Table 2.

Multivariate analysis for professional acceptance of artificial intelligence (AI) applications in Ophthalmology.

		Assistive tool for PECPs				CDS tool for PECPs				Diagnostic tool for PECPs				Assertive tool for ophthalmologists				CDS tool for ophthalmologists				Diagnostic tool for ophthalmologists
		OR	95% CI		p -value	OR	95% CI		p -value	OR	95% CI		p -value	OR	95% CI		p -value	OR	95% CI		p -value	OR	95% CI		p -value
Age		0.982	0.953	1.012	0.236	1.002	0.977	1.027	0.884	1.020	0.999	1.042	0.065	1.002	0.971	1.035	0.892	1.017	0.992	1.044	0.188	1.026	1.004	1.049	0.019
Gender	Female	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
	Male	1.253	0.794	1.976	0.332	1.191	0.830	1.711	0.343	1.089	0.798	1.486	0.590	1.316	0.817	2.121	0.259	1.434	0.991	2.076	0.056	1.398	1.020	1.914	0.037
Clinical experience	Currently in training	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
	<20 years	2.158	0.674	6.910	0.195	0.806	0.287	2.263	0.683	1.018	0.446	2.323	0.966	2.450	0.956	6.280	0.062	0.951	0.389	2.325	0.912	0.747	0.328	1.700	0.487
	>20 years	1.676	0.437	6.423	0.451	0.700	0.214	2.291	0.556	1.007	0.382	2.654	0.988	3.702	1.096	12.510	0.035	1.165	0.395	3.436	0.782	1.037	0.394	2.727	0.941
Geographical region	East Asia and Pacific	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
	Europe and Central Asia	1.200	0.450	3.204	0.716	1.000	0.475	2.103	0.999	1.334	0.700	2.543	0.380	0.638	0.274	1.486	0.298	1.292	0.574	2.908	0.536	1.068	0.565	2.018	0.840
	Latin America & the Caribbean	0.415	0.192	0.898	0.025	0.722	0.381	1.369	0.318	1.010	0.568	1.797	0.973	3.595	0.809	15.987	0.093	1.297	0.599	2.809	0.509	2.195	1.137	4.236	0.019
	Middle east and North Africa	0.578	0.153	2.187	0.419	0.832	0.254	2.721	0.761	0.833	0.290	2.393	0.735	1.793	0.224	14.323	0.582	0.996	0.266	3.728	0.995	0.740	0.250	2.188	0.586
	North America	1.000				2.965	0.372	23.658	0.305	1.869	0.488	7.160	0.361	1.174	0.145	9.542	0.881	0.983	0.205	4.703	0.983	2.210	0.567	8.615	0.253
	South Asia	0.874	0.381	2.006	0.751	1.008	0.552	1.840	0.980	0.987	0.595	1.637	0.960	0.598	0.287	1.249	0.171	0.785	0.432	1.428	0.428	0.604	0.364	1.000	0.050
	Sub-Saharan Africa	0.455	0.049	4.244	0.490	0.480	0.083	2.777	0.413	0.661	0.107	4.090	0.656	1.000				0.554	0.095	3.245	0.513	2.061	0.222	19.089	0.524
Income level	Resource-constrained	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
	Resource-abundant	0.630	0.345	1.150	0.132	0.914	0.583	1.434	0.696	0.738	0.501	1.086	0.124	0.776	0.422	1.428	0.416	0.799	0.502	1.270	0.342	0.543	0.367	0.805	0.002
Self-rated understanding of AI	Very poor	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
	Below average	0.713	0.078	6.553	0.765	1.286	0.315	5.261	0.726	0.418	0.050	3.489	0.420	0.611	0.070	5.293	0.655	1.058	0.295	3.798	0.931	0.851	0.210	3.450	0.821
	Average	0.587	0.073	4.714	0.616	0.840	0.226	3.125	0.795	0.107	0.014	0.837	0.033	0.608	0.076	4.865	0.639	1.499	0.441	5.094	0.517	0.325	0.086	1.226	0.097
	Above average	0.575	0.071	4.632	0.603	1.061	0.284	3.968	0.930	0.121	0.016	0.949	0.044	0.670	0.083	5.379	0.706	1.712	0.502	5.842	0.391	0.324	0.086	1.223	0.096
	Excellent	0.620	0.069	5.557	0.669	1.196	0.284	5.030	0.807	0.137	0.017	1.124	0.064	0.643	0.072	5.766	0.693	1.525	0.400	5.814	0.537	0.418	0.102	1.709	0.225

^*Wherein “ref” denotes the reference category.

The color values are added to draw attention of readers to analyses for which p-value was < 0.05.