Adapting a home telemonitoring intervention for underserved Hispanic/Latino patients with type 2 diabetes: an acceptability and feasibility study
Open accessAbstract
Background: Home telemonitoring is a promising approach to optimizing outcomes for patients with Type 2 Diabetes; however, this care strategy has not been adapted for use with understudied and underserved Hispanic/Latinos (H/L) patients with Type 2 Diabetes. Methods: A formative, Community-Based Participatory Research approach was used to adapt a home telemonitoring intervention to facilitate acceptability and feasibility for vulnerable H/L patients. Utilizing the ADAPT-ITT framework, key stakeholders were engaged over an 8-month iterative process using a combination of strategies, including focus groups and structured interviews. Nine Community Advisory Board, Patient Advisory, and Provider Panel Committee focus group discussions were conducted, in English and Spanish, to garner stakeholder input before intervention implementation. Focus groups and structured interviews were also conducted with 12 patients enrolled in a 1-month pilot study, to obtain feedback from patients in the home to further adapt the intervention. Focus groups and structured interviews were approximately 2 hours and 30 min, respectively. All focus groups and structured interviews were audio-recorded and professionally transcribed. Structural coding was used to mark responses to topical questions in the moderator and interview guides. Results: Two major themes emerged from qualitative analyses of Community Advisory Board/subcommittee focus group data. The first major theme involved intervention components to maximize acceptance/usability. Subthemes included tablet screens (e.g., privacy/identity concerns; enlarging font sizes; lighter tablet to facilitate portability); cultural incongruence (e.g., language translation/literacy, foods, actors “who look like me”); nursing staff (e.g., ensuring accessibility; appointment flexibility); and, educational videos (e.g., the importance of information repetition). A second major theme involved suggested changes to the randomized control trial study structure to maximize participation, including a major restructuring of the consenting process and changes designed to optimize recruitment strategies. Themes from pilot participant focus group/structured interviews were similar to those of the Community Advisory Board such as the need to address and simplify a burdensome consenting process, the importance of assuring privacy, and an accessible, culturally congruent nurse. Conclusions: These findings identify important adaptation recommendations from the stakeholder and potential user perspective that should be considered when implementing home telemonitoring for underserved patients with Type 2 Diabetes. Trial registration: NCT03960424; ClinicalTrials.gov (US National Institutes of Health). Registered 23 May 2019. Registered prior to data collection. https://www.clinicaltrials.gov/ct2/show/NCT03960424?term=NCT03960424&draw=2&rank=1
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The technology acceptability and feasibility theme arose in six studies and comprised three sub-themes: convenience and acceptability, technology feasibility, and barriers of rural areas.
“This theme arose in six studies [19, 22–25, 27] and comprise the following sub-themes: (1) Convenience & Acceptability; (2) Technology feasibility; and (3) Barriers of rural areas.”
From Use of telemonitoring in patient self-management of chronic disease: a qualitative meta-synthesis (2023) · cites this paper as [27]
In three studies, participants found devices difficult to use, accentuated by generational differences, with older participants generally less confident and less able to use them.
“In three studies, [19, 23, 27] participants found devices difficult to use, which was accentuated by generational differences, with older participants generally less confident and less able to use them.”
From Use of telemonitoring in patient self-management of chronic disease: a qualitative meta-synthesis (2023) · cites this paper as [27]
The importance of education regarding device usage was highlighted in three studies, though this is likely dependent on the specific devices used.
“Whilst this is likely to be dependent on specific devices used, the importance of education regarding device usage was highlighted in three studies. [24, 25, 27]”
From Use of telemonitoring in patient self-management of chronic disease: a qualitative meta-synthesis (2023) · cites this paper as [27]
Consideration of cultural differences was highlighted when creating educational videos, as many patients felt the content and/or technology were not culturally appropriate, particularly for the Hispanic and Latino population.
“Consideration of cultural differences was highlighted when creating educational videos to supplement the device/application, as many patients felt the content and/or technology were not “culturally appropriate”, particularly targeting the Hispanic and Latino population [27].”
