The Health Belief Model and smoking cessation behaviours

Applying the Health Belief Model to assess prevention services among young adults Raffy R. Luquis and Weston S. Kensinger

School of Behavioral Sciences and Education, Penn State Harrisburg, Middletown, PA, USA

ABSTRACT The Health Belief Model (HBM) is one of the many models in health education thatcan be used as the basis for health promotion programs. The Patient Protection and Affordable Care Act promoted the benefits of preventive care while reducing barriers for young adults to access the health insurance and preventive measures. The purpose of this analysis was to assess the perceived susceptibility, perceived serious- ness of health conditions and access to preventive services among young adults. Data were collected from 821 young adults in the north- east region of the United States. Results indicated that there were significant differences based on gender, health status and age on the perceived susceptibility or perceived seriousness of eight major health conditions. In addition, there were significant differences between males and females in regards to the use of prevention services based on their perceptions of susceptibility and seriousness. Results of this study indicate that the HBM constructs of perceived susceptibility and perceived seriousness might play a significant role for young adults to use health preventive services. Future health education and promotion efforts to increase use of preventive services should focus on percep- tions of susceptibility and seriousness in young adults.

ARTICLE HISTORY Received 17 February 2018 Accepted 15 November 2018

KEYWORDS Preventive services; health promotion; health education; health behaviors; Health Belief Model (HBM)

Introduction

Developed in the 1950s, the Health Belief Model (HBM) is one of the most frequently used models in health promotion programs to help explain why an individual may or may not engage in preventive health measures (Rosenstock 1966) and was initially developed to help predict individuals behavioral reactions to disease and treatment they received (Champion and Skinner 2008). According to the HBM, the constructs of perceived seriousness, susceptibility, benefits, barriers, cues to action and self-efficacy can be used to explain whether a person takes actions to prevent, to screen for or improve health behaviors. As such, based on the HBM, individuals who perceive high susceptibility and seriousness would be more likely to take actions toward preventing the disease as long as the health benefits surpass the barriers, and they feel they have the capability to engage in the behavior. Several of the HBM constructs have been found to be useful to predict health-promoting behaviors. For example, O’Connor et al. (2014) found that perceived barriers and benefits were strong predictors for

CONTACT Raffy R. Luquis [email protected] School of Behavioral Sciences and Education, Penn State Harrisburg, W314 Olmsted, 777 West Harrisburg Pike, Middletown, PA 17057-4898, USA

INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 2019, VOL. 57, NO. 1, 37–47 https://doi.org/10.1080/14635240.2018.1549958

© 2018 Institute of Health Promotion and Education

young people with mental health to engage in help-seeking behaviors. Similarly, Gulliver, Griffiths and Christensen (2010) found that perceive barriers deterred young adults with mental health from seeking help. According to a meta-analysis on the effectiveness of the HBM in predicting behaviors, perceived benefits and barriers emerged as strong predictors of engaging in the health behavior, while the relationship between susceptibility, severity and the behavior was low or nonexistent (Carpenter 2010). Research examining the influence of the constructs of perceived susceptibility and perceived seriousness have been mixed and met with ambiguity. Previous research focused on the construct of perceived seriousness did not signifi- cantly influence self-care measures (Harvey and Lawson 2009; Hsieh et al. 2016). While some literature suggests that beliefs about perceived susceptibility are predictive of engaging in health promoting behaviors such as healthy diet and exercise, smoking cessation, self-examinations and dental care (Abraham and Sheeran 2005), in general, many persons’ own perception of susceptibility is underestimated (Orji, Vassileva, & Mandryk 2012). According to Brewer et al. (2007), it is posited that susceptibility is an understudied aspect of risk perception and should be researched further. Although the HBM has been a useful theoretical framework to investigate a wide range of health behaviors (Orji, Vassileva, & Mandryk 2012), it has been suggested that beliefs about health risks may predict the likelihood of health behaviors (Champion and Skinner 2008; Ahadzadeh et al. 2015). Thus, it is important to understand the role of not only beliefs about barriers and benefits but also how the other constructs within HBM, as these influence healthy behaviors by young adults. For example, Ghaffari, Gharlipour and Rakhshanderou (2016) found that premarital sexual abstinence was associated with knowledge, perceived susceptibility, perceived benefits, perceived bar- riers, perceived self-efficacy, subjective norms and religious beliefs among young people. Thus, using the HBM as a framework is both a systematic and theoretical approach (Henshaw and Freedman-Doan 2009) and can help uncover the beliefs of young adults regarding accessing preventative services as applicable.

