Evidence map›Paper›PMID 41132439›Full record

ArticleDigital health

Development of a nurse-led mHealth intervention framework for patients with chronic diseases: A systematic review and Delphi study.

Jianing Hua, Dan Sun, Huihong Wang, Jiang Chang, Guo Fei, Qing Zhou, Ning Hui, Danfeng Gu, Lihong Zhu

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Trial
  2. Article
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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

9 authors.

Jianing HuaBurn & Trauma Treatment Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.ORCID https://orcid.org/0000-0002-0691-0764
Dan SunBurn & Trauma Treatment Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.
Huihong WangNursing department, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.
Jiang ChangBurn & Trauma Treatment Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.
Guo FeiBurn & Trauma Treatment Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.
Qing ZhouBurn & Trauma Treatment Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.
Ning HuiBurn & Trauma Treatment Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.ORCID https://orcid.org/0000-0002-2712-0577
Danfeng GuNursing department, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.ORCID https://orcid.org/0000-0002-3367-4656
Lihong ZhuBurn & Trauma Treatment Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: mHealth is increasingly becoming popular and useful for managing chronic diseases. Nurse-led mHealth services offer a patient-centred perspective, but many existing solutions lack a robust empirical foundation. Therefore, this study aimed to address this gap by developing a comprehensive framework to support mHealth implementation through a systematic review and the Delphi method. Specifically, the study sought to create a nurse-led mobile health (mHealth) intervention framework designed for managing patients with chronic diseases. Methods: We conducted a systematic review of PubMed, Web of Science, Cochrane Library, CNKI, and Wanfang databases to identify existing nurse-led mHealth intervention programs. Items from these articles were compiled into an inclusion list, and the Delphi method was applied to rank their priority. The Delphi process involved 13 nursing specialists and was conducted over two rounds using a Likert priority scale (1-5) to establish consensus. Results: Based on the systematic review (included 16 articles for full review) and study group contributions, 36 potential framework items were identified. In the initial round of the Delphi study, specialists rejected 7 of the 36 items and recommended merging 6. In the subsequent round, the specialists recommended removing the self-monitoring diet items. The final items were consolidated into a 22-item nurse-led mHealth intervention framework categorized into three domains: pre-hospital evaluation, in-hospital intervention, and post-hospital continuity. Conclusions: The Delphi-approved items offer a basis for evidence-based nurse-led mHealth intervention frameworks. These findings highlight the need for an intervention framework and its practical integration into the existing mHealth system.

Indexed as

chronic diseasesDelphi techniquedigital healthNurse's rolepatient-centred care

Identifiers

PMID41132439
PMCPMC12541158

What OpenQuestion holds

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Registered trials

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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.