Evidence map›Paper›PMID 32523670›Full record

ArticleTherapeutic advances in endocrinology and metabolism2020

A qualitative study of users' experiences after 3 months: the first Rwandan diabetes self-management Smartphone application "Kir'App".

Claudine B Kabeza, Lorenz Harst, Peter E H Schwarz, Patrick Timpel

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Article in Therapeutic advances in endocrinology and metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

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6citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Claudine B KabezaUniversity of Rwanda, College of Medicine and Health Sciences/ Rwamagana Campus, Rwanda Department for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, Deutschland, Dresden, 01307, Germany.ORCID https://orcid.org/0000-0002-1218-5941
Lorenz HarstResearch Association Public Health Saxony, Centre for Evidence-Based Healthcare, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Sachsen, Germany.
Peter E H SchwarzDepartment for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland Germany German Centre for Diabetes Research (DZD e.V.), Neuherberg, Germany Paul Langerhans Institute Dresden of the Helmholtz Centre Munich at University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
Patrick TimpelDepartment for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOwing to the increasing popularity of smartphones in Rwanda, almost 75% of the entire population currently has access to the internet. Although it has been shown that smartphone applications can support diabetes self-management, there was no diabetes self-management application available in Rwanda until April 2019. Based on the findings of a prior study assessing the needs and expectations of potential users, 'Kir'App' was developed to fill that void. The aim of this study was to evaluate users' experiences after 3 months of use of the first Kir'App prototype.

methodsThe participants of the previous study were recruited to take part in the current study. Semi-structured, in-depth, face-to-face interviews were conducted. Findings were analysed thematically using Mayring's method of qualitative content analysis. Both deductive and inductive approaches were used to analyse transcripts according to the original categories and subcategories of the previous study.

resultsA total of 14 people with either type 1 or type 2 diabetes participated in the study. Age of participants ranged from 19 to 70 years, with a mean age of 34.4 years. Seven of the eight original themes and one additional theme were subjoined: diabetes education and desired information provision; increased diabetes knowledge and awareness; monitoring and reminder functions; nutrition; physical activity; coping with burden of disease; app features; use behaviour and usability. Overall, participants stated that the app increased their diabetes knowledge and assisted them with their diabetes self-management.

conclusionsWe found that the first prototype of Kir'App meets the overall needs and expectations of participating Rwandan diabetics. Having followed a strict user-centred design process, their qualitative insights will help to further improve the app.

Indexed as

diabetesexperiencesKir’AppRwanda

Identifiers

PMID32523670
PMCPMC7236575

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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.