of self-efficacy, people regulate their behaviors with the help of a visual representation of their consequences (Renkl, 2014). The formation of links between a stimulus and the subsequent reaction is influenced by these processes of self-control. Bandura’s work played a significant role in the emergence of innovative approaches to therapeutic and social interventions. The most noticeable benefit is the application of modeling procedures in order to form new cognitive and behavioral competencies through change.

Health Belief Model

The health belief model is one of the earliest and most widely used to explain risky and proactive behavior and address it. It was developed in the 20 century to understand the reasons for low participation in free government programs for the prevention and diagnosis of various diseases (Montanaro & Bryan, 2014). According to this model, the likelihood that a patient will take preventive measures depends on a set of factors. In particular, perceived susceptibility, severity, benefits, and barriers play a vital role in one’s behaviors. For example, to adjust his or her behavior, a person should be aware of vulnerability to sexually-transmitted infections (STIs), which implies awareness of the riskiness of this type of behavior in general (Montanaro & Bryan, 2014). Thus, patients who are aware of the importance of using condoms may not consider it necessary to use them if they have only one sexual partner. Thus, it is not just awareness that is important, but awareness of personal vulnerability to STIs.

Willingness to visit a doctor or eliminate an inappropriate behavior depends on two factors: the degree of awareness of the threat to health and the belief that certain behaviors will reduce this threat. The health belief model clarifies the unwillingness of young people to adhere to such behaviors that decrease the risk of an accident or dangerous illness. According to O’Connor, Martin, Weeks, and Ong (2014), they do not consider the threat real, so they are reluctant to change their behavior. For the same reason, many older people cannot address bad habits, for example, smoking since they do not believe that such a refusal will significantly reduce the threat to their well-being. Knowing that behavior awareness is critical allows creating interventions that would clearly represent potential adverse effects, which is likely to help people to reconsider their actions.

Fogg Behavior Model

Among the total number of everyday activities and those that are more complicated, there are few of those that people have learned to do with ease. More often, everything new passes through the initial rejection and opposition (Oinas-Kukkonen, 2013). In the fields of the workplace environment, transportation, or any other area, the document flow, the corporate values, and goals may encounter resistance. As noted by Masthoff, Grasso, and Ham (2014), in order to ensure that change in behavior will occur, it is necessary that three elements coincide at one time, including motivation, ability, and triggers. According to Fogg’s behavior model, if the behavior does not change, it means that at least one of these three components is missing.

Motivation types may be different such as reward or threat of penalty, each of which is equally effective in both horizontal and vertical directions (Cameron & Green, 2015). In general, motivators can be divided into internal ones and external ones depending on the situation. The internal motivators may involve curiosity, comfort, competitiveness, recognition, and a number of other factors unrelated to external circumstances (Riekert, Ockene, & Pbert, 2013). Intrinsic motivators are difficult to change, they should be realized and used to benefit people and improve their behaviors (Crutzen, 2014). External motivators are financial rewards, public recognition, promotion, or threat of dismissal – they can be artificially created, yet they work in a shorter term than internal ones.

The concept of the ability refers to the fact of how easy it is for a person to change his or her behavior (Riekert et al., 2013). It is critical to pay attention to skills that people have not yet mastered, and additional time along with emotional and physical efforts should also be taken into account. Interestingly, the ability is not a property of a product, but it is a property of a person. At the same time, Gabrielli et al. (2014) suppose that it is more difficult for some people to perform one or another activity is much more difficult than for others. Therefore, personal attitudes and abilities should compose the basis of potential change. In order to increase skills, it is important to teach people, offering relevant training, books, educational videos, technical support, et cetera.

Triggers are events that force one to change one’s behavior, be it a positive or negative incentive. For example, a reminder, message, personal request, to-do list, a phrase heard, or image is seen may be listed among the most widespread triggers (Riekert et al., 2013). With different levels of motivation and skills, various types of triggers are used. If the motivation and abilities are high, then a trigger is needed. In case, motivation is high, and skills are insufficient, one needs an instruction type trigger to encourage others. Thus, the combination of the three mentioned components is vital for achieving change in one’s behavior.

Based on the identified Fogg behavior model, it is possible to suppose a hypothetical situation when a company needs to create a corporate portal as an effective and visited place. The first step towards employee engagement is that employees post their photos in a user profile, which can be organized through a competition for the best profile (Riekert et al., 2013). In light of the above model, it is necessary to assemble three components: motivation, skills, and triggers. The motivators can be the recognition of colleagues, the desire to look beautiful, competitiveness, or even social pressure from your colleagues. To make it easy for people to fill out a profile, it is worth publishing a video about creating a profile, creating various nominations, inviting a professional photographer, and arranging a vote (Schoech, Boyas, Black, & Elias-Lambert, 2013). As for triggers, it can be an email with the announcement of the event, the date of completion of the competition, or the elements of gamification.

