# eHealth Literacy and Type 2 Diabetes Prevention Among At-Risk Populations: Mechanistic Systematic Review Using Theory-Driven Thematic Analysis

**Authors:** Jingyi Li, Arina Anis Azlan, Nurzihan Hassim, Yuan Wang, Ruina Guo

PMC · DOI: 10.2196/77788 · 2026-03-10

## TL;DR

This paper reviews how eHealth literacy helps prevent type 2 diabetes in at-risk groups, highlighting key mechanisms and gaps in current research.

## Contribution

The study is the first to systematically map eHealth literacy mechanisms in T2D prevention using a theory-driven thematic analysis.

## Key findings

- eHealth literacy primarily supports prevention through knowledge, behavioral regulation, and social influences.
- Most studies focused on health and information literacy, neglecting critical eHL and media literacy.
- Positive outcomes include weight loss, improved glycemic markers, and better lifestyle behaviors.

## Abstract

Type 2 diabetes (T2D) is emerging as a growing global public health crisis. Early and effective interventions can reduce T2D incidence among at-risk populations. Compared with traditional approaches, digital health technologies offer promising opportunities for prevention, with eHealth literacy (eHL) emerging as a critical determinant of digital prevention outcomes.

This systematic review aims to synthesize and explain the pathways and mechanisms through which eHL supports T2D prevention among at-risk populations.

We searched Scopus, Web of Science, and PubMed databases for English-language original research published between January 1, 2000, and August 14, 2025. Studies included were prevention research involving eHL engagement among populations at risk for T2D. Nonoriginal literature, such as editorials and abstracts, as well as research protocols, was excluded. The findings were synthesized using a thematic analysis approach, integrating the Theoretical Domains Framework with the eHL model. Two reviewers independently screened literature and extracted data, and discrepancies were resolved by a third reviewer. The Mixed Methods Appraisal Tool was used to assess risk of bias.

This review included 28 studies (n=13,100), mostly quantitative and published within the past decade, targeting people with prediabetes, prior gestational diabetes, and overweight/metabolic risk. Study quality was moderate to high (Mixed Methods Appraisal Tool 60%‐100%) with no high risk of bias. eHL supported prevention mainly through knowledge (28/28), behavioral regulation (16/28), social influences (15/28), environmental resources (12/28), and goals (11/28), while emotions, memory, attention, decision process, and beliefs about competence were rarely addressed. Health literacy (27/28), information literacy (20/28), and communicative eHL (20/28) were most common; critical eHL and media literacy were not addressed. Studies reported positive outcomes: high engagement, weight loss (≥5%), improved glycemic markers, and enhanced lifestyle behaviors.

This is the first systematic exploration of eHL mechanism pathways in T2D prevention via theoretical mapping. We found interventions yield positive effects despite highly uneven mechanism application: extant research relies excessively on knowledge and behavioral pathways while underemphasizing emotional support, autonomy, and critical evaluation—factors linked to long-term adherence. We provide a mechanism-based framework and identify critical gaps, including the absence of focus on critical eHL and media literacy. This review is limited by substantial variation across studies that did not allow for meta-analysis and by the limited evidence base on eHL. Future interventions should explore and test emotional and autonomy support, information discernment training, and accessibility optimization in T2D prevention. These comprehensive, equity-focused intervention approaches will help ensure that eHL becomes a truly effective public health tool that benefits everyone, especially at-risk and vulnerable populations.

## Linked entities

- **Diseases:** Type 2 diabetes (MONDO:0005148), prediabetes (MONDO:0006920), gestational diabetes (MONDO:0005406)

## Full-text entities

- **Genes:** DSPP (dentin sialophosphoprotein) [NCBI Gene 1834] {aka DFNA39, DGI1, DMP3, DPP, DSP}
- **Diseases:** acanthosis nigricans (MESH:D000052), sputum stasis (MESH:D014647), overweight (MESH:D050177), obese (MESH:D009765), smoking (MESH:D015208), gestational diabetes (MESH:D016640), anxiety (MESH:D001007), Prediabetes (MESH:D011236), Diabetes (MESH:D003920), nonalcoholic fatty liver disease (MESH:D065626), dyslipidemia (MESH:D050171), pains (MESH:D010146), metabolic syndrome (MESH:D024821), Yang deficiency (MESH:D016711), chronic diseases (MESH:D002908), type 1 diabetes (MESH:D003922), depression (MESH:D003866), sleep deprivation (MESH:D012892), NIDDM (MESH:D003924), insulin resistance (MESH:D007333), Weight loss (MESH:D015431), COVID-19 (MESH:D000086382), HCAI (MESH:C536430), WOS (MESH:C563636), Hypertension (MESH:D006973)
- **Chemicals:** blood glucose (MESH:D001786), cholesterol (MESH:D002784), sugar (MESH:D000073893), fat (MESH:D005223), glucose (MESH:D005947), alcohol (MESH:D000438), carbohydrate (MESH:D002241), sodium (MESH:D012964), HDL: density lipoprotein cholesterol (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12975002/full.md

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Source: https://tomesphere.com/paper/PMC12975002