t lifestyle” were the least common reasons.


We investigated predictors of the intention to undergo specific health guidance using the HBM components. Perceived threat, net benefit, perceived severity, perceived benefit, and perceived barriers, were associated with intention, and net benefit was a stronger predictor than perceived benefit and perceived barriers.

Our data indicate that net benefit was a stronger predictor of intention than were perceived benefit and perceived barriers. Other studies have investigated perceived benefit/barriers to participation in health-promotion programs [9-12,14,16,18,19]. Some of these analyzed the correlation between benefit/barriers and participation without integrating the two components [12, 17-19]. Thus, there is little information regarding net benefit. However, some studies of health behavior have examined decisional balance [21,22]. These suggested that individuals in the action/maintenance stage perceived more pros (benefits) than cons (barriers), and those in the pre-contemplation stage perceived more cons than pros [21,22]. In this study, people who perceived more benefit than barriers had a greater intention to participate, so our finding is consistent these studies [21,22]. This finding suggests the importance of the combined influence of perceived benefit and perceived barriers, demonstrating that both elevating perceived benefit and reducing perceived barriers are important. Such a change may increase the difference between perceived benefit and perceived barriers and thereby improve participation rates.

We also investigated the reasons that participants did not undergo specific health guidance. The most common answers were “can’t take time” and “don’t know contents.” Many previous studies have reported that time was the most important barrier to participation in WHP programs [9-14]. However, Middlestadt and colleagues reported that individuals with high intention to participate in a worksite wellness program regarded programs that take place outside of work hours or during work hours and at a convenient location as facilitators of participation [12]. Thus, time is a particularly important factor because it can represent both a benefit of and a barrier to WHP programs. Few studies have examined the “don’t know contents” rationale, but Fletcher and colleagues reported that a lack of instructions was one of the barriers to participation in a physical activity program [18]. Therefore, health insurance providers should explain the contents of specific health guidance to patients. These findings will be useful for developing intervention programs to improve the rate of specific health guidance participation.

Perceived threat was a significant predictor of intention, but was weaker than net benefit. This is thought to be due to the fact that perceived susceptibility was not significantly correlated with intention. Some previous studies reported that perceived susceptibility and perceived severity were significant predictors of intention/ behavior, whereas others have not found them to be predictors [22-28]. Therefore, whether perceived threat, perceived severity, and perceived susceptibility correlate with the likelihood of undergoing specific health guidance should be investigated in future research.

The present study has some limitations. First, intention was used, and whether those intentions translate into actually undergoing specific health guidance is uncertain. Second, a self-reported questionnaire was used, and the reliability of responses should be examined. Third, confounders related to the intention to undergo specific health guidance such as lifestyle, health status, working time, and support by management were not investigated and should be a focus of future research.

The strength of this study lies in the fact that we analyzed not only the four subcomponents of the HBM, but also perceived threat and net benefit; these latter two factors explained 39.1% of the variation. Therefore, the HBM can sufficiently predict intention to undergo specific health guidance.


The present study explored the predictors of intention of Japanese workers to undergo specific health guidance using the Health Belief Model. The model using four subcomponents (Model 1) and that using the two main components (perceived threat and net benefit; Model 2) both predicted intention; however, net benefit was a stronger predictor of intention than were perceived benefit or perceived barriers. Therefore, our data suggest that net benefit should be used in analyses based on the HBM, and it is important to both increase benefit and decrease barriers to improve participation in health-promotion programs.


