ArticleJournal of medical Internet research2020
The Use of Technology for Communicating With Clinicians or Seeking Health Information in a Multilingual Urban Cohort: Cross-Sectional Survey.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04378738 (The Role of Social Media as an Information Source in Covid19 Pandemic), which is not on this map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Role of Social Media as an Information Source in Covid19 Pandemic
Who cites it
28 citing papers in PubMed, 46 citations in OpenAlex.
- Identifying trajectories across care modalities before and after COVID-19 using sequence analysis.NPJ digital medicine · 2026Article
- Identifying Skill and Usability Barriers to Digital Health Tool Use Among Older Adult Patients in US Safety Net Clinics: Mixed Methods Study.JMIR human factors · 2026Article
- Trajectories of In-Person and Remote Care Utilization: A Sequence Analysis of Primary Care Modalities Pre- and Post-COVID-19.Research square · 2025Article
- A self-report measure of digital skills needed to use digital health tools among older adults-the Skills Measurement and Readiness Training for Digital Health (SMART Digital Health) Scale.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Factors impacting electronic patient-generated data use in safety-net systems: a qualitative study.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Lower Use of and Potential Barriers to Using Patient Portals Among Limited English Proficient Latino and Chinese American Adults: A Health Techquity Concern.The Permanente journal · 2025Article
- The Effects of the COVID-19 Pandemic on Age-Based Disparities in Digital Health Technology Use: Secondary Analysis of the 2017-2022 Health Information National Trends Survey.Journal of medical Internet research · 2024Observational
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- Visual Impairment from Uncorrected Refractive Error among Participants in a Novel Program to Improve Eye Care Access among Low-Income Adults in Michigan.Ophthalmology · 2024Article
- Health Equity in the Veterans Health Administration From Veterans' Perspectives by Race and Sex.JAMA network open · 2024Article
- Factors Associated with Korean American Women's Health-Related Internet Use: Findings from Andersen's Behavioral Model.Journal of immigrant and minority health · 2024Article
- Lessons learned from a multi-site collaborative working toward a digital health use screening tool.Frontiers in public health · 2024Article
- Factors Associated With Online Patient-Provider Communications Among Cancer Survivors in the United States During COVID-19: Cross-sectional Study.JMIR cancer · 2023Article
- Results of a Remotely Delivered Hypertension and Lipid Program in More Than 10 000 Patients Across a Diverse Health Care Network.JAMA cardiology · 2023Article
- The Impact of the COVID-19 Pandemic on Internet Use and the Use of Digital Health Tools: Secondary Analysis of the 2020 Health Information National Trends Survey.Journal of medical Internet research · 2022Article
- Barriers and Facilitators to the Implementation of Family-Centered Technology in Complex Care: Feasibility Study.Journal of medical Internet research · 2022Article
- Consumer Health Informatics for Racial and Ethnic Minoritized Communities: Minor Progress, Major Opportunities.Yearbook of medical informatics · 2022Review
- Impact of language preference and health literacy on health information-seeking experiences among a low-income, multilingual cohort.Patient education and counseling · 2022Article
- Chinese Americans' Use of Patient Portal Systems: Scoping Review.JMIR human factors · 2022Article
- Challenges and Opportunities in Using Telehealth for Diabetes Care.Diabetes spectrum : a publication of the American Diabetes Association · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundTechnology is being increasingly used to communicate health information, but there is limited knowledge on whether these strategies are effective for vulnerable populations, including non-English speaking or low-income individuals.
objectiveThis study assessed how language preferences (eg, English, Spanish, or Chinese), smartphone ownership, and the type of clinic for usual source of care (eg, no usual source of care, nonintegrated safety net, integrated safety net, private or community clinic, academic tertiary medical center, or integrated payer-provider) affect technology use for health-related communication.
methodsFrom May to September 2017, we administered a nonrandom, targeted survey to 1027 English-, Spanish-, and Chinese-speaking San Francisco residents and used weighted multivariable logistic regression analyses to assess predictors of five technology use outcomes. The three primary predictors of interest-language preference, smartphone ownership, and type of clinic for usual care-were adjusted for age, gender, race or ethnicity, limited English proficiency, educational attainment, health literacy, and health status. Three outcomes focused on use of email, SMS text message, or phone apps to communicate with clinicians. The two other outcomes were use of Web-based health videos or online health support groups.
resultsNearly one-third of participants watched Web-based health videos (367/1027, 35.74%) or used emails to communicate with their clinician (318/1027, 30.96%). In adjusted analyses, individuals without smartphones had significantly lower odds of texting their clinician (adjusted odds ratio [aOR] 0.27, 95% CI 0.13-0.56), using online health support groups (aOR 0.14, 95% CI 0.04-0.55), or watching Web-based health videos (aOR 0.31, 95% CI 0.15-0.64). Relative to English-speaking survey respondents, individuals who preferred Chinese had lower odds of texting their clinician (aOR 0.25, 95% CI 0.08-0.79), whereas Spanish-speaking survey respondents had lower odds of using apps to communicate with clinicians (aOR 0.34, 95% CI 0.16-0.75) or joining an online support group (aOR 0.30, 95% CI 0.10-0.92). Respondents who received care from a clinic affiliated with the integrated safety net, academic tertiary medical center, or integrated payer-provider systems had higher odds than individuals without a usual source of care at using emails, SMS text messages, or apps to communicate with clinicians.
conclusionsIn vulnerable populations, smartphone ownership increases the use of many forms of technology for health purposes, but device ownership itself is not sufficient to increase the use of all technologies for communicating with clinicians. Language preference impacts the use of technology for health purposes even after considering English proficiency. Health system factors impact patients' use of technology-enabled approaches for communicating with clinicians. No single factor was associated with higher odds of using technology for all health purposes; therefore, existing disparities in the use of digital health tools among diverse and vulnerable populations can only be addressed using a multipronged approach.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.