European Journal of Oncology Nursing 18 (2014) 72e77
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European Journal of Oncology Nursing journal homepage: www.elsevier.com/locate/ejon
Factors associated with adherence to fecal occult blood testing for colorectal cancer screening among adults in the Republic of Korea Nayoung Bae a, Sunhee Park b, *, Sungwon Lim c a
Kyung Hee University Hospital at Gangdong, Seoul, Republic of Korea College of Nursing Science, East-West Nursing Research Institute, Kyung Hee University, 26 Kyunghee-daero, Dongdaemun-gu, Seoul 130-071, Republic of Korea c National Evidence-based Health Care Collaborating Agency, Seoul, Republic of Korea b
a b s t r a c t Keywords: Colorectal cancer Screening behavior Fecal occult blood testing Health belief model Korean
Purpose: Repeated participation in fecal occult blood testing (FOBT) is one of the major factors affecting the long-term success of population-based colorectal cancer screening programs. The aim of this study is to explore strong factors linked to repeated participation in FOBT in the prior decade (2002e2011) among adults using the Health Belief Model (HBM) after controlling for other covariates. Methods: Data were obtained from South Korean adults, aged 50 years and over, who visited a national health screening center within a magnet hospital (N ¼ 237). A pilot test was conducted to investigate the internal consistency of the HBM instruments and the clarity of survey questions. Sample characteristics and rates of adherence to FOBT screening were examined using means and frequencies. Important factors associated with adherence to FOBT were examined using multivariate logistic regression analysis. Results: About 44% of the respondents were adherent to FOBT screening over the prior decade. Four out of the six HBM-driven factors (perceived susceptibility, severity, and barriers, and health motivation) were statistically significant. Those with greater levels of susceptibility and health motivation and lower levels of severity and barriers were more likely to adhere to FOBT. Conclusions: Health professionals should focus more on the four modifiable HBM-related factors to encourage adults to adhere to FOBT. Intervention programs, which lower perceived severity and barriers and increase susceptibility and health motivation, should be developed and implemented. Ó 2013 Elsevier Ltd. All rights reserved.
Introduction Colorectal cancer is a major cause of cancer deaths worldwide (World Health Organization, 2012). It was the 7th leading cause of death in 2008 (World Health Organization, 2008). Colorectal cancer is common in western developed countries (Centers for Disease Control and Prevention, n.d.; Haggar and Boushey, 2009). However, recent statistics have shown a significant increase in colorectal cancer in East Asian countries (e.g., South Korea, China, and Japan) (Moghimi-Dehkordi and Safaee, 2012; Pourhoseingholi, 2012; Sung, 2007; Sung et al., 2005). Kim et al. (2011) attribute the increased prevalence of colorectal cancer in South Korea, in part, to a change toward westernized lifestyles, i.e. high meat consumption. According the National Cancer Registry of South Korea, colorectal
* Corresponding author. Tel.: þ82 2 961 0874; fax: þ82 2 961 9398. E-mail addresses: [email protected] (N. Bae), [email protected], [email protected] (S. Park), [email protected] (S. Lim). 1462-3889/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ejon.2013.09.001
cancer ranked second-highest among males (15.2%) and thirdhighest among females (10.6%) in the rates of cancer incidence (Statistics Korea, 2012). Also, the number of deaths per 100,000 persons due to colorectal cancer has risen from 8.8 persons in 2000 to 15.4 persons in 2011 (Statistics Korea, 2012). Thus, it is critical to implement intervention strategies to resolve problems related to colorectal cancer in South Korea. Of the available approaches such as screening, diagnosis, and treatment (Karsa et al., 2010), colorectal cancer screening is cost-effective, and early detection through screening tests significantly enhances cancer survival rates. Accordingly, colorectal cancer screening is strongly encouraged in diverse countries (e.g., Europe, the United States, and South Korea) (Korean National Cancer Center, 2011; Minozzi et al., 2012). The current literature suggests three strengths of FOBT: (a) FOBT is a non-invasive and simple test, which causes minimal harm (Levin et al., 2008; Ministry of Health and Long-Term Care, 2009), (b) the test is affordable (Heitman et al., 2008; Pignone et al., 2011), and (c) the test has been effective in preventing deaths due to colorectal cancer (Pignone et al., 2011).
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However, the test rates for colorectal cancer (35.3%) in South Korea are lower than those for the stomach (64.6%) and cervical cancer (62.4%) (Korean National Cancer Center, 2011). In particular, rates of FOBT are much lower than those for other types of cancer screening. In 2008, only 21.2% of the target examinees in South Korea participated in an FOBT (Shim et al., 2010), although the rate in 2008 is about twice the rate in 2004 (10.5%) (Choi et al., 2012). Furthermore, the rates of FOBT adherence are lower than the rate of one-time FOBT (Fenton et al., 2010). This is a critical matter because repeated FOBT is a major factor affecting the long-term success of population-based screening programs (Janda et al., 2010; Lieberman, 2007). Given efficacy of FOBT and the importance of FOBT adherence, it is urgent to enhance the rates of adherence to FOBT (Fenton et al., 2010; Janda et al., 2010). To do so, significant factors associated with adherence to FOBT must be understood. However, currently little is known about the correlates of FOBT adherence (Beydoun and Beydoun, 2008; Janda et al., 2010). Thus, this study aims to explore the strong factors linked to repeated FOBT among adults aged 50 years and over in South Korea. More specifically, this study focuses on factors derived from the Health Belief Model (HBM): Beydoun and Beydoun (2008) have suggested the necessity of examining the associations between HBM-related factors and FOBT adherence because they are likely to differ from HBM-related factors affecting the initiation of colorectal cancer screening (i.e., CRC). For instance, they propose that levels of self-efficacy and the characteristics of perceived barriers and benefits could be different. Theoretical underpinnings The HBM was developed to understand why programs targeting health behavior changes showed limited success in the 1950s, and since then it has been widely used to elucidate the changes and maintenance of health behaviors (Janz et al., 2005). The HBM is a value-expectancy theory. A person’s engagement in certain behaviors depends on that person’s values and expectation in relation to those behaviors. Values imply the desire to avoid ailments or to get well, and expectations means the belief that certain health activities would avoid or improve illnesses (Champion and Skinner, 2008). The HBM is composed of six components: perceived susceptibility, severity, barriers, and benefits, health motivation, and selfefficacy (Champion and Skinner, 2008; Janz et al., 2005; Rosenstock et al., 1988). Perceived susceptibility and perceived severity mean a person’s belief regarding, respectively, the risks and serious consequences of a health condition. The combination of these two components serves as perceived threat. Perceived barriers signifies adverse aspects of taking a health-related action, while perceived benefits implies the positive effects of taking an action. If a person considers that benefits are greater than barriers, it is more likely that the person engages in the behavior. Health motivation is the desire to engage in a certain behavior. The last component of the HBM is self-efficacy, which is confidence in successfully performing a specific behavior. Methods Sample and procedure This study used a cross-sectional survey design, and collected data from 265 adults aged 50 years and over, who visited a national health screening center within a magnet hospital located in Seoul, South Korea. After obtaining IRB approval for the current research from the magnet hospital (Approval number: KHNMC IRB 2011070), data were collected for approximately one month, from October 29 to the December 31, 2011. Those who did not undergo
73
Table 1 Information on the subscales in the health belief model. Subscale
The number of items
Measurement
Possible score range
Mean (standard deviation)
Cronbach’s alpha
Perceived susceptibility Perceived severity Health motivation Perceived barriers Perceived benefits Self-efficacy
5
5-point Likert Scale ranging from strongly disagree to strongly agree
5e25
2.23 (0.67)
0.88
7e35
2.67 (0.69)
0.83
7e35
3.71 (0.49)
0.70
6
6e30
2.22 (0.59)
0.79
6
6e30
3.86 (0.55)
0.91
5
5e25
3.77 (0.44)
0.54
7 7
