Top

BMC Public Health

Published in:

Open Access 01-12-2021 | Lung Cancer | Research

Extended parallel process model (EPPM) in evaluating lung Cancer risk perception among older smokers

Authors: Fatemeh Zarghami, Hamid Allahverdipour, Mohammad Asghari Jafarabadi

Published in: BMC Public Health | Issue 1/2021

Abstract

Background

There is a lack of scientific literature on the application of fear appeals theories to evaluate lung cancer risk perception among smokers. The aim of the present study is to apply the Extended Parallel Process Model (EPPM) to discover the perception of the smokers about their lifetime risk of developing lung cancer (perceived susceptibility), their perception of lung cancer survival (perceived severity), response efficacy, self-efficacy, and readiness to quit.

Methods

In this cross-sectional study, 215 eligible smokers (aged 45 years and over who have smoked at least 1 pack per day in the last 5 years) were recruited. The data collection tool was designed using validate self-report questionnaires and it was contained items on the perceived risk of a smoker contracting lung cancer and perceived lung cancer survival rate. It also had questions to measure the main constructs of the EPPM and Readiness to quit (“Low_Readiness”, and “High_Readiness”). To test how the data support conceptual EPPM to data, Generalized Structural Equation Modeling (GSEM) was used.

Results

Findings showed a significant relationship between Perceived_Susceptibility and Perceived_Response Efficacy; (B = 1.16, P < 0.001); between Perceived_Susceptibility and Perceived_Self Efficacy, (B = -0.93, P < 0.001), Perceived_Severity, and Perceived_Response Efficacy (B = 1.07, P < 0.001). There was also a significant relationship between Perceived_Threat and Perceived_Response Efficacy; between Perceived_Threat and Perceived_Self Efficacy. The relationship between High_Readiness and Perceived_Self Efficacy, and between High_Readiness and Perceived_Severity also were significant. However, the relationships between High_Readiness and Perceived_Threat were not significant (P > 0.05).

Conclusion

Perceived_threat and Perceived_efficacy were important for smokers with low readiness to quit, while Perceived_efficacy was most important for smokers with high readiness to quit. These findings could be used in promoting lung cancer awareness and designing smoking cessation programs based on smokers’ stages of change.

Ghasemian A, Rezaei N, Saeedi Moghaddam S, et al. Tobacco Smoking Status and the Contribution to Burden of Diseases in Iran, 1990–2010: findings from the Global Burden of Disease Study 2010. Arch Iran Med. 2015;18(8):493–501. https://doi.org/10.1015/188/AIM.006.CrossRefPubMed

Rezaei S, Akbari Sari A, Arab M, Majdzadeh R, Mohammadpoorasl A. Estimating the economic burden of cancer deaths attributable to smoking in Iran. J Res Health Sci. 2015;15(4):228-33.

Moosazadeh M, Ziaaddini H, Mirzazadeh A, Ashrafi-Asgarabad A, Haghdoost AA. Meta-analysis of Smoking Prevalence in Iran. Addict Health. 2013 Summer-Autumn;5(3-4):140-53.

Lung Cancer Statistics | How Common is Lung Cancer. Accessed December 30, 2019. https://www.cancer.org/cancer/lung-cancer/about/key-statistics.html

Cancer of the Lung and Bronchus - SEER Stat Fact Sheets. Accessed December 3, 2016. https://seer.cancer.gov/statfacts/html/lungb.html

O'Keeffe LM, Taylor G, Huxley RR, Mitchell P, Woodward M, Peters SAE. Smoking as a risk factor for lung cancer in women and men: a systematic review and meta-analysis. BMJ Open. 2018;8(10):e021611. https://doi.org/10.1136/bmjopen-2018-021611.

