Unveiling Patient Trust in Physicians Across China: Insights from a Nationwide Cross-Sectional Study

Figures & data

Table 1 Sample Characteristics of 28,760 Participants Included in Our Study

Extent of TIP Characteristics	Strongly disagree	Disagree	Moderate	Agree	Strongly agree	Overall
Hospital type
General hospital	15 (22.4%)	80 (39.0%)	925 (42.8%)	4509 (42.0%)	6668 (42.7%)	12,197 (42.4%)
TCM hospital	12 (17.9%)	51 (24.9%)	499 (23.1%)	2526 (23.5%)	3428 (22.0%)	6516 (22.7%)
MC hospital	22 (32.8%)	56 (27.3%)	531 (24.5%)	2539 (23.7%)	3106 (19.9%)	6254 (21.7%)
Other specialty hospital	18 (26.9%)	18 (8.8%)	208 (9.6%)	1153 (10.7%)	2396 (15.4%)	3793 (13.2%)
Hospital region
Eastern	35 (52.2%)	81 (39.5%)	825 (38.1%)	4208 (39.2%)	7086 (45.4%)	12,235 (42.5%)
Central	5 (7.5%)	43 (21.0%)	521 (24.1%)	2512 (23.4%)	4177 (26.8%)	7258 (25.2%)
Western	27 (40.3%)	81 (39.5%)	817 (37.8%)	4007 (37.4%)	4335 (27.8%)	9267 (32.2%)
Convenient payment
No	34 (50.7%)	76 (37.1%)	738 (34.1%)	2220 (20.7%)	1966 (12.6%)	5034 (17.5%)
Yes	33 (49.3%)	129 (62.9%)	1425 (65.9%)	8507 (79.3%)	13,632 (87.4%)	23,726 (82.5%)
Volunteer guidance
No	43 (64.2%)	117 (57.1%)	1126 (52.1%)	1725 (16.1%)	827 (5.3%)	3838 (13.3%)
Yes	24 (35.8%)	88 (42.9%)	1037 (47.9%)	9002 (83.9%)	14,771 (94.7%)	24,922 (86.7%)
Enough seats available
No	47 (70.1%)	125 (61.0%)	1227 (56.7%)	3021 (28.2%)	2067 (13.3%)	6487 (22.6%)
Yes	20 (29.9%)	80 (39.0%)	936 (43.3%)	7706 (71.8%)	13,531 (86.7%)	22,273 (77.4%)
Title of physician
Without a senior title	22 (32.8%)	56 (27.3%)	611 (28.2%)	2775 (25.9%)	3879 (24.9%)	7343 (25.5%)
With a senior title	45 (67.2%)	149 (72.7%)	1552 (71.8%)	7951 (74.1%)	11,719 (75.1%)	21,416 (74.5%)
Missing	0 (0%)	0 (0%)	0 (0%)	1 (0.0%)	0 (0%)	1 (0.0%)
Physicians’s patience
No	50 (74.6%)	138 (67.3%)	1109 (51.3%)	1329 (12.4%)	489 (3.1%)	3115 (10.8%)
Yes	17 (25.4%)	67 (32.7%)	1054 (48.7%)	9398 (87.6%)	15,109 (96.9%)	25,645 (89.2%)
Privacy protection
No	34 (50.7%)	92 (44.9%)	847 (39.2%)	979 (9.1%)	402 (2.6%)	2354 (8.2%)
Yes	33 (49.3%)	113 (55.1%)	1316 (60.8%)	9748 (90.9%)	15,196 (97.4%)	26,406 (91.8%)
Age
<=17	1 (1.5%)	1 (0.5%)	23 (1.1%)	108 (1.0%)	165 (1.1%)	298 (1.0%)
[18,35]	35 (52.2%)	115 (56.1%)	1171 (54.1%)	5563 (51.9%)	7747 (49.7%)	14,631 (50.9%)
[36,59]	19 (28.4%)	59 (28.8%)	744 (34.4%)	3876 (36.1%)	5585 (35.8%)	10,283 (35.8%)