an FOBT in the past were excluded from the sample because it was not possible to include these persons as a separate category of the outcome (FOBT adherence), due to the small numbers of respondents (n ¼ 28). Thus, the subjects for this study were those who had an FOBT at least once during the prior decade (2002e 2011) (n ¼ 237). For the current research, the survey questions were revised, and medical terms were paraphrased to enhance clarity. For example, the HBM instruments, which were originally developed for colon cancer, were modified to precisely examine their associations with FOBT. Also, medical terminologies (e.g., FOBT) were changed into easy terms (e.g., stool test) for a better understanding among laypersons. Thus, prior to the full-scale study, a pilot test was performed at the end of October in 2011 on 40 adults, aged 50 years and over in order to examine the clarity of survey questions and the internal consistency of the HBM instruments. The internal consistency of the HBM variables in the pilot study was satisfactory in general: Cronbach’s alpha varied from 0.58 to 0.92. In the full-scale study, cronbach’s alpha for self-efficacy was 0.54, and the other HBM-related factors demonstrated a satisfactory level of internal consistency (Cronbach’s alpha > 0.7) (Table 1). The average age of the respondents was 60 years, and about 55% were in their 50’s (Table 2). Approximately half of the subjects were male (46%) and had a job (46%) at the time of the survey. The majority of respondents graduated from high school (46%), followed by college graduation or higher (30%). A relative majority of the respondents (39%) had a monthly household income ranging from 2.01 to 4 million won (KRW). The average household income in South Korea in 2012 was approximately 4 million won (Korean Statistical Information Service, 2010), which is equivalent to 3597 US dollars. For more detailed sample characteristics, please refer to Table 2. Measures of main interest Adherence to fecal occult blood test A question asking if the respondent had had an FOBT at least every other year during the prior decade (2002e2011) was used. Before 2011, the South Korean government had recommended an FOBT every two years, but since 2011 it has recommended an annual FOBT (Ministry of Government Legislation, 2011a, b). Thus, the current study defined adherence to FOBT as an FOBT every 1e2 years because the respondents were asked about their history of FOBT during the 10 years prior to data collection (2002e2011). Yeses were coded with a value of 1, and noes were coded with a value of 0. Health Belief Model instrument Six factors of main interest in this study (perceived susceptibility, perceived severity, health motivation, perceived barriers,
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Table 2 Sample characteristics (N ¼ 237). Characteristic Age (Unit: Years) 50e59 60e69 70 and over Gender Male Female Employment Status Employed Not Employed Education Level Middle School Graduation or Lower High School Graduation College Graduation or Higher Monthly Household Income (Unit: Million won) 2 and Lower 2.01e4 4.01 and Higher Interest in Health Very High Average Very Low Interest in Health Information Very high Average Very low Familial Cancer History Yes No
Table 3 Inspection rates of adherence to FOBT Screening (N ¼ 237). N (%) 130 (54.9) 82 (34.6) 25 (10.5) 109 (46.0) 128 (54.0) 109 (46.0) 128 (54.0) 57 (24.1) 108 (45.5) 72 (30.4) 82 (35.2) 90 (38.6) 61 (26.2) 88 (37.2) 143 (60.3) 6 (2.5) 106 (44.7) 124 (52.3) 7 (3.0) 96 (40.5) 141 (59.5)
perceived benefits, and self-efficacy) were selected based on the HBM (Rosenstock et al., 1988). The HBM scale for colon cancer screening, developed by Jacobs (2002), was adapted for this study to measure the aforementioned six constructs related to FOBT. The total number of items used in this instrument was 36. Each item was measured on a 5-point Likert scale varying from strongly disagree (1) to strongly agree (5), and the mean score of items representing each subscale was calculated. Higher scores represent higher levels of the measured factor (Table 1). Perceived susceptibility was measured with five questions, which asked subjects about their perceived risks for the development of colorectal cancer (e.g., a higher risk for developing colon cancer within the next ten years). Perceived severity was measured with seven questions, which asked subjects about the detrimental consequences of colon cancer (e.g., changes in lifestyles, relationships with partners, and fear of colorectal cancer). Health motivation was measured with seven questions, which asked subjects about health promoting behaviors to maintain optimum health (e.g., balanced meals, exercise, and regular health checks). Perceived barriers was measured with six questions, which asked subjects about their perceived deterrents to FOBT (e.g., unpleasantness, embarrassment, and excessive time required for the tests). Perceived benefits was measured with six questions, which asked subjects about the positive consequences of FOBT (e.g., reduced worries and risks of death due to colon cancer, and an increased chance of early detection of colorectal cancer). Self-efficacy was measured with five questions, which asked subjects about their confidence in successfully performing FOBT (e.g., knowing how to have an FOBT and making reservations for the test). Measures to control for the effects Additionally, demographics and other factors, which have shown strong associations with FOBT in previous empirical studies, were included as covariates in the analysis (Haggar and Boushey,
Frequency (%) Yes No
105 132
(44.3) (55.7)
Note. Fecal occult blood testing refers to annual or biannual participation in FOBT for the past 10 years (2002e2011).
2009; Vernon, 1997). This was necessary to achieve more precise results (Allison, 1999b). Age. Respondents’ ages were used as a continuous variable, without modification. Gender. Male respondents were coded with a value of 0, and female counterparts were coded with a value of 1. Employment Status. Respondents who held a job at the time of survey were coded with a value of 1, and others were coded with a value of 0. Education Level. One question asking the respondent’s highest level of education was used. The three possible responses were middle school graduation or lower (1), high school graduation (2), and college graduation or higher (3). Monthly Household Income. One question asking the respondent’s average monthly household income was used. The three possible responses varied from 2 million won (KRW) or lower (1) to 4.01 million won or higher (3). Interest in Health. One question asking the respondents about their level of interest in their health was used. The three possible responses varied from very low (1) to very high (3). Interest in Health Information. One question asking the respondents about their level of interest in health information obtained from mass media was used. The three possible responses varied from very low (1) to very high (3). Familial Cancer History. Respondents with a history of cancer in their family were coded with a value of 1, and others were coded with a value of 0. Data analysis Before conducting the analysis, the internal consistency of the HBM constructs was examined using Cronbach’s alpha (Hatcher, 1994). Sample characteristics and rates of adherence to FOBT screening were examined using means and frequencies (Elliot, 1995). A multivariate logistic regression analysis was performed twice to examine the associations between HBM factors and adherence to FOBT screening (Allison, 1999a). In Model 1, the HBMrelated factors were used as covariates; in Model 2, demographics and other factors, which have relationships with FOBT in the literature, were included as covariates along with the HBM-related factors in order to attain more accurate parameter estimates of the HBM-related factors. Multicollinearity among the independent variables was examined before conducting the multivariate logistic regression analysis, and it was found not to be a problem in this study (Allison, 1999b). Results Approximately 44% of the respondents were adherent to FOBT screening over the prior decade (2002e2011). This means that 44% of the subjects have had an FOBT every 1e2 years during the past 10 years (Table 3). Table 4 shows the factors related to adherence to FOBT screening. In Model 1, which examined relationships between the HBM-related factors and adherence to FOBT screening, four out of the six factors were statistically significant (perceived susceptibility, perceived severity, health motivation, and perceived
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Table 4 Factors associated with adherence to FOBT screening. Correlate
Model 1 OR
Perceived Susceptibility 1.642 Perceived Severity 0.582 Health Motivation 2.073 Perceived Barriers 0.442 Perceived Benefits 1.021 Self-Efficacy 1.358 Age Gender (Reference ¼ Male) Employment Status (Reference ¼ Not employed) Education Level (Reference: Middle School Graduation or Lower) High school Graduation College Graduation or Higher Monthly Household Income (Reference: 2 million won and Lower) 2.01e4 Million Won 4.01 Million Won and Higher Interest in Health Interest in Health Information Familial Cancer History
Model 2 95% CI 1.027, 0.365, 1.055, 0.255, 0.587, 0.660,
2.624 0.930 4.073 0.766 1.774 2.796
p-value
OR
95% CI
p-value
0.038 0.024 0.034 0.004 0.943 0.406
1.829 0.522 2.688 0.378 0.862 1.695 0.996 1.199 0.693
1.070, 0.315, 1.199, 0.209, 0.468, 0.770, 0.950, 0.614, 0.351,
3.124 0.867 6.030 0.683 1.585 3.732 1.044 2.344 1.366
0.027 0.012 0.016 0.001 0.632 0.190 0.863 0.595 0.289
1.983 1.631
0.898, 4.375 0.645, 4.127
0.090 0.301
0.671 0.279 1.288 0.551 0.966
0.332, 0.113, 0.633, 0.283, 0.527,
0.267 0.006 0.485 0.080 0.912
1.358 0.691 2.620 1.074 1.774
Note. OR ¼ odds ratio; CI ¼ Confidence Interval. Model 1 includes the six HBM-related factors as covariates. Model 2 includes control factors as well as the six factors used in Model 1 as covariates.