Alberg AJ, Nonemaker J. Who is at high risk for lung cancer? Population-level and individual-level perspectives. Semin Respir Crit Care Med. 2008;29(3):223–32. https://doi.org/10.1055/s-2008-1076742.CrossRefPubMedPubMedCentral

Alberg AJ, Samet JM. Epidemiology of lung cancer. Chest. 2003;123(1 Suppl):21S–49S. https://doi.org/10.1378/chest.123.1_suppl.21s.CrossRefPubMed

CDC-Division of Cancer Prevention and Control C. CDC - What Are the Risk Factors for Lung Cancer? Smoking. Published 2019. Accessed 3 Dec 2018. https://www.cdc.gov/cancer/lung/basic_info/risk_factors.htm

10.

Briss P, Rimer B, Reilley B, Coates RC, Lee NC, Mullen P, et al. Promoting informed decisions about cancer screening in communities and healthcare systems. Am J Prev Med. 2004;26(1):67–80. https://doi.org/10.1016/j.amepre.2003.09.012.CrossRefPubMed

11.

Witte K, Gary Meyers, Martel D. SAGE Books - Effective Health Risk Messages: A Step-by-Step Guide. Published 2001. Accessed 31 Dec 2019. http://sk.sagepub.com/books/effective-health-risk-messages

12.

Chen LS, Kaphingst KA. Risk perceptions and family history of lung Cancer: differences by smoking status. Public Health Genomics. 2010;14(1):26–34. https://doi.org/10.1159/000294151.CrossRefPubMedPubMedCentral

13.

Witte K. Fear control and danger control: a test of the extended parallel process model (EPPM). Commun Monogr. 1994;61(2):113–34. https://doi.org/10.1080/03637759409376328.CrossRef

14.

Wong NCH, Cappella JN. Antismoking threat and efficacy appeals: effects on smoking cessation intentions for smokers with low and high readiness to quit. J Appl Commun Res JACR. 2009;37(1):1–20. https://doi.org/10.1080/00909880802593928.CrossRefPubMed

15.

Morman MT. The influence of fear appeals, message design, and masculinity on men’s motivation to perform the testicular self-exam. J Appl Commun Res. 2000;28(2):91–116. https://doi.org/10.1080/00909880009365558.CrossRef

16.

Hubbell AP. Mexican American women in a rural area and barriers to their ability to enact protective behaviors against breast cancer. Health Commun. 2006;20(1):35–44. https://doi.org/10.1207/s15327027hc2001_4.CrossRefPubMed

17.

Cho H, Salmon CT. Fear appeals for individuals in different stages of change: intended and unintended effects and implications on public health campaigns. Health Commun. 2006;20(1):91–9. https://doi.org/10.1207/s15327027hc2001_9.CrossRefPubMed

18.

Birmingham WC, Hung M, Boonyasiriwat W, Kohlmann W, Walters ST, Burt RW, et al. Effectiveness of the extended parallel process model in promoting colorectal cancer screening: EPPM in CRC screening. Psychooncology. 2015;24(10):1265–78. https://doi.org/10.1002/pon.3899.CrossRefPubMedPubMedCentral

19.

Brown VJ. Risk perception: It’s personal. Environ Health Perspect. 2014;122(10):A276–9. https://doi.org/10.1289/ehp.122-A276.CrossRefPubMedPubMedCentral

20.

Fischhoff B, Bostrom A, Jacobs Quadrel M. Risk Perception and Communication. Vol 14; 1993. https://doi.org/10.1146/annurev.pu.14.050193.001151.CrossRef

21.

Termeh Zonouzy V, Niknami S, Ghofranipour F, Montazeri A. An educational intervention based on the extended parallel process model to improve attitude, behavioral intention, and early breast cancer diagnosis: a randomized trial. Int J Women’s Health. 2018;11:1–10. https://doi.org/10.2147/IJWH.S182146.CrossRef

22.

Chen L, Yang X, Fu L, Liu X, Yuan C. Using the Extended Parallel Process Model to Examine the Nature and Impact of Breast Cancer Prevention Information on Mobile-Based Social Media: Content Analysis. JMIR MHealth UHealth. 2019;7(6). https://doi.org/10.2196/13987.

