Table 3.

Summary of Hierarchical Regression Analyses Predicting Client Service Experience

Outcome Variable	White				Ethnic minority
	B (SE)	β	R2	ΔR2	B (SE)	β	R2	ΔR2
Access
Model 1			.09	.09			.05	.05
Age	.03 (.02)	.39			.01 (.01)	.19
Gender	−.52(.30)	−.24			−.17 (30)	−.09
Participant type	−.78 (.44)	−.40			.09 (.37)	.04
Model 2			.11	.02			.28	.23
Age	.03 (.02)	.41			.01 (.01)	.17
Gender	−.46 (.31)	−.21			−.08 (.27)	−.04
Participant type	−.74 (.45)	−.38			.50 (.36)	.24
Ethnic match	.09 (.12)	.11			.31 (.14)	.37*
Discriminations	.08 (.11)	.10			.14 (.10)	.22
Quality of Care
Model 1			.06	.06			.03	.03
Age	.02 (.02)	.31			−.99 (.01)	−.04
Gender	−.23 (.29)	−.11			−.27 (.27)	−.16
Participant type	−.27 (.43)	−.15			.05 (.34)	.03
Model 2			.10	.04			.34	.31
Age	.02 (.02)	.33			−.00 (.01)	−.06
Gender	−.17 (.30)	−.08			−.19 (.23)	−.11
Participant type	−.23 (.44)	−.12			.47 (.31)	.24
Ethnic match	.11 (.12)	.13			.29 (.13)	.38*
Discriminations	.12 (.11)	.16			.17 (.09)	.31*
Satisfaction
Model 1			.14	.14			.11	.11
Age	.02 (.02)	.25			.02 (.01)	.27
Gender	−.28 (.32)	−.12			.22 (.33)	.10
Participant type	.22 (.48)	.10			.12 (.42)	.05
Model 2			.15	.01			.26	.15
Age	.02 (.02)	.25			.02 (.01)	.26
Gender	−.28 (.32)	−.12			.30 (.31)	.14
Participant type	.19 (.49)	.25			.51 (.42)	.21
Ethnic match	−.03 (.13)	−.03			.29 (.17)	.31
Discriminations	.08 (.12)	.09			.12 (.11)	.17
Outcomes
Model 1			.07	.07			.00	.00
Age	.02 (.02)	.34			.00 (.01)	.02
Gender	.24 (.27)	.12			−.06 (.36)	−.03
Participant type	−.29 (.40)	−.17			.01 (.45)	.00
Model 2			.16	.09			.20	.20
Age	.02 (.01)	.37			.00 (.01)	−.01
Gender	.30 (.27)	.16			−.02 (.33)	−.01
Participant type	−.25 (.39)	−.15			.28 (.45)	.11
Ethnic match	.11 (.10)	.15			.08 (.18)	.08
Discriminations	.20 (.09)	.27*			.30 (.12)	.41*

Note. SE is the standard error of B.

^*p < .05.