Table 4.
Patient Factors Associated with Screening Completion (N=529)
| Variable | Bivariable Model | Multivariable Modela |
|---|---|---|
|
| ||
| Age | 1.05 (1.01, 1.08); p=.0064 | 1.05 (1.02, 1.09); p=.0050 |
|
| ||
| Gender | ||
| Female (n=235) | 1.17 (0.78, 1.74); p=.4461 | |
| Male (n=294) | Reference | |
|
| ||
| Race | ||
| White (n=463) | 1.40 (0.79, 2.46); p=.2495 | |
| Non-White (n=66) | Reference | |
|
| ||
| Education | ||
| Less than high school (n=20) | 1.31 (0.42, 4.13); p=.6407 | |
| High school graduate or equivalent (n=94) | 1.01 (0.57, 1.80); p=.9625 | |
| Some college (n=233) | 0.99 (0.63, 1.55); p=.9687 | |
| College graduate or higher (n=182) | Reference | |
|
| ||
| Perceived Financial Adequacy | ||
| Have enough for special things (=288) | 0.84 (0.56, 1.25); p=.3919 | |
| Barely or Not Enough (n=241) | Reference | |
|
| ||
| Family History of Lung Cancer | ||
| Yes (n=143) | 1.48 (0.92, 2.36); p=.1057 | 1.39 (0.84, 2.31); p=.2044 |
| No (n=386) | Reference | Reference |
|
| ||
| Smoking Status | ||
| Currently smokes (n=233) | 1.01 (0.68, 1.51); p=.9580 | |
| Used to smoke (n=296) | Reference | |
|
| ||
| Knowledge: Lung Cancer Risk & Screening | 1.04 (1.00, 1.09); p=.0323 | 1.24 (1.07, 1.44); p=.0045 |
|
| ||
| Lung Cancer Screening Health Beliefs | ||
|
| ||
| Perceived Risk of Lung Cancer | 0.94 (0.84, 1.05); p=.2787 | |
|
| ||
| Perceived Benefits of Lung Cancer Screening | 0.94 (0.88, 1.01); p=.0741 | 1.00 (0.93, 1.08); p=.9850 |
|
| ||
| Perceived Barriers to Lung Cancer Screening | 1.03 (1.00, 1.05); p=.0338 | 0.99 (0.96, 1.02); p=.4650 |
|
| ||
| Self-Efficacy for Lung Cancer Screening | 1.11 (1.06, 1.16); p<.0001 | 1.12 (1.05, 1.19); p=.0003 |
|
| ||
| Psychological Characteristics | ||
|
| ||
| Stigma | 0.99 (0.92, 1.07);p=.8262 | |
|
| ||
| Mistrust (Trust) | 0.97 (0.90, 1.04); p=.4250 | |
|
| ||
| Perception that Lung Cancer Screening Decision was Shared | 1.01 (1.00, 1.01)); p=.0348 | 1.00 (1.00, 1.01); p=.5333 |
Multivariable model includes independent variables that had p<.20 from bivariate models.
Values are OR (95% CI) from logistic regression models of screening completion (n=399, 75.4%) versus non-completion (n=130, 24.6%).
The odds ratio (OR) for continuous predictors is per a 1-point increase.