Table 2.
Multivariable Logistic Regression Models for User Issues and Personal Connection
| Outcomes by patient characteristics | Odds ratio (OR) | Lower 95% | Upper 95% | pvalue |
|---|---|---|---|---|
| Having an unresolvable user issue: | ||||
| Age | 1.025∗ | 0.990 | 1.064 | 0.159 |
| Female gender | 0.239 | 0.086 | 0.597 | 0.002 |
| Nonbinary/other gender | 0.403 | 0.003 | 4.894 | 0.528 |
| Cognitive diagnosis | 2.634 | 0.856 | 8.146 | 0.091 |
| Preferred language is not English | 9.059 | 3.397 | 27.027 | <0.001 |
| Inpatient setting | 0.844 | 0.298 | 2.304 | 0.743 |
| Having a personal connection that“felt right”: | ||||
| Age | 0.979† | 0.945 | 1.012 | 0.211 |
| Female gender | 1.036 | 0.448 | 2.434 | 0.934 |
| Nonbinary/other gender | 0.460 | 0.031 | 68.307 | 0.660 |
| Cognitive diagnosis | 0.392 | 0.115 | 1.315 | 0.128 |
| Preferred language is not English | 0.189 | 0.060 | 0.528 | 0.001 |
Reference levels are gender = male, diagnosis = noncognitive, language = English, setting/location = outpatient, and attending tech history is internet = none and cell = none.
∗
For each year increase of age, the OR increases by 2.6%.
†
For each year increase of age, the OR decreases by 2.1%.