23.

Ooms J, Jansen C, Hoeks J. The EPPM put to the test: evaluating four basic propositions. Dutch J Appl Linguist. 2015;4(2):241–56. https://doi.org/10.1075/dujal.4.2.07oom.CrossRef

24.

Chen L, Yang X. Using EPPM to evaluate the effectiveness of fear appeal messages across different media outlets to increase the intention of breast self-examination among Chinese women. Health Commun. 2019;34(11):1369–76. https://doi.org/10.1080/10410236.2018.1493416.CrossRefPubMed

25.

Mazloomy Mahmoodabad SS, Gerayllo S, Mizani N. Factors Influencing Skin Cancer Preventive Behaviors Based on the Extended Parallel Process Model in Yazd University of Medical Sciences Students, 2017. J Community Health Res. 2019. Published online October 12, 2019. https://doi.org/10.18502/jchr.v8i3.1563.

26.

(PDF) The Effects of Fear Appeals and Message Format on Promoting Skin Cancer Prevention Behaviors among College Students. Accessed 28 Mar 2020. https://www.researchgate.net/publication/339450046_The_Effects_of_Fear_Appeals_and_Message_Format_on_Promoting_Skin_Cancer_Prevention_Behaviors_among_College_Students

27.

Pengchit W, Walters ST, Simmons RG, Kohlmann W, Burt RW, Schwartz MD, et al. Motivation-based intervention to promote colonoscopy screening: an integration of a fear management model and motivational interviewing. J Health Psychol. 2011;16(8):1187–97. https://doi.org/10.1177/1359105311402408.CrossRefPubMedPubMedCentral

28.

Gollust SE, Schroeder SA, Warner KE. Helping smokers quit: understanding the barriers to utilization of smoking cessation services. Milbank Q. 2008;86(4):601–27. https://doi.org/10.1111/j.1468-0009.2008.00536.x.CrossRefPubMedPubMedCentral

29.

Sharifirad G, charkazi A, Berdi-Ghourchaei A, Shahnazi H, Moudi M, et al. Smoking Behavior Based on Stages of Change Model Among Iranian Male Students in 2009-2010 Academic Year. Zahedan J Res Med Sci. 2012;14(1):e93610.

30.

Jafari T, Shahrokhi S. Prevention, Treatment, and Control of Cigarett Use. Published online 2010. http://nafass.old.piho.ir/UploadedFiles/XFiles/nafass/pdf/dastor%20ol%20amal%20ejrayee.pdf

31.

Soltanipour S, Heidarzadeh A, Jafarinezhad A. Reliability and validity of the Persian [Farsi] version of the risk perception survey-diabetes mellitus. East Mediterr Health J. 2014;20(3):190–5. https://doi.org/10.26719/2014.20.3.190.CrossRefPubMed

32.

Graybill FA. An Introduction to Linear Statistical Models, Vol 1. 1st ed. NY: McGraw-Hill Co; 1961.

33.

Guenther WC. Desk calculation of probabilities for the distribution of the sample correlation coefficient. Am Stat. 1977;31(1):45–8. https://doi.org/10.1080/00031305.1977.10479195.CrossRef

34.

Zar JH. Biostatistical analysis. 2nd. Prentice-Hall - Google Search. Biostatistical Analysis. Published 1984. Accessed 6 Nov 2019. https://www.google.com/search?q=Biostatistical+Analysis.+Second+Edition.+Prentice-Hall&oq=Biostatistical+Analysis.+Second+Edition.+Prentice-Hall&aqs=chrome..69i57.500j0j7&sourceid=chrome&ie=UTF-8

35.

Tinsley H, Brown S. Handbook of Applied Multivariate Statistics and Mathematical Modeling. 1st ed: Academic Press; 2000. https://doi.org/10.1016/B978-0-12-691360-6.X5000-9.

36.

