ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2021
Investigating Health Information Technology Usage by Sociodemographic Subpopulations to Increase Community Engagement in Healthcare: An Analysis of the Health Information National Trends Survey.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Effectiveness of Digital Health Interventions on Body Weight and Dietary Intake Outcomes Among Culturally and Linguistically Diverse (CALD) and Indigenous Populations: A Systematic Review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Pooled it
- Usage Trends and Data Sharing Practices of Healthcare Wearable Devices Among US Adults: Cross-Sectional Study.Journal of medical Internet research · 2025Article
- Population Digital Health: Continuous Health Monitoring and Profiling at Scale.Online journal of public health informatics · 2024Article
- Health Information Technology Use among Chronic Disease Patients: An Analysis of the United States Health Information National Trends Survey.Applied clinical informatics · 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
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is well known that the US is plagued by health inequities: unjust differences in morbidity and mortality rates by sociodemographic factors. A potential method to address such inequities lies in utilizing health information technologies (HIT) to reach under-resourced populations and increase their involvement in healthcare. Previous researchers have done just this, using HIT tools to engage under-resourced communities and improve outcomes. However, it is unclear how HIT usage varies by sociodemographic characteristics. This study investigated this question through analysis of the Health Information National Trends Survey (HINTS) and proposed tailored HIT interventions for specific subpopulations. Internet, smartphone, and wearable device usage were analyzed by age, race/ethnicity, educational attainment, and income; purposes of HIT usage were assessed; and logistic regression models were conducted to determine associations between purposes of HIT usage and sociodemographic predictors. Results showed that Black/African American, Latinx, and Asian populations all had significantly increased use of health videos, while participants with low educational attainment had significantly decreased use of many HIT tools. Thus, this study highlights effective interventions for specific racial/ethnic populations and showcases a need for HIT tools inclusive towards low education populations to increase their engagement in healthcare and reduce inequities.
Indexed as
Identifiers
35308912PMC8861741W4287494684What OpenQuestion holds
Registered trials
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.