While young adults are exposed to higher rates of harmful health outcomes (e.g. sexually transmitted infections [STIs], mental health, substances use), studies have shown that a high percentage of young adults received no preventive care, counseling or reported low screenings rates (Adams et al. 2018; Fortuna, Robbins, and Halterman 2009; Minino et al. 2007). The Patient Protection and Affordable Care Act (ACA) encourages health promotion and disease prevention by making preventive care more accessible and affordable for many Americans, especially among young adults who may be more likely to delay preventive care because of cost (i.e. barrier to access) (Koh and Sebelius 2010; USDHHS 2010; Sommers et al. 2013). While preventative health screenings and services play a large role in the early diagnosis of chronic diseases (Bauer et al. 2014), a large portion of Americans receive only half of the services that are recommended (Koh and Sebelius 2010). Previous researchers have estimated that up to 70% of young adults do not engage in any preventative health care or counseling (Fortuna, Robbins, and Halterman 2009). Young adults between the ages of 19 and 26 benefited from a provision in ACA because it allowed them to stay on their parents’ or legal guardians’ health insurance plan, and the law also instituted insurance market regulations, insurance exchanges and expan- sion of Medicaid eligibility for those with a demonstrated financial need regardless of age (Sommers et al. 2013). By increasing access and decreasing cost, it could potentially help to

38 R. R. LUQUIS AND W. S. KENSINGER

eliminate barriers to preventative services, which is one of the central constructs of the HBM. Jerant et al. (2013), who found that preventive care increase after gaining health insurance coverage, supported this.

Based on the HBM, access to health insurance (decrease barrier) and the promo- tion of the benefits of preventive services, as supported by the ACA, would encourage young people to engage in preventive behaviors; however, people may not engage in preventive behaviors unless they perceive susceptibility and severity of disease. As such, previous data analysis by the authors showed that having health insurance was a main factor in receiving preventive services such as wellness checkup, blood pressure and cholesterol screening (Luquis and Kensinger 2017); however, the con- structs of perceived susceptibility and seriousness were not examined in relationship to health outcome and access to preventive services among young adults. Thus, the purpose of this analysis was to explore whether perceived susceptibility and serious- ness of health outcomes influence access to preventive services among young adults with health insurance. Specifically, the study addressed the following questions: (1) what are the perceptions of susceptibility and severity of health outcomes by partici- pants’ characteristics? and (2) are there any differences in the perceived susceptibility, severity and use of preventive care by participants’ characteristics among those with health-care insurance?

Materials and methods

Sample selection

One thousand young adults between the ages of 19 and 34 years (with equal numbers of both males and females) residing in the northeast region of the United States (Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island and Vermont) were recruited via email to participate in this study (Luquis and Kensinger 2017).

According to 2014 population estimates, there were approximately 12.2 million young adults between 19 and 34 years of age residing in the northeast region, including 36.5% between the ages of 19 and 24, 32.7% between 25 and 29 and 30.8% between 30 and 34. The population estimates also showed that there was an equal distribution of males (50.1%) and females (49.9%) in this region (U.S. Census Bureau 2014). The sample size was calculated using an online sample size calculator based on confidence level of 95% and confidence interval of 3% to represent the target population (Creative Research Systems 2012).