barriers). In Model 2, the associations between the HBM-related factors and adherence to FOBT were investigated after controlling for demographics and other factors. In this analysis, the four HBMrelated factors that demonstrated statistical significance in Model 1 remained statistically significant. With a one-unit increase in susceptibility and health motivation, the likelihood of being adherent to FOBT screening goes up by 83% and 169%, respectively. On the other hand, with a one-unit increase in severity and barriers, the likelihood of being adherent to FOBT screening decreases by 48% and 62%, respectively. In addition, monthly household income was another factor strongly related to adherence to FOBT screening. As compared to those whose monthly household income was 2 million won and lower, those whose monthly household income was 4.01 million won and higher were less likely to be adherent to FOBT screening (72% decrease in the likelihood of being adherent to FOBT).
more FOBT screenings among 17.8% of the male subjects and 13.7% of the female subjects (Gellad et al., 2011). Given that the follow-up period is lengthier in this study than in the previous studies, a higher adherence rate of FOBT in this study is somewhat surprising. This discrepancy in the adherence rates may be partly attributable to the fact that the subjects in this study were those who visited a national health screening center for preventive health examinations. Empirical evidence shows that those who had preventive health examinations had a greater likelihood for being adherent to FOBT than those who did not (Fenton et al., 2010). This is because those who have health examinations are more likely to have an opportunity to obtain advice from health professionals for adherence with FOBT screening (Fenton et al., 2007). Also, because this institution is a nationally renowned hospital, the current participants might have high trust toward FOBT and thus more actively take part in ongoing FOBT screening (Park, 2010).
Discussion
Factors associated with FOBT adherence
Rates of FOBT adherence
Of the six HBM-related constructs, four factors (perceived susceptibility, perceived severity, perceived barriers, and health motivation) were statistically significant in bivariate analyses. The effects of these four factors remained significant in multivariate analysis, which adjusted for the influences of control factors (e.g., demographics, interest in health, and family cancer history). Of the four strong HBM-related factors, three factors (i.e., perceived susceptibility, perceived barriers, and health motivation) demonstrated expected associations. However, the relationship between perceived severity and FOBT adherence was counterintuitive. In this study, a greater level of perceived severity was associated with lower adherence to FOBT screening. In the present literature, there is a paucity of studies examining the association between the HBM-related factors and persistent adherence with FOBT, although there are some studies exploring the relationship of the HBM-related factors with either one-time FOBT or other colorectal cancer screening behaviors (Javadzade et al., 2012; Kiviniemi et al., 2011; Menon et al., 2003; Sun et al., 2004; Sung et al., 2008). In general, the directions of the relationships between the HBM-related factors (perceived susceptibility, perceived barriers, and health motivation) and adherence to FOBT in this study are in accordance with the findings of empirical
In this study, approximately, 44% of the subjects had FOBTs on a regular basis during the prior decade. Currently, there are no studies that have investigated adherence to FOBT among South Korean adults. Recently, Shim et al. (2010) explored the rate of onetime FOBT using data acquired from a representative sample of the South Korean adult population in 2008. The rate of FOBT in this study (44.3%) is higher than it (21.2%) in the study by Shim et al. (2010). The difference in the screening rates of FOBT between these two studies conducted in South Korea may be due to the fact that prior screenings are an important predictor of FOBT adherence (Myers et al., 1993). Given that the participants in this study were those who had at least one prior FOBT, they are more likely to have the test again than those who did not. With respect to the rates of FOBT adherence, the rate found in the present study is generally higher than those of studies conducted in other countries. In a longitudinal study, about 44% of the subjects adhered to FOBT during the 2-year follow-up period (Fenton et al., 2010). Another 2-year follow-up study of women showed that 29% of the subjects were adherent to FOBT (O’Malley et al., 2002). Lastly, a 5-year longitudinal study showed four or
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studies investigating the relationships between the HBM-driven factors and diverse cancer screening behavior: Colorectal cancer screening behavior (CCSB) has a positive association with perceived susceptibility and health motivation, but a negative association with perceived barriers (Kiviniemi et al., 2011; Menon et al., 2003; Sun et al., 2004). In particular, Vernon (1997) proposes that health motivation is one of the most important factor differentiating persistent adherents from non-adherents. In addition, the inverse relationship between perceived severity and adherence to FOBT found in this study replicates the results of previous empirical studies (Kiviniemi et al., 2011; Sun et al., 2004; Sung et al., 2008). In a review study by Kiviniemi et al. (2011), the theoretical association between perceived severity and CCSB remains uncertain, while the majority of the HBM-driven factors (e.g., susceptibility and barriers) had the expected relationship with CCSB, which includes FOBT. As a potential reason for this relation between perceived severity and FOBT, Sung et al. (2008) state that Chinese adults may have strategies to avoid facing the unfavorable consequences of the tests. This is also the case among various ethnic groups (e.g., Australians, ChineseeAmericans, and the French). Adults have frequently reported worries or fears of positive test results (i.e., indicating cancer) as one of the main reasons for avoiding FOBT (Dent et al., 1983; Sun et al., 2004; Vernon, 1997). Another important issue to consider in this study is the nonsignificant effects of self-efficacy and perceived benefits. Beydoun and Beydoun (2008) describe that perceived benefits and selfefficacy may play a different role among adherents of CCSB, as compared to non-adherents. They suggest that those who have experienced screening tests may not need a further increase in selfefficacy, while those who have not experienced the tests may need greater levels of self-efficacy in order to adhere to the tests (Beydoun and Beydoun, 2008). The literature indicates that perceived benefits is a factor associated with endoscopic procedures (colonoscopy and sigmoidoscopy) rather than FOBT, which is consistent with the current finding. More specifically, changes in the levels of perceived benefits across stages of behavior (precontemplation, contemplation, and action), derived from the transtheoretical model, significantly differed among endoscopic procedures but not in FOBT (Rawl et al., 2005). Similarly, perceived benefits were a strong factor affecting endoscopic procedures but not FOBT (James et al., 2002). This may be, in part, due to the fact that perceived benefits plays a pivotal role in sick-role behaviors (Galloway, 2003; Janz and Becker, 1984). FOBT is known as a preventive behavior, whereas endoscopic procedures such as colonoscopy and sigmoidoscopy are known as sick-role behaviors (e.g., early diagnosis of colorectal cancer) (James et al., 2002). In this context, FOBT may be less strongly tied to perceived benefits. Of the control factors, monthly household income (2 million won and lower vs. 4.01 million won and higher) strongly correlated with FOBT adherence; those with higher incomes were less likely to adhere to FOBT. Existing review studies generally suggest that lower incomes are linked to reduced cancer screening rates (e.g., colonoscopy, sigmoidoscopy, and FOBT) (Holden et al., 2010; Vernon, 1997), which is the opposite of the current finding. The costs for the test may be partly attributable to the current finding. Adults with higher incomes may prefer endoscopies, which serves as a diagnostic examination for colorectal cancer, to a standard FOBT since they do not have monetary burdens of endoscopy whose cost is much more expensive than FOBT. An empirical study of Filipino American immigrants supports the statement indicating that income was the one of the two important factors explaining a difference in selection between colonoscopy and FOBT, and those with a higher income tended to choose colonoscopy rather than FOBT (Maxwell et al., 2008).