Ryan H, Trosclair A, Gfroerer J. Adult current smoking: differences in definitions and prevalence estimates—NHIS and NSDUH, 2008. J Environ Public Health. https://doi.org/10.1155/2012/918368.

37.

Tindle HA, Stevenson Duncan M, Greevy RA, et al. Lifetime Smoking History and Risk of Lung Cancer: Results From the Framingham Heart Study. JNCI J Natl Cancer Inst. 2018;110(11):1201–7. Published online May 16, 2018. https://doi.org/10.1093/jnci/djy041.CrossRefPubMed

38.

Wehring HJ, Liu F, McMahon RP, Mackowick KM, Love RC, Dixon L, et al. Clinical characteristics of heavy and non-heavy smokers with schizophrenia. Schizophr Res. 2012;138(0):285–9. https://doi.org/10.1016/j.schres.2012.03.024.CrossRefPubMedPubMedCentral

39.

Key Statistics for Lung Cancer. Published 2019. Accessed 3 Dec 2018. https://www.cancer.org/cancer/non-small-cell-lung-cancer/about/key-statistics.html

40.

Peto J. That the effects of smoking should be measured in pack-years: misconceptions 4. Br J Cancer. 2012;107(3):406–7. https://doi.org/10.1038/bjc.2012.97.CrossRefPubMedPubMedCentral

41.

Prochaska JO, Diclemente CC, Norcross JC. In search of how people change. Applications to addictive behaviors. Am Psychol. 1992;47(9):1102–14. https://doi.org/10.1037//0003-066x.47.9.1102.CrossRefPubMed

42.

Jhun H-J, Seo H-G. The stages of change in smoking cessation in a representative sample of Korean adult smokers. J Korean Med Sci. 2006 Oct;21(5):843–8. https://doi.org/10.3346/jkms.2006.21.5.843.CrossRefPubMedPubMedCentral

43.

Muthén LK, Muthén B. Mplus statistical analysis with latent variables: User’s guide. Muthén & Muthén; 2010. Accessed 31 Dec 2019. http://www.statmodel.com

44.

Gore TD, Bracken CC. Testing the theoretical design of a health risk message: reexamining the major tenets of the extended parallel process model. Health Educ Behav Off Publ Soc Public Health Educ. 2005;32(1):27–41. https://doi.org/10.1177/1090198104266901.CrossRef

45.

Chen L-S, Kaphingst KA, Tseng T-S, Zhao S. How are lung cancer risk perceptions and cigarette smoking related?—testing an accuracy hypothesis. Transl Cancer Res. 2016;5(Suppl 5):S964–71. https://doi.org/10.21037/tcr.2016.10.75.CrossRefPubMedPubMedCentral

46.

Lundborg P, Lindgren B. Do they know what they are doing? Risk perceptions and smoking behaviour among Swedish teenagers. J Risk Uncertain. 2004;28(3):261–86. https://doi.org/10.1023/B:RISK.0000026098.84109.62.CrossRef

47.

Finney Rutten LJ, Blake KD, Hesse BW, Augustson EM, Evans S. Illness representations of lung cancer, lung cancer worry, and perceptions of risk by smoking status. J Cancer Educ Off J Am Assoc Cancer Educ. 2011;26(4):747–53. https://doi.org/10.1007/s13187-011-0247-6.CrossRef

48.

Weinstein ND, Marcus SE, Moser RP. Smokers’ unrealistic optimism about their risk. Tob Control. 2005;14(1):55–9. https://doi.org/10.1136/tc.2004.008375.CrossRefPubMedPubMedCentral

49.

Helweg-Larsen M, Nielsen GA. Smoking cross-culturally: risk perceptions among young adults in Denmark and the United States. Psychol Health. 2009;24(1):81–93. https://doi.org/10.1080/08870440801932656.CrossRefPubMed

50.

Liu J-T, Hsieh C-R. Risk perception and smoking behavior: empirical evidence from Taiwan. J Risk Uncertain. 1995;11(2):139–57.CrossRef

51.

