Cancer Screening Perception Scale: Development and Construct Validation
- 178 Downloads
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.
KeywordsCancer screening perception scale Factor analysis Construct validation Psychometrics
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.
- 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.Curry SJ, Byers T, Hewitt M (eds) (2003) Fulfilling the potential for cancer prevention and early detection. National Academies Press, Washington, DCGoogle Scholar
- 5.Goroll AH, Mulley AG (2012) Primary care medicine: office evaluation and management of the adult patient. Lippincott Williams & Wilkins, PhiladelphiaGoogle Scholar
- 10.De Vellis RF (2003) Scale Development, 2nd edn. Sage, LondonGoogle Scholar
- 11.Rosenstock IM, Strecher VJ, Becker MH (1988) Social learning theory and the health belief model. Health Educ Behav 15(2):175–183Google Scholar
- 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
- 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.Bond T, Fox CM (2015) Applying the rasch model: fundamental measurement in the human sciences. Routledge, New YorkGoogle Scholar
- 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
- 23.Hair JF, Black WC, Babin BJ, Anderson RE (2010) Multivariate data analysis: a global perspective. Pearson Education Inc., New JerseyGoogle Scholar
- 24.Tabachnik BG, Fidell LS (2001) Using multivariate statistics. Allyn and Bacon, LondonGoogle Scholar
- 25.Arbuckle J, Wothke W (1999) AMOS 4 user’s reference guide. Smallwaters Corp, ChicagoGoogle Scholar
- 26.Ogden J (2012) Health psychology. McGraw-Hill Education, UKGoogle Scholar
- 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.Williams B, Brown T, Onsman A (2012) Exploratory factor analysis: a five-step guide for novices. Australas J Paramed 8(3):1Google Scholar
- 29.Costello AB (2009) Getting the most from your analysis. Pan 12(2):131–146Google Scholar
- 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.de Winter JCF, Dodou D, Wieringa PA (2009) Exploratory factor analysis with small sample sizes. Multivar Behav Res 44(2):147–181Google Scholar