| Literature DB >> 32998298 |
Qike Jia1, Hongliang Chen2, Xuewei Chen3, Qichuan Tang4.
Abstract
PURPOSE: The current study aims to explore the barriers for middle-aged Chinese to learn about and uptake low-dose computed tomography (LDCT) lung cancer screening.Entities:
Keywords: low-dose CT; lung cancer screening; prevention
Mesh:
Year: 2020 PMID: 32998298 PMCID: PMC7579028 DOI: 10.3390/ijerph17197107
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Descriptive Statistics (N = 640).
| Variables | Mean/Percentage | SD | Min | Max |
|---|---|---|---|---|
|
| ||||
| Gender (male) a | 56.67% | |||
| Age | 48.02 | 5.07 | 40 | 60 |
| Household income | 2.76 | 1.23 | 1 | 7 |
| 1 = Below 5000 RMB | 10.5% | |||
| 2 = 5001–12,000 RMB | 38.1% | |||
| 3 = 12,001–25,000 RMB | 30.8% | |||
| 4 = 25,001–35,000 RMB | 10.8% | |||
| 5 = 35,001–55,000 RMB | 6.7% | |||
| 6 = 55,001–80,000 RMB | 1.7% | |||
| 7 = Above 80,001 RMB | 1.4% | |||
| Educational Attainment | 5.34 | 0.96 | 2 | 7 |
| 1 = No education experience | 0% | |||
| 2 = Elementary school | 0.6% | |||
| 3 = Middle school | 4.8% | |||
| 4 = High school | 11.6% | |||
| 5 = Associate degree | 30.8% | |||
| 6 = Bachelor degree | 46.9% | |||
| 7 = Graduate degree | 5.3% | |||
| City Size | 3.73 | 1.10 | 1 | 5 |
| 1 = Villages | 1.7% | |||
| 2 = County-level/Township-level cities | 14.7% | |||
| 3 = Prefecture-level cities | 23.9% | |||
| 4 = Provincial capital cities | 28.7% | |||
| 5 = Beijing/Shanghai/Guangzhou/Shenzhen | 30.9% | |||
| Current or former smokers a | 33.59% | |||
| Family medical history a | 13.12% | |||
| Health insurance coverage (yes) a | 95.47% | |||
| Disease burden | 1.64 | 0.58 | 1 | 4.29 |
a Represents the frequency of a dichotomous variable.
Descriptive Statistics of Independent and Dependent Variables (N = 640).
| Variables | Mean | SD | Min | Max |
|---|---|---|---|---|
|
| ||||
| Intention to have LDCT | 3.02 | 1.20 | 1 | 5 |
| Intention to learn about LDCT | 3.55 | 1.03 | 1 | 5 |
|
| ||||
| Cost concerns | 2.12 | 0.99 | 1 | 5 |
| Access challenges | 2.06 | 1.10 | 1 | 5 |
| Distrust in hospitals | 2.84 | 0.87 | 1 | 4.80 |
| Distrust in doctors | 2.95 | 0.92 | 1 | 5 |
| Fear of disease | 2.75 | 1.04 | 1 | 5 |
| Lack of knowledge | 6.30 | 1.66 | 1.70 | 10 |
| Optimistic bias | 0.48 | 1.12 | −3 | 4 |
Standardized Ordinary Least Squares Regression predicting intention to learn about and uptake Low-Dose Computed Tomography (LDCT) Lung Cancer Screening (N = 640).
| Variables | Model1 a | VIF c | Model2 a | VIF | Model3 b | VIF | Model4 b | VIF |
|---|---|---|---|---|---|---|---|---|
|
| ||||||||
| Cost concerns | −0.19 *** | 1.47 | −0.19 *** | 1.48 | −0.22 *** | 1.47 | −0.23 *** | 1.48 |
| Access challenges | −0.06 | 1.44 | −0.06 | 1.49 | 0.00 | 1.44 | −0.01 | 1.49 |
| Distrust in hospitals | −0.08 | 2.50 | −0.05 | 2.53 | 0.02 | 2.50 | 0.06 | 2.53 |
| Distrust in doctors | 0.01 | 2.42 | −0.01 | 2.45 | −0.11 † | 2.42 | −0.13 * | 2.45 |
| Fears of disease | −0.12 ** | 1.16 | −0.10 ** | 1.21 | −0.09 * | 1.16 | −0.07 † | 1.21 |
| Lack of knowledge | −0.22 *** | 1.01 | −0.18 *** | 1.06 | −0.22 *** | 1.01 | −0.21 *** | 1.06 |
| Optimistic bias | −0.12 ** | 1.01 | −0.08 * | 1.15 | −0.20 * | 1.01 | −0.18 *** | 1.15 |
|
| ||||||||
| Gender (male) | −0.06 | 1.39 | −0.03 | 1.39 | ||||
| Age | 0.08 * | 1.07 | 0.06 † | 1.07 | ||||
| Household income | 0.10 * | 1.35 | 0.07 † | 1.35 | ||||
| Educational attainment | 0.10 ** | 1.20 | 0.07 † | 1.20 | ||||
| City size | 0.00 | 1.24 | 0.07 † | 1.24 | ||||
| Smoking history | 0.09 * | 1.48 | 0.02 | 1.48 | ||||
| Family medical history | 0.06 | 1.07 | 0.02 | 1.07 | ||||
| Insurance coverage | 0.06 † | 1.04 | 0.07 * | 1.04 | ||||
| Disease burden | 0.08 * | 1.15 | 0.11 ** | 1.15 | ||||
| Adjusted R Squared | 0.09 *** | 0.21 *** | 0.07 *** | 0.21 *** |
Note. † p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001. a DV = intention to learn about LDCT scan; b DV = intention to uptake LDCT scan; c VIF stands for Variance Inflation Factor.