Table 3 Hierarchical multiple linear regression predicting the willingness of healthcare professionals to continue participating in telemedicine (n = 560) ^a.

Variables	Model 1			Model 2			Model 3			Model 4			Model 5 ^b
Variables	β	95%CI	P	β	95%CI	P	β	95%CI	P	β	95%CI	P	β	95%CI	P
1. Socio-demographics
Professional title
Junior (Ref.)
Intermediate	− 0.10	− 0.27, − 0.01	0.040	− 0.01	− 0.09, 0.06	0.700	0.02	− 0.03, 0.08	0.418	0.02	− 0.03, 0.08	0.395	0.02	− 0.02, 0.09	0.234
Senior	− 0.15	− 0.37, − 0.09	0.001	− 0.03	− 0.13, 0.03	0.198	0.02	− 0.03, 0.09	0.268	0.02	− 0.03, 0.09	0.338	0.04	− 0.01, 0.11	0.071
Years of telemedicine experience	0.09	0.01, 0.03	0.030	0.05	0.01, 0.02	0.027	0.03	− 0.01, 0.01	0.119	0.03	− 0.01, 0.01	0.130	0.02	− 0.01, 0.01	0.171
	Adj R ²= 0.018, ΔR² = 0.007*
2. TAM constructs
Usefulness				0.82	0.77, 0.86	< 0.001	0.30	0.24, 0.36	< 0.001	0.25	0.18, 0.32	< 0.001	0.18	0.01, 0.25	< 0.001
				Adj R² = 0.689, ΔR² = 0.667***
3. TPB constructs
Subjective norms							0.64	0.55, 0.67	< 0.001	0.61	0.51, 0.64	< 0.001	0.48	0.39, 0.53	< 0.001
							Adj R² = 0.821, ΔR² = 0.131***
4. Patient accessibility
Patient coverage										0.10	0.03, 0.15	0.004	0.07	0.01, 0.13	0.031
										Adj R² = 0.823, ΔR² = 0.003**
5. Satisfaction													0.24	0.16, 0.30	< 0.001
													Adj R² = 0.835, ΔR² = 0.012***

^aOnly variables retained in the final multivariable model after stepwise selection are shown in the table. All assumptions for linear regression models were examined (linearity, normality, independence, and homoscedasticity) and were fulfilled.
^bDurbin-Watson = 1.941, F = 405.12, P < 0.001; All VIF values were < 5 and Tolerance values were > 0.2.
*P < 0.05, **P < 0.01, ***P < 0.001.

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