Essay Example on Health Belief Model: Explaining and Predicting Health Behaviors

Introduction

The Health Belief Model (HBM) is a theory that is useful in guiding health promotion and disease deterrence programs (Jeihooni et al., 2016). It helps in explaining and predicting how people change their health behaviors (Razmara et al., 2018). HBM is the most commonly used models for understanding individual health behaviors (Laranjo, 2016). The fundamental constructs of the HBM are focused on explaining a person's belief regarding his or her health conditions, which are then vital in predicting one's health-related behaviors.

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The HBM is comprised of six key constructs; four perceived constructs, cue to action, and self-efficacy (US Department of Health and Human Services, 2005). The first perceived construct, perceived susceptibility refers to an individual's subjective perception of the risk of developing illness (Ahadzadeh et al., 2015). Another HBM construct, perceived severity, is a person's perception of the seriousness of developing a disease based on the social and medical consequences (Chin & Mansori, 2019). Third, perceived benefits are a person's feelings of the effectiveness of available strategies in treatment or prevention of illness (Herrmann et al., 2018). Next, perceived barriers are an individual's perception of the hindrances to performing recommended health actions based on the costs and benefits (Wilson et al., 2018). On the other hand, cues to action refer to internal or external motivators that influence a person's decision to perform recommended health actions (Saghafi-Asl et al., 2020). Lastly, self-efficacy can be described as an individual's confidence in successfully implementing healthy behavior (Tshuma et al., 2017).

There are key considerations which should be made when using the HBM in changing participants' behavior. First, the model can be used to gather information by carrying out a health needs assessment to determine individuals at risk of a particular health issue and the populations that need to be targeted (Rural Health Information Hub, 2020). Second, the HBM can be used to convey the consequences of the health issue related to risk behaviors with clarity and unambiguity, thus helping in understanding perceived severity. Third, it can be used to communicate to the target group the steps that should be taken in implementing a recommended intervention and describing the benefits to action. Fourth, it provides help in the identification and reduction of barriers to activity. Lastly, the HBM provides support that boosts participants' self-efficacy and the likelihood of attaining the desired behavior (Rural Health Information Hub, 2020).

How the HBM Informs the use of MAP-IT Model

The MAP-IT model is a framework that can be utilized in the planning and evaluation of public health interventions in a community (Community Tool Box, 2019). The MAP-IT is an acronym for Mobilize, Assess, Plan, Implement, and Track (Community Tool Box, 2019). The HBM informs the use of MAP-IT is that it helps to assess people's perceived risk of developing a disease. Following an understanding of their perceived susceptibility, the MAP-IT model can then be used to mobilize people and organizations into a coalition with a common interest of attaining good health.

The HBM can also inform the MAP-IT model because it helps to address a person's perception of the seriousness of developing a disease based on the social and medical consequences. If it is established that people view themselves as being at a high risk of contracting an illness, then the 'assess' element of the MAP-IT can be used to identify community needs and resources that could be used to reduce the likelihood of developing the disease. Using MAP-IT, people at risk of developing the disease can be identified, the resources available to address the illness are mapped, and additional resources are sought.

The HBM further informs the MAP-IT because of its cue to action construct or the internal and external motivators associated with behavioral change. When the cues to action have been identified, all stakeholders who can help the affected community accomplish the desired health behavior change are identified.

Benefits and Limitations of Using MAP-IT in the Proposed SSP

Various benefits can be attributed to the use of MAP-IT in the proposed SSP. First, MAP-IT was chosen because it incorporates all stakeholders. Because of this, the program will be fully supported by the community- thus increasing the likelihood of achieving the desired objectives and goals (Community Tool Box, 2019b). Second, MAP-IT can be used to identify community resources that could be used to address the identified health issues (Community Tool Box, 2019b). Additionally, it can be used to establish resources that are needed to succeed in the program. Because of this, the MAP-IT approach enables program planners to estimate the resource-related costs of the program.

Despite its benefits, MAP-IT has some limitations. First, it can be time-consuming because each of the five steps of the model is comprehensive. Therefore, it may not be effective when limited time is available for a program. Second, because it is detailed and requires a lot of time to implement, it can be costly to implement health behavior change using the model.

References

Ahadzadeh, A. S., Pahlevan Sharif, S., Ong, F. S., & Khong, K. W. (2015). Integrating health belief model and technology acceptance model: An investigation of health-related internet use. Journal of Medical Internet Research, 17(2). https://doi.org/10.2196/jmir.3564

Chin, J. H., & Mansori, S. (2019). Theory of Planned Behavior and Health Belief Model: Females' intention on breast cancer screening. Cogent Psychology, 6(1), 1647927. https://doi.org/10.1080/23311908.2019.1647927

Community Tool Box. (2019a). Chapter 2. Other models for promoting community health and development. Retrieved from https://ctb.ku.edu/en/table-of-contents/overview/models-for-community-health-and-development/map-it/main#mobilize

Community Tool Box. (2019b). Section 14. MAP-IT: A Model for Implementing Healthy People 2020. Retrieved from https://ctb.ku.edu/en/table-of-contents/overview/models-for-community-health-and-development/map-it/main#mobilize

Herrmann, A., Hall, A., & Proietto, A. (2018). Using the Health Belief Model to explore why women decide for or against the removal of their ovaries to reduce their risk of developing cancer. BMC Women's Health, 18(1), 184. https://doi.org/10.1186/s12905-018-0673-2

Jeihooni, A. K., Hidarnia, A., Kaveh, M. H., Hajizadeh, E., & Askari, A. (2016). Application of the health belief model and social cognitive theory for osteoporosis preventive nutritional behaviors in a sample of Iranian women. Iranian Journal of Nursing and Midwifery Research, 21(2), 131-141. https://doi.org/10.4103/1735-9066.178231

Laranjo, L. (2016). Chapter 6-Social media and health behavior change. In S. Syed-Abdul, E. Gabarron, & A. Y. S. Lau (Eds.), Participatory Health Through Social Media (pp. 83-111). Academic Press. https://doi.org/10.1016/B978-0-12-809269-9.00006-2

Razmara, A., Aghamolaei, T., Madani, A., Hosseini, Z., & Zare, S. (2018). Prediction of safe driving Behaviours based on health belief model: The case of taxi drivers in Bandar Abbas, Iran. BMC Public Health, 18(1), 380. https://doi.org/10.1186/s12889-018-5300-5

Rural Health Information Hub. (2020). The health belief model. https://www.ruralhealthinfo.org/toolkits/health-promotion/2/theories-and-models/health-belief

Saghafi-Asl, M., Aliasgharzadeh, S., & Asghari-Jafarabadi, M. (2020). Factors influencing weight management behavior among college students: An application of the Health Belief Model. PLOS ONE, 15(2), e0228058. https://doi.org/10.1371/journal.pone.0228058

Tshuma, N., Muloongo, K., Nkwei, E. S., Alaba, O. A., Meera, M. S., Mokgobi, M. G., & Nyasulu, P. S. (2017). The mediating role of self-efficacy in the relationship between premotivational cognitions and engagement in multiple health behaviors: A theory-based cross-sectional study among township residents in South Africa. Journal of Multidisciplinary Healthcare, 10, 29-39. https://doi.org/10.2147/JMDH.S112841

Wilson, K., Clark, A. F., & Gilliland, J. A. (2018). Understanding child and parent perceptions of barriers influencing children's active school travel. BMC Public Health, 18(1), 1053. https://doi.org/10.1186/s12889-018-5874-y