Limitations of the study This study is subject to five limitations. First, the sample of the current study is not representative to the South Korean population aged 50 years and over. Thus, the sample characteristics of the study should be taken into consideration in interpreting the findings. Second, this study used a cross-sectional design to collect data. Hence, no causal inference between the covariates and the outcome could be explored. Third, information of this study was collected based on self-repots, and thus recall bias might exist. Fourth, this study could not adjust for all the factors that may affect the outcome. Therefore, caution is needed in the interpretation of the results. Finally, a level of internal consistency for self-efficacy was lower than the recommended value (i.e., Cronbach’s alpha ¼ 0.54). However, this value may not be a problem given that the value of 0.7 is a general rule of thumb and the social science literature occasionally reports values lower than 0.6 (Hatcher, 1994). Conclusion This study revealed that four HBM-related factors (i.e., perceived susceptibility, perceived severity, perceived barriers, and health motivation) had a strong association with adherence to FOBT, even after adjusting for the other covariates. A higher likelihood of repeated participation in FOBT was associated with a greater level of perceived susceptibility and health motivation, while it was linked with lower levels of perceived severity and perceived barriers. This implies that health professionals should put more focus on the four modifiable HBM-related factors in order to encourage adults to adhere to FOBT. Intervention programs, which aim to lower perceived severity and barriers, and increase susceptibility and health motivation, should be developed and implemented. Future research should be directed toward exploring the empirical evidence on factors linked to FOBT adherence. In order to investigate the associations between the HBM-related factors and FOBT adherence, a more refined research design (e.g., the utilization of a longitudinal study design and a representative sample) must be taken into account. By doing so, more accurate findings (e.g., causal inference and the generalizability of the findings) can be obtained. Conflict of interest statement All the authors do not have any conflicts of interest. Acknowledgement This research was supported by a grant from the Seoul Nurses Association in 2011. References Allison, P.D., 1999a. Logistic Regression Using SAS: Theory and Application. SAS Institute, Cary, NC. Allison, P.D., 1999b. Multiple Regression: a Primer. Pine Forge Press, Thousand Oaks, CA. Beydoun, H.A., Beydoun, M.A., 2008. Predictors of colorectal cancer screening behaviors among average-risk older adults in the United States. Cancer Causes & Control 19, 339e359. Centers for Disease Control and Prevention, n.d. 2008 Top Ten Cancers in the U.S. Champion, V.L., Skinner, C.S., 2008. The health belief model. In: Glanz, Karen, Rimer, Barbara K., Viswanath, K. (Eds.), Health Behavior and Health Education: Theory, Research, and Practice, fourth ed. Jossey-Bass, san Francisco, CA, pp. 45e65. Choi, K.S., Lee, H.Y., Jun, J.K., Shin, A., Park, E.C., 2012. Adherence to follow-up after a positive fecal occult blood test in an organized colorectal cancer screening program in Korea, 2004-2008. Journal of Gastroenterology and Hepatology 27, 1070e1077.
N. Bae et al. / European Journal of Oncology Nursing 18 (2014) 72e77 Dent, O.F., Bartrop, R., Goulston, K.J., Chapuis, P.H., 1983. Participation in faecal occult blood screening for colorectal cancer. Social Science & Medicine 17, 17e23. Elliot, R.J., 1995. Learning SAS in the Computer Lab. Wadsworth, Belmont, CA. Fenton, J.J., Cai, Y., Weiss, N.S., Elmore, J.G., Pardee, R.E., Reid, R.J., et al., 2007. Delivery of cancer screening: how important is the preventive health examination? Archives of Internal Medicine 167, 580e585. Fenton, J.J., Elmore, J.G., Buist, D.S., Reid, R.J., Tancredi, D.J., Baldwin, L.M., 2010. Longitudinal adherence with fecal occult blood test screening in community practice. Annals of Family Medicine 8, 397e401. Galloway, R.D., 2003. Health promotion: causes, beliefs and measurements. Clinical Medicine & Research 1, 249e258. Gellad, Z.F., Stechuchak, K.M., Fisher, D.A., Olsen, M.K., McDuffie, J.R., Ostbye, T., et al., 2011. Longitudinal adherence to fecal occult blood testing impacts colorectal cancer screening quality. The American Journal of Gastroenterology 106, 1125e1134. Haggar, F.A., Boushey, R.P., 2009. Colorectal cancer epidemiology: incidence, mortality, survival, and risk factors. Clinics in Colon and Rectal Surgery 22, 191e197. Hatcher, L., 1994. A Step-by-step Approach to Using the Sas System for Factor Analysis and Structural Equation Modeling. SAS Institute Inc., Cary, NC. Heitman, S.J., Au, F., Manns, B.J., McGregor, S.E., Hilsden, R.J., 2008. Nonmedical costs of colorectal cancer screening with the fecal occult blood test and colonoscopy. Clinical Gastroenterology and Hepatology 6, 912e917 e911. Holden, D.J., Jonas, D.E., Porterfield, D.S., Reuland, D., Harris, R., 2010. Systematic review: enhancing the use and quality of colorectal cancer screening. Annals of Internal Medicine 152, 668e676. Jacobs, L.A., 2002. Health beliefs of first-degree relatives of individuals with colorectal cancer and participation in health maintenance visits: a populationbased survey. Cancer Nursing 25, 251e265. James, A.S., Campbell, M.K., Hudson, M.A., 2002. Perceived barriers and benefits to colon cancer screening among African Americans in North Carolina: how does perception relate to screening behavior? Cancer Epidemiologh Biomarkers & Prevention 11, 529e534. Janda, M., Hughes, K.L., Auster, J.F., Leggett, B.A., Newman, B.M., 2010. Repeat participation in colorectal cancer screening utilizing fecal occult blood testing: a community-based project in a rural setting. Journal of Gastroenterology and Hepatology 25, 1661e1667. Janz, N.K., Becker, M.H., 1984. The health belief model: a decade later. Health Education Quarterly 11, 1e47. Janz, N.K., Champion, V.L., Strecher, V.J., 2005. The health belief model. In: Glanz, Karen, Rimer, Barbara K., Lewis, Frances Marcus (Eds.), Health Behavior and Health Education: Theory, Research, and Practice, third ed. Jossey-Bass, San Francisco, CA, pp. 45e66. Javadzade, S.H., Mostafavi, F., Hasanzade, A., Reisi, M., Shahnazi, H., Sharifirad, G., 2012. Factors associated with the fecal occult blood testing for colorectal cancer screening based on health belief model structures in moderate risk individuals, Isfahan, 2011. Journal of Education and Heatlh Promotion 1. Karsa, L.V., Lignini, T.A., Patnick, J., Lambert, R., Sauvaget, C., 2010. The dimensions of the CRC problem. Best Practice & Research. Clinical Gastroenterology 24, 381e 396. Kim, J., Park, S., Nam, B.H., 2011. The risk of colorectal cancer is associated with the frequency of meat consumption in a population-based cohort in Korea. Asian Pacific Journal of Cancer Prevention 12, 2371e2376. Kiviniemi, M.T., Bennett, A., Zaiter, M., Marshall, J.R., 2011. Individual-level factors in colorectal cancer screening: a review of the literature on the relation of individual-level health behavior constructs and screening behavior. Psychooncology 20, 1023e1033. Korean National Cancer Center, 2011. A Survey of Cancer Screening Behavior. Korean Statistical Information Service, 2010. Korean Statistical Information Service: the Average Household Income in 2012. Levin, B., Lieberman, D.A., McFarland, B., Andrews, K.S., Brooks, D., Bond, J., et al., 2008. Screening and surveillance for the early detection of colorectal cancer and