From Use of telemonitoring in patient self-management of chronic disease: a qualitative meta-synthesis (2023) · cites this paper as [27]
Three studies suggested that the barrier of device difficulty could be better managed with improved education and support.
“Three studies [24, 25, 27] however, suggested this barrier could be better managed with improved education and support.”
From Use of telemonitoring in patient self-management of chronic disease: a qualitative meta-synthesis (2023) · cites this paper as [27]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
(1998) · Cited by 13,501 · see citing works
Unequal treatment: confronting racial and ethnic disparities in health care
(2003) · Choice Reviews Online · doi:10.5860/choice.40-5843 · Cited by 7,043 · see citing works
Inzucchi, S. E., Bergenstal, R. M., Buse, J. B., Diamant, M., Ferrannini, E., Nauck, M., Peters, A. L., Tsapas, A., Wender, R., & Matthews, D. R. (2012) · Diabetologia · doi:10.1007/s00125-012-2534-0 · Cited by 3,919 · see citing works
Using Community-Based Participatory Research to Address Health Disparities
Wallerstein, N. B., & Duran, B. (2006) · Health Promotion Practice · doi:10.1177/1524839906289376 · Cited by 2,243 · see citing works
Community-based participatory research for health : from process to outcomes
Minkler, M., & Wallerstein, N. B. (2008) · Cited by 2,089 · see citing works
Codebook Development for Team-Based Qualitative Analysis
MacQueen, K. M., McLellan, E., Kay, K., & Milstein, B. (1998) · CAM Journal · doi:10.1177/1525822x980100020301 · Cited by 1,675 · cited 1× · see citing works
“Structural coding was used to mark responses to topical questions in the interview guide [44].”
MethodIsrael, B. A., Schulz, A. J., Parker, E. A., & Becker, A. B. (2001) · Education for Health: Change in Learning & Practice · doi:10.1080/13576280110051055 · Cited by 936 · see citing works
Ethnic disparities in diabetic complications in an insured population
Karter, A. J. (2002) · JAMA · doi:10.1001/jama.287.19.2519 · Cited by 840 · see citing works
The ADAPT-ITT Model: A Novel Method of Adapting Evidence-Based HIV Interventions
Wingood, G. M., & DiClemente, R. J. (2008) · JAIDS Journal of Acquired Immune Deficiency Syndromes · doi:10.1097/qai.0b013e3181605df1 · Cited by 664 · see citing works
Self-citationIon Concentration Polarization by Bifurcated Current Path
Kim, J., Cho, I., Lee, H., & Kim, S. J. (2017) · Scientific Reports · doi:10.1038/s41598-017-04646-0 · Cited by 644 · see citing works
Disparities in Incidence of Diabetic End-Stage Renal Disease According to Race and Type of Diabetes
Cowie, C. C., Port, F. K., Wolfe, R. A., Savage, P. J., Moll, P. P., & Hawthorne, V. M. (1989) · New England Journal of Medicine · doi:10.1056/nejm198910193211603 · Cited by 507 · see citing works
Non-Insulin-Dependent Diabetes Mellitus in Minorities in the United States
Carter, J. S., Pugh, J., & Monterrosa, A. (1996) · Annals of Internal Medicine · doi:10.7326/0003-4819-125-3-199608010-00011 · Cited by 504 · see citing works
Holkup, P. A., Tripp-Reimer, T., Salois, E. M., & Weinert, C. (2004) · Advances in Nursing Science · doi:10.1097/00012272-200407000-00002 · Cited by 477 · see citing works
Harris, M. I., Klein, R., Cowie, C. C., Rowland, M., & Byrd-Holt, D. D. (1998) · Diabetes Care · doi:10.2337/diacare.21.8.1230 · Cited by 400 · see citing works
