Which set of criteria determines how you choose among thoughts, actions, goals, and ideals?

8.01.3.2.3 Commentary

The HBM has provided a useful framework for investigating health behaviors and identifying key health beliefs, has been widely used, and has met with moderate success in predicting and changing a range of health behaviors (for a detailed review see Sheeran and Abraham, 2003). However, most tests of HBM have employed cross-sectional correlational designs. There is a clear need for more experimental studies to test the causal impact of manipulating HBM cognitions on behavior (see Sheeran et al., 2014). There is also a need for more tests of HBM-based interventions that include mediation analyses to examine whether any effects on behavior are mediated by changes in HBM cognitions.

The key strength of the HBM lies in the fact that it was developed by researchers directly working with health behaviors and so many of the concepts possess face-validity to those working in this area. This common-sense operationalization of a number of cognitive variables relevant to the performance of health behavior partly accounts for the model's popularity. However, compared to other similar social cognitive models of health behaviors, the HBM suffers from a number of weaknesses. The way in which the variables in the HBM combine to produce behavior has not been precisely specified (but see Becker and Rosenstock, 1987) and, as a result, the HBM is frequently tested as six independent predictors of behavior (Fig. 1). In addition, various researchers have used somewhat different operationalizations of the six constructs (see Rosenstock, 1974; Becker and Maiman, 1983). Together these factors have weakened the status of the HBM as a coherent SCM of health behavior (Abraham and Sheeran, 2015). Moreover, key social cognitive variables, found to be highly predictive of behavior in other models, are not incorporated in the HBM. For example, social pressure is a key component of the Theory of Planned Behavior/Reasoned Action Approach which does not appear in the HBM. In addition, self-efficacy beliefs which have been found to be powerful predictors of behavior in models based upon Social Cognitive Theory (Bandura, 1986) are not explicitly included in the HBM, although Rosenstock et al. (1988) proposed that self-efficacy should be added to the model. Studies that have tested the predictive utility of an extended HBM, including self-efficacy, have generally found that it is a useful additional predictor (e.g., Norman and Brain, 2005). Perhaps most importantly, the HBM does not include a measure of intention as specified in other SCMs such as the Theory of Planned Behavior and Protection Motivation Theory. A measure of intention would be expected to mediate the effects of HBM cognitions on behavior. In not specifying a causal ordering among the variables, as is done in other models, more powerful analyses of data and clearer indications of how interventions may have their effects are precluded in the HBM. Several authors have noted, for example, that threat is perhaps best seen as a more distal predictor of behavior acting via influences upon outcome expectancies. Finally, the model is static; there is no distinction between a motivational stage dominated by cognitive variables and a volitional phase where action is planned, performed and maintained (Schwarzer, 1992). Such distinctions are thought to be important in understanding various health behaviors. Hence, while an extremely popular SCM, it is also limited in a number of ways and for this reason may receive relatively less attention in the future.

Health belief model

The Health Belief Model (HBM) is another extensively researched model of health behavior (Hochbaum & Rosenstock, 1952). The HBM attempts to predict health-related behavior in terms of certain belief patterns. A person's motivation to undertake a health behavior can be divided into three categories: individual perceptions, modifying factors, and likelihood of action. Individual perceptions are factors that affect the perception of illness and with the importance of health to the individual, perceived susceptibility, and perceived severity. Modifying factors include demographic variables, perceived threat, and cues to action. The likelihood of action is the perceived benefits minus the perceived barriers of taking the recommended health action. The combination of these factors causes a response that often manifests into the likelihood of that behavior occurring (Janz & Becker, 1984; Rosenstock & Strecher, 1988).

The HBM proposes that the perception of a personal health behavior threat is influenced by at least three factors, general health values, which include interest and concern about health; specific health beliefs about vulnerability to a particular health threat; and beliefs about the consequences of the health problem (Hochbaum & Rosenstock, 1952). If a person perceives a threat to their health, is consecutively cued to action, and their perceived benefits outweigh the perceived barriers, then they are likely to undertake the recommended preventive health action. A schematic representation of the model is shown in Fig. 2.2.

