What can you learn from a person by the way they say “hello”? A lot, apparently, and in a manner that can diminish their access to a variety of resources and necessities.
First coined by Dr. John Baugh during a 1999 study, the term “linguistic profiling” describes the discrimination that a person may face based solely upon their linguistic characteristics. After presenting a number of different groups with dialect stimuli, the researchers concluded that speaking accented English can decrease the honesty of landlords and that many native English listeners in the United States are able to infer the "race" of a speaker after hearing a single word—“hello”.
In comparison to discrimination triggered by visual cues such as skin colour, little attention has been paid to auditory cues that cause similar effect. However, given the pandemic and the rise of telemedicine, it is important now, more than ever, to consider the ramifications of linguistic profiling on access to healthcare.
Dialects and Discrimination
Drawing on linguistic anthropological thought, it is perhaps prudent to first consider the markers of a “dialect”, how they differ from standard “languages”, and their purported connection to ethnicity. In comparison to English, African-American and Chicano dialects are characterised by the presence of different variables such as unique phonetic features (e.g. replacement of final /th/ with /f/ in words). Prevalent linguistic ideologies such as the Monoglot “Standard” then use these differences to arbitrarily assert the existence of some intrinsic hierarchy, manifesting as different pronunciations, between ethnic and socioeconomic groups. When combined with other discriminatory beliefs, this may result in differential treatment.
Race in Healthcare
Previous studies have already shown that racial prejudice can manifest in face-to-face interactions with healthcare professionals in the form of denial of treatment and false beliefs. Though practitioners may claim to be unbiased, these discriminatory behaviours arise from unconscious biases that nonetheless affect their treatment of patients (Sabin and Greenwald, 2012). For example, the 2012 experiment conducted by Dr. Janice A. Sabin and Dr. Anthony G. Greenwald found that as implicit pro-White bias increased, prescribing narcotic (pain relief) medication decreased for African-American patients (Sabin and Greenwald, 2012). No effects in the reverse direction were found (Sabin and Greenwald, 2012). Similarly, Dr. Kelly M. Hoffman found widespread false beliefs among medical students about biological differences between ethnic groups, leading to diminished accuracy in treatment recommendations (Hoffman et al. 2016).
“Are you taking patients?”
In a 2019 pilot study, Dr. Tamara G.J. Leech examined how cues in the form of racialized names (e.g. “Keisha Jackson”) or racialized accents can individually affect access to pediatric healthcare services over the telephone. Though further studies have not been conducted, initial results have found that the children of “Black” callers were, overall, less likely to be accepted as patients. In these instances, office staff either outright rejected the caller or engaged in passive rejection by refusing to answer the question. This reaction to “Blackness” over the phone mirrors the one found by Purnell et al. in their study on landlords and undergraduate students.
In the same paper that they present their findings about medical students, Hoffman et al. (2016) identify two potential ways that discrimination may arise in healthcare:
The physician recognizes their patients’ pain, but does not provide treatment due to racially-motivated reasons;
The physician does not recognize their patients’ pain due to racially-motivated reasons, and thus cannot provide treatment.
Following this framework, advances in telehealth will need to remain wary in countering both kinds of discrimination, possibly by modifying or introducing new training programs to medical practitioners. Moreover, in Black or Latinx associated accents, it will be important to investigate how other linguistically-transmittable variables such as gender, language ability, and/or other accents may affect access to healthcare.
This article is written in collaboration with the Health and Human Rights (HHR) subcommittee of the University of Toronto International Health Program. If you found its contents interesting, please consider attending the 2021 HHR Conference and/or submitting an abstract to the 2021 HHR Research Poster Fair.
More information on seminars, speakers, and scheduling can be found on our Facebook page: https://bit.ly/2VHNt7I
Event: UTIHP HHR Research Poster Fair 2021
Time: March 9th, 2021 - March, 12th 2021
Topic: The Future of Healthcare Accessibility Through Telehealth
Presentation format: Online poster fair
Abstract submission: http://ow.ly/323T50Cy9t0
Hill, Jane H. “Language in white racism: an overview,” In The Everyday Language Of White Racism, (Malden, MA: Wiley-Blackwell, 2008), pp. 31-48.
Leech, Tamara G.J., Irby-Shasanmi, Amy, Mitchell, Anne L. 2019. “‘Are you accepting new patients?’ A pilot field experiment on telephone-based gatekeeping and Black patients’ access to pediatric care.” Health Services Research Suppl 1 (February): 234-242. https://doi.org/10.1111/1475-6773.13089.
Purnell, Thomas, Idsardi, William, Baugh, John. 1999. “Perceptual and Phonetic Experiments on American English Dialect Identification.” Journal of Language and Social Psychology 18, no. 1 (March): 10-30. https://doi.org/10.1177/0261927X99018001002.
Sabin, Janice A., Greenwald, Anthony G. The Influence of Implicit Bias on Treatment Recommendations for 4 Common Pediatric Conditions: Pain, Urinary Tract Infection, Attention Deficit Hyperactivity Disorder, and Asthma.” American Journal of Public Health 102, no. 5 (May): 988-995. https://doi.org/10.2105/AJPH.2011.300621.
Hoffman, Kelly M., Trawalter, Sophie, Axt, Jordan R., Oliver, M. Norman. 2016. Racial Bias In Pain Assessment And Treatment Recommendations, And False Beliefs About Biological Differences Between Blacks And Whites.” Proceedings of the National Academy of Sciences 113, no. 16 (April): 4296-4301. https://doi.org/10.1073/pnas.1516047113.