Theory of Planned Behavior

In accordance with the theory of planned behavior, the intention of a person to act in one way or another is caused by three factors: attitudes towards behavior, perceived norms, and perceived control over behavior. In particular, assessment of usefulness and pleasure, how people around approve of such behavior, and how they actually behave matter (Ajzen & Sheikh, 2013; Greaves, Zibarras, & Stride, 2013). The identified model was elaborated by Icek Ajzen in order to explain various forms of human activity, and it was repeatedly used to study different behaviors in various fields (Kim, Njite, & Hancer, 2013; Paul, Modi, & Patel, 2016). For example, eco-friendly hotels and restaurants are largely designed with the help of the theory of planned behavior.

The above considerations are critical in specific circumstances, projects, and programs when it is necessary to change people’s behavior (Cheng & Huang, 2013). In a corresponding way, behavioral beliefs produce a favorable or unfavorable attitude towards the expected actions and views, while normative beliefs lead to perceived social pressure or subjective norms. In combination, attitudes toward behavior, subjective norms, and the perception of behavioral control promote the formation of behavioral intentions (Han, 2015). As a basic rule, if the attitude and the subjective norm are more favorable, then the perceived control will be more significant, and a person’s intention to achieve the corresponding behavior will be stronger.

The recent research project in the tourism industry has led to the conclusion that past preferences help predict later behavior, provided that the circumstances remain relatively stable (Chen & Tung, 2014). At the same time, Ajzen’s theory of planned behavior may help explain why ad campaigns that simply represent information do not work (Kautonen, van Gelderen, & Fink, 2015). A simple increase in knowledge will not contribute to a significant change in behavior. Campaigns targeting relationships perceived norms, and control in implementing changes or buying certain products have better results. As in management, programs that focus only on explaining the importance of something (knowledge transfer) have a small chance of success. Rather, people should be persuaded to change their intent by paying a lot of attention to relationships, subjective norms, and perceived control of behavior.

Theory of Reasoned Action

The theory of reasonable actions developed by Fishbein and Ajzen is the most frequently cited and recognized in the field of predicting behavior. Its pivotal principle is that people focus on ideas and acceptable information in their actions rather than on rational arguments (Head & Noar, 2014). The theory states that the behavioral intentions of a person are, as a rule, the most representative predictors of how a person will behave. In turn, behavioral intentions can be predicted if there is knowledge about attitudes and ideas relating to them (Lee, Ham, & Kim, 2013; Mishra, Akman, & Mishra, 2014). In particular, behavioral intentions for the implementation of a certain behavior, for example, the choice of a particular area for training indicate the function of two factors. The first one is the personal attitudes of an individual regarding behavior, and the subjective norm associated with other people’s ideas about how he or she should act in such situations is the second. Each of these factors is calculated using the value model of expectations by assuming a combination of a number of characteristic ideas about perceived expectations compiled in evaluative expressions.

When analyzing the behavior of employees of the organization, the influence of factors on the adoption of innovation and the intention of a person is regarded as the immediate predecessor of an action (Alryalat, Rana, & Dwivedi, 2015). According to the theory of reasonable action, intentions are determined by personal attitudes in relation to behavior and the subjective norm. An attitude to behavior is defined as positive or negative feelings of an individual associated with the performance of certain actions. Similarly, a subjective norm is created derived from normative ideas that others can think about how to act in such situations, each of which is determined by the motivation to follow them. It should be clarified that the subjective norm implies an individual’s perception that most people who are important to consider that should or should not be performed certain actions.

In one of his early studies, with the help of the proposed model, Fishbein tried to predict the moment when the students of the university where he worked had entered premarital sex (Ajzen, 2015). At the beginning of the semester, attitudes towards premarital sexual relations as well as ideas about what others mean about it were evaluated, and motivation for submission to the pressure of significant others was revealed. At the end of the semester, a study was conducted on the question of when students were actually involved in premarital sex, and the research results exceeded all expectations. A number of subsequent studies carried out by other authors also confirmed the high predictability of the proposed theoretical model (Montano & Kasprzyk, 2015; Davis, Campbell, Hildon, Hobbs, & Michie, 2015).

Diffusion of Innovation Theory

In the diffusion of innovation (DOI) theory, Everett Rogers, took a new approach to the phenomenon of information flow and its effects on a person, proposing the theory for introducing innovations or adaptations. Diffusion is defined as the process of communicating innovation through certain channels in a certain period of time to the participants of the social system (Zhang, Yu, Yan, & Spil, 2015). The analysis of various empirical studies led the scholar to the conclusion that the process of accepting new ideas and products consists of stages: concentration, interest, assessment, verification, recognition, and corroboration.

