Speaking the Language of Inclusion: Examining English Languages Requirements in Cardiovascular Digital Health Trials

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Eltahir , Ashish Sarraju , View ORCID Profile Daniel Seung Kim , View ORCID Profile Fatima Rodriguez doi: https://doi.org/10.1101/2025.06.10.25329222 Narayan Schütz 1 Division of Cardiovascular Medicine, Department of Medicine, Stanford University , Stanford, CA, USA 2 Department of Psychiatry and Behavioral Sciences, Stanford University , Stanford, CA, USA 3 Clinical Excellence Research Center, Stanford University , Stanford, CA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ritu Doijad 1 Division of Cardiovascular Medicine, Department of Medicine, Stanford University , Stanford, CA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ahmed A. Eltahir 1 Division of Cardiovascular Medicine, Department of Medicine, Stanford University , Stanford, CA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ashish Sarraju 4 Department of Cardiovascular Medicine, Cleveland Clinic Cleveland , OH, USA 5 Cleveland Clinic Coordinating Center for Clinical Research , Cleveland, OH, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Daniel Seung Kim 1 Division of Cardiovascular Medicine, Department of Medicine, Stanford University , Stanford, CA, USA 6 Center for Digital Health, Stanford University , Stanford, CA, USA 7 Wu Tsai Human Performance Alliance, Stanford University , Stanford, CA, USA 8 Cardiovascular Institute, Stanford University , Stanford, CA, USA 9 Division of Cardiology, Department of Medicine, University of Washington , Seattle, WA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Daniel Seung Kim For correspondence: kimds{at}stanford.edu frodrigu{at}stanford.edu Fatima Rodriguez 1 Division of Cardiovascular Medicine, Department of Medicine, Stanford University , Stanford, CA, USA 6 Center for Digital Health, Stanford University , Stanford, CA, USA 7 Wu Tsai Human Performance Alliance, Stanford University , Stanford, CA, USA 8 Cardiovascular Institute, Stanford University , Stanford, CA, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Fatima Rodriguez For correspondence: kimds{at}stanford.edu frodrigu{at}stanford.edu Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF ABSTRACT Background Cardiovascular medicine is rapidly evolving, as it integrates digital technologies intended to decentralize care from the clinic and/or hospital setting into patient’s homes and communities. However, clinical trials of digital technologies are frequently written and communicated solely in English, potentially exacerbating existing racial and ethnic differences in cardiovascular-related health outcomes. In this work, we evaluated the language-related inclusion and exclusion criteria of digital health trials related to cardiovascular medicine registered on ClinicalTrials.gov . Methods Planned, ongoing, and completed digital health trials were identified using the ClinicalTrials.gov website interface using terms related to digital health (see https://cardio-lang-inclusion.streamlit.app/ for detailed methods and data visualization). Only digital trials testing an intervention, conducted within the United States, and studying adults were included in analyses. The identified digital health trials were further subset to select for those related to cardiovascular medicine (i.e., prevention, weight loss and cardiometabolic disease, coronary disease, vascular disease, and arrhythmias). Natural language processing was leveraged to process the 1192 digital health trials’ inclusion and exclusion criteria. Results There were a total of 1192 digital health trials related to cardiovascular medicine were identified. Over a third (470 (39.4%)) listed English language fluency as an inclusion criteria, while 196 (16.4%) excluded non-English language fluent participants. In total, 611 (51.3%) of the analyzed digital trials in cardiovascular medicine excluded participation of non-English language fluent patients (see Figure 1 ). Manual chart review of 50 random digital health trials in cardiovascular medicine demonstrated that 23 (46%) required English language fluency as an inclusion criteria and 2 (4%) excluded non-English language fluent patients from participation. These findings align with the broader automated natural language processing analysis. Conclusions We found that there was frequent exclusion of non-English language fluent patients from digital health trials in cardiovascular medicine. This may limit the generalizability of digital health trials, which is critical as we transition to decentralized clinical practice using computers and smartphones and require an accompanying rigorous evidence base. What is the clinical question being addressed? Trials in digital health use text curated by investigators. However, with the large numbers of non-English-fluent individuals in the US, these trials may exclude minority populations. Hence, we sought to investigate whether digital health trials required English fluency for participation. What is the main finding? 