≥60	12 (17.9%)	30 (14.6%)	225 (10.4%)	1180 (11.0%)	2101 (13.5%)	3548 (12.3%)
Sex
Female	42 (62.7%)	138 (67.3%)	1432 (66.2%)	6703 (62.5%)	10,256 (65.8%)	18,571 (64.6%)
Male	25 (37.3%)	67 (32.7%)	731 (33.8%)	4024 (37.5%)	5342 (34.2%)	10,189 (35.4%)
Better educated
No	11 (16.4%)	31 (15.1%)	301 (13.9%)	1717 (16.0%)	2357 (15.1%)	4417 (15.4%)
Yes	56 (83.6%)	174 (84.9%)	1862 (86.1%)	9009 (84.0%)	13,241 (84.9%)	24,342 (84.6%)
Missing	0 (0%)	0 (0%)	0 (0%)	1 (0.0%)	0 (0%)	1 (0.0%)
Occupation
Unemployed/retired	20 (29.9%)	56 (27.3%)	471 (21.8%)	2295 (21.4%)	3589 (23.0%)	6431 (22.4%)
Public sector	10 (14.9%)	53 (25.9%)	568 (26.3%)	2834 (26.4%)	4724 (30.3%)	8189 (28.5%)
Non-public sector	37 (55.2%)	96 (46.8%)	1122 (51.9%)	5580 (52.0%)	7258 (46.5%)	14,093 (49.0%)
Missing	0 (0%)	0 (0%)	2 (0.1%)	18 (0.2%)	27 (0.2%)	47 (0.2%)
Total cost
<=150	13 (19.4%)	51 (24.9%)	535 (24.7%)	2797 (26.1%)	4469 (28.7%)	7865 (27.3%)
(150,400]	19 (28.4%)	66 (32.2%)	750 (34.7%)	3937 (36.7%)	5463 (35.0%)	10,235 (35.6%)
>400	35 (52.2%)	88 (42.9%)	878 (40.6%)	3992 (37.2%)	5665 (36.3%)	10,658 (37.1%)
Missing	0 (0%)	0 (0%)	0 (0%)	1 (0.0%)	1 (0.0%)	2 (0.0%)
Annual household income
<=60,000	39 (58.2%)	114 (55.6%)	1168 (54.0%)	6078 (56.7%)	8287 (53.1%)	15,686 (54.5%)
(60,000,120,000)	15 (22.4%)	42 (20.5%)	482 (22.3%)	2498 (23.3%)	3917 (25.1%)	6954 (24.2%)
≥120,000	13 (19.4%)	49 (23.9%)	513 (23.7%)	2151 (20.1%)	3394 (21.8%)	6120 (21.3%)
Insurance
Uninsured	7 (10.4%)	30 (14.6%)	227 (10.5%)	1009 (9.4%)	1441 (9.2%)	2714 (9.4%)
Government Insurance Scheme (GIS)	13 (19.4%)	26 (12.7%)	248 (11.5%)	1117 (10.4%)	2204 (14.1%)	3608 (12.5%)
Urban Employees Basic Medical Insurance (UEBMI)	18 (26.9%)	58 (28.3%)	645 (29.8%)	3343 (31.2%)	4942 (31.7%)	9006 (31.3%)
Urban and Rural Residents Basic Medical Insurance (RBMI)	19 (28.4%)	50 (24.4%)	690 (31.9%)	3424 (31.9%)	4632 (29.7%)	8815 (30.7%)
New Rural Cooperative Medical Insurance (NRCMI)	9 (13.4%)	25 (12.2%)	269 (12.4%)	1554 (14.5%)	1917 (12.3%)	3774 (13.1%)
Commercial insurance	1 (1.5%)	12 (5.9%)	53 (2.5%)	183 (1.7%)	289 (1.9%)	538 (1.9%)
Medical aid	0 (0%)	3 (1.5%)	10 (0.5%)	26 (0.2%)	38 (0.2%)	77 (0.3%)
Missing	0 (0%)	1 (0.5%)	21 (1.0%)	71 (0.7%)	135 (0.9%)	228 (0.8%)
Household registration
Rural	23 (34.3%)	71 (34.6%)	660 (30.5%)	3161 (29.5%)	4013 (25.7%)	7928 (27.6%)
Urban	44 (65.7%)	134 (65.4%)	1503 (69.5%)	7566 (70.5%)	11,585 (74.3%)	20,832 (72.4%)