The DOI proposes that at the beginning, a sufficiently large number of people learn about innovations through media sources. Then it is adopted by a small group of the population (2.5 percent) that easily accepts abstract ideas and is willing to take risks (Al-Zoubi, 2013). They are followed by the early adepts (13.5 percent), who are respected people and opinion leaders able to convince others. With the inclusion of the early majority population, the degree of innovation adoption reaches the average. Then, a new idea or product is recognized by the late majority, which accounts for 34 percent of the population (Owolabi Yusuf & Mat Derus, 2013). Ultimately, the group of laggards, who are conservative, suspicious of new trends, and often lacking funds, changes their attitude towards innovation. It is considered that innovation is accepted by in case at least six percent of the population recognized it.

More to the point, Rogers believed that interpersonal communication among people of the same community or group and age is rather important, but the patriotic appeals from the government are likely to be ineffective. The reliability of the communicative source partly predetermines the success of a campaign, and the mass media cannot change the behavior of those who confidently take a different point of view (Karakaya, Hidalgo, & Nuur, 2014). A considerable change in relation to innovations in society, as a rule, takes place when the majority accepts it. In general, this theory allows understanding how to introduce some new product into the public consciousness.

Conclusion

To conclude, it should be emphasized that several behavior change models were discussed in this section to reveal their potential in introducing innovations and ensuring their successful recognition. Even though some of the mentioned theories such as the health belief model and transtheoretical model are used in healthcare to correct inappropriate attitudes, their utilization in social sciences is also evident. The literature review shows that theories of reasonable actions and planned behavior are more detailed than others, while they mainly focus on entrepreneurial behavior changes and target employees. From the great variety of available models, self-efficiency was noted as one of the most feasible and relevant behavior change models due to its emphasis on a person’s awareness of his or her own strengths, their further improvement, and overall personality development. In general, it is evident that the selection of one or another theory depends on the problem to be resolved, the setting, and the target audience for behavior alteration.

References

Ajzen, I. (2015). The theory of planned behaviour is alive and well, and not ready to retire: A commentary on Sniehotta, Presseau, and Araújo-Soares. Health Psychology Review, 9(2), 131-137.

Ajzen, I., & Sheikh, S. (2013). Action versus inaction: Anticipated affect in the theory of planned behavior. Journal of Applied Social Psychology, 43(1), 155-162.

Alryalat, M. A. A., Rana, N. P., & Dwivedi, Y. K. (2015). Citizen’s adoption of an e-government system: Validating the extended theory of reasoned action (TRA). International Journal of Electronic Government Research (IJEGR), 11(4), 1-23.

Al-Zoubi, M. I. (2013). Predicting e-business adoption through integrating the constructs of the Rogers’s diffusion of innovation theory combined with technology-organization-environment model. International Journal of Advanced Computer Research, 3(4), 63-73.

Bullough, A., Renko, M., & Myatt, T. (2014). Danger zone entrepreneurs: The importance of resilience and self‐efficacy for entrepreneurial intentions. Entrepreneurship Theory and Practice, 38(3), 473-499.

Cameron, E., & Green, M. (2015). Making sense of change management: A complete guide to the models, tools and techniques of organizational change (4th ed.). Philadelphia, PA: Kogan Page Publishers.

Chen, M. F., & Tung, P. J. (2014). Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. International Journal of Hospitality Management, 36, 221-230.

Cheng, H. H., & Huang, S. W. (2013). Exploring antecedents and consequence of online group-buying intention: An extended perspective on theory of planned behavior. International Journal of Information Management, 33(1), 185-198.

Clark, P. G. (2013). Toward a transtheoretical model of interprofessional education: Stages, processes and forces supporting institutional change. Journal of Interprofessional Care, 27(1), 43-49.

Crutzen, R. (2014). The behavioral intervention technology model and intervention mapping: The best of both worlds. Journal of Medical Internet Research, 16(8), 188-198.

Davis, R., Campbell, R., Hildon, Z., Hobbs, L., & Michie, S. (2015). Theories of behaviour and behaviour change across the social and behavioural sciences: A scoping review. Health Psychology Review, 9(3), 323-344.

Diniz, I. M., Duarte, M. D. F. S., Peres, K. G., de Oliveira, E. S., & Berndt, A. (2015). Active commuting by bicycle: Results of an educational intervention study. Journal of Physical Activity and Health, 12(6), 801-807.

Faqih, K. M. (2013). Exploring the influence of perceived risk and internet self-efficacy on consumer online shopping intentions: Perspective of technology acceptance model. International Management Review, 9(1), 67-77.

Friman, M., Huck, J., & Olsson, L. (2017). Transtheoretical model of change during travel behavior interventions: An integrative review. International Journal of Environmental Research and Public Health, 14(6), 581-596.

Gabrielli, S., Forbes, P., Jylhä, A., Wells, S., Sirén, M., Hemminki, S.,… Jacucci, G. (2014). Design challenges in motivating change for sustainable urban mobility. Computers in Human Behavior, 41, 416-423.

