Do they speak like me? Exploring how perceptions of linguistic difference may influence patient perceptions of healthcare providers

Figures & data

Table 1. Sample characteristics, N = 282^a.

	N (%) or mean (SD)
Age (years)	36.4 (11.04)
Race
White	184 (65.2%)
Others^#	98 (34.8%)
Ethnicity
Hispanic or Latino	78 (27.7%)
Not Hispanic or Latino	204 (72.3%)
Education
Some college or below	64 (22.7%)
College graduates and above	218 (77.3%)
Gender
Male	198 (70.2%)
Female	84 (29.8%)

a Participants were recruited from the online crowdsourcing platform, MTurk.

# Others include Black or African American (n = 20; 7.1%), Asian (n = 56; 19.9%), American Indian, Alaska Native, Native Hawaiian, or other Pacific Islander (n = 12; n = 4.3%), Other (n = 1; 0.4%), or multiple races (n = 9; n = 3.2%).

Figure 1. Indirect pathway from speech styles to VC’s evaluation via perceived linguistic similarity (N = 282)^a.

**p < 0.01, ***p < 0.001, ns: not statistically significant. ^aN = 282 participants were randomized to view one of the two speech style conditions (Standard American English (SAE) and African American English (AAE)). Hayes PROCESS Macro was used to model the mediated association between speech type and outcome variables. The SAE condition was the reference group. AAE (vs. SAE) was associated with decreased perceived linguistic similarity. Decrease in perceived linguistic similarity was positively associated with decreased evaluation of Black VC. The unstandardized coefficient and the standard error denote each path. Covariates were excluded from the analysis because the study used random assignments.

Data Availability Statement

Data are available upon request.