Helweg-Larsen M, Stancioff LM. Acculturation matters: risk perceptions of smoking among Bosnian refugees living in the United States. J Immigr Minor Health. 2008;10(5):423–8. https://doi.org/10.1007/s10903-007-9107-1.CrossRefPubMed

52.

Katapodi MC, Lee KA, Facione NC, Dodd MJ. Predictors of perceived breast cancer risk and the relation between perceived risk and breast cancer screening: a meta-analytic review. Prev Med. 2004;38(4):388–402. https://doi.org/10.1016/j.ypmed.2003.11.012.CrossRefPubMed

53.

Savoy E, Reitzel LR, Scheuermann TS, Agarwal M, Mathur C, Choi WS, et al. Risk perception and intention to quit among a tri-ethnic sample of nondaily, light daily, and moderate/heavy daily smokers. Addict Behav. 2014 Oct;39(10):1398–403. https://doi.org/10.1016/j.addbeh.2014.05.002.CrossRefPubMedPubMedCentral

54.

Ziebarth NR. Lung cancer risk perception biases. Prev Med. 2018;110:16–23. https://doi.org/10.1016/j.ypmed.2018.01.020.CrossRefPubMed

55.

Ziebarth N. Biased lung Cancer risk perceptions: smokers are misinformed. Jahrb Für Natl Stat. 2018;238:395–421. https://doi.org/10.1515/jbnst-2018-0017.CrossRef

56.

Masiero M, Lucchiari C, Pravettoni G. Personal fable: optimistic Bias in cigarette smokers. Int J High Risk Behav Addict. 2015;4(1):e20939. https://doi.org/10.5812/ijhrba.20939.CrossRefPubMedPubMedCentral

57.

Poggiolini C. High self-efficacy regarding smoking cessation may weaken the intention to quit smoking. Cogent Psychol. 2019;6(1). https://doi.org/10.1080/23311908.2019.1574096.

58.

Fotuhi O, Fong GT, Zanna MP, Borland R, Yong H-H, Cummings KM. Patterns of cognitive dissonance-reducing beliefs among smokers: a longitudinal analysis from the international tobacco control (ITC) four country survey. Tob Control. 2013 Jan;22(1):52–8. https://doi.org/10.1136/tobaccocontrol-2011-050139.CrossRefPubMed

59.

Popova L. The extended parallel process model: illuminating the gaps in research. Health Educ Behav. 2012;39(4):455–73. https://doi.org/10.1177/1090198111418108.CrossRefPubMed

60.

Allahverdipour H, MacIntyre R, Hidarnia A, et al. Assessing protective factors against drug abuse among high school students: self-control and the extended parallel process model. J Addict Nurs. 2007;18(2):65–73. https://doi.org/10.1080/10884600701334820.CrossRef

Title: Extended parallel process model (EPPM) in evaluating lung Cancer risk perception among older smokers
Authors: Fatemeh Zarghami
Hamid Allahverdipour
Mohammad Asghari Jafarabadi
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Lung Cancer
Lung Cancer
Lung Cancer
Published in: BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-021-11896-1

2024 ASCO Annual Meeting

Springer Medicine

Extended parallel process model (EPPM) in evaluating lung Cancer risk perception among older smokers

Abstract

Background

Methods

Results

Conclusion

2024 ASCO Annual Meeting

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 1/2021

Determinants of perceived health and unmet healthcare needs in universal healthcare systems with high gender equality

Patients at high risk for a severe clinical course of COVID-19 — small-area data in support of vaccination and other population-based interventions in Germany

Empowerment among adult patients with type 2 diabetes: age differentials in relation to person-centred primary care, community resources, social support and other life-contextual circumstances

What have we learned about COVID-19 volunteering in the UK? A rapid review of the literature

Community interventions for improving adult mental health: mapping local policy and practice in England

Portuguese Physical Literacy Assessment Questionnaire (PPLA-Q) for adolescents (15–18 years) from grades 10–12: development, content validation and pilot testing