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adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US multi-society task force on colorectal cancer, and the American College of Radiology. Gastroenterology 134, 1570e1595. Lieberman, D., 2007. Colorectal cancer screening in primary care. Gastroenterology 132, 2591e2594. Maxwell, A.E., Danao, L.L., Crespi, C.M., Antonio, C., Garcia, G.M., Bastani, R., 2008. Disparities in the receipt of fecal occult blood test versus endoscopy among Filipino American immigrants. Cancer Epidemiology, Biomarkers & Prevention 17, 1963e1967. Menon, U., Champion, V.L., Larkin, G.N., Zollinger, T.W., Gerde, P.M., Vernon, S.W., 2003. Beliefs associated with fecal occult blood test and colonoscopy use at a worksite colon cancer screening program. Journal of Occupational and Environmental Medicine 45, 891e898. Ministry of Government Legislation, 2011a. Enforcement Decree of the National Health Insurance Act (April 22, 2011). Ministry of Government Legislation, 2011b. Enforcement Decree of the National Health Insurance Act (June 30, 2011). Ministry of Health and Long-Term Care, 2009. Fecal Occult Blood Test for Colorectal Cancer Screening: an Evidence-based Analysis. In: Ontario Health Technology Assessment Series, vol. 9, pp. 1e40. Minozzi, S., Armaroli, P., Segnan, N., 2012. European guidelines for quality assurance in colorectal cancer screening and diagnosis. First Editioneprinciples of evidence assessment and methods for reaching recommendations. Endoscopy 44 (Suppl. 3), SE9e14. Moghimi-Dehkordi, B., Safaee, A., 2012. An overview of colorectal cancer survival rates and prognosis in Asia. World Journal of Gastrointestinal Oncology 4, 71e75. Myers, R.E., Balshem, A.M., Wolf, T.A., Ross, E.A., Millner, L., 1993. Adherence to continuous screening for colorectal neoplasia. Medical Care 31, 508e519. O’Malley, A.S., Forrest, C.B., Mandelblatt, J., 2002. Adherence of low-income women to cancer screening recommendations. Journal of General Internal Medicine 17, 144e154. Park, D.I., 2010. The significance of fecal immunochemical test in national cancer screening program. Intestinal Research 8, 200e201. Pignone, M.P., Flitcroft, K.L., Howard, K., Trevena, L.J., Salkeld, G.P., St John, D.J., 2011. Costs and cost-effectiveness of full implementation of a biennial faecal occult blood test screening program for bowel cancer in Australia. The Medical Journal of Australia 194, 180e185. Pourhoseingholi, M.A., 2012. Increased burden of colorectal cancer in Asia. World Journal of Gastrointestinal Oncology 4, 68e70. Rawl, S.M., Menon, U., Champion, V.L., May, F.E., Loehrer Sr., P., Hunter, C., et al., 2005. Do benefits and barriers differ by stage of adoption for colorectal cancer screening? Health Education Research 20, 137e148. Rosenstock, I.M., Strecher, V.J., Becker, M.H., 1988. Social learning theory and the health belief model. Health Education Quarterly 15, 175e183. Shim, J.I., Kim, Y., Han, M.A., Lee, H.Y., Choi, K.S., Jun, J.K., et al., 2010. Results of colorectal cancer screening of the national cancer screening program in Korea, 2008. Cancer Research and Treatment 42, 191e198. Statistics Korea, 2012. The Incidence and Mortality of Cancer. Sun, W.Y., Basch, C.E., Wolf, R.L., Li, X.J., 2004. Factors associated with colorectal cancer screening among ChineseeAmericans. Preventive Medicine 39, 323e329. Sung, J., 2007. Colorectal cancer screening: its time for action in Asia. Cancer Detection and Prevention 31, 1e2. Sung, J.J., Choi, S.Y., Chan, F.K., Ching, J.Y., Lau, J.T., Griffiths, S., 2008. Obstacles to colorectal cancer screening in Chinese: a study based on the health belief model. The American Journal of Gastroenterology 103, 974e981. Sung, J.J., Lau, J.Y., Goh, K.L., Leung, W.K., 2005. Increasing incidence of colorectal cancer in Asia: implications for screening. The Lancet Oncology 6, 871e876. Vernon, S.W., 1997. Participation in colorectal cancer screening: a review. Journal of the National Cancer Institute 89, 1406e1422. World Health Organization, 2008. Ten Leading Causes of Deaths in 2008. World Health Organization, 2012. Cancer.
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European Journal of Oncology Nursing journal homepage: www.elsevier.com/locate/ejon
Factors associated with adherence to fecal occult blood testing for colorectal cancer screening among adults in the Republic of Korea Nayoung Bae a, Sunhee Park b, *, Sungwon Lim c a
Kyung Hee University Hospital at Gangdong, Seoul, Republic of Korea College of Nursing Science, East-West Nursing Research Institute, Kyung Hee University, 26 Kyunghee-daero, Dongdaemun-gu, Seoul 130-071, Republic of Korea c National Evidence-based Health Care Collaborating Agency, Seoul, Republic of Korea b
a b s t r a c t Keywords: Colorectal cancer Screening behavior Fecal occult blood testing Health belief model Korean
Purpose: Repeated participation in fecal occult blood testing (FOBT) is one of the major factors affecting the long-term success of population-based colorectal cancer screening programs. The aim of this study is to explore strong factors linked to repeated participation in FOBT in the prior decade (2002e2011) among adults using the Health Belief Model (HBM) after controlling for other covariates. Methods: Data were obtained from South Korean adults, aged 50 years and over, who visited a national health screening center within a magnet hospital (N ¼ 237). A pilot test was conducted to investigate the internal consistency of the HBM instruments and the clarity of survey questions. Sample characteristics and rates of adherence to FOBT screening were examined using means and frequencies. Important factors associated with adherence to FOBT were examined using multivariate logistic regression analysis. Results: About 44% of the respondents were adherent to FOBT screening over the prior decade. Four out of the six HBM-driven factors (perceived susceptibility, severity, and barriers, and health motivation) were statistically significant. Those with greater levels of susceptibility and health motivation and lower levels of severity and barriers were more likely to adhere to FOBT. Conclusions: Health professionals should focus more on the four modifiable HBM-related factors to encourage adults to adhere to FOBT. Intervention programs, which lower perceived severity and barriers and increase susceptibility and health motivation, should be developed and implemented. Ó 2013 Elsevier Ltd. All rights reserved.
Introduction Colorectal cancer is a major cause of cancer deaths worldwide (World Health Organization, 2012). It was the 7th leading cause of death in 2008 (World Health Organization, 2008). Colorectal cancer is common in western developed countries (Centers for Disease Control and Prevention, n.d.; Haggar and Boushey, 2009). However, recent statistics have shown a significant increase in colorectal cancer in East Asian countries (e.g., South Korea, China, and Japan) (Moghimi-Dehkordi and Safaee, 2012; Pourhoseingholi, 2012; Sung, 2007; Sung et al., 2005). Kim et al. (2011) attribute the increased prevalence of colorectal cancer in South Korea, in part, to a change toward westernized lifestyles, i.e. high meat consumption. According the National Cancer Registry of South Korea, colorectal
* Corresponding author. Tel.: þ82 2 961 0874; fax: þ82 2 961 9398. E-mail addresses: [email protected] (N. Bae), [email protected], [email protected] (S. Park), [email protected] (S. Lim). 1462-3889/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ejon.2013.09.001
cancer ranked second-highest among males (15.2%) and thirdhighest among females (10.6%) in the rates of cancer incidence (Statistics Korea, 2012). Also, the number of deaths per 100,000 persons due to colorectal cancer has risen from 8.8 persons in 2000 to 15.4 persons in 2011 (Statistics Korea, 2012). Thus, it is critical to implement intervention strategies to resolve problems related to colorectal cancer in South Korea. Of the available approaches such as screening, diagnosis, and treatment (Karsa et al., 2010), colorectal cancer screening is cost-effective, and early detection through screening tests significantly enhances cancer survival rates. Accordingly, colorectal cancer screening is strongly encouraged in diverse countries (e.g., Europe, the United States, and South Korea) (Korean National Cancer Center, 2011; Minozzi et al., 2012). The current literature suggests three strengths of FOBT: (a) FOBT is a non-invasive and simple test, which causes minimal harm (Levin et al., 2008; Ministry of Health and Long-Term Care, 2009), (b) the test is affordable (Heitman et al., 2008; Pignone et al., 2011), and (c) the test has been effective in preventing deaths due to colorectal cancer (Pignone et al., 2011).
