Physician Visit for symptoms
The largest prospective examination of the HBM's ability to predict utilization of services is reported by Berkanovic et. al. who based their analyses on panel data available from the Los Angeles Health Survey (a three-stage random probability sample of households in Los Angeles County). In the 1976 sample, 1,883 potential adults respondents were selected, of those selected, 1,210 were ultimately successfully interviewed (response rate= 64%) During a 3-month period, demographic and health data were gathered during initial personal interviews with telephone follow-up interviews conducted every 6 weeks thereafter for approximately one year. During the study period, symptoms were reported by 769 respondents and information was obtained on use of physician services for their symptoms. A total of 1,679 "most important" symptom episodes were noted with individual respondents reporting from 1-17 symptoms (Janz et al.,1984).
HBM dimensions were operationalized by both general and symptom-specific levels. So in a nutshell, different questions and approaches were followed through for both general oriented and symptom-specific levels. The general oriented had more items for each construct of the HBM. The symptom-specific levels were addressed in an easy response to five specific questions.
Results:
The results showed that with the exception of the correlation between general-level "barriers" and use, all of the HBM predictors were found to be significantly associated with the use of physician services for symptoms.
Limitations:
The authors provided 2 cautionary notes:
An additional study limitation is the definition of "susceptibility" which incorporated the dimension of "belief in the efficacy of preventative health behavior", which in turn may lead to creating multicollinearity.
(http://deepblue.lib.umich.edu/bitstream/handle/2027.42/66877/10.1177_109019818401100101.pdf;jsessionid=12B6F01777C18E990D642553EA80907B?sequence=2)
HBM dimensions were operationalized by both general and symptom-specific levels. So in a nutshell, different questions and approaches were followed through for both general oriented and symptom-specific levels. The general oriented had more items for each construct of the HBM. The symptom-specific levels were addressed in an easy response to five specific questions.
Results:
The results showed that with the exception of the correlation between general-level "barriers" and use, all of the HBM predictors were found to be significantly associated with the use of physician services for symptoms.
Limitations:
The authors provided 2 cautionary notes:
- All of the HBM constructs were inter-correlated, creating multicollinearity, making it difficult to distribute the variance these dimensions shared in common.
- And because specific belief data were obtained after the care-seeker decisions were made, causal interpretation for the symptom-specific items remains speculative
An additional study limitation is the definition of "susceptibility" which incorporated the dimension of "belief in the efficacy of preventative health behavior", which in turn may lead to creating multicollinearity.
(http://deepblue.lib.umich.edu/bitstream/handle/2027.42/66877/10.1177_109019818401100101.pdf;jsessionid=12B6F01777C18E990D642553EA80907B?sequence=2)
Influenza
The outbreak of the Swine Flu during 1976 provided much information to be assessed through the HBM. The health beliefs and Swine Flu inoculation status were given through surveys to a random selection of 122 senior citizens; those of which were considered active in two senior centers. A 45-item interview schedule elicited respondents' beliefs along all of the major HMB constructs. The results of this indicated that the HBM constructs were able to distinguish inoculation program participants from nonparticipants, and these relationships were statistically significant for susceptibility, efficacy, and safety. But some problems were evident with the interpretation of severity. (Janz et al.,1984).
Limitations:
Some limits were on internal and external validity which included the use of retrospective design and a rather circumscribed sample of the population at risk.
(http://deepblue.lib.umich.edu/bitstream/handle/2027.42/66877/10.1177_109019818401100101.pdf;jsessionid=12B6F01777C18E990D642553EA80907B?sequence=2)
Limitations:
Some limits were on internal and external validity which included the use of retrospective design and a rather circumscribed sample of the population at risk.
(http://deepblue.lib.umich.edu/bitstream/handle/2027.42/66877/10.1177_109019818401100101.pdf;jsessionid=12B6F01777C18E990D642553EA80907B?sequence=2)
Field study to promote bicycle safety helmets
The HBM was used as a guide to evaluate the decision-making factors contributing to the adoption and consistent use of bicycle safety helmets. A survey, administered by trained telephone interviewers, lasted approximately 15-20 minutes. The respondents were told that their phone numbers were selected randomly and their responses to the survey were to be used in planning safety programs for children. The researchers put forth four hypotheses to be answered throughout the study as well.