Measures

Using previously validated and reliable inventories, the authors developed a 40-question online survey, which inquired about participants’ demographic characteristics, health insurance coverage, type of coverage, source of health care and barriers to care (Luquis and Kensinger 2017). The survey further inquired whether participants received preven- tive health services, as well as possible reasons for not getting them. Perceived suscept- ibility for eight health major health conditions (cancer, diabetes, asthma, high blood

INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 39

pressure, cardiovascular disease, poor mental health, obesity and STIs) was measured with a single item, for example ‘compared to most people your age and sex, what would you say your chances are for developing sexually transmitted infections?’ on a 5-point Likert scale (1 = much lower than average, 5 = much higher than average). Similarly, perceived seriousness for each of the eight health conditions was assessed by asking participants to respond to statement such as ‘compared to most people of your age and sex, getting/ having a sexually transmitted infection would be serious problem’ on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) (Wang et al. 2009). Finally, participants were asked whether they have had or received health preventive services, including routine wellness exam, and screenings for obesity, HIV, STIs, depression, blood pressure/hyper- tension, diabetes and cancer among others, as mandated by the ACA (USDHHS 2010; Centers for Medicare and Medicaid Services n.d.).

Data collection and analysis

The Survey Monkey platform was selected to conduct the online survey as it provided greater assurance of anonymity, completion by a respondent at his or her convenience and accessibility to a wide geographical area (Luquis and Kensinger 2017). Survey Monkey platform has been used in other online surveys including a study on internet users and cyber abuse (Vakhitova and Reynald 2014), a study in about abortion and contraception among women in five countries (Wiebe et al. 2013) and a study on understanding millennial shoppers (Hall and Towers 2017). Thus, it was deemed appropriate for this investigation. Participants received an email invitation from Survey Monkey to request their participation in the survey. The Survey Monkey Audience was chosen as it provided the advantage to recruit participants from the diverse population based on the target criteria, which is benchmark regularly to ensure that the participants are representative. Participants were instructed to read the informed consent letter including issues regarding anonymity and contact information of the authors. Institutional Review Board approval from the Office of Research Protection at the Pennsylvania State University was obtained prior to the survey; participants completed an informed consent, which informed of the anonymity for all responses.

The Statistical Package for the Social Sciences version 24 was used to complete the data analysis. Descriptive statistics including frequency distribution, mean and standard devia- tion were used to examine participant’s responses. t-Test and analysis of variance (ANOVA) were used to assess perception of susceptibility and seriousness by participants’ character- istics. The level of statistical significance was set at p < .05 for all statistical measures.

Results

Demographics of participants

While 946 participants who completed the survey fit the initial inclusion criteria, for the purpose of the analysis, only 821 participants, those who reported that they had health insurance, were included. The participants were between the ages of 19 and 34, with a mean age of 27.20 (±4.57) and 77% falling between the ages of 25 and 34. Seventy percent of participants were White, 56% were female and 41% completed

40 R. R. LUQUIS AND W. S. KENSINGER

a bachelor’s degree or higher. Finally, approximately half of the participants (51.7%) described their health as excellent or very good and a third indicated that it was good (see Table 1).

Perceptions of susceptibility and seriousness

Participants were asked to assess their susceptibility and seriousness of developing one of eight health conditions. Average susceptibility and seriousness scores were calculated for each of the health conditions. A series of t-test and ANOVA analyses were conducted to examine the perception susceptibility and seriousness scores by partici- pants’ characteristics. The analyses showed significant differences on average perception susceptibility and seriousness scores by gender, health status and age. The analysis showed no significant difference based on race/ethnicity or education level. On average, females felt more susceptible and seriousness to cancer (p < .001), diabetes (p < .001), obesity (p < .001) and cardiovascular disease (p < .05). Females perceived more susceptibility to poor mental health (p < .01), and seriousness about asthma (p < .01), STIs (p < .05), and high blood pressure (p < .05) than males. Males felt more susceptible to STIs (p < .001) than females. Those who reported excellent/very good health felt less susceptible to cancer (p < .001), diabetes (p < .001), obesity (p < .001), asthma (p < .001), high blood pressure (p < .001), cardiovascular disease (p < .001) and mental health (p < .001) than their counterparts. Those who reported fair/poor health per- ceived more seriousness about cancer (p < .01) than their counterparts did. Older participants felt more susceptible to cancer (p < .05), obesity (p < .001) and