N. Bae et al. / European Journal of Oncology Nursing 18 (2014) 72e77
However, the test rates for colorectal cancer (35.3%) in South Korea are lower than those for the stomach (64.6%) and cervical cancer (62.4%) (Korean National Cancer Center, 2011). In particular, rates of FOBT are much lower than those for other types of cancer screening. In 2008, only 21.2% of the target examinees in South Korea participated in an FOBT (Shim et al., 2010), although the rate in 2008 is about twice the rate in 2004 (10.5%) (Choi et al., 2012). Furthermore, the rates of FOBT adherence are lower than the rate of one-time FOBT (Fenton et al., 2010). This is a critical matter because repeated FOBT is a major factor affecting the long-term success of population-based screening programs (Janda et al., 2010; Lieberman, 2007). Given efficacy of FOBT and the importance of FOBT adherence, it is urgent to enhance the rates of adherence to FOBT (Fenton et al., 2010; Janda et al., 2010). To do so, significant factors associated with adherence to FOBT must be understood. However, currently little is known about the correlates of FOBT adherence (Beydoun and Beydoun, 2008; Janda et al., 2010). Thus, this study aims to explore the strong factors linked to repeated FOBT among adults aged 50 years and over in South Korea. More specifically, this study focuses on factors derived from the Health Belief Model (HBM): Beydoun and Beydoun (2008) have suggested the necessity of examining the associations between HBM-related factors and FOBT adherence because they are likely to differ from HBM-related factors affecting the initiation of colorectal cancer screening (i.e., CRC). For instance, they propose that levels of self-efficacy and the characteristics of perceived barriers and benefits could be different. Theoretical underpinnings The HBM was developed to understand why programs targeting health behavior changes showed limited success in the 1950s, and since then it has been widely used to elucidate the changes and maintenance of health behaviors (Janz et al., 2005). The HBM is a value-expectancy theory. A person’s engagement in certain behaviors depends on that person’s values and expectation in relation to those behaviors. Values imply the desire to avoid ailments or to get well, and expectations means the belief that certain health activities would avoid or improve illnesses (Champion and Skinner, 2008). The HBM is composed of six components: perceived susceptibility, severity, barriers, and benefits, health motivation, and selfefficacy (Champion and Skinner, 2008; Janz et al., 2005; Rosenstock et al., 1988). Perceived susceptibility and perceived severity mean a person’s belief regarding, respectively, the risks and serious consequences of a health condition. The combination of these two components serves as perceived threat. Perceived barriers signifies adverse aspects of taking a health-related action, while perceived benefits implies the positive effects of taking an action. If a person considers that benefits are greater than barriers, it is more likely that the person engages in the behavior. Health motivation is the desire to engage in a certain behavior. The last component of the HBM is self-efficacy, which is confidence in successfully performing a specific behavior. Methods Sample and procedure This study used a cross-sectional survey design, and collected data from 265 adults aged 50 years and over, who visited a national health screening center within a magnet hospital located in Seoul, South Korea. After obtaining IRB approval for the current research from the magnet hospital (Approval number: KHNMC IRB 2011070), data were collected for approximately one month, from October 29 to the December 31, 2011. Those who did not undergo
73
Table 1 Information on the subscales in the health belief model. Subscale
The number of items
Measurement
Possible score range
Mean (standard deviation)
Cronbach’s alpha
Perceived susceptibility Perceived severity Health motivation Perceived barriers Perceived benefits Self-efficacy
5
5-point Likert Scale ranging from strongly disagree to strongly agree
5e25
2.23 (0.67)
0.88
7e35
2.67 (0.69)
0.83
7e35
3.71 (0.49)
0.70
6
6e30
2.22 (0.59)
0.79
6
6e30
3.86 (0.55)
0.91
5
5e25
3.77 (0.44)
0.54
7 7
an FOBT in the past were excluded from the sample because it was not possible to include these persons as a separate category of the outcome (FOBT adherence), due to the small numbers of respondents (n ¼ 28). Thus, the subjects for this study were those who had an FOBT at least once during the prior decade (2002e 2011) (n ¼ 237). For the current research, the survey questions were revised, and medical terms were paraphrased to enhance clarity. For example, the HBM instruments, which were originally developed for colon cancer, were modified to precisely examine their associations with FOBT. Also, medical terminologies (e.g., FOBT) were changed into easy terms (e.g., stool test) for a better understanding among laypersons. Thus, prior to the full-scale study, a pilot test was performed at the end of October in 2011 on 40 adults, aged 50 years and over in order to examine the clarity of survey questions and the internal consistency of the HBM instruments. The internal consistency of the HBM variables in the pilot study was satisfactory in general: Cronbach’s alpha varied from 0.58 to 0.92. In the full-scale study, cronbach’s alpha for self-efficacy was 0.54, and the other HBM-related factors demonstrated a satisfactory level of internal consistency (Cronbach’s alpha > 0.7) (Table 1). The average age of the respondents was 60 years, and about 55% were in their 50’s (Table 2). Approximately half of the subjects were male (46%) and had a job (46%) at the time of the survey. The majority of respondents graduated from high school (46%), followed by college graduation or higher (30%). A relative majority of the respondents (39%) had a monthly household income ranging from 2.01 to 4 million won (KRW). The average household income in South Korea in 2012 was approximately 4 million won (Korean Statistical Information Service, 2010), which is equivalent to 3597 US dollars. For more detailed sample characteristics, please refer to Table 2. Measures of main interest Adherence to fecal occult blood test A question asking if the respondent had had an FOBT at least every other year during the prior decade (2002e2011) was used. Before 2011, the South Korean government had recommended an FOBT every two years, but since 2011 it has recommended an annual FOBT (Ministry of Government Legislation, 2011a, b). Thus, the current study defined adherence to FOBT as an FOBT every 1e2 years because the respondents were asked about their history of FOBT during the 10 years prior to data collection (2002e2011). Yeses were coded with a value of 1, and noes were coded with a value of 0. Health Belief Model instrument Six factors of main interest in this study (perceived susceptibility, perceived severity, health motivation, perceived barriers,
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Table 2 Sample characteristics (N ¼ 237). Characteristic Age (Unit: Years) 50e59 60e69 70 and over Gender Male Female Employment Status Employed Not Employed Education Level Middle School Graduation or Lower High School Graduation College Graduation or Higher Monthly Household Income (Unit: Million won) 2 and Lower 2.01e4 4.01 and Higher Interest in Health Very High Average Very Low Interest in Health Information Very high Average Very low Familial Cancer History Yes No
Table 3 Inspection rates of adherence to FOBT Screening (N ¼ 237). N (%) 130 (54.9) 82 (34.6) 25 (10.5) 109 (46.0) 128 (54.0) 109 (46.0) 128 (54.0) 57 (24.1) 108 (45.5) 72 (30.4) 82 (35.2) 90 (38.6) 61 (26.2) 88 (37.2) 143 (60.3) 6 (2.5) 106 (44.7) 124 (52.3) 7 (3.0) 96 (40.5) 141 (59.5)
perceived benefits, and self-efficacy) were selected based on the HBM (Rosenstock et al., 1988). The HBM scale for colon cancer screening, developed by Jacobs (2002), was adapted for this study to measure the aforementioned six constructs related to FOBT. The total number of items used in this instrument was 36. Each item was measured on a 5-point Likert scale varying from strongly disagree (1) to strongly agree (5), and the mean score of items representing each subscale was calculated. Higher scores represent higher levels of the measured factor (Table 1). Perceived susceptibility was measured with five questions, which asked subjects about their perceived risks for the development of colorectal cancer (e.g., a higher risk for developing colon cancer within the next ten years). Perceived severity was measured with seven questions, which asked subjects about the detrimental consequences of colon cancer (e.g., changes in lifestyles, relationships with partners, and fear of colorectal cancer). Health motivation was measured with seven questions, which asked subjects about health promoting behaviors to maintain optimum health (e.g., balanced meals, exercise, and regular health checks). Perceived barriers was measured with six questions, which asked subjects about their perceived deterrents to FOBT (e.g., unpleasantness, embarrassment, and excessive time required for the tests). Perceived benefits was measured with six questions, which asked subjects about the positive consequences of FOBT (e.g., reduced worries and risks of death due to colon cancer, and an increased chance of early detection of colorectal cancer). Self-efficacy was measured with five questions, which asked subjects about their confidence in successfully performing FOBT (e.g., knowing how to have an FOBT and making reservations for the test). Measures to control for the effects Additionally, demographics and other factors, which have shown strong associations with FOBT in previous empirical studies, were included as covariates in the analysis (Haggar and Boushey,
Frequency (%) Yes No
105 132
(44.3) (55.7)
Note. Fecal occult blood testing refers to annual or biannual participation in FOBT for the past 10 years (2002e2011).
