The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Towards an Effective Health Interventions Design: An Extension of the Health Belief Model
Open accessAbstract
INTRODUCTION: The recent years have witnessed a continuous increase in lifestyle related health challenges around the world. As a result, researchers and health practitioners have focused on promoting healthy behavior using various behavior change interventions. The designs of most of these interventions are informed by health behavior models and theories adapted from various disciplines. Several health behavior theories have been used to inform health intervention designs, such as the Theory of Planned Behavior, the Transtheoretical Model, and the Health Belief Model (HBM). However, the Health Belief Model (HBM), developed in the 1950s to investigate why people fail to undertake preventive health measures, remains one of the most widely employed theories of health behavior. However, the effectiveness of this model is limited. The first limitation is the low predictive capacity (R(2) < 0.21 on average) of existing HBM's variables coupled with the small effect size of individual variables. The second is lack of clear rules of combination and relationship between the individual variables. In this paper, we propose a solution that aims at addressing these limitations as follows: (1) we extended the Health Belief Model by introducing four new variables: Self-identity, Perceived Importance, Consideration of Future Consequences, and Concern for Appearance as possible determinants of healthy behavior. (2) We exhaustively explored the relationships/interactions between the HBM variables and their effect size. (3) We tested the validity of both our proposed extended model and the original HBM on healthy eating behavior. Finally, we compared the predictive capacity of the original HBM model and our extended model. METHODS: To achieve the objective of this paper, we conducted a quantitative study of 576 participants' eating behavior. Data for this study were collected over a period of one year (from August 2011 to August 2012). The questionnaire consisted of validated scales assessing the HBM determinants - perceived benefit, barrier, susceptibility, severity, cue to action, and self-efficacy - using 7-point Likert scale. We also assessed other health determinants such as consideration of future consequences, self-identity, concern for appearance and perceived importance. To analyses our data, we employed factor analysis and Partial Least Square Structural Equation Model (PLS-SEM) to exhaustively explore the interaction/relationship between the determinants and healthy eating behavior. We tested for the validity of both our proposed extended model and the original HBM on healthy eating behavior. Finally, we compared the predictive capacity of the original HBM model and our extended model and investigated possible mediating effects. RESULTS: The results show that the three newly added determinants are better predictors of healthy behavior. Our extended HBM model lead to approximately 78% increase (from 40 to 71%) in predictive capacity compared to the old model. This shows the suitability of our extended HBM for use in predicting healthy behavior and in informing health intervention design. The results from examining possible relationships between the determinants in our model lead to an interesting discovery of some mediating relationships between the HBM's determinants, therefore, shedding light on some possible combinations of determinants that could be employed by intervention designers to increase the effectiveness of their design. CONCLUSION: Consideration of future consequences, self-identity, concern for appearance, perceived importance, self-efficacy, perceived susceptibility are significant determinants of healthy eating behavior that can be manipulated by healthy eating intervention design. Most importantly, the result from our model established the existence of some mediating relationships among the determinants. The knowledge of both the direct and indirect relationships sheds some light on the possible combination rules.
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Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.191 · Cited by 43,925
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
In search of how people change: Applications to addictive behaviors.
Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992) · American Psychologist · doi:10.1037/0003-066x.47.9.1102 · Cited by 8,596
The Health Belief Model: a decade later.
Janz, N. K., & Becker, M. H. (1984) · Health Education Quarterly · doi:10.1177/109019818401100101 · Cited by 8,437
Historical Origins of the Health Belief Model
Rosenstock, I. M. (1974) · Health Education Monographs · doi:10.1177/109019817400200403 · Cited by 6,116
Social Learning Theory and the Health Belief Model
Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988) · Health Education Quarterly · doi:10.1177/109019818801500203 · Cited by 5,564 · cited 3×
“For instance, self-efficacy was added as an extension to the original HBM (Rosenstock et al., 1988).”
BackgroundMethodInfluentialWhy People Use Health Services
Rosenstock, I. M. (1966) · The Milbank Memorial Fund Quarterly · doi:10.2307/3348967 · Cited by 2,305
The consideration of future consequences: Weighing immediate and distant outcomes of behavior.
Strathman, A., Gleicher, F., Boninger, D. S., & Edwards, C. S. (1994) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.66.4.742 · Cited by 1,782 · cited 6×
“Since its development, CFC has successfully predicted a range of behaviors, including health concern, environmental behavior, and cigarette or alcohol use (Strathman et al., 1994).”
BackgroundMethodInfluentialA Meta-Analysis of the Effectiveness of Health Belief Model Variables in Predicting Behavior
Carpenter, C. J. (2010) · Health Communication · doi:10.1080/10410236.2010.521906 · Cited by 1,604
Cited by
Parwati, N. M., Bakta, I. M., Januraga, P. P., & Wirawan, I. M. A. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182413238 · Cited by 56
Mediators of screening uptake in a colorectal cancer screening intervention among Hispanics
Shokar, N. K., Salinas, J., & Dwivedi, A. (2022) · BMC Cancer · doi:10.1186/s12885-021-09092-w · Cited by 12
Metadata
- Authors
- Orji, R., Vassileva, J., & Mandryk, R.
- Venue
- Online Journal of Public Health Informatics
- Publisher
- University of Illinois Libraries
- Published
- 2012-12-30
- Volume
- 4
- Issue
- 3
- ISSN
- 1947-2579 (ISSN-L)
- OpenAlex
- W2107894836
- Cited by
- 448
- References
- 11
- FWCI
- 5.35
- Type
- journal article
- Language
- en
- Open access
- gold
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