Table 1. Participant demographics and health insurance status. n %

Gender Male 359 44.0 Female 456 56.0

Race/Ethnicity White 559 70.8 Black/African- 56 7.1 American 96 12.2 Hispanic 78 9.9 Other

Age 19–24 242 29.5 25–29 276 33.6 30–34 303 36.9 Mean (SD) = 27.20 (4.57)

Education attainment High school graduate or less 179 22.7 Some college/Assoc. degree 287 36.5 Bachelor degree or more 321 40.8

Health status Excellent/Very good 423 51.7 Good 270 33.0 Fair/Poor 125 15.3

Type of health insurance Private 544 69.0 Public/Medicaid 244 31.0

N = 821, percentage based on those participants that answered the questions; missing data were excluded.

INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 41

cardiovascular disease (p < .001), while younger participants felt more susceptible and perceived more seriousness to STIs (p < .05) (see Table 2).

Preventive services in relationship to perceptions of susceptibility and seriousness

A series of two-way ANOVAs were conducted to examine the effect of gender, health status, age and whether participants received preventive services on their perceptions of susceptibility and seriousness among participants who reported that they had health insurance (i.e. decreased barrier). The analyses showed a statistically significant inter- action between the effect of gender and whether they received cancer, obesity, depres- sion and suicide screenings on their perception of susceptibility of cancer, obesity and mental health. Females who received cancer screenings perceived higher susceptibility about developing cancer (i.e. cervical, testicular, skin etc.) than males who received screenings (p < .05). Similarly, females who received obesity screenings and/or counsel- ing on weight management perceived higher susceptibility of developing obesity than males who received the same screenings/counseling (p < .05). Likewise, females who received depression and suicide screenings and/or counseling perceived higher suscept- ibility on developing a poor mental health condition (p < .01; p < .05), respectively. There were no significant differences based on single effect of gender or receiving the screenings (p > .05). Finally, the analysis also showed a statistically significant interac- tion between the effect of gender and whether they received cancer screenings on their perception of seriousness of cancer. Males who received cancer screening reported lower perception of seriousness about developing cancer than females who received the screening (p < .05); there were also statistically significant differences between male and females (p < .001) and between those who received and did not receive the screening service (p < .05). The analyses showed no significant interaction between the effect of gender and whether they received obesity, depression or suicide screenings (see Table 3).

Discussion

In the present study, the results showed differences on the perception susceptibility and seriousness scores by gender, health status and age. The results of this study indicated that the HBM constructs of perceived susceptibility and perceived seriousness might play a significant role for young adults with health insurance in addressing health outcomes, which may result in harmful consequences later in their lives. In general, females felt both more susceptible and seriousness about cancer, diabetes, obesity and cardiovascular disease. Similarly, females felt more susceptibility to poor mental health and perceived more seriousness about asthma, STIs and high blood pressure. These results are similar to previous studies in which gender differences concerning perceptions of susceptibility and seriousness have been reported. Wang et al. (2009) found that females reported higher perceived risk (i.e. susceptibility) and worry (i.e. seriousness) for cancer, heart disease, diabetes and stroke than men. Similarly, Das and Evans (2014) found differences in weight management perceptions between first-year male and female college students. Interestingly, results showed that males felt more susceptible to STIs than females,

42 R. R. LUQUIS AND W. S. KENSINGER

Ta b le

2. M ea n sc or es

of p er ce p ti on

s of

su sc ep ti b ili ty

an d se ri ou

sn es s b y p ar ti ci p an ts ’ ch ar ac te ri st ic s.