2009; Vernon, 1997). This was necessary to achieve more precise results (Allison, 1999b). Age. Respondents’ ages were used as a continuous variable, without modification. Gender. Male respondents were coded with a value of 0, and female counterparts were coded with a value of 1. Employment Status. Respondents who held a job at the time of survey were coded with a value of 1, and others were coded with a value of 0. Education Level. One question asking the respondent’s highest level of education was used. The three possible responses were middle school graduation or lower (1), high school graduation (2), and college graduation or higher (3). Monthly Household Income. One question asking the respondent’s average monthly household income was used. The three possible responses varied from 2 million won (KRW) or lower (1) to 4.01 million won or higher (3). Interest in Health. One question asking the respondents about their level of interest in their health was used. The three possible responses varied from very low (1) to very high (3). Interest in Health Information. One question asking the respondents about their level of interest in health information obtained from mass media was used. The three possible responses varied from very low (1) to very high (3). Familial Cancer History. Respondents with a history of cancer in their family were coded with a value of 1, and others were coded with a value of 0. Data analysis Before conducting the analysis, the internal consistency of the HBM constructs was examined using Cronbach’s alpha (Hatcher, 1994). Sample characteristics and rates of adherence to FOBT screening were examined using means and frequencies (Elliot, 1995). A multivariate logistic regression analysis was performed twice to examine the associations between HBM factors and adherence to FOBT screening (Allison, 1999a). In Model 1, the HBMrelated factors were used as covariates; in Model 2, demographics and other factors, which have relationships with FOBT in the literature, were included as covariates along with the HBM-related factors in order to attain more accurate parameter estimates of the HBM-related factors. Multicollinearity among the independent variables was examined before conducting the multivariate logistic regression analysis, and it was found not to be a problem in this study (Allison, 1999b). Results Approximately 44% of the respondents were adherent to FOBT screening over the prior decade (2002e2011). This means that 44% of the subjects have had an FOBT every 1e2 years during the past 10 years (Table 3). Table 4 shows the factors related to adherence to FOBT screening. In Model 1, which examined relationships between the HBM-related factors and adherence to FOBT screening, four out of the six factors were statistically significant (perceived susceptibility, perceived severity, health motivation, and perceived
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Table 4 Factors associated with adherence to FOBT screening. Correlate
Model 1 OR
Perceived Susceptibility 1.642 Perceived Severity 0.582 Health Motivation 2.073 Perceived Barriers 0.442 Perceived Benefits 1.021 Self-Efficacy 1.358 Age Gender (Reference ¼ Male) Employment Status (Reference ¼ Not employed) Education Level (Reference: Middle School Graduation or Lower) High school Graduation College Graduation or Higher Monthly Household Income (Reference: 2 million won and Lower) 2.01e4 Million Won 4.01 Million Won and Higher Interest in Health Interest in Health Information Familial Cancer History
Model 2 95% CI 1.027, 0.365, 1.055, 0.255, 0.587, 0.660,
2.624 0.930 4.073 0.766 1.774 2.796
p-value
OR
95% CI
p-value
0.038 0.024 0.034 0.004 0.943 0.406
1.829 0.522 2.688 0.378 0.862 1.695 0.996 1.199 0.693
1.070, 0.315, 1.199, 0.209, 0.468, 0.770, 0.950, 0.614, 0.351,
3.124 0.867 6.030 0.683 1.585 3.732 1.044 2.344 1.366
0.027 0.012 0.016 0.001 0.632 0.190 0.863 0.595 0.289
1.983 1.631
0.898, 4.375 0.645, 4.127
0.090 0.301
0.671 0.279 1.288 0.551 0.966
0.332, 0.113, 0.633, 0.283, 0.527,
0.267 0.006 0.485 0.080 0.912
1.358 0.691 2.620 1.074 1.774
Note. OR ¼ odds ratio; CI ¼ Confidence Interval. Model 1 includes the six HBM-related factors as covariates. Model 2 includes control factors as well as the six factors used in Model 1 as covariates.
barriers). In Model 2, the associations between the HBM-related factors and adherence to FOBT were investigated after controlling for demographics and other factors. In this analysis, the four HBMrelated factors that demonstrated statistical significance in Model 1 remained statistically significant. With a one-unit increase in susceptibility and health motivation, the likelihood of being adherent to FOBT screening goes up by 83% and 169%, respectively. On the other hand, with a one-unit increase in severity and barriers, the likelihood of being adherent to FOBT screening decreases by 48% and 62%, respectively. In addition, monthly household income was another factor strongly related to adherence to FOBT screening. As compared to those whose monthly household income was 2 million won and lower, those whose monthly household income was 4.01 million won and higher were less likely to be adherent to FOBT screening (72% decrease in the likelihood of being adherent to FOBT).
more FOBT screenings among 17.8% of the male subjects and 13.7% of the female subjects (Gellad et al., 2011). Given that the follow-up period is lengthier in this study than in the previous studies, a higher adherence rate of FOBT in this study is somewhat surprising. This discrepancy in the adherence rates may be partly attributable to the fact that the subjects in this study were those who visited a national health screening center for preventive health examinations. Empirical evidence shows that those who had preventive health examinations had a greater likelihood for being adherent to FOBT than those who did not (Fenton et al., 2010). This is because those who have health examinations are more likely to have an opportunity to obtain advice from health professionals for adherence with FOBT screening (Fenton et al., 2007). Also, because this institution is a nationally renowned hospital, the current participants might have high trust toward FOBT and thus more actively take part in ongoing FOBT screening (Park, 2010).