The HBM has been used to aid understanding in sexual risk-taking behavior among various age (Brown, DiClemente, & Reynolds, 1991) and cultural groups (Lin, Simoni, & Zemon, 2005). Numerous studies have examined the capacity of the HBM to predict whether sexually active adolescents and young adults will use protection against STIs during sexual or oral intercourse and found support for HBM in understanding safe sex behaviors (Brown et al., 1991; Laraque, Mclean, & Brown-Peterside, 1997; Lin et al., 2005). HBM has been found to account for 43% of the variance in safe sex intentions in young adolescents (Petosa & Jackson,1991). Furthermore, Downing-Matibag and Geisinger (2012) demonstrated that the HBM can serve as a useful framework for understanding sexual risk-taking during casual hookups, as adolescents' assessments of their own and peers' susceptibility to STIs are often misinformed and situational characteristics, such as spontaneity, undermine adolescents' sexual self-efficacy.

However, there are issues with using the HBM and meta-analyses have found mixed results of its effectiveness (Carpenter, 2010; Taylor, 2006). In a UK review of research utilizing HBM there was no evidence that HBM-based interventions have contributed positively to overall improved health outcomes in the United Kingdom (Taylor, 2006). Furthermore, a meta-analysis of 18 studies found perceived barriers and perceived benefits to be the strongest predictors of behavior, but perceived severity was weak (Carpenter, 2010). Carpenter (2010) suggested that future research should examine possible mediation and moderation between the core components of the HBM, than to explore direct effects. However, another meta-analysis of 18 studies investigated interventions based on the HBM to improve health adherence, with 83% of these studies reporting improved adherence and 39% of studies showing moderate to large effect sizes. Yet only six of the studies included explored the model in its entirety (Jones, Smith, & Llewellyn, 2014). Health adherence to teenagers attending routine STI screenings and taking oral contraception pills has been reported as an issue, and as discussed above, the HBM can assist in understanding adolescents' safe sex intentions (Goyal, Witt, Gerber, Hayes, & Zaoutis, 2013). Therefore, despite the criticisms discussed here, there is evidence that the HBM can assist in understanding sexual risk-taking behavior in teenagers.

Commentary

The HBM has provided a useful framework for investigating health behaviors and identifying key health beliefs, has been widely used, and has met with moderate success in predicting a range of health behaviors (for reviews see Janz and Becker, 1984; Harrison et al., 1992; Abraham and Sheeran, 2015). The strength of the HBM lies in the fact that it was developed by researchers directly working with health behaviors and so many of the concepts possess face-validity to those working in this area. This common-sense operationalization of a number of cognitive variables relevant to the performance of health behavior partly account for the model's popularity.

However, compared to other similar social cognitive models of health behaviors, the HBM suffers from a number of weaknesses. The way in which the variables in the HBM combine to produce behavior has not been precisely specified (but see Becker and Rosenstock, 1987) and, as a result, the HBM is frequently tested as six independent predictors of behavior. In addition, various researchers have used somewhat different operationalizations of the six constructs (see Rosenstock, 1974; Becker and Maiman, 1983). Together these factors have weakened the status of the HBM as a coherent SCM of health behavior (Conner, 1993; Sheeran and Abraham, 1995). Moreover, key social cognitive variables, found to be highly predictive of behavior in other models, are not incorporated in the HBM. For example, intentions to perform a behavior and social pressure are key components of the Theory of Reasoned Action/Planned Behavior which do not appear in the HBM. Also, perceptions of personal control over the performance of the behavior (self-efficacy beliefs) which have been found to be such powerful predictors of behavior in models based upon Social Cognitive Theory (Bandura, 1982; Schwarzer and Fuchs, 1996) are not explicitly included in the HBM, although Rosenstock et al. (1988) proposed that self-efficacy should be added to the model. Studies that have tested the predictive utility of an extended HBM, including self-efficacy, have generally found that it is a useful additional predictor (e.g., Norman and Brain, 2005; Schmiege et al., 2007). In addition, in not specifying a causal ordering among the variables, as is done in other models, more powerful analysis of data and clearer indications of how interventions may have their effects are precluded in the HBM. Several authors have noted, for example, that threat is perhaps best seen as a more distal predictor of behavior acting via influences upon outcome expectancies. Finally, the model is static; there is no distinction between a motivational stage dominated by cognitive variables and a volitional phase where action is planned, performed and maintained (Schwarzer, 1992). Such distinctions are thought to be important in understanding various health behaviors. Hence, while an extremely popular SCM for use in understanding health behavior, it is also in a number of ways limited and may receive relatively less attention in the future.

