The Health Belief Model (HBM)

The HBM is one of the most widely used and one of the broadest of health behavior theories. HBM is primarily a cognitively-based theory. HMB originated in the 1950s when a social psychologist working for the U.S. Public Health Service attempted to understand why individuals failed to participate in a tuberculosis (TB) screening program. The TB screening was free and convenient (mobile clinics came into each neighborhood). Yet despite the seeming appeal of such free screening, very few people came out to be screened. The HBM grew out of an attempt to understand what motivated people to participate in such health interventions. Specifically, the researcher wanted to know what the determinants of being screened were. His initial conclusion was that: people were more likely to be screened if they a) thought they were at risk of TB, and b) believed that early detection of TB was beneficial.

This observation makes perfect sense in hindsight. Free, accessible screening is only a first step. In order to convince people to come out to receive such screening, those people have to believe that TB is a scary disease for which they are at risk, and that catching TB early is beneficial. If people are unaware of the significance of the condition, or they do not believe they are at risk, they will not participate. Moreover, if they do not believe early detection is beneficial - for example, if they believe the condition is universally fatal - then they will not participate. From these insights grew the HBM.

HBM is what is known as a value expectancy theory. This means that individuals make decisions based upon the expected value of each course of action. As such, individuals consider two factors: 1) the subjective value of the outcome, and 2) the subjective probability or expectation that an action will achieve the outcome. That is, people determine both what they expect will happen based on a certain action, whether that is good or bad, and how likely it is that such an outcome will happen.

Components of the HBM

The HBM states that an individual will take action to prevent, screen for or control a condition associated with poor health if:

  1. he believes he is susceptible to the conditions.
  2. he believes the condition and the consequences are severe.
  3. he perceives that taking some action X has some benefit in terms of reducing the threat.
  4. he perceives that the barriers to taking the action are low.
  5. there are cues to action or triggers.
  6. the person believes that he can do the behavior that will produce the desired outcome (self efficacy).

To apply the HBM to the TB example, an individual will seek screening for TB if the perceived threat is high, meaning the individual feels they are at risk of TB and that he/she feels that TB is a dangerous and often fatal disease. Further, the individual must believe that screening for TB is beneficial, perhaps because he has learned from a physician or another source that cases diagnosed early can be treated effectively. Not only must the perceived threat and perceived benefit be high, but perceived barriers must be low. The screening should be readily available, and low-cost or free. The individual who desires screening should be able to be screened without losing work time, without incurring financial costs, etc. A cue to action will also influence the likelihood that an individual will be screened: maybe the individual knows someone with TB, or perhaps a public service message on the radio or a story in the newspaper about the severity of TB would serve as a cue to action. If the story included a tragic tale of an individual who was not screened and died, that could strengthen the cue to action. Finally, the individual needs to believe that they are able to receive such screening, and that, should they be screened, they will be able to receive the needed treatment to cure the disease.

Evidence and Critiques of the HBM

Research generally indicates that the components of the HBM do in fact help to predict health behaviors. Perceived barriers tend to be the most significant predictor of health behavior, suggesting that those planning public health interventions should be particularly conscious of perceived barriers. Yet while the components of the model do in fact suggest that the HBM may be a beneficial tool for understanding and encouraging health behavior, there have also been considerable criticisms of the model. The most common critique of the HBM is that it places its focus on individual decisions. As such, it does not account for the significance of social and environmental factors explicitly. Social and environmental factors will influence the cost-benefit calculus that individuals are argued to engage in when making decisions. Some individuals will have complete information, others not. Some will have correct information; other will make decisions based on rumors or other incorrect information. As such, disparities in knowledge are a crucial consideration for understanding the health behavior decisions individuals reach. Some people may not have chosen to be screened for TB because they were unaware of its severity. Others may have thought it was a disease that only affected certain types of people. This was clearly a problem when HIV-AIDS was first discovered, as the majority of individuals felt it was only a gay men s disease. This further emphasizes the importance of information dissemination in public health interventions.

A second critique of the HMB is that the model acts as though all six components are equally important for understanding health behavior. Yet there is reason to believe that different components may be more or less relevant in interaction with other components. That is, if perceived threat is incredibly high, people may be willing to overcome higher barrier levels than when perceived threat is low. Likewise, if the condition is seen as exceptionally mild, any barrier may be too high.

Finally, more a point than a critique, is that the barriers and benefits for a given health behavior may not be constant across all groups of people, much less all individuals. Different people smoke for different reasons, for example. Some people may believe that quitting smoking will result in weight gain. Others may want to quit, but be unable to afford quit-smoking programs. Some others may feel that smoking is crucial to their acceptance within their community or cultural group. Given this point, it may be beneficial for those planning public health interventions to conduct interviews or focus groups with relevant individuals in order to gain a useful insight into the relevant costs and benefits.