G en d er

H ea lt h st at us

A g e

H ea lt h co n d it io n

M al e

M (S D )

Fe m al e

M (S D )

Ex ce lle n t/ V er y g oo d

M (S D )

G oo d

M (S D )

Fa ir /P oo r

M (S D )

18 – 24

M (S D )

25 – 29

M (S D )

30 – 34

M (S D )

C an ce r su sc ep ti b ili ty

2. 34

(1 .0 2)

2. 65

(.9 8) c

2. 30

(1 .0 6)

2. 66

(.9 0)

2. 87

(.9 2)

c 2. 37

(1 .0 1)

2. 51

(1 .0 1)

2. 61

(1 .0 0) a

t/ F

− 4. 37

20 .7 7

3. 70

C an ce r se ri ou

sn es s

3. 54

(1 .2 8)

3. 95

(1 .1 4) c

3. 63

(1 .2 9)

3. 82

(1 .1 5)

4. 04

(1 .1 1)

b 3. 83

(1 .1 9)

3. 68

(1 .2 8)

3. 76

(1 .1 9)

t/ F

− 4. 79

5. 97

.9 36

D ia b et es

su sc ep ti b ili ty

2. 34

(1 .0 5)

2. 67

(1 .0 4) c

2. 25

(1 .0 2)

2. 73

(.9 6)

2. 96

(1 .1 1)

c 2. 43

(1 .0 4)

2. 53

(1 .0 9)

2. 59

(1 .0 3)

t/ F

− 4. 34

32 .2 1

1. 52

D ia b et es

se ri ou

sn es s

3. 34

(1 .1 9)

3. 64

(1 .0 5) c

3. 45

(1 .1 6)

3. 51

(1 .0 7)

3. 61

(1 .1 1)

3. 52

(1 .1 7)

3. 46

(1 .1 5)

3. 51

(1 .0 6

t/ F

− 3. 73

.9 70

.1 91

O b es it y su sc ep ti b ili ty

2. 35

(1 .1 7)

2. 64

(1 .2 4) b

2. 20

(1 .1 2)

2. 72

(1 .1 5)

3. 08

(1 .3 8)

c 2. 26

(1 .2 2)

2. 57

(1 .2 2)

2. 66

(1 .1 8) b

t/ F

− 3. 32

33 .0 7

7. 54

O b es it y se ri ou

sn es s

3. 30

(1 .1 7)

3. 56

(1 .0 8) b

3. 37

(1 .1 5)

3. 44

(1 .1 0)

3. 65

(1 .1 2)

3. 42

(1 .2 2)

3. 47

(1 .1 3)

3. 42

(1 .0 6)

t/ F

− 3. 27

2. 89

.1 57

A st h m a su sc ep ti b ili ty

2. 26

(1 .1 3)

2. 39

(1 .1 6)

2. 15

(1 .1 1)

2. 44

(1 .1 4)

2. 70

(1 .1 9)

c 2. 39

(1 .2 0)

2. 27

(1 .1 5)

2. 35

(1 .0 9)

t/ F

− 1. 64

13 .3 2

.7 13

A st h m a se ri ou

sn es s

3. 10

(1 .1 0)

3. 29

(1 .0 0) a

3. 18

(1 .0 6)

3. 21

(1 .0 6)

3. 26

(.9 4)

3. 26

(1 .0 7)

3. 19

(1 .0 5)

3. 17

(1 .0 0)

t/ F

− 2. 52

.2 75

.5 07

ST I su sc ep ti b ili ty

2. 18

(1 .1 4) c

1. 83

(1 .0 3)

2. 05

(1 .1 4)

1. 92

(1 .0 3)

1. 89

(1 .0 4)

2. 15

(1 .1 0)

b 1. 98

(1 .0 8)

1. 84

(1 .0 6)

t/ F

4. 55

1. 75

5. 57

ST I se ri ou

sn es s

3. 51

(1 .2 3)

3. 69

(1 .1 4) a

3. 57

(1 .2 3)

3. 60

(1 .1 4)

3. 76

(1 .1 0)

3. 75

(1 .1 9)

a 3. 62

(1 .2 1)

3. 48

(1 .1 4)

t/ F

− 2. 05

1. 31

3. 64

H ig h Bl oo d Pr es su re

su sc ep ti b ili ty

2. 62

(1 .0 7)

2. 63

(1 .0 2)

2. 41

(1 .0 4)

2. 80

(.9 5)

