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Journal of Cancer Education

, Volume 33, Issue 2, pp 269–277 | Cite as

Cancer Screening Perception Scale: Development and Construct Validation

  • Mohd Ihsani Mahmood
  • Shamsul Azhar Shah
  • Norfazilah Ahmad
  • Norazman Mohd Rosli
Article
  • 197 Downloads

Abstract

The aim of this study was to demonstrate the construct validity of a newly developed cancer screening perception scale as a measure of the perception of cancer screening in general among high-risk but healthy asymptomatic groups.

The cancer screening perception scale (CSPS) was developed based on extensive literature reviews guided by The Health Belief Model. Fifty-five written items were initially pooled, reviewed by experts for face validity, pretested by 25 healthcare workers and translated into Malay using simple back translation. The scale was then distributed to 300 respondents from two health clinics for construct validation purposes. The obtained data were analyzed using the varimax rotation method for exploratory factor analysis (EFA). The data was submitted for further confirmatory factor analysis using AMOS software.

Based on EFA, the results produced five constructs as predicted: perceived severity, perceived susceptibility, perceived benefits, perceived barriers, and cues for action. Two items with low factor loading and unrelated to the recovered domains were removed. Perceived barriers and cues for action had three and two sub-domains respectively which were further confirmed to fit the measurement and structural models. CFA demonstrated the scale fitted GFI = 0.936, CFI = 0.935, RMSEA = 0.076, NORMEDCHISQ = 2.162. The scale discriminated between the domains. Cronbach’s alpha for perceived severity, perceived susceptibility, perceived benefits, perceived barrier, and cues for action were 0.907, 0.877, 0.940, 0.864 and 0.938, respectively.

The cancer screening perception scale with its promising psychometric properties is now available to measure risks to high-risk but healthy, asymptomatic groups aged 18 and above and can also be used for larger scale study purposes.

Keywords

Cancer screening perception scale Factor analysis Construct validation Psychometrics 

Notes

Acknowledgment

The research project was part of doctorate research which funded by the Peruntukan Dana Fundamental PPUKM with the Project Code FF-2015-348 and received ethical approval from the National Medical Research Centre of Malaysia with code approval NMRR-15-1399-26609 (IIR). A special thanks to those direct and indirectly involved in the research.