Table 2 Distribution of Responses and Percentages for TIP Outcome

Extent of TIP	Number of participants	Percentage
Strongly disagree	67	0.23%
Disagree	205	0.71%
Moderate	2163	7.52%
Agree	10,727	37.30%
Strongly agree	15,598	54.24%

Table 3 The Results of the Univariate Analysis

Characteristics	P-value
Hospital type	<0.001
General hospital
TCM hospital
MC hospital
Other specialty hospital
Hospital region	<0.001
Eastern
Central
Western
Convenient payment	<0.001
No
Yes
Volunteer guidance	<0.001
No
Yes
Enough seats available	<0.001
No
Yes
Title of physician	<0.05
Without a senior title
With a senior title
Missing
Physicians’s patience	<0.001
No
Yes
Privacy protection	<0.001
No
Yes
Age	<0.001
<=17
[18,35]
[36,59]
≥60
Sex	<0.001
Female
Male
Better educated	<0.05
No
Yes
Missing
Occupation	<0.001
Unemployed/retired
Public sector
Non-public sector
Missing
Total cost	<0.001
<=150
(150,400]
>400
Missing
Annual household income	<0.001
<=60,000
(60,000,120,000)
≥120,000
Insurance	<0.001
Uninsured
Government Insurance Scheme (GIS)
Urban Employees Basic Medical Insurance (UEBMI)
Urban and Rural Residents Basic Medical Insurance (RBMI)
New Rural Cooperative Medical Insurance (NRCMI)
Commercial insurance
Medical aid
Missing
Household registration	<0.001
Rural
Urban

Table 4 Multilevel Regression Analysis About the Association Between TIP and Different Covariates

Characteristic	OR^a	95% CI^a	p-value
Hospital type
General hospital	—	—
TCM hospital	0.90	0.76, 1.08	0.3
MC hospital	1.00	0.84, 1.21	>0.9
Other specialty hospital	1.37	1.08, 1.73	0.010
Hospital region
Eastern	—	—
Central	0.93	0.77, 1.12	0.4
Western	0.94	0.80, 1.11	0.5
Convenient payment
No	—	—
Yes	1.40	1.25, 1.58	<0.001
Volunteer guidance
No	—	—
Yes	3.20	2.86, 3.59	<0.001
Enough seats available
No	—	—
Yes	2.83	2.55, 3.15	<0.001
Title of physician
Without a senior title	—	—
With a senior title	1.16	1.03, 1.31	0.012
Physicians’s patience
No	—	—
Yes	5.71	5.10, 6.38	<0.001
Privacy protection
No	—	—
Yes	3.03	2.67, 3.43	<0.001
Age
<=17	—	—
[18,35]	1.16	0.69, 1.93	0.6
[36,59]	1.22	0.73, 2.03	0.5
≥60	1.18	0.70, 1.98	0.5
Sex
Female	—	—
Male	1.16	1.03, 1.29	0.010
Better educated
No	—	—
Yes	0.97	0.85, 1.11	0.6
Occupation
Unemployed/retired	—	—
Public sector	1.07	0.90, 1.28	0.4
Non-public sector	1.00	0.86, 1.15	>0.9
Total cost
<=150	—	—
(150,400]	0.90	0.79, 1.02	0.11
>400	0.91	0.79, 1.03	0.14
Annual household income
<=60,000	—	—
(60,000,120,000)	1.05	0.92, 1.19	0.5
≥120,000	0.86	0.75, 0.98	0.025
Insurance
Uninsured	—	—
Government Insurance Scheme (GIS)	0.93	0.73, 1.19	0.6
Urban Employees Basic Medical Insurance (UEBMI)	1.08	0.88, 1.32	0.4
Urban and Rural Residents Basic Medical Insurance (RBMI)	1.04	0.86, 1.25	0.7
New Rural Cooperative Medical Insurance (NRCMI)	1.25	1.01, 1.56	0.043
Commercial insurance	0.80	0.56, 1.16	0.2
Medical aid	0.66	0.31, 1.37	0.3
Household registration
Rural	—	—
Urban	1.16	1.01, 1.33	0.038

Abbreviations: ^aOR, Odds Ratio; CI, Confidence Interval.

Figure 1 Sensitive analysis using multilevel regression model by removing participants answering with “moderate”.

Figure 2 The results of the association between TIP and covariates based on ordinary logistic regression model without including multiple levels.