2. 92

(1 .0 5)

c 2. 60

(1 .0 7)

2. 55

(1 .0 1)

2. 70

(1 .0 3)

t/ F

− .2 14

18 .0 5

1. 45

H ig h Bl oo d Pr es su re

se ri ou

sn es s

3. 33

(1 .1 3)

3. 50

(.9 9)

a 3. 39

(1 .1 1)

3. 43

(1 .0 1)

3. 45

(1 .0 0)

3. 46

(1 .1 1)

3. 38

(1 .0 7)

3. 41

(1 .0 0)

t/ F

− 2. 29

.2 30

.3 74

C ar d io va sc ul ar

D is ea se

su sc ep ti b ili ty

2. 37

(1 .0 3)

2. 58

(.9 9) b

2. 27

(1 .0 2)

2. 68

(.9 4)

2. 79

(.9 9)

c 2. 24

(.9 3)

2. 55

(1 .0 1)

2. 62

(1 .0 4) c

t/ F

− 2. 95

19 . 96

10 .2 1

C ar d io va sc ul ar

D is ea se

se ri ou

sn es s

3. 52

(1 .1 5)

3. 65

(1 .0 4)

3. 55

(1 .1 4)

3. 62

(1 .0 6)

3. 66

(.9 9)

3. 56

(1 .1 7)

3. 56

(1 .1 2)

3. 63

(1 .0 2)

t/ F

− 1. 75 1

.5 94

.4 44

M en ta l h ea lt h su sc ep ti b ili ty

2. 47

(1 .1 9)

2. 72

(1 .2 2) b

2. 33

(1 .1 3)

2. 81

(1 .2 0)

3. 12

(1 .3 1)

c 2. 67

(1 .2 7)

2. 55

(1 .2 2)

2. 62

(1 .1 7)

t/ F

− 2. 98

26 .8 6

.6 41

M en ta l h ea lt h se ri ou

sn es s

3. 48

(1 .2 1)

3. 63

(1 .0 9)

3. 55

(1 .1 8)

3. 66

(1 .1 3)

3. 66

(1 .1 3)

3. 60

(1 .2 4)

3. 52

(1 .1 4)

3. 54

(1 .0 8)

t/ F

− 1. 76

.7 22

.3 21

ST I: Se xu al ly tr an sm

it te d in fe ct io n . H ig h er

sc or es

re p re se n t in cr ea se d su sc ep ti b ili ty

an d se ri ou

sn es s;

a p -v al ue

≤ .0 5,

b p- va lu e ≤ .0 1,

c p -v al ue

≤ .0 01 .

INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 43

which may be a reflection of differences in sexual behaviors across gender. It was not surprising to find that those who reported excellent/very good health status felt less susceptible to seven of the eight health outcomes than their counterparts did. Finally, older participants felt more susceptible to negative health outcomes that may affect them later in life (i.e. cancer, obesity, cardiovascular disease) as compared to younger partici- pants who perceived more susceptibility and seriousness about STIs. Health communica- tion messages can be perceived as more relevant if they are tailored to an individual based on his or her perceptions of susceptibility and severity about specific health outcomes (Cohn et al. 2018; Kreuter and Wray 2003). Similarly, health education specialists should also consider health status and age when developing targeted messages to young people about preventive care and health promotion activities.

When it comes to the utilization of preventive services in relationship to perceptions of susceptibility, the results showed an interaction between the effect of gender and whether they received cancer, obesity, depression and suicide screenings based on their perception of susceptibility of related health outcomes. Overall, females who received screenings and/or counseling for cancer, obesity, depression and suicide reported higher susceptibility about developing cancer, obesity and mental health illnesses than males. Previous researchers have suggested that females are more willing to seek preventative care (Bertakis et al. 2000). Given the emphasis on the prevention of cervical cancer, obesity (i.e. weight management/body image), and mental health problems among young females, females are probably more likely to feel susceptible and speak with health-care providers about these issues more than males. On the contrary, males who reported receiving cancer screening felt less seriousness about the getting/having cancer than their counterparts. A previous study showed that enrollment in health insurance was associated with higher utilization of preventive health services such as cancer screening among older adults; however, the study failed to show any differences based on gender or perception of susceptibility (Jerant et al. 2013). The current study asked participants to rate their perceptions of susceptibility to a health outcomes and whether they received related screening services; however, the