6.3.2 Health Belief Model

The Health Belief Model proposes that people are most likely to take preventative action if they perceive the threat of a health risk to be serious, if they feel they are personally susceptible and if there are fewer costs than benefits to engaging in it [14]. Therefore, a central aspect of the Health Belief Model is that behavior change interventions are more effective if they address an individual’s specific perceptions about susceptibility, benefits, barriers, and self-efficacy [5]. Interventions focusing on this model may involve risk calculation and prediction, as well as personalized advice and education.

D. Health Belief Model

The health belief model was one of the first models to adapt theory from the behavioral sciences to health problems, and it remains one of the most widely recognized conceptual frameworks of health behavior. It emerged in the 1950s, during a time in history when a modest number of preventive health services were available, such as flu vaccines and chest X rays for tuberculosis screening [38]. The model was based on an assumption that people fear diseases, and that health actions are motivated in relation to the degree of fear (perceived threat) and expected fear-reduction potential of actions, as long as that potential outweighs practical and psychological obstacles to taking action (net benefits) [14].

The four key constructs of the health belief model are identified as perceived susceptibility and perceived severity (two dimensions of “threat”), and perceived benefits and perceived barriers (the components of “net benefits”). More recent adaptations have added the concepts “cue to action,” a stimulus to undertake behavior; and self-efficacy, or confidence in one's ability to perform an action [39]. While the health belief model was originally conceived as an explanatory model, it has some applications for planning change, as well. The most promising use of the health belief model in designing interventions is as a foundation for developing messages that may persuade individuals to make healthy decisions.

To what extent does the health belief model fit well with nutrition intervention? Does it help us understand how people view their eating habits and can it motivate them to make healthy changes? In fact, the health belief model is of limited use for primary prevention of chronic diseases such as cardiovascular disease and cancer. However, it can play an important role in interventions for persons with clinical nutrition-related risk factors, such as high blood cholesterol or diabetes. Such individuals are faced with the important and often overriding concern about health. For practitioners, health concerns—emphasized by applying the health belief model—are most likely to be influential when they are emphasized in a clear and specific manner, placed in the context of overall risk for diseases, and when dietary change recommendations can be linked prospectively to tangible risk reduction [15]. Symptomatic patients also tend to be more motivated [40].

BEHAVIOR CHANGE THEORIES AND STRATEGIES FOR CHANGE

Two theories of behavior change, the health belief model and social cognitive theory, have been widely used to develop strategies to help patients learn to adopt healthy behaviors and to work with their clinicians to improve their health. These theories are summarized below, and specific questions and teaching strategies clinicians can use are presented.

The Health Belief Model (HBM) was developed in the 1950s to explain why people did or did not take part in programs to detect or prevent disease, such as x-ray screenings to detect tuberculosis.6 The model was later applied to how people responded to illnesses that had been diagnosed, including adherence to medical regimens. Since then, the HBM has been used widely in studies of health behavior. The HBM proposes that preventive or therapeutic recommendations by the clinician are more likely to be followed if the patient feels that:

I am susceptible to this disease.