Results:
The results for the study showed that three of the four hypotheses offered confirmation for the HBM.
The first hypothesis, perceived susceptibility and perceived severity were found to compose the single-dimension construct of perceived threat.
Second, five of the six cues to action emerged to significantly influence perceptions of threat. Respondents exposed to cues had greater perceptions of threat than respondents not exposed to the cues.
Third, perceived threat consistently predicted bicycle helmet attitudes, intentions, and behaviors. Regression analyses revealed that the greater the perception of threat, the more favorable the attitudes toward bicycle safety helmets.
Through the fourth hypothesis, cues to action were neither directly nor indirectly related to attitudes, intentions, or behaviors. Cues consistently and systematically predicted perceived threat and perceived threat consistently and systematically predicted attitudes, intentions, helmet ownership, and helmet usage.
Limitations:
Future Research is said to assess both perceived threat and perceived barriers and benefits to gain better understanding of how these (Witte et al.,1993).
(http://crx.sagepub.com/content/20/4/564.full.pdf+html)
- Hypothesis 1: Perceived susceptibility and perceived severity of bicycle injury compose the single dimension of perceived threat.
- Hypothesis 2: Cues to action will increase perceptions of threat about bicycling injuries.
- Hypothesis 3: The greater the perception of threat of bicycle injury, the more favorable the attitudes toward safety helmets, the stronger intentions to purchase helmets, the greater the likelihood of helmet ownership, and the greater the likelihood of helmet usage.
- Hypothesis 4: Cues to action will indirectly influence attitudes toward safety helmets, intentions to purchase safety helmets, safety helmet ownership, and safety helmet usage, as mediated by perceived threat.
Results:
The results for the study showed that three of the four hypotheses offered confirmation for the HBM.
The first hypothesis, perceived susceptibility and perceived severity were found to compose the single-dimension construct of perceived threat.
Second, five of the six cues to action emerged to significantly influence perceptions of threat. Respondents exposed to cues had greater perceptions of threat than respondents not exposed to the cues.
Third, perceived threat consistently predicted bicycle helmet attitudes, intentions, and behaviors. Regression analyses revealed that the greater the perception of threat, the more favorable the attitudes toward bicycle safety helmets.
Through the fourth hypothesis, cues to action were neither directly nor indirectly related to attitudes, intentions, or behaviors. Cues consistently and systematically predicted perceived threat and perceived threat consistently and systematically predicted attitudes, intentions, helmet ownership, and helmet usage.
Limitations:
- There was no way for researchers to check objectively whether respondents actually purchased helmets or whether their children were to consistently use them.
- Exposure to community-wide cues were measured in a self-report manner, so the researchers don't know what the true exposure to community cues were.
- There was no way for the researchers to know whether they actually counseled patients to use safety helmets, nor was there any means to check whether the prescription pads had been in use.
- Lastly, the researchers decision not to measure perceived benefits or barriers was a limitation. If those constructs would have been measured and apart of the study, they would've helped the studies results come to a better conclusion of how the roles of cues to action helped promote protection behaviors.
Future Research is said to assess both perceived threat and perceived barriers and benefits to gain better understanding of how these (Witte et al.,1993).
(http://crx.sagepub.com/content/20/4/564.full.pdf+html)
Measuring Mammography and Breast Cancer Beliefs in african american women
Although intervention trials have demonstrated significant improvement in mammography adherence for African American women, many of the current measurement tools used in these interventions have not been assessed for validity and reliability in ethnic minorities. This study had assessed the validity and reliability of Health Belief Model (HBM) variables, that are often the target of mammography interventions. Scale validity and reliability was assessed for HBM scales in a sample of 344 low-income African American women. Validity was supported through exploratory factor analysis and theoretical prediction of relationships. Attempts to increase mammography screening have successfully used the Health Belief Model to tailor interventions to women’s health beliefs for both African American and Caucasian women, and the variables in the Health Belief Model have been found to predict mammography screening in both African American and Caucasian populations.