Table 3. Perceived susceptibility and seriousness means scores preventive service by gender. Preventive service

Cancer screening Obesity screening Depression screening Suicide screening

Susceptibility mean (SD) Male Yes 2.22 (1.09) 2.62 (1.16) 2.77 (1.25) 2.53 (1.23) No 2.37 (1.01) 2.28 (1.16) 2.38 (1.16) 2.45 (1.19)

Female Yes 2.83 (.89)a 3.29 (1.18)a 3.46 (1.24)b 3.39 (1.27)a

No 2.59 (1.00) 2.46 (1.19) 2.52 (1.13) 2.67 (1.20) F 4.28 5.25 7.84 4.85

Seriousness mean (SD) Male Yes 3.19 (1.33)a 3.44 (1.23) 3.46 (1.25) 3.43 (1.20) No 3.65 (1.25) 3.25 (1.15) 3.48 (1.20) 3.49 (1.21)

Female Yes 3.96 (1.15) 3.50 (1.07) 3.77 (1.08) 3.75 (1.07) No 3.95 (1.12) 3.57 (1.09) 3.58 (1.08) 3.61 (1.09)

F 4.84 1.78 1.04 .488

Higher scores represent increased susceptibility and seriousness; ap-value ≤ .05, bp-value ≤ .01.

44 R. R. LUQUIS AND W. S. KENSINGER

study did not account for other variables which might have had an influence on whether they sought the preventive service after feeling susceptible, such as participa- tion in a health promotion program or advice from a health-care provider.

While the study contributed to the application of the HBM to understand how perceptions of susceptibility and seriousness relate to use of preventive care among young adults, several limitations need consideration. The sample included a slightly higher percentage of participants ages 25–34 and females; thus, finding should not be generalized to all young adults. There is a possibility for bias in responses as participants might have provided ‘socially acceptable’ responses and/or given their self-interest in this study. Given the anonymity nature of the survey, nonrespondent data were not collected and thus characterization cannot be made about them. Finally, due to the cross-sectional nature of this study, we need to preclude making causal statements regarding our results.

In the future, researchers should continue to explore the differences in perceptions of susceptibility and severity based on the HBM across gender to enable health education specialists to develop appropriate health promotion and prevention strategies based on gender differences. Studies should also continue to explore the relationship between the utilization of preventive services and the perceptions of susceptibility and seriousness among young adults and whether gender has an effect on this relationship. Studies should also include measurements of self-efficacy and other modifying factors to assess engagement in preventive services among this group. Finally, studies should consider using random sampling methodologies to gather responses from diverse members of this group in order to make better generalizations.

Conclusions

The results of this study suggest that perceptions of susceptibility and seriousness of health outcomes are related to individual’s characteristics (i.e. gender, age), and that those perceptions might influence the utilization of preventive services among those with health- care coverage. Similarly, these results support the notion that when young adults feel susceptible to negative health outcomes and when health-care coverage is available, young adults will seek out preventative care services. Thus, while the future of the ACA is uncertain, health education specialists and health-care professionals should continue to emphasize the use of preventive care services (i.e. health screening and counseling) among young adults. Similarly, health education specialists and health-care professionals should continue to inform young adults about the susceptibility and seriousness of major adverse health conditions, when developing programs to increase the use of prevention screenings in young adults, as these perceptions might play an important role among this group. Hence, future health education and promotion efforts to increase use of preventive services should continue to focus on perceptions of health risk.

Disclosure statement

No potential conflict of interest was reported by the authors.

INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 45

Ethical approval

The study is compliant with the Office for Research Protections, Human Subjects Research, of the Pennsylvania State University.

ORCID

Raffy R. Luquis http://orcid.org/0000-0002-6925-2420

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