I believe that the disease is serious.

I believe that the benefits of the recommended treatment will outweigh the costs or barriers involved in following it.

I am confident that I can carry out the recommended treatment successfully.

In addition, HBM suggests that patients are more likely to follow recommendations if they are exposed to cues to action, such as written or telephone reminders, or public announcements such as posters and public service advertisements on radio.

The HBM provides a useful framework for guiding clinicians’ thinking about how to teach their patients and persuade them to follow the treatment plan. A good way to begin, once the initial history or complaint has been discussed, is to ask four basic open-ended questions:

What concerns you most about your asthma?

What do you know about asthma?

What concerns do you have about the medicines?

What would you like to do that you can't do now because of your asthma?

These questions invite patients to talk about their feelings, but focus the issue on what matters to them about asthma. The answers will often provide clues the clinician can follow up on to assess specific areas of the HBM. For example, it is often not clear how susceptible patients feel about different aspects of asthma or asthma diagnosis. A clinician may not be sure whether the family believes the patient has asthma at all. Other families may readily accept the notion that the patient has asthma, but not believe that it is a chronic problem that exists even when symptoms are not present. Some patients may agree they have asthma, but not believe they are susceptible to having serious asthma exacerbations. These issues can be explored with follow-up questions directed at the issue of susceptibility. For example, “How likely is it that your child will have another asthma attack like this one?” or “Do you think you will continue to have asthma symptoms in the next year?” or “How do you feel about the idea that your child has asthma?” Similarly, the patient or family's perception of the seriousness of asthma can be explored with questions such as “How serious do you think your asthma is?” or “What do you think will happen if your child's asthma is not treated?” The answers to these questions are likely to bring out the patient's feelings about susceptibility and seriousness, and the clinician can then engage in a discussion with the patient and provide accurate information.

The four basic questions listed above are also likely to provide information about the patient's perception of the potential benefits of following the clinician's recommended treatment, as well as perceived barriers to doing so. If the recommended treatment is new, the patient is not likely to have given much thought to the potential benefits of following it. The clinician may be able to use the patients’ answers to questions about concerns to help patients link the problems they want solved to what the clinician teaches them about the benefits of therapy. For example, “What benefits do you think you might get if you took the inhaled corticosteroid every day?” If the patient is not sure, the clinician can then tie the potential benefits to the patient's expressed concerns: “Earlier you said you were bothered by not being able to sleep through the night. The inhaled corticosteroid that I'd like to prescribe for you will help you to do that. It will also enable you to be physically active without wheezing or coughing. What do you think about that?” A good follow-up question is “Can you think of any other ways this treatment might help your asthma or your ability to do the things you want?” Questions like this will help patients make more connections between the therapy proposed and the benefits they want. With both children and adults, tying the use of the treatment to achieving goals the patients want over a short period of time can help patients perceive the benefits of therapy, motivate them to follow it, and provide them with criteria for recognizing that the treatment is working.

Identifying perceived barriers to following a recommended treatment may be more straightforward, and is one of the goals of the well-known strategy of tailoring the regimen to the patient. Clinicians should discuss specific plans for taking a new medicine at home with the patient, and ask, “What problems do you think you will have in carrying this out the way we have discussed?” A good follow-up question that goes beyond details of administration is “Are there any other problems or concerns you have about following this plan?” Patient beliefs that the medicines may be harmful should be followed with more specific questions, such as “What harm do you think the medicine may cause?” or “What led you to think that this might be a problem?”

Finally, patient or family confidence that the treatment plan can be followed and used to control asthma should be assessed with questions such as “How sure are you that you can give the medicine to your child with the inhaler and spacer?” or “How sure are you that you can control your asthma using the written treatment plan I've given you?” If patients are not sure, then follow up with open-ended probes such as “I can sense you aren't completely sure. What part are you not so sure of?” This approach will enable patients to bring up all the relevant issues before they leave the office.

