Evidence map›Paper›PMID 41181559›Full record

ArticleDigital health

The readiness to use quantified self-technology: A case of diabetic patients from a hospital in Bulawayo, Zimbabwe.

Belinda Mutunhu Ndlovu, Baldreck Chipangura, Shawren Singh

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Belinda Mutunhu NdlovuSchool of Computing, University of South Africa, Pretoria, South Africa.ORCID https://orcid.org/0000-0001-6046-3240
Baldreck ChipanguraSchool of Computing, University of South Africa, Pretoria, South Africa.ORCID https://orcid.org/0000-0001-5334-0808
Shawren SinghSchool of Computing, University of South Africa, Pretoria, South Africa.ORCID https://orcid.org/0000-0001-5038-0724

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Quantified self-technology (QST) can potentially improve the monitoring and management of diabetes. Despite its potential, its uptake by diabetics in developing countries is notably low. This study investigated the underlying factors influencing the readiness of diabetics to adopt QST. The research question posed was, 'What are the factors that inform the readiness of diabetics to adopt QST in developing countries?'. Methods: Semi-structured interviews were employed to collect qualitative data from a sample of 35 participants aged between 18 and 65 from a hospital in the city of Bulawayo, Zimbabwe. The participants were selected through self-selection sampling technique. Data was analysed using Braun and Clarke's thematic data analysis. Results: Three factors were found to drive the readiness to adopt QST and they are awareness, optimism and social support. Conversely, two factors were found to inhibit the readiness to adopt QST and they are insecurity and challenges. Conclusion: The findings suggest that patients are more likely to be ready to use QST if they are aware of the technology, optimistic and have adequate social support from family and community. Moreover, readiness can be enhanced if the patients' challenges are addressed and insecurities are demystified. The implications of QST on diabetics are that it enhances self-monitoring of diabetes, which in turn improves preventative health and reduces hospital visits by diabetics. The implication on health policy is that adoption of QST reduces health cost of treating diabetes, hence, policies should provide enabling environment for the use of QST technologies by diabetics.

Indexed as

adoptiondiabetesdiabetes monitoringquantified self technologyTechnology readiness

Identifiers

PMID41181559
PMCPMC12576210

What OpenQuestion holds

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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.