Results:
The utility of using the health belief model in the development and refinement of scales for predicting mammography screening behavior in African American women is evident. For this study they tested the psychometric properties of health belief scales in low-income African American women living in a Midwestern urban area and found the scales to have acceptable validity and reliability. However, since cultural norms can vary among sub-populations within racial and ethnic groups, it is important to validate these scales with other subgroups of African American women for conceptual, scale, and norm equivalence (Champion et al., 2008).
(http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2902247/)
Results:
The utility of using the health belief model in the development and refinement of scales for predicting mammography screening behavior in African American women is evident. For this study they tested the psychometric properties of health belief scales in low-income African American women living in a Midwestern urban area and found the scales to have acceptable validity and reliability. However, since cultural norms can vary among sub-populations within racial and ethnic groups, it is important to validate these scales with other subgroups of African American women for conceptual, scale, and norm equivalence (Champion et al., 2008).
(http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2902247/)
Applying the health belief model to college students' health behavior
The purpose of this research was to investigate how university students' nutrition beliefs influence their health behavioral intention. While using the health belief model for this study it attempts to investigate college students' health behavior, address the determinants of eating behavior and physical activity, and it assesses if those underlying factors are interrelated. The insight into how and why health behaviors are developed is important to the success and adaptability of promoting healthy lifestyles to college students. This study used an online survey engine (Qulatrics.com) to collect data from college students. Out of 253 questionnaires collected, 251 questionnaires (99.2%) were used for the statistical analysis.
Results:
The results of this study provide evidence that college students’ health behaviors show that nutrition knowledge leads to an increase in nutrition confidence. This nutrition confidence also influences Health Beliefs, and positive Health Beliefs lead to an increase in behavioral Intention to Eat Health Food and do Physical Activity. These current findings from the study help support the hypothesis that perceptions of high benefit and low barrier regarding healthy diet will influence behavioral intentions. The findings are also consistent with research showing that university-sponsored physical activity and health classes have the potential to positively affect the attitudes and behaviors of the students. Although the study proposed that susceptibility and severity may have an effect on college students’ behavioral intention, the study did not find a significant result within its population of college students.
Limitations:
Although the results of this study suggested that Health Beliefs had a significant effect on the behavioral intention to eat healthy food and do physical activity, these results should be viewed with limited generalization because all participants lived in the Southwestern region of the United States. In other words, the results may not be able to represent all college students. The findings need to be validated by applying the model to other consumer groups and other circumstances. Another limitation would consist of the participants of the study to be volunteers. Being volunteers in the study could mean that the group may have been more motivated or interested in learning about healthy food than those who did not participate in the study. Further research with other college students throughout the country is needed to confirm the findings (Kim et al., 2012).
(http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3542446/)
Results:
The results of this study provide evidence that college students’ health behaviors show that nutrition knowledge leads to an increase in nutrition confidence. This nutrition confidence also influences Health Beliefs, and positive Health Beliefs lead to an increase in behavioral Intention to Eat Health Food and do Physical Activity. These current findings from the study help support the hypothesis that perceptions of high benefit and low barrier regarding healthy diet will influence behavioral intentions. The findings are also consistent with research showing that university-sponsored physical activity and health classes have the potential to positively affect the attitudes and behaviors of the students. Although the study proposed that susceptibility and severity may have an effect on college students’ behavioral intention, the study did not find a significant result within its population of college students.
Limitations:
Although the results of this study suggested that Health Beliefs had a significant effect on the behavioral intention to eat healthy food and do physical activity, these results should be viewed with limited generalization because all participants lived in the Southwestern region of the United States. In other words, the results may not be able to represent all college students. The findings need to be validated by applying the model to other consumer groups and other circumstances. Another limitation would consist of the participants of the study to be volunteers. Being volunteers in the study could mean that the group may have been more motivated or interested in learning about healthy food than those who did not participate in the study. Further research with other college students throughout the country is needed to confirm the findings (Kim et al., 2012).
(http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3542446/)