Effectiveness of mHealth interventions for patients with diabetes: An overview of systematic reviews
Kitsiou, S., Paré, G., Jaana, M., & Gerber, B. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0173160 · Cited by 390 · see citing works
Shea, S., Weinstock, R. S., Teresi, J. A., Palmas, W., Starren, J. B., Cimino, J. J., Lai, A. M., Field, L., Morin, P. C., Goland, R., et al. (2009) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m3157 · Cited by 375 · see citing works
Gregg, E. W., Zhuo, X., Cheng, Y. J., Albright, A. L., Narayan, K. M. V., & Thompson, T. J. (2014) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(14)70161-5 · Cited by 304 · see citing works
Inzucchi, S. E., Bergenstal, R. M., Buse, J. B., Diamant, M., Ferrannini, E., Nauck, M. A., Peters, A. L., Τσάπας, Α., Wender, R. C., & Matthews, D. R. (2012) · Diabetes Spectrum · doi:10.2337/diaspect.25.3.154 · Cited by 290 · see citing works
Randomized consent designs for clinical trials: An update
Zelen, M. (1990) · Statistics in Medicine · doi:10.1002/sim.4780090611 · Cited by 289 · see citing works
Faruque, L. I., Wiebe, N., Ehteshami-Afshar, A., Liu, Y., Dianati-Maleki, N., Hemmelgarn, B. R., Manns, B. J., & Tonelli, M. (2017) · Canadian Medical Association Journal · doi:10.1503/cmaj.150885 · Cited by 281 · cited 1× · see citing works
“One meta-analysis of randomized trials using home telemonitoring showed improvements in Type 2 Diabetes patient problem areas [18].”
MethodHome telehealth for diabetes management: a systematic review and meta‐analysis
Polisena, J., Tran, K., Cimon, K., Hutton, B., McGill, S., & Palmer, K. (2009) · Diabetes, Obesity and Metabolism · doi:10.1111/j.1463-1326.2009.01057.x · Cited by 239 · see citing works
Heisler, M. (2007) · Archives of Internal Medicine · doi:10.1001/archinte.167.17.1853 · Cited by 234 · see citing works
Telemedicine Application in the Care of Diabetes Patients: Systematic Review and Meta-Analysis
Marcolino, M. S., Maia, J. X., Alkmim, M. B. M., Boersma, E., & Ribeiro, A. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0079246 · Cited by 215 · cited 1× · see citing works
“Greater well-being was also reported by patients using home telemonitoring compared to usual care [20].”
BackgroundTeleHealth Improves Diabetes Self-Management in an Underserved Community
Davis, R. M., Hitch, A. D., Salaam, M. M., Herman, W. H., Zimmer-Galler, I. E., & Mayer-Davis, E. J. (2010) · Diabetes Care · doi:10.2337/dc09-1919 · Cited by 215 · see citing works
Lee, S. W. H., Chan, C. K. Y., Chua, S. S., & Chaiyakunapruk, N. (2017) · Scientific Reports · doi:10.1038/s41598-017-12987-z · Cited by 200 · see citing works
Effects of Ethnicity and Nephropathy on Lower-Extremity Amputation Risk Among Diabetic Veterans
Young, B. A., Maynard, C. C., Reiber, G. E., & Boyko, E. J. (2003) · Diabetes Care · doi:10.2337/diacare.26.2.495 · Cited by 175 · see citing works
Initial National Priorities for Comparative Effectiveness Research
Institute of Medicine (2009) · National Academies Press eBooks · doi:10.17226/12648 · Cited by 173 · see citing works
Su, D., Zhou, J., Kelley, M. S., Michaud, T. L., Siahpush, M., Kim, J., Wilson, F., Stimpson, J. P., & Pagán, J. A. (2016) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2016.04.019 · Cited by 164 · see citing works