By using the HBM as a framework for asking questions to assess patients’ asthma knowledge, beliefs, and skills, the clinician can identify key issues that need to be addressed to make patients able and willing to follow the treatment plan. The strength of HBM is that it helps identify areas in which discussion and teaching are needed to change patient behavior. Its limitation, however, is that it doesn't tell us much about how behavior change occurs or how the clinician can facilitate change. For that, we turn to cognitive social theory and the self-regulation process.

Social cognitive theory (SCT) describes the process by which people set and achieve goals through a process known as self-regulation.7,8 Most people self-regulate their behavior to some extent, and can learn, either spontaneously or with coaching, to

Control problem behaviors, such as smoking;

Master valued skills, such as playing a musical instrument;

Achieve goals, such as completing a medical residency.

In self-regulation, the individual attempts to reach desired outcomes by a process that includes controlling three factors: (1) behaviors, such as trying out new strategies and self-observation of the results; (2) personal thoughts, such as reactions to the success of one's own behavior, or setting new goals; and (3) environmental factors. Environmental factors include both physical factors, such as the presence or lack of needed equipment or space, and social factors, such as the presence of a teacher or coach to help acquire knowledge or skills. Self-regulation is the process by which an individual attempts to control the interaction of these three factors to achieve a goal. For example, a student learning to play an instrument may: (1) decide to master a simple piece of music (personal—goal setting); (2) to play the music repeatedly until he or she can do it without mistakes (behavioral—trying a strategy); and (3) finding a place to practice where he or she won't be disturbed by others (environmental).

Coaching by an expert is an important aid in learning to self-regulate behavior. For example, the student might have a teacher who could demonstrate how the music should sound when played correctly, provide feedback about how well the student was playing, and suggest new strategies to help the student play better. Similarly, consider a patient with asthma who has experienced difficulty in controlling flare-ups with a beta-agonist delivered by metered-dose inhaler (MDI). His doctor has suggested that he may not be using the MDI correctly and so is not getting the needed dose of medicine. The patient might (1) decide that he would master MDI technique (personal—goal setting); (2) ask the doctor to demonstrate the correct technique, then practice doing what the doctor did, while reviewing a list to make sure he was following all the steps (behavioral—trying a strategy and self-monitoring the results); and (3) ask the doctor to watch him practice and provide feedback about how he was doing (environmental—use of a coach to assist in self-monitoring and interpreting the results).

Self-regulation is a cyclic process that typically is repeated until a problem is solved or controlled or a skill mastered. The cycle includes (1) deciding to try a specific strategy to reach a goal; (2) initiating the action and self-monitoring to see how it works; (3) making a judgment of success or failure; (4) experiencing an increase or decrease in self-efficacy–self-confidence that the action can be performed successfully and helps achieve the overall goal; and (4) repeating the cycle by modifying the strategy to correct actions that didn't work or to improve on those that did. To amplify the example above, the patient who had just learned proper technique for using a metered dose inhaler from his doctor might (1) decide to try the new technique for the next 2 weeks, while (2) keeping a diary of symptom-free days to see whether his asthma control was improving; (3) review the diary at the end of 2 weeks to decide whether his control had improved; and (4) depending on the result, experience an increase in self-efficacy that he could control his asthma by using the new technique, or perhaps feel a reduction in self-efficacy if the symptom diary didn't show a positive change.

This example highlights the importance of two critical aspects in the self-regulation cycle. The first is that increased self-efficacy is critical to encourage repeated efforts to improve.7,8 Research shows that as self-efficacy increases, people are more likely to repeat an action, and are more likely to persist in the face of difficulty. For example, as a child makes initial progress in learning a musical instrument and gains confidence that she can play well, she often begins to play the instrument much more frequently, and is willing to tackle more complicated pieces of music. Improvement in self-efficacy is not guaranteed, however, and reduced self-efficacy can bring the cycle to a halt.