References

  1. 1.
    World Health Organization (2009) Global health risks: mortality and burden of disease attributable to selected major risks. World Health Organization (WHO), Geneva, SwitzerlandGoogle Scholar
  2. 2.
    Curry SJ, Byers T, Hewitt M (eds) (2003) Fulfilling the potential for cancer prevention and early detection. National Academies Press, Washington, DCGoogle Scholar
  3. 3.
    Wardle J, Robb K, Vernon S, Waller J (2015) Screening for prevention and early diagnosis of cancer. Am Psychol 70(2):119CrossRefPubMedGoogle Scholar
  4. 4.
    Glasgow RE, Marcus AC, Bull SS, Wilson KM (2004) Disseminating effective cancer screening interventions. Cancer 101(S5):1239–1250CrossRefPubMedGoogle Scholar
  5. 5.
    Goroll AH, Mulley AG (2012) Primary care medicine: office evaluation and management of the adult patient. Lippincott Williams & Wilkins, PhiladelphiaGoogle Scholar
  6. 6.
    Farooqui M, Hassali MA, Knight A, Shafie AA, Farooqui MA, Saleem F, Aljadhey H (2013) A qualitative exploration of Malaysian cancer patients’ perceptions of cancer screening. BMC Public Health 13(1):1CrossRefGoogle Scholar
  7. 7.
    Parsa P, Kandiah M, Abdul Rahman H, Zulkefli NM (2006) Barriers for breast cancer screening among Asian women: a mini literature review. Asian Pac J Cancer Prev 7(4):509PubMedGoogle Scholar
  8. 8.
    Lasser KE, Ayanian JZ, Fletcher RH, Good DMJ (2008) Barriers to colorectal cancer screening in community health centers: a qualitative study. BMC Fam Pract 9(1):1CrossRefGoogle Scholar
  9. 9.
    Markovic M, Kesic V, Topic L, Matejic B (2005) Barriers to cervical cancer screening: a qualitative study with women in Serbia. Soc Sci Med 61(12):2528–2535CrossRefPubMedGoogle Scholar
  10. 10.
    De Vellis RF (2003) Scale Development, 2nd edn. Sage, LondonGoogle Scholar
  11. 11.
    Rosenstock IM, Strecher VJ, Becker MH (1988) Social learning theory and the health belief model. Health Educ Behav 15(2):175–183Google Scholar
  12. 12.
    Antshel KM (2002) Integrating culture as a means of improving treatment adherence in the Latino population. Psychol Health Med 7(4):435–449CrossRefGoogle Scholar
  13. 13.
    Lynn MR (1986) Determination and quantification of content validity. Nurs Res 35(6):382–386CrossRefPubMedGoogle Scholar
  14. 14.
    Rosnah I, Hassim IN, Shafizah AS (2013) A systematic translation and cultural adaptation process for Three-Factor Eating Questionnaire (TFEQ-R21). Med J Malaysia 68(5):425Google Scholar
  15. 15.
    Brislin RW (1976) Comparative research methodology: cross-cultural studies. Int J Psychol 11(3):215–29CrossRefGoogle Scholar
  16. 16.
    Naing L (2010) Reliability analysis. First UKMMC Intermediate to Advance Biostatistics in Medical Sciences Workshop. Anjuran Jabatan Kesihatan Masyarakat, Faculty Perubatan, Universiti Kebangsaan Malaysia, Cheras, Kuala LumpurGoogle Scholar
  17. 17.
    Bond T, Fox CM (2015) Applying the rasch model: fundamental measurement in the human sciences. Routledge, New YorkGoogle Scholar
  18. 18.
    Bentler PM (1990) Comparative fit indexes in structural models. Psychol Bull 107(2):238CrossRefPubMedGoogle Scholar
  19. 19.
    Jöreskog KG, Sörbom D (1986) LISREL VI: analysis of linear structural relationships by maximum likelihood, instrumental variables, and least squares methods. Scientific Software, ArizonaGoogle Scholar
  20. 20.
    Bollen KA (1989) A new incremental fit index for general structural equation models. Sociol Methods Res 17(3):303–316CrossRefGoogle Scholar
  21. 21.
    Browne MW, Cudeck R (1992) Alternative ways of assessing model fit. Sociol Methods Res 21(2):230–258CrossRefGoogle Scholar
  22. 22.
    Marsh HW, Hocevar D (1985) Application of confirmatory factor analysis to the study of self-concept: first-and higher order factor models and their invariance across groups. Psychol Bull 97(3):562CrossRefGoogle Scholar
  23. 23.
    Hair JF, Black WC, Babin BJ, Anderson RE (2010) Multivariate data analysis: a global perspective. Pearson Education Inc., New JerseyGoogle Scholar
  24. 24.
    Tabachnik BG, Fidell LS (2001) Using multivariate statistics. Allyn and Bacon, LondonGoogle Scholar
  25. 25.
    Arbuckle J, Wothke W (1999) AMOS 4 user’s reference guide. Smallwaters Corp, ChicagoGoogle Scholar
  26. 26.
    Ogden J (2012) Health psychology. McGraw-Hill Education, UKGoogle Scholar
  27. 27.
    Hafizah P, Zaleha MI, Shamsul AS (2002) The validation of questionnaire on risk perception of developing five most common non-communicable diseases in Malaysia. J Nurs Health Sci 1(2):29–35Google Scholar
  28. 28.
    Williams B, Brown T, Onsman A (2012) Exploratory factor analysis: a five-step guide for novices. Australas J Paramed 8(3):1Google Scholar
  29. 29.
    Costello AB (2009) Getting the most from your analysis. Pan 12(2):131–146Google Scholar
  30. 30.
    Schermelleh-Engel K, Moosbrugger H, Müller H (2003) Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychol Res Online 8(2):23–74Google Scholar
  31. 31.
    de Winter JCF, Dodou D, Wieringa PA (2009) Exploratory factor analysis with small sample sizes. Multivar Behav Res 44(2):147–181Google Scholar

Copyright information

© American Association for Cancer Education 2016

Authors and Affiliations

  1. 1.Community Health Department, UKM Medical CenterNational University of Malaysia, Jalan Yaacob LatiffKuala LumpurMalaysia

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