Table 5.
Factors Associated with Decision to Screen for Lung Cancer (N=529)
| Variable | Bivariable Model | Multivariable Modela |
|---|---|---|
|
| ||
| Age | 1.13 (1.05, 1.22); p=.0009 | 1.12 (1.04, 1.22);p=.0050 |
|
| ||
| Gender | ||
| Female (n=235) | 0.73 (0.33, 1.62); p=.4364 | |
| Male (n=294) | Reference | |
|
| ||
| Race | ||
| White (n=463) | 1.36 (0.45, 4.09); p=.5863 | |
| Non-White (n=66) | Reference | |
|
| ||
| Education | ||
| Less than high school (n=20) | >99 (<0.1, >999); p=.9998 | |
| High school graduate or equivalent (n=94) | 0.59 (0.19,1.80); p=.3507 | |
| Some college (n=233) | 0.74 (0.28, 1.91); p=.5297 | |
| College graduate or higher (n=182) | reference | |
|
| ||
| Perceived Financial Adequacy | ||
| Enough for special things (n=288) | 0.79 (0.35, 1.79); p=.5684 | |
| Barely or Not Enough (n=241) | Reference | |
|
| ||
| Family History of Lung Cancer | ||
| Yes (n=143) | 0.64 (0.28, 1.49); p=.3044 | |
| No (n=386) | Reference | |
|
| ||
| Smoking Status | ||
| Currently Smokes (n=233) | 1.00 (0.45, 2.25); p=.9963 | |
| Used to Smoke (n=296) | reference | |
|
| ||
| Knowledge: Lung Cancer Risk & Screening | 0.97 (0.63, 1.51); p=.9092 | |
|
| ||
| Lung Cancer Screening Health Beliefs | ||
|
| ||
| Perceived Risk of Lung Cancer | 0.82 (0.64, 1.05); p=.1099 | 0.93 (0.69, 1.25); p=.6146 |
|
| ||
| Perceived Benefits of Lung Cancer Screening | 0.80 (0.71, 0.92); p=.0011 | 0.87 (0.74, 1.02); p=.0787 |
|
| ||
| Perceived Barriers to Lung Cancer Screening | 1.07 (1.02, 1.12); p=.0068 | 1.02 (0.95, 1.09); p=.5594 |
|
| ||
| Self-Efficacy for Lung Cancer Screening | 1.14 (1.06, 1.23); p=.0008 | 1.11 (1.00, 1.23); p=.0407 |
|
| ||
| Psychological Characteristics | ||
|
| ||
| Stigma | 0.89 (0.76, 1.04); p=.1464 | 0.91 (0.76, 1.08); p=.2677 |
|
| ||
| Mistrust (Trust) | 0.93 (0.81, 1.07); p=.2953 | |
|
| ||
| Perception that Lung Cancer Screening Decision was Shared | 1.00 (0.99, 1.01); p=.8695 | |
Multivariable model includes independent variables that had p<.20 from bivariate models.
Values are OR (95% CI) from logistic regression models of decision to opt-in (n=504, 95.3%) versus deciding to not opt-in (n=25, 4.7%).
The odds ratio (OR) for continuous predictors is per a 1-point increase.