The role of coaching is important to help the learner gain confidence and repeat the self-regulation process. Coaches can do this in several ways. First, the coach can help the learner pick goals that can be achieved over a short period of time, to increase the chances of success. Most weight-loss programs, for example, set a goal of losing 1 to 2 pounds per week—a goal that can be readily achieved and builds confidence that the diet is working. Second, the coach can teach the learner how to self-observe, and can provide direct feedback about success. Third, the coach can help learners reach appropriate judgments about success. Many people find it difficult initially to tell if they are doing well, and counseling and problem solving can help their confidence grow as they learn.

There are three ways in which self-efficacy can be increased, and clinicians can make use of all of these with patients learning to control asthma. The first is verbal persuasion; that is, telling the patient that he or she is capable of learning the skills needed to control asthma. This is the least effective method, but because these methods are additive in effect, it is a good place to start. The second way is vicarious experience, which occurs when the patient talks with or observes another patient who has mastered the same skill. This is more effective because the other patient is a more believable model. For a patient, seeing that another patient has learned to use a metered dose inhaler with a spacer leads to the thought “If she can do it, I can do it too,” which is more convincing than the word of the doctor, because the patient is likely to think that “This doctor has had years of training; of course he thinks it is easy.” The most effective way in which self-efficacy can be increased, however, is by direct practice with feedback that leads to a series of short-term successes as the skill increases. All three approaches should be used when possible. Verbal persuasion can be done to initiate the process. Most clinicians can also allude to the fact that they have other patients who have mastered the skill, which is providing vicarious experience secondhand. In group asthma education programs, the health educator may be able to have parents who have learned a skill demonstrate it to others to take full advantage of vicarious experience. Finally, by following a model of teaching the skill based on self-regulation theory, most clinicians, alone or with the help of practice staff, can successfully lead the patient to learn the skill with demonstration plus practice with feedback under the guidance of a coach. This model is outlined in Box 25-1.

Repeating the main teaching steps as outlined in step 7 is important for two reasons. First, it takes more time than we usually imagine to fully establish a skill and to work out all the problems in using it. Second, many skills decay over time and need reinforcement. Asking patients to self-monitor for a brief time until they learn key skills is important, because self-monitoring increases the desire to improve performance. By using this teaching process, clinicians can stimulate patients to set goals and start the self-regulation process, thus helping patients improve their control of asthma.

Health belief model

The Health Belief Model (HBM) is a widely used cognitive model of health behavior that was developed in the 1950s to explain the lack of participation in Public Health Service programs, responses to experienced symptoms, and medical compliance. At the most basic level, the HBM is a value-expectancy theory: behavior is dependent on (1) the subjective value placed on the outcome and (2) the expectation that an action will lead to that outcome. In the context of health-related behaviors, the valued outcome is typically the improvement of health or avoidance of poor health; the expectation is the individual’s belief that a health action can increase the likelihood of the outcome. Whether an individual chooses to engage in health-related behaviors is further dependent on his/her perceptions of (1) susceptibility to the health threat, (2) severity of the health threat, (3) likelihood of reducing the threat by engaging in the behavior, and (4) costs associated with engaging in the behavior.

Applied to tanning, the HBM suggests that individuals will engage in sun protection (e.g., wear sunscreen) if they perceive themselves to be vulnerable (due to family cancer history and skin type) to a severe health threat (skin cancer), and believe that the benefits associated with engaging in the protective behavior (diminishing risk for skin cancer) outweigh the costs (money spent on sunscreen). The utility of a psychosocial model, including components of the HBM, in explaining sun protection among young non-Hispanic Caucasian women has been tested longitudinally. Results indicated that the relationship between objective risk and intentions to sun protect and sunbathe was fully mediated by perceived susceptibility to skin cancer and photoaging. Namely, participants at greater objective risk reported higher perceived susceptibility, which was associated with increased intentions to sun protect and decreased intentions to sunbathe. Perceived severity was not related to actual behavior 1-week prior to follow-up.