Artinian, N. T., Washington, O. G. M., & Templin, T. (2001) · Heart & Lung · doi:10.1067/mhl.2001.112684 · Cited by 162 · see citing works
Trief, P. M., Izquierdo, R. E., Eimicke, J. P., Teresi, J. A., Goland, R., Palmas, W., Shea, S., & Weinstock, R. S. (2012) · Ethnicity and Health · doi:10.1080/13557858.2012.700915 · Cited by 112 · see citing works
George, S., Hamilton, A., & Baker, R. S. (2012) · International Journal of Telemedicine and Applications · doi:10.1155/2012/715194 · Cited by 110 · see citing works
1. Improving Care and Promoting Health in Populations: Standards of Medical Care in Diabetes—2018
American Diabetes Association (2017) · Diabetes Care · doi:10.2337/dc18-s001 · Cited by 103 · see citing works
Gender and Racial Disparities in the Management of Diabetes Mellitus Among Medicare Patients
Chou, A. F., Brown, A. F., Jensen, R. E., Shih, S. C., Pawlson, G., & Scholle, S. H. (2007) · Women s Health Issues · doi:10.1016/j.whi.2007.03.003 · Cited by 92 · see citing works
Wilson, C., Alam, R., Latif, S., Knighting, K., WILLIAMSON, S. L., & Beaver, K. (2011) · Health & Social Care in the Community · doi:10.1111/j.1365-2524.2011.01017.x · Cited by 90 · see citing works
Wu, C., Wu, Z., Yang, L., Zhu, W., Zhang, M., Zhu, Q., Chen, X., & Pan, Y. (2018) · Medicine · doi:10.1097/md.0000000000012962 · Cited by 86 · see citing works
Tortolero, S. R., Markham, C. M., Parcel, G. S., Peters, R. J., Escobar‐Chaves, S. L., Basen-Engquist, K. M., & Lewis, H. L. (2005) · Health Promotion Practice · doi:10.1177/1524839904266472 · Cited by 81 · see citing works
Culturally Targeted Strategies for Diabetes Prevention in Minority Population
Lagisetty, P., Priyadarshini, S., Terrell, S., Hamati, M. C., Landgraf, J. M., Chopra, V., & Heisler, M. (2017) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721716683811 · Cited by 81 · see citing works
Larkey, L., Gonzalez, J., Mar, L. E., & Glantz, N. M. (2008) · Contemporary Clinical Trials · doi:10.1016/j.cct.2008.08.003 · Cited by 62 · see citing works
Isaacs, T., Hunt, D. S., Ward, D. M., Rooshenas, L., & Edwards, L. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6374 · Cited by 53 · see citing works
Mance, G. A., Mendelson, T., Byrd, B., Jones, J., & Tandon, D. (2010) · Progress in Community Health Partnerships: Research, Education, and Action · doi:10.1353/cpr.0.0112 · Cited by 51 · see citing works
Wilson, T. E., Fraser-White, M., Williams, K. M., Pinto, A. R., Agbetor, F., Camilien, B., Henny, K. D., Browne, R. C., Gousse, Y., Taylor, T., et al. (2014) · AIDS Education and Prevention · doi:10.1521/aeap.2014.26.5.383 · Cited by 39 · see citing works
Self-citationCan mHealth Interventions Reduce Health Disparities among Vulnerable Populations?
Peek, M. E. (2017) · Diversity & Equality in Health and Care · doi:10.21767/2049-5471.100091 · Cited by 38 · see citing works
Improving diabetes care: the model for health care reform
Kahn, R., & Anderson, J. E. (2009) · Diabetes Care · doi:10.2337/dc09-0184 · Cited by 35 · cited 1× · see citing works
“Interventions based on models that involve cultural, personal, caregiver, and community factors and tailor care to patient preferences have demonstrated greater effectiveness [28].”
BackgroundRacial and ethnic disparities in the quality of diabetes care in a nationally representative sample.
