e.g. mhealth
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Skip search results from other journals and go to results- 17 Journal of Medical Internet Research
- 10 JMIR Formative Research
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Role and Use of Race in Artificial Intelligence and Machine Learning Models Related to Health
Appropriate inclusion of race within AI and ML models can identify differences in the outcomes of people with different backgrounds, creating opportunities for mitigation [2]. Yet, numerous examples exist of inappropriate inclusion of race or proxies of race in health-related models, which can harm large segments of the population [3].
J Med Internet Res 2025;27:e73996
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Substance use (SU) prevalence varies across demographics such as age, gender, race, and ethnicity. During the COVID-19 pandemic, these differences became more pronounced. The pandemic not only increased global SU, with overdose deaths rising by 29.4% [1], but also exacerbated societal and racial inequalities [2,3] and significantly impacted mental health [4-7].
JMIR Infodemiology 2025;5:e67333
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Terminology and Definitions of Racial Health Equity in Prominent Health Websites: Systematic Review
race
J Med Internet Res 2025;27:e64868
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Covariates including age, sex, race and ethnicity, BMI, education level, and perceived financial well-being were obtained through self-report. Age was treated as a continuous variable, representing the participants’ age in years. Sex was a categorical variable, categorized as male, female, or other. Race and ethnicity were also categorical variables, encompassing diverse categories such as NHW, NHB, Hispanic, and Other.
JMIR Form Res 2025;9:e58916
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Specifically, this review was done to (1) describe study characteristics of m Health interventions for exercise adherence in HF including details of sample demographics, sample sizes, exercise program, and theoretical frameworks; (2) summarize types of m Health technology used to improve exercise adherence in patients with HF; (3) highlight how the term “adherence” was defined and how it was measured across m Health studies and adherence achieved; and (4) highlight the effect of age, sex, race, NYHA functional
J Med Internet Res 2025;27:e54524
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We estimated odds ratios (OR) for diabetes by race or ethnicity and asthma status under 4 EHR-based estimation methods that we describe herein. First, “naïve” models were estimated by fitting a logistic regression model for observed diabetes status (DM*) on the total sample (n=454,612).
JMIR Med Inform 2024;12:e58085
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Younger age, Black race, and unstable or lower income are each associated with discontinuations and being lost to follow-up [14]. We have observed similar levels of Pr EP retention in the PHSKC Sexual Health Clinic (SHC), with 40% of Pr EP users discontinuing the intervention at least once within 12 months [15].
JMIR Res Protoc 2024;13:e56587
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Despite substantial evidence that Black YMSM-YTW experience sexual racism in online dating, there is no evidence about whether this results in quantifiable differences in online sexual partnering by race and ethnicity.
Research consistently finds high levels of within–race and ethnicity sexual partnering among young MSM [7,13-17]. A recent study suggested that sexual exclusivity among Black sexual minority men may be partially protective against the psychological impacts of racial discrimination [18].
JMIR Public Health Surveill 2024;10:e54215
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By “minoritized,” we refer to systemic oppression across a range of contexts by the majority group (in the United States, by White communities), and by “ethnoracial” we recognize that cultural groups are typically racialized, meaning treated as a race, and thus use a term that combines “ethnicity” and “race” [8]. Ethnoracial disparities are, therefore, inequalities along ethnic and racial group lines.
JMIR Form Res 2024;8:e55759
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We used ANOVA to assess engagement and changes in clinical outcomes by age, race/ethnicity, and gender.
The study was approved by the WCG Institutional Review Board (Wisdo.001.1/26/2023). Since all data were routinely collected during the intervention, this protocol was considered exempt from additional consent. All data were deidentified. Participants received 1 year of free access to the platform but no other compensation.
JMIR Form Res 2024;8:e58263
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