Glanz, K. (2015). Health behavior: Theory, research, and practice (5th ed.). San Francisco, CA: John Wiley & Sons.

Greaves, M., Zibarras, L. D., & Stride, C. (2013). Using the theory of planned behavior to explore environmental behavioral intentions in the workplace. Journal of Environmental Psychology, 34, 109-120.

Han, H. (2015). Travelers’ pro-environmental behavior in a green lodging context: Converging value-belief-norm theory and the theory of planned behavior. Tourism Management, 47, 164-177.

Head, K. J., & Noar, S. M. (2014). Facilitating progress in health behaviour theory development and modification: The reasoned action approach as a case study. Health Psychology Review, 8(1), 34-52.

Karakaya, E., Hidalgo, A., & Nuur, C. (2014). Diffusion of eco-innovations: A review. Renewable and Sustainable Energy Reviews, 33, 392-399.

Kautonen, T., van Gelderen, M., & Fink, M. (2015). Robustness of the theory of planned behavior in predicting entrepreneurial intentions and actions. Entrepreneurship Theory and Practice, 39(3), 655-674.

Kim, Y. J., Njite, D., & Hancer, M. (2013). Anticipated emotion in consumers’ intentions to select eco-friendly restaurants: Augmenting the theory of planned behavior. International Journal of Hospitality Management, 34, 255-262.

Kowalski, K., Jeznach, A., & Tuokko, H. A. (2014). Stages of driving behavior change within the transtheoretical model (TM). Journal of Safety Research, 50, 17-25.

Lee, J., Ham, C. D., & Kim, M. (2013). Why people pass along online video advertising: From the perspectives of the interpersonal communication motives scale and the theory of reasoned action. Journal of Interactive Advertising, 13(1), 1-13.

Lent, R. W., & Brown, S. D. (2013). Social cognitive model of career self-management: Toward a unifying view of adaptive career behavior across the life span. Journal of Counseling Psychology, 60(4), 557-568.

Lokhorst, A. M., Werner, C., Staats, H., van Dijk, E., & Gale, J. L. (2013). Commitment and behavior change: A meta-analysis and critical review of commitment-making strategies in environmental research. Environment and Behavior, 45(1), 3-34.

Masthoff, J., Grasso, F., & Ham, J. (2014). Preface to the special issue on personalization and behavior change. User Modeling and User-Adapted Interaction, 24(5), 345-350.

Mazur, J. E. (2016). Learning & behavior (8th ed.). New York, NY: Routledge.

Mishra, D., Akman, I., & Mishra, A. (2014). Theory of reasoned action application for green information technology acceptance. Computers in Human Behavior, 36, 29-40.

Montanaro, E. A., & Bryan, A. D. (2014). Comparing theory-based condom interventions: Health belief model versus theory of planned behavior. Health Psychology, 33(10), 1251-1260.

Montano, D. E., & Kasprzyk, D. (2015). Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. Health Behavior: Theory, Research and Practice, 95-124.

O’Connor, P. J., Martin, B., Weeks, C. S., & Ong, L. (2014). Factors that influence young people’s mental health help‐seeking behaviour: A study based on the Health Belief Model. Journal of Advanced Nursing, 70(11), 2577-2587.

Oinas-Kukkonen, H. (2013). A foundation for the study of behavior change support systems. Personal and Ubiquitous Computing, 17(6), 1223-1235.

Owolabi Yusuf, M. B., & Mat Derus, A. (2013). Measurement model of corporate zakat collection in Malaysia: A test of diffusion of innovation theory. Humanomics, 29(1), 61-74.

Paul, J., Modi, A., & Patel, J. (2016). Predicting green product consumption using theory of planned behavior and reasoned action. Journal of Retailing and Consumer Services, 29, 123-134.

Renkl, A. (2014). Toward an instructionally oriented theory of example‐based learning. Cognitive Science, 38(1), 1-37.

Riekert, K. A., Ockene, J. K., & Pbert, L. (Eds.). (2013). The handbook of health behavior change (5th ed.). New York, NY: Springer.

Sallis, J. F., Owen, N., & Fisher, E. (2015). Ecological models of health behavior. Health behavior: Theory, research, and practice, 5, 43-64.

Schoech, D., Boyas, J. F., Black, B. M., & Elias-Lambert, N. (2013). Gamification for behavior change: Lessons from developing a social, multiuser, web-tablet based prevention game for youths. Journal of Technology in Human Services, 31(3), 197-217.

Zhang, X., Yu, P., Yan, J., & Spil, I. T. A. (2015). Using diffusion of innovation theory to understand the factors impacting patient acceptance and use of consumer e-health innovations: A case study in a primary care clinic. BMC Health Services Research, 15(1), 71-86.