Article Figures & Data
Figures
- Figure 1.
Five-factor general colorectal cancer screening measurement model.
Tables
- Table 1.
Demographic characteristics by race and sex from a colorectal cancer screening intervention trial of primary care patients (n = 1,413)
Total (n = 1,411%*) Caucasian males (n = 274%) Caucasian females (n = 291%) African American males (n = 195%) African American females (n = 653%) Test of difference Age, mean 59.2 59.3 59.4 58.1 59.4 F(3) = 2.11, P = 0.086 Marital status Married/partner 42.7 62.8 45.7 62.6 27.0 χ2(3) = 143.9, P < 0.001 Educational attainment <High school 13.1 2.9 6.2 21.5 17.9 χ2(9) = 376.9, P < 0.001 High school/GED 36.4 17.5 23.7 44.6 47.6 Some college 18.2 11.3 16.5 21.0 21.0 4-y college degree+ 32.3 68.2 53.6 12.8 13.5 -
* Some percentages may not add up to 100 due to “refused” and “don't know” responses.
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- Table 2.
Internal consistency reliabilities for five psychosocial scales by race and sex from a colorectal cancer screening intervention trial of primary care patients (n= 1,413)
Constructs Cronbach's α Total (N = 1,411) Caucasian males (n = 274) Caucasian females (n = 291) African American males (n = 195) African American females (n = 653) Salience and coherence 0.563 0.576 0.599 0.552 0.548 Cancer worries 0.600 0.695 0.692 0.570 0.528 Perceived susceptibility 0.647 0.695 0.763 0.526 0.598 Response efficacy 0.637 0.471 0.605 0.683 0.662 Social influence 0.612 0.541 0.551 0.673 0.604 - Table 3.
Results of the single-group and multigroup confirmatory factor analysis of the 16 general colorectal cancer screening items for four race-sex subgroups (n= 1,413) from a colorectal cancer screening intervention trial of primary care patients
Model n χ2 Scaling correction factor Mean-adjusted χ2* df P CFI RMSEA (90% CI) Five-factor White males 274 176.916 171.053 94 0.000 0.892 0.055 (0.041-0.068) White females 291 182.742 154.442 94 0.000 0.914 0.047 (0.033-0.060) Black males 195 119.911 96.601 94 0.407 0.994 0.012 (0.000-0.040) Black females 653 244.121 213.081 94 0.000 0.912 0.044 (0.036-0.052) Five-factor and two correlated errors White males 274 126.920 123.250 92 0.016 0.956 0.035 (0.016-0.050) White females 291 141.781 121.686 92 0.021 0.958 0.033 (0.014-0.048) Black males 195 110.253 90.348 92 0.529 0.999 0.000 (0.000-0.037) Black females 653 187.851 164.390 92 0.000 0.947 0.035 (0.026-0.043) 1. Unconstrained 1,413 566.809 1.14 497.715 368 0.000 0.959 0.016 (0.012-0.019) 2. Equal factor loadings 1,413 650.201 1.19 546.768 401 0.000 0.954 0.016 (0.012-0.019) 3. Equal factor loadings with rcc_low constraint released 1,413 614.380 1.19 518.120 398 0.000 0.962 0.015 (0.011-0.018) Model comparisons χ2diff Difference df Difference test scaling correction factor Mean-adjusted χ2diff† P 1 vs 2 83.392 33 1.75 47.635 0.048 1 vs 3 47.571 30 1.76 27.000 0.623 -
Abbreviations: df, degrees of freedom; scf, scaling correction factor; dtscf, difference test scaling correction factor; RMSEA, root mean square error of approximation.
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↵* The mean-adjusted χ2 is used when the outcome variables has a non-normal distribution. Satorra and Bentler (61) showed that if the usual normal-theory χ2 test statistic is divided by a scaling correction factor, the scaled statistic better approximates a χ2 distribution.
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↵† The difference between two mean-adjusted χ2 for nested models does not follow a χ2 distribution. Satorra and Bentler (66) showed that the following equation for the mean-adjusted difference statistic, which incorporates a difference test scaling correction factor, does follow a χ2 distribution. Mean-adjusted χ2diff = (χ 2nested (χ 2nested − χ 2comparison) / dtscf. dtscf = (dfnested × scfnested − dfcomparison × scfcomparison) / (dfnested − dfcomparison).
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Question no. Variable name Item description Salience and coherence: the perception that performing a health behavior is consistent with beliefs about how to protect and maintain health C1 Cc_sense Colorectal cancer screening makes sense to me. C3 Cc_import Having colorectal cancer screening is an important thing for me to do. C4 Cc_protect Having colorectal cancer screening can help to protect my health. C6 Rcc_healthy I will be just as healthy if I avoid having colorectal cancer screening Cancer worries: concerns about negative consequences of completing the behavior C5 Cc_abnormal I am afraid of having an abnormal colorectal cancer screening test result. C8 Cc_show I am worried that colorectal cancer screening will show that I have colorectal cancer or polyps. Perceived susceptibility: subjective personal risk for developing colorectal cancer or polyps C11 Cc_chigh The chance that I might develop colorectal cancer is high. C12 Rcc_low Compared with other persons my age, I am at lower risk for colorectal cancer. C13 Cc_likely It is very likely that I will develop colorectal cancer or polyps. C15 Cc_phigh The chances that I will develop colorectal polyps are high. Response efficacy: the belief that adopting a behavior will be effective in reducing disease threat C14 Cc_prevented When colorectal polyps are found and removed, colorectal cancer can be prevented C16 Cc_early When colorectal cancer is found early, it can be cured. Social influence: perceived beliefs about and desire to comply with key references' attitudes toward the behavior C2 Cc_famdo I want to do what members of my immediate family think I should do about colorectal cancer screening. C7 Cc_famthk Members of my immediate family think I should have colorectal cancer screening. C9 Cc_drdo My doctor or health professional thinks I should have colorectal cancer screening. C10 Cc_drthk I want to do what my doctor or health professional thinks I should do about colorectal cancer screening.
Volume 14, Issue 12
