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Racial and Ethnic Health Disparities"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Mental health workforce research treats South Asian Americans as a single group, yet they speak many mutually unintelligible languages, and language concordance shapes whether people with limited English proficiency (LEP) reach and stay in care. We measured the availability, geographic concentration, and affordability of psychotherapists listing eight South Asian languages. We analyzed 347,464 Psychology Today directory profiles (2025), identified providers listing Hindi, Urdu, Punjabi, Gujarati, Bengali, Tamil, Telugu, or Nepali, and linked counts to American Community Survey (2019\u20132023) speaker and LEP populations. We computed listed providers per 100,000 speakers and per 100,000 LEP speakers, supply-need alignment, geographic concentration, and payment acceptance and session price. Of all therapists, 2,310 (0.66%) listed a South Asian language; 59.4% of them listed two or more. Listed availability per 100,000 LEP speakers ranged from 1,160 for Hindi to 22.8 for Nepali, and per 100,000 speakers from 213.7 (Urdu) to 7.6 (Nepali); provider shares were unevenly aligned with LEP shares (index of dissimilarity, 0.41). Of Nepali LEP speakers, 43.0% lived in a state with no provider listing Nepali, against 0.9% for Hindi, and the languages with the fewest listed providers had the largest LEP shares and most recent arrivals. Providers listing a South Asian language were more often out-of-network (adjusted odds ratio, 1.58; 95% CI, 1.31\u20131.92) and charged $3.90 more per session (95% CI, 1.16\u20136.64). Language differences in listed provider availability within the South Asian population are large and invisible in aggregated data, pointing to the need for disaggregated data systems, language-specific workforce development, and affordability policy.<\/jats:p>","DOI":"10.1007\/s40615-026-03193-7","type":"journal-article","created":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T17:54:51Z","timestamp":1790445291000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Disaggregating the South Asian Category: Language-Concordant Psychotherapist Availability and Affordability in the United States"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8467-7048","authenticated-orcid":false,"given":"Nari","family":"Yoo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1913-1789","authenticated-orcid":false,"given":"Manvinder","family":"Gill","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,26]]},"reference":[{"key":"3193_CR1","doi-asserted-by":"publisher","unstructured":"Adia AC, Nazareno J, Operario D, Ponce NA. Health conditions, outcomes, and service access among Filipino, Vietnamese, Chinese, Japanese, and Korean adults in California, 2011\u20132017. Am J Public Health [Internet]. 2020;110:520\u20136. Available from: https:\/\/doi.org\/10.2105\/ajph.2019.305523","DOI":"10.2105\/ajph.2019.305523"},{"key":"3193_CR2","doi-asserted-by":"publisher","unstructured":"Holland AT, Palaniappan LP. Problems with the collection and interpretation of Asian-American health data: omission, aggregation, and extrapolation. Ann Epidemiol [Internet]. 2012;22:397\u2013405. Available from: https:\/\/doi.org\/10.1016\/j.annepidem.2012.04.001","DOI":"10.1016\/j.annepidem.2012.04.001"},{"key":"3193_CR3","doi-asserted-by":"publisher","unstructured":"Kauh TJ, Read JG, Scheitler AJ. The Critical Role of Racial\/Ethnic Data Disaggregation for Health Equity. Popul Res Policy Rev [Internet]. 2021;40:1\u20137. 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It analyzed de-identified data from the Psychology Today therapist directory and aggregate estimates from the American Community Survey and did not involve interaction with human participants. Consent to participate was not applicable because the study did not enroll individual participants; it used publicly observable directory data and aggregate census estimates.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}