Discussion
Factors associated with FOBT adherence
Rates of FOBT adherence
Of the six HBM-related constructs, four factors (perceived susceptibility, perceived severity, perceived barriers, and health motivation) were statistically significant in bivariate analyses. The effects of these four factors remained significant in multivariate analysis, which adjusted for the influences of control factors (e.g., demographics, interest in health, and family cancer history). Of the four strong HBM-related factors, three factors (i.e., perceived susceptibility, perceived barriers, and health motivation) demonstrated expected associations. However, the relationship between perceived severity and FOBT adherence was counterintuitive. In this study, a greater level of perceived severity was associated with lower adherence to FOBT screening. In the present literature, there is a paucity of studies examining the association between the HBM-related factors and persistent adherence with FOBT, although there are some studies exploring the relationship of the HBM-related factors with either one-time FOBT or other colorectal cancer screening behaviors (Javadzade et al., 2012; Kiviniemi et al., 2011; Menon et al., 2003; Sun et al., 2004; Sung et al., 2008). In general, the directions of the relationships between the HBM-related factors (perceived susceptibility, perceived barriers, and health motivation) and adherence to FOBT in this study are in accordance with the findings of empirical
In this study, approximately, 44% of the subjects had FOBTs on a regular basis during the prior decade. Currently, there are no studies that have investigated adherence to FOBT among South Korean adults. Recently, Shim et al. (2010) explored the rate of onetime FOBT using data acquired from a representative sample of the South Korean adult population in 2008. The rate of FOBT in this study (44.3%) is higher than it (21.2%) in the study by Shim et al. (2010). The difference in the screening rates of FOBT between these two studies conducted in South Korea may be due to the fact that prior screenings are an important predictor of FOBT adherence (Myers et al., 1993). Given that the participants in this study were those who had at least one prior FOBT, they are more likely to have the test again than those who did not. With respect to the rates of FOBT adherence, the rate found in the present study is generally higher than those of studies conducted in other countries. In a longitudinal study, about 44% of the subjects adhered to FOBT during the 2-year follow-up period (Fenton et al., 2010). Another 2-year follow-up study of women showed that 29% of the subjects were adherent to FOBT (O’Malley et al., 2002). Lastly, a 5-year longitudinal study showed four or
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studies investigating the relationships between the HBM-driven factors and diverse cancer screening behavior: Colorectal cancer screening behavior (CCSB) has a positive association with perceived susceptibility and health motivation, but a negative association with perceived barriers (Kiviniemi et al., 2011; Menon et al., 2003; Sun et al., 2004). In particular, Vernon (1997) proposes that health motivation is one of the most important factor differentiating persistent adherents from non-adherents. In addition, the inverse relationship between perceived severity and adherence to FOBT found in this study replicates the results of previous empirical studies (Kiviniemi et al., 2011; Sun et al., 2004; Sung et al., 2008). In a review study by Kiviniemi et al. (2011), the theoretical association between perceived severity and CCSB remains uncertain, while the majority of the HBM-driven factors (e.g., susceptibility and barriers) had the expected relationship with CCSB, which includes FOBT. As a potential reason for this relation between perceived severity and FOBT, Sung et al. (2008) state that Chinese adults may have strategies to avoid facing the unfavorable consequences of the tests. This is also the case among various ethnic groups (e.g., Australians, ChineseeAmericans, and the French). Adults have frequently reported worries or fears of positive test results (i.e., indicating cancer) as one of the main reasons for avoiding FOBT (Dent et al., 1983; Sun et al., 2004; Vernon, 1997). Another important issue to consider in this study is the nonsignificant effects of self-efficacy and perceived benefits. Beydoun and Beydoun (2008) describe that perceived benefits and selfefficacy may play a different role among adherents of CCSB, as compared to non-adherents. They suggest that those who have experienced screening tests may not need a further increase in selfefficacy, while those who have not experienced the tests may need greater levels of self-efficacy in order to adhere to the tests (Beydoun and Beydoun, 2008). The literature indicates that perceived benefits is a factor associated with endoscopic procedures (colonoscopy and sigmoidoscopy) rather than FOBT, which is consistent with the current finding. More specifically, changes in the levels of perceived benefits across stages of behavior (precontemplation, contemplation, and action), derived from the transtheoretical model, significantly differed among endoscopic procedures but not in FOBT (Rawl et al., 2005). Similarly, perceived benefits were a strong factor affecting endoscopic procedures but not FOBT (James et al., 2002). This may be, in part, due to the fact that perceived benefits plays a pivotal role in sick-role behaviors (Galloway, 2003; Janz and Becker, 1984). FOBT is known as a preventive behavior, whereas endoscopic procedures such as colonoscopy and sigmoidoscopy are known as sick-role behaviors (e.g., early diagnosis of colorectal cancer) (James et al., 2002). In this context, FOBT may be less strongly tied to perceived benefits. Of the control factors, monthly household income (2 million won and lower vs. 4.01 million won and higher) strongly correlated with FOBT adherence; those with higher incomes were less likely to adhere to FOBT. Existing review studies generally suggest that lower incomes are linked to reduced cancer screening rates (e.g., colonoscopy, sigmoidoscopy, and FOBT) (Holden et al., 2010; Vernon, 1997), which is the opposite of the current finding. The costs for the test may be partly attributable to the current finding. Adults with higher incomes may prefer endoscopies, which serves as a diagnostic examination for colorectal cancer, to a standard FOBT since they do not have monetary burdens of endoscopy whose cost is much more expensive than FOBT. An empirical study of Filipino American immigrants supports the statement indicating that income was the one of the two important factors explaining a difference in selection between colonoscopy and FOBT, and those with a higher income tended to choose colonoscopy rather than FOBT (Maxwell et al., 2008).
Limitations of the study This study is subject to five limitations. First, the sample of the current study is not representative to the South Korean population aged 50 years and over. Thus, the sample characteristics of the study should be taken into consideration in interpreting the findings. Second, this study used a cross-sectional design to collect data. Hence, no causal inference between the covariates and the outcome could be explored. Third, information of this study was collected based on self-repots, and thus recall bias might exist. Fourth, this study could not adjust for all the factors that may affect the outcome. Therefore, caution is needed in the interpretation of the results. Finally, a level of internal consistency for self-efficacy was lower than the recommended value (i.e., Cronbach’s alpha ¼ 0.54). However, this value may not be a problem given that the value of 0.7 is a general rule of thumb and the social science literature occasionally reports values lower than 0.6 (Hatcher, 1994). Conclusion This study revealed that four HBM-related factors (i.e., perceived susceptibility, perceived severity, perceived barriers, and health motivation) had a strong association with adherence to FOBT, even after adjusting for the other covariates. A higher likelihood of repeated participation in FOBT was associated with a greater level of perceived susceptibility and health motivation, while it was linked with lower levels of perceived severity and perceived barriers. This implies that health professionals should put more focus on the four modifiable HBM-related factors in order to encourage adults to adhere to FOBT. Intervention programs, which aim to lower perceived severity and barriers, and increase susceptibility and health motivation, should be developed and implemented. Future research should be directed toward exploring the empirical evidence on factors linked to FOBT adherence. In order to investigate the associations between the HBM-related factors and FOBT adherence, a more refined research design (e.g., the utilization of a longitudinal study design and a representative sample) must be taken into account. By doing so, more accurate findings (e.g., causal inference and the generalizability of the findings) can be obtained. Conflict of interest statement All the authors do not have any conflicts of interest. Acknowledgement This research was supported by a grant from the Seoul Nurses Association in 2011. References Allison, P.D., 1999a. Logistic Regression Using SAS: Theory and Application. SAS Institute, Cary, NC. Allison, P.D., 1999b. Multiple Regression: a Primer. Pine Forge Press, Thousand Oaks, CA. Beydoun, H.A., Beydoun, M.A., 2008. Predictors of colorectal cancer screening behaviors among average-risk older adults in the United States. Cancer Causes & Control 19, 339e359. Centers for Disease Control and Prevention, n.d. 2008 Top Ten Cancers in the U.S. Champion, V.L., Skinner, C.S., 2008. The health belief model. In: Glanz, Karen, Rimer, Barbara K., Viswanath, K. (Eds.), Health Behavior and Health Education: Theory, Research, and Practice, fourth ed. Jossey-Bass, san Francisco, CA, pp. 45e65. Choi, K.S., Lee, H.Y., Jun, J.K., Shin, A., Park, E.C., 2012. Adherence to follow-up after a positive fecal occult blood test in an organized colorectal cancer screening program in Korea, 2004-2008. Journal of Gastroenterology and Hepatology 27, 1070e1077.
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