Table 7. Logistic regression analysis of factors influencing awareness, usage, and attitudes towards mHealth.
| Outcome | Factors† | OR | P value |
|---|---|---|---|
| mHealth awareness score ≥6 (out of 7) (n=36) | Age (years)‡ | 1.02 | 0.257 |
| Chinese ethnicity | 0.51 | 0.105 | |
| Married | 0.57 | 0.203 | |
| Smartphone use score‡ | 1.69 | <0.001 | |
| mHealth usage score ≥4 (out of 7) (n=11) | Age (years)‡ | 1.00 | 0.620 |
| Chinese ethnicity | 0.36 | 0.026 | |
| Employment | 3.71 | 0.022 | |
| Education (diploma/degree) | 0.88 | 0.765 | |
| Smartphone use score‡ | 1.77 | 0.004 | |
| Agree that mHealth has potential to improve health (n=99) | Housing (private) | 2.12 | 0.038 |
| Smartphone use score‡ | 1.10 | 0.329 | |
| Keen to learn about and try new mHealth solutions in future (n=128) | Chinese ethnicity | 0.36 | 0.252 |
| Mandarin language | 0.67 | 0.644 | |
| Housing (private) | 3.18 | 0.008 | |
| Smartphone use score‡ | 1.33 | 0.007 | |
| Willing to pay for mHealth (n=26) | Housing (private) | 3.36 | 0.006 |
†, only factors identified as statistically significant in univariate analysis were included in the multiple logistic regression models. Subsequently, P values <0.05 were considered statistically significant (factors in bold). Odds-ratio (OR) >1 implies a positive relationship with the outcome, OR <1 implies a negative relationship with the outcome. ‡, for age and smartphone use score, the ORs are in relation to a one unit increase in the factor (i.e., a 1-year increase in age, or a 1 unit increase in smartphone use score).