Health Belief Model

The Health Belief Model (HBM) hypothesizes that health-related behavior depends on the combination of several factors, namely, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy. Perceived susceptibility refers to an individual's opinion of the chances of contracting the illness condition. Perceived severity refers to an individual's opinion of how serious a condition and its consequences are. Perceived benefits refer to one's belief in the efficacy of the recommended health behavior in reducing the risk or seriousness of the condition. Perceived barriers refer to the perception of cost associated with adhering to a recommended health behavior if it is likely to be beneficial in reducing or eliminating the perceived threat. Self-efficacy refers to the level of confidence in one's ability to perform the health behavior in question. Those persons who have low self-efficacy will have low confidence in their ability, which will have an effect on the likelihood of the behavior being performed. The HBM has been applied with considerable success to a range of health behaviors and populations, particularly preventive behaviors, such as diet, exercise, smoking cessation, vaccination, and contraception and sick role behaviors such as adherence to recommended medical treatments.

C. Health Belief Model

The health belief model is a psychological model that attempts to explain and predict health behaviors by focusing on the attitudes and beliefs of individuals. The key variables of the health belief model are as follows [4]:

Degree of perceived risk of a disease. This variable includes perceived susceptibility of contracting a health condition and its perceived severity once contracted.

Perceived benefits of diet adherence. A second benefit is the believed effectiveness of dietary strategies designed to help reduce the threat of disease.

Perceived barriers to diet adherence. This variable includes potential negative consequences that may result from taking particular health actions, including physical (weight gain or loss), psychological (lack of spontaneity in food selection) and financial demands (cost of new foods).

Cues to action. Events that motivate people to take action in changing their dietary habits are crucial determinants of change.

Self-efficacy. A very important variable is the belief in being able to successfully execute the dietary behavior required to produce the desired outcomes [5, 6, 7].

Other variables. Demographic, sociopsychological, and structural variables affect an individual's perceptions of dietary change and thus indirectly influence his ability to sustain new eating behaviors.

Motivation for change depends on the presence of a sufficient degree of perceived risk in combination with sufficient self-efficacy. Perceived risk without self-efficacy tends to result in defensive cognitive coping, such as denial, rationalization, and projection, rather than behavior change. The first element of this change model can easily be converted to a degree of perceived promise (for a positive goal), being the cross-product of perceived probability of obtaining the eventual reward.

The health belief model

The health belief model (HBM) is a value-expectancy theory, and assumes that an individual's behavior is guided by expectations of consequences of adopting new practices (Janz et al., 2002). The model has four key concepts (Hornik, 1991; Fisher and Fisher, 1992):

Susceptibility: does the person perceive vulnerability to the specific disease?

Severity: does the individual perceive that getting the disease has negative consequences?

Benefits minus costs: what are the positive and negative effects of adopting a new practice?

Health motive: does the person have concern about the consequences of contracting the disease?

In addition, self-efficacy, a sense of competence as a cogent agent of long-term behavior change, has recently been integrated into HBM. Thus, increased sexual risk-taking or unprotected sex may be explained and addressed by HMB as follows: one's beliefs about the benefits of condoms (protection from HIV or STDs) do not outweigh the costs of condom use (pleasure reduction due to reduced sensation, partner-related concerns such as creation of distrust in a relationship or reduction of spontaneity); interventions would focus on shifting the benefit–cost. A criticism of this model is that it lacks clear definitions of components and the relationship between them; thus the model has been critiqued for inconsistent measurement in both descriptive and intervention research. HBM has been further critiqued for not fully addressing several behavioral determinants, including socio-cultural factors, and assuming that health is a high priority for most individuals (thus, it may not be applicable to those who do not place as high a value on health).