611/1192 (51.3%) digital health trials required English language fluency for participation. This limits the generalizability of current digital health trials. As we move toward more decentralized care, we will need a broad evidence base that includes non-English-fluent individuals. Integration of digital technologies, intended to decentralize care from the clinic and/or hospital setting into patient’s homes and communities, has the potential to revolutionize clinical practice of cardiovascular medicine 1 . However, clinical trials of digital technologies are frequently written and communicated solely in English 2 , in a time when >67 million residents of the United States (US) speak a language other than English at home 3 . This is particularly deleterious for Hispanic/Latinx individuals, among whom >15.9 million indicated limited ability to understand spoken or written English 3 . Combined with the higher rates of cardiovascular risk factors in the Hispanic/Latinx population, potential exclusion of non-English language fluent participants can potentially exacerbate existing differences in cardiovascular-related health outcomes 4 . This work was reviewed by the Stanford Institutional Review Board and deemed exempt due to retrospective analysis of public data. Here, we evaluated the inclusion and exclusion criteria of digital health trials related to cardiovascular medicine registered on ClinicalTrials.gov , to extrapolate participation of non-English language proficient individuals. Planned, ongoing, and completed digital health trials were identified using the ClinicalTrials.gov website interface using terms related to digital health, including “digital therapy”, “smartphone”, and “mobile app” (see https://cardio-lang-inclusion.streamlit.app/ ) for detailed methods and data visualization). Only digital trials testing an intervention, conducted within the United States, and studying adults were included in analyses. The identified digital health trials were further subset using ClinicalTrials.gov to select for those related to cardiovascular medicine via use of terms such as, “metabolic syndrome”, “diabetes”, “hypertension”, “hyperlipidemia”, “heart disease”, “arrhythmias”, and “physical activity”. Based on the search criteria, 1192 digital health trials related to cardiovascular medicine were identified. Of these, 629 were were focused on cardiometabolic disease, diabetes, and/or weight-related disorders (52.8%), 354 focused on existing cardiovascular disease including coronary, peripheral, and cerebrovascular arterial diseases and/or arrhythmias (29.7%), and 209 were focused on lifestyle and/or behavioral factor interventions (e.g., physical activity, 17.5%). Natural language processing was leveraged to process the 1192 digital health trials’ inclusion and exclusion criteria. Over a third (470 (39.4%)) listed English language fluency as an inclusion criteria, while 196 (16.4%) excluded non-English language fluent participants. In total, 611 (51.3%) of the analyzed digital trials in cardiovascular medicine excluded participation of non-English language fluent patients (see Figure 1 ). These results did not significantly differ by disease category (e.g., cardiometabolic disease vs cardiovascular disease vs lifestyle/behavioral factors) nor by type of digital intervention (e.g., smartphone-based study vs. telemedicine vs. artificial intelligence based study). Manual chart review of 50 random digital health trials in cardiovascular medicine demonstrated that 23 (46%) required English language fluency as an inclusion criteria and 2 (4%) excluded non-English language fluent patients from participation. These findings align with the broader automated natural language processing analysis. Download figure Open in new tab Figure 1. Use of English language fluency as an inclusion or exclusion criteria in clinical trials of digital health interventions (N=1196). A total of 611 (51.3%) of digital health trials used English language fluency as either an inclusion or exclusion criteria (i.e., excluded non-English language fluent patients from participation). 196 (16.4%) excluded non-English language fluent patients. 