  1. Ministry of Health and Welfare (2006) National Health and Nutrition Survey. http://www.mhlw.go.jp/houdou/2008/04/dl/h0430-2c.pdf
  2. Office for Life-Style Related Diseases Control Health Service Bureau Ministry of Health, Labour and Welfare (2006) Outline for the results of the National Health and Nutrition Survey Japan. http://www.nih.go.jp/eiken/english/research/pdf/nhns2006_outline.pdf
  3. Ministry of Health, Labour and Welfare (2007) Chapter 4: Future health promotion and medicine—Reforming the medical architecture. In: The white paper of the Ministry of Health and Welfare in Heisei 19, KouseiToukeiKyokai, Tokyo, 97-161.
  4. Muramoto, A., Yamamoto, N., Nakamura, M., et al. (2010) Effect of intensive lifestyle intervention programs on metabolic syndrome and obesity: How much weight reduction is needed to improve metabolic comorbidities? Journal of Japan Society for the Study of Obesity, 16, 182-187.
  5. Moriguchi, J., Matsuo, F., Ejima, K., et al. (2011) Effectiveness of specific health guidance against metabolic syndrome. Official Journal of Japan Society of Ningen Dock, 26, 75-79.
  6. Ohnishi, C., Eba, I., Fukuchi, K., et al. (2011) Effect of specific health guidance on patients with extremely high serum triglyceride levels. Official Journal of Japan Society of Ningen Dock,25, 831-836.
  7. Ministry of Health and Welfare. (2010) About implementation status of specific health checkup and specific health guidance in 2008. http://www.mhlw.go.jp/bunya/shakaihosho/iryouseido01/pdf/info03n-01.pdf
  8. Ministry of Health and Welfare. (2011) About implementation status of specific health checkup and specific health guidance in 2009. http://www.mhlw.go.jp/bunya/shakaihosho/iryouseido01/dl/info03_h21_00.pdf
  9. Braeckman, L., Maes, L., Bellemans, M., et al. (1998) Workers participation in a nutrition education programme. Archives of Public Health, 56, 275-289.
  10. Groeneveld, I.F., Proper, K.I., van der Beek, A.J., et al. (2009) Factors associated with non-participation and dropout in a lifestyle intervention for workers with an elevated risk of cardiovascular disease. The International Journal of Behavioral Nutrition and Physical Activity, 6, 80. doi:10.1186/1479-5868-6-80
  11. Kruger, J., Yore, M.M., Bauer, D.R., et al. (2007) Selected barriers and incentives for worksite health promotion services and policies. American Journal of Health Promotion, 21, 439-447. doi:10.4278/0890-1171-21.5.439
  12. Middlestadt, S.E., Sheats, J.L., Geshnizjani, A., et al. (2011) Factors associated with participation in work-site wellness programs: Implications for increasing willingness among rural service employees. Health Education and Behavior, 38, 502-509. doi:10.1177/1090198110384469
  13. Anspaugh, D.J., Hunter, S. and Savage, P. (1996) Enhancing employee participation in Corporate Health Promotion Programs. American Journal of Health Behavior, 20, 112-120.
  14. Mavis, B.E., Stachnik, T.J., Gibson, C.A., et al. (1992) Issues related to participation in worksite health promotion: A preliminary study. American Journal of Health Promotion, 7, 53-60. doi:10.4278/0890-1171-7.1.53
  15. Gucciardi, E., Cameron, J.I., Liao, C.D., et al. (2007) Program design features that can improve participation in health education interventions. BMC Medical Research Methodology, 7, 47. doi:10.1186/1471-2288-7-47
  16. Veitch, J., Clavisi, O. and Owen, N. (1999) Physical activity initiatives for male factory workers: Gatekeepers’ perceptions of potential motivators and barriers. Australian and New Zealand Journal of Public Health, 23, 505-510. doi:10.1111/j.1467-842X.1999.tb01307.x
  17. Alexy, B.B. (1991) Factors associated with participation or nonparticipation in a workplace wellness center. Research in Nursing and Health, 14, 33-40.
  18. Fletcher, G.M., Behrens, T.K. and Domina, L. (2008) Barriers and enabling factors for work-site physical activity programs: a qualitative examination. Journal of Physical Activity andHealth, 5, 418-429.
  19. Sallis, J.F., Hovell, M.F. and Hofstetter, C.R. (1992) Predictors of adoption and maintenance of vigorous physical activity in men and women. Preventive Medicine, 21, 237-251. doi:10.1016/0091-7435(92)90022-A
  20. Janz, N.K. and Becker, M.H. (1984) The Health Belief Model: A decade later. Health Education Quarterly, 11, 1-47. doi:10.1177/109019818401100101
  21. Champion, V.L. and Skinner, C.S. (2008) The Health Belief Model. In: Glanz, K., Rimer, B.K. and Viswanath, K. Eds., Health behavior and health education: Theory, research, and practice. 4th Edition, Jossey-Bass, San Francisco, 189-193.
  22. Blue, C.L. and Valley, J.M. (2002) Predictors of influenza vaccine. Acceptance among healthy adult workers. Official Journal of the American Association of Occupational Health Nurses, 50, 227-233.
  23. Shahrabani, S. and Benzion, U. (2010) Workplace vaccination and other factors impacting influenza vaccination decision among employees in Israel. International Journal of Environmental Research and Public Health, 7, 853-869. doi:10.3390/ijerph7030853
  24. Hay, J.L., Ford, J.S., Klein, D., et al. (2003) Adherence to colorectal cancer screening in mammography-adherent older women. Journal of Behavioral Medicine, 26, 553-576. doi:10.1023/A:1026253802962
  25. Cam, O. and Gumus, A.B. (2009) Breast cancer screening behavior in Turkish women: Relationships with health beliefs and self-esteem, body perception and hopelessness. Asian Pacific Journal of Cancer Prevention, 10, 49-56.
  26. Carpenter, C.J. (2010) A meta-analysis of the effectiveness of health belief model variables in predicting behaveior. Health Communication, 25, 661-669. doi:10.1080/10410236.2010.521906
  27. Painter, J.E., Sales, J.M., Pazol, K., et al. (2010) Psychosocial correlates of intention to receive an influenza vaccination among rural adolescents. Health Education Research, 25, 853-864. doi:10.1093/her/cyq037
  28. Morowatisharifabad, M.A. (2009) The Health Belief Model variables as predictors of risky driving behaviors among commuters in Yazd, Iran. Traffic Injury Prevention, 10, 436-440. doi:10.1080/15389580903081016

Journal Menu >>