Richard, P., Alexandre, P. K., Lara, A., & Akamigbo, A. B. (2011) · Europe PMC (PubMed Central) · doi:10.13016/uyno-cxqy · Cited by 28 · see citing works
Pekmezaris, R., Kozikowski, A., Pascarelli, B., Wolf‐Klein, G. P., Boye‐Codjoe, E., Jacome, S. N., Madera, D., Tsang, D., Guerrero, B., Medina, R., et al. (2019) · JMIR Formative Research · doi:10.2196/13197 · Cited by 22 · see citing works
Self-citationMendenhall, T. J., Whipple, H. M., Harper, P., et al. (2008) · Families Systems & Health · doi:10.1037/1091-7527.26.2.225 · Cited by 18 · see citing works
Walker, R. J., Smalls, B. L., Bonilha, H. S., Campbell, J. A., & Egede, L. E. (2013) · PubMed · Cited by 15 · see citing works
Mendenhall, T. J., Harper, P. G., Henn, L. L., Rudser, K. D., & Schoeller, B. P. (2013) · Families Systems & Health · doi:10.1037/fsh0000003 · Cited by 14 · see citing works
Web-Based Specialist Support for Spinal Cord Injury Person’s Care: Lessons Learned
Mea, V. D., Marin, D., Rosin, C., & Zampa, A. (2012) · International Journal of Telemedicine and Applications · doi:10.1155/2012/861860 · Cited by 9 · see citing works
Richard, P., Alexandre, P. K., Younis, M. Z., Lara, A., & Akamigbo, A. B. (2010) · Ageing International · doi:10.1007/s12126-010-9101-0 · Cited by 6 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [46]Luborsky MR. The identification and analysis of themes and patterns. In: Gubrium JF, Sankar A, editors. Qualitative methods in aging research, vol. 168. Sage focus edition. Thousand Oaks, CA, USA: Sage Publications; 1994. p. 189–210.
Cited by
Sorted by citations
Leo, D. G., Buckley, B. J. R., Chowdhury, M., Harrison, S. L., Isanejad, M., Lip, G. Y. H., Wright, D. J., Lane, D. A., & the TAILOR investigators (2022) · Journal of Medical Internet Research · doi:10.2196/35508 · Cited by 62 · see citing works
Use of telemonitoring in patient self-management of chronic disease: a qualitative meta-synthesis
Creber, A., Leo, D. G., Buckley, B. J. R., Chowdhury, M., Harrison, S. L., Isanejad, M., Lane, D. A., & on behalf of the TAILOR investigators (2023) · BMC Cardiovascular Disorders · doi:10.1186/s12872-023-03486-3 · Cited by 50 · see citing works
- Authors
- Pekmezaris, R., Williams, M. S., Pascarelli, B., Finuf, K. D., Harris, Y. T., Myers, A. K., Taylor, T., Kline, M., Patel, V. H., Murray, L. M., McFarlane, S. I., Pappas, K., Lesser, M. L., Makaryus, A. N., Martinez, S., Kozikowski, A., Polo, J., Guzman, J., Zeltser, R., Marino, J., Pena, M., DiClemente, R. J., & Granville, D.
- Affiliations
- Northwell Health (US)
- North Shore University Hospital (US)
- SUNY Downstate Health Sciences University (US)
- Nassau University Medical Center (US)
- Mount Sinai Health System (US)
- New York University (US)
- Corresponding author
- Finuf, Kayla D.
- ORCID
- Venue
- BMC Medical Informatics and Decision Making
- Published
- 2020-12
- Volume
- 20
- Issue
- 1
- Pages
- 324-324
- ISSN
- 1472-6947 (ISSN-L)
- PMC
- PMC7720574
- OpenAlex
- W3111180642
- Cited by
- 26
- References
- 50
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 9 · 2023: 8 · 2022: 4
- FWCI
- 2.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Patient-Centered Outcomes Research Institute (AD-2017C3-9185)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- home health monitoring, type 2 diabetes, Hispanic patients, underserved populations, intervention adaptation, acceptability, feasibility, community-based participatory research, stakeholder engagement, culturally congruent care, informed consent process, recruitment strategies, ADAPT-ITT framework, diabetes self-management education, educational videos, patient privacy
- MeSH terms
- Diabetes Mellitus, Type 2, Feasibility Studies, Health Promotion, Hispanic or Latino, Humans, Interviews as Topic, Patient Acceptance of Health Care, Pilot Projects, Focus Groups, Telemedicine, Monitoring, Ambulatory, Vulnerable Populations, Qualitative Research, Healthcare Disparities, Culturally Competent Care
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
