Table 3. Logistic regression model: unadjusted and adjusted odds ratios for access to the internet and comfort with technology in relation to use of the High-Touch method for consent completion. Models adjusted for age, race and ethnicity, education, and consent language. Analysis used Firth bias correction for small-cell adjustment.
| Variablesa | Values (N=605) | P value | |
|---|---|---|---|
| Access to internet, unadjusted ORb (95% CI) | |||
| Yes | 0.390 (0.217-0.702) | <.005 | |
| No | Reference | ||
| Comfort with technology, unadjusted OR (95% CI) | |||
| Comfortable | 0.082 (0.042-0.160) | <.001 | |
| Neutral | 0.199 (0.077-0.510) | <.005 | |
| Uncomfortable | Reference | ||
| Access to internet, adjusted OR (95% CI)c | |||
| Yes | 1.029 (0.498-2.125) | Not significant | |
| No | Reference | ||
| Comfort with technology, adjusted OR (95% CI)c | |||
| Comfortable | 0.118 (0.055-0.255) | <.001 | |
| Neutral | 0.212 (0.077-0.587) | <.005 | |
| Uncomfortable | Reference | ||
Findings reflect the relationship between structural (internet access) and cognitive (technology comfort) dimensions of the Digital Divide Framework. The adjusted model included age, race and ethnicity, education, and consent language as covariates to account for potential confounding. Penalized logistic regression using Firth bias correction was applied due to sparse cells in some categories. Interaction terms between technology comfort × age, technology comfort × race and ethnicity, internet access × age, and internet access × race and ethnicity were tested but were not statistically significant (all P>.24). Missing covariate data were handled via complete-case analysis (8 participants excluded). Sensitivity analyses were conducted and confirmed the robustness of the primary findings.
OR: odds ratio.
Covariates included in adjusted models: Age (18‐29, 30‐39, 40‐49, 50‐59, 60‐69, 70‐79, ≥80 y), race and ethnicity (underrepresented vs non–underrepresented), education (1-8), and consent language (English vs Spanish).