Evidence mapPaperPMID 41358248Full record

ReviewFrontiers in public health2025

Application of persuasive system design in mobile health interventions for chronic disease management: a mini review.

Kai Zhang, Yurong Jiang, Keyue Xi, Ningna Sun

Abstract readReview
In one paragraph

Review in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kai ZhangDepartment of Industrial Design, School of Art, Jiangsu University, Zhenjiang, Jiangsu, China.
Yurong JiangDepartment of Industrial Design, School of Art, Jiangsu University, Zhenjiang, Jiangsu, China.
Keyue XiDepartment of Industrial Design, School of Art, Jiangsu University, Zhenjiang, Jiangsu, China.
Ningna SunDepartment of Industrial Design, School of Art, Jiangsu University, Zhenjiang, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Persuasive System Design (PSD) has emerged as a pivotal framework in the development of mobile health (mHealth) interventions aimed at chronic disease management. While numerous systems have been designed under its theoretical guidance, the implementation patterns of its design principles and the efficacy of resulting interventions remain inadequately synthesized. This mini-review consolidates recent evidence to elucidate the application characteristics of the PSD framework, revealing a structural imbalance in the adoption of its principles: a predominant focus on primary task and dialogue support, contrasted with a notable underutilization of social support and credibility-enhancing features. Furthermore, we explore the adaptive mechanisms linking PSD principles with specific mHealth functions and technological platforms, highlighting how such synergies can be tailored to diverse clinical contexts. Critical methodological shortcomings are also identified, including an overreliance on physiological outcomes in randomized controlled trials and a general neglect of qualitative insights and health economic evaluations. By identifying these gaps and trends, this review aims to inform the future development of theoretically grounded, persuasive, and sustainable digital health interventions for chronic disease management.

Indexed as

Disease ManagementPersuasive CommunicationTelemedicineChronic DiseaseHumansSocial Supportchronic diseasesmHealthpersuasive system designpersuasive technologyPSD framework

Identifiers

PMID41358248
PMCPMC12675468

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.