470 (39.4%) required English language fluency as an inclusion criteria for participation. Created in BioRender. Kim, D. (2025) https://BioRender.com/o46f078 We performed a separate manual review of all digital health trials that had their study protocols uploaded to ClinicalTrials.gov , but did not mention English language fluency as an inclusion criteria or exclusion criteria (N=38). On review of the study protocols, 4 (10.5%) trials required English language fluency as an inclusion criteria and 2 (5.3%) excluded non-English language fluent patients. These findings suggest that some trials may have not accurately reported their language requirements on ClinicalTrials.gov , leading to a potential underestimation of language restrictions in the natural language processing analysis. While we note that 120 (10.0%, 120/1196) of digital trials offered translation services (with 95% of non-English support for digital trials being in Spanish), future trials of digital interventions should specifically focus on Spanish language support to increase generalizability of findings to the broader US population. This is of importance as digital interventions are increasingly adopted in the clinical realm, as a rigorous evidence base in a variety of diseases and conditions is currently needed. Moreover, continued exclusion of non-English language fluent patients from digital health trials may exacerbate existing differences in cardiovascular outcomes, particularly in the Hispanic/Latinx population that have greater existing prevalence of cardiovascular risk factors 4 . Our analysis has several limitations. First, our analyses were based on data provided by investigators on ClinicalTrials.gov , which may be incomplete. Moreover, our search may have missed relevant digital trials that did not have appropriate search terms inputted by investigators. Second, demographics (e.g., race/ethnicity, gender, level of education, etc.) of the study population for each digital health trial could not be extracted for the present analysis based on available data on ClinicalTrials.gov . Future analysis of such data would be valuable in providing further evidence on potential differences between studied populations and the broader United States population. In summary, we found frequent exclusion of non-English language fluent patients from digital health trials in cardiovascular medicine. This may limit the generalizability of digital health trials, which is critical as we transition to decentralized clinical practice using computers and smartphones and require an accompanying rigorous evidence base. However, with future investment in multi-lingual support, this represents a potentially solvable problem (particularly with recent advances in technology), and moreover, a solution that could potentially close the gap in health-related outcomes in cardiovascular medicine 5 . Data Availability All data and code are available at a third party website (see separately). https://cardio-lang-inclusion.streamlit.app/ DISCLOSURES D.S.K. reports grant support from Amgen and the Bristol Myers Squibb Foundation (via the Robert A. Winn Excellence in Clinical Trials Career Development Award) and consulting fees from Alphabet, outside the submitted work. F.R. reports equity from Carta Healthcare and HealthPals, and consulting fees from HealthPals, Novartis, Novo Nordisk, Esperion Therapeutics, Movano Health, Kento Health, Inclusive Health, Edwards, Arrowhead Pharmaceuticals, HeartFlow, and iRhythm, outside the submitted work. FUNDING The funders had no role in the interpretation of data or publication. N.S. is supported by the Swiss National Science Foundation under the Postdoc.Mobility Fellowship 210803 and the Wu Tsai Human Performance Alliance Postdoctoral Fellowship. D.S.K. is supported by the Wu-Tsai Human Performance Alliance as a Clinician-Scientist Fellow, the Stanford Center for Digital Health as a Digital Health Scholar, the Pilot Grant from the Stanford Center for Digital Health, NIH 1L30HL170306, the Robert A. Winn Excellence in Clinical Trials Career Development Award, the American Heart Association (AHA) Career Development Award (AHA 25CDA1436622), and the American Diabetes Association (ADA) Pathway to Stop Diabetes Initiator Award (7-25-INI-11). F.R. is supported by grants from the NIH National Heart, Lung, and Blood Institute (R01HL168188; R01HL167974, R01HL169345), the American Heart Association/Harold Amos Medical Faculty Development Program, and the Doris Duke Foundation (Grant #2022051). Works Cited 1. ↵ Kim DS , Eltahir AA , Ngo S , Rodriguez F. Bridging the Gap: How Accounting for Social Determinants of Health Can Improve Digital Health Equity in Cardiovascular Medicine . Curr Atheroscler Rep . 2024 ; 27 : 9 . OpenUrl PubMed 2. ↵ Miao BY , Sushil M , Xu A , et al. Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing . Lancet Digit Heal . 2024 ; 6 : e222 – e229 . OpenUrl 3. ↵ Anon. Census Bureau Releases 2020 Demographic Analysis Estimates Accessed June 8, 2025 . https://www.census.gov/newsroom/press-releases/2020/2020-demographic-analysis-estimates.html . 4. ↵ Gomez S , Blumer V , Rodriguez F. Unique Cardiovascular Disease Risk Factors in Hispanic Individuals . Curr Cardiovasc Risk Rep . 2022 ; 16 : 53 – 61 . OpenUrl CrossRef PubMed 5. ↵ Blood AJ , Cannon CP , Gordon WJ , et al. Results of a Remotely Delivered Hypertension and Lipid Program in More Than 10□000 Patients Across a Diverse Health Care Network . JAMA Cardiol . 2023 ; 8 : 12 – 21 . OpenUrl PubMed View the discussion thread. Back to top Previous Next Posted June 11, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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