Evidence map›Paper›PMID 37546497›Full record

ArticleBelitung nursing journal2022

Developing, validating, and pre-testing of a diabetic care self-management mobile health application: A technology-based intervention for patients with diabetes in Malaysia.

Mohd Khairul Zul Hasymi Firdaus, Piyanuch Jittanoon, Umaporn Boonyasopun

Abstract read
In one paragraph

Article in Belitung nursing journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

3 authors.

Mohd Khairul Zul Hasymi FirdausKulliyyah of Nursing, International Islamic University Malaysia, Malaysia.ORCID https://orcid.org/0000-0002-2549-3265
Piyanuch JittanoonFaculty of Nursing, Prince of Songkla University, Thailand.
Umaporn BoonyasopunFaculty of Nursing, Prince of Songkla University, Thailand.ORCID https://orcid.org/0000-0002-8388-6710

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Technology-based intervention showed a promising approach to health promotion strategies. There had been limited knowledge of the existing program for technology-based intervention in promoting foot care and dietary behavior modification. Thus, a mobile app was developed as an alternative strategy for promoting foot care and dietary behavior modification. Objective: This paper aims to elaborate on the process of developing, validating, and examining the Diabetic Care Self-Management Mobile Health Application (Diabetic Care). Methods: There are two phases conducted. The first phase is the process of developing and validating Diabetic Care. Intervention Mapping (IM) Framework was used to guide the process of developing Diabetic Care, while in assessing validity, guidance from Kassam-Adams et al. was used. A team of experts was appointed to validate the mobile app developed. Next, the usability of Diabetic Care was conducted among ten conveniently chosen patients with diabetes in a governmental primary care clinic. Results: The process of developing Diabetic Care was clearly explained. The Diabetic Care app showed a good I-CVI score (1.00) and general CVI score (1.00) after the expert team assessed. During the trial, two drawbacks were identified and explored to find solutions. Conclusion: The Diabetic Care app is proven appropriate to be employed in the study. Even though there were two drawbacks encountered, however, possible solutions were able to be explored in addressing the issues. Further research should be conducted to examine the effectiveness of this mobile app in modifying foot care behavior and dietary behavior. Hence, it will assist in the translation of advanced technology in nursing care.

Indexed as

diabetes mellitushealth promotionMalaysiamobile applicationsnursingself-managementtechnology

Identifiers

PMID37546497
PMCPMC10401381

What OpenQuestion holds

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LicenceCC BY-NC
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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.