Evidence map›Paper›PMID 38962354›Full record

ArticleAfrican health sciences2024

Elderly people's perceptions on the use of mobile phones to support the self-management of long-term illnesses at Kiruddu National Referral Hospital.

Peterson Mulinde

Abstract read
In one paragraph

Article in African health sciences, 2024. 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

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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

4 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

1 author.

Peterson MulindeMakerere University College of Computing and Information Sciences, Information Technology.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The global estimate of the aging population is progressively increasing in low and middle-income countries and this is accompanied by the limitations associated with the need for equitable and efficient healthcare delivery among this dire population. Unfortunately, despite the increasing numbers, the adoption of mobile phones is not balanced in the different populations with research showing young persons' adoption rate is higher than that of elderly persons. Objective: This current study was conducted to identify elderly people's perceptions of the use of mobile phones to support the self-management of long-term illnesses at Kiruddu National Referral Hospital. Methods: This descriptive-cross-sectional design study was conducted on a sample population of 30 elderly individuals older than 60 years admitted at the outpatient department of Kiruddu National Referral Hospital, Kampala, Uganda. We conducted face-to-face interviews following an interview guide and one focus group discussion. We later used a feature mobile phone and a tablet mobile phone to assess the individual ease of use of each device. The audio recordings were professionally transcribed and transcripts were coded into NVIVO version 12 analysis software for thematic analysis. Results: Almost all of the respondents who visited the facility had an ailment that hindered their full utilization of the mobile phone to support their self-care. This together with other factors like financial constraints, lack of support from the health workers on how to use mobile phones to support health, inadequate support from the facility, and cost of mobile data among others. Background and Conclusion: This study provides empirical evidence that there is hardly a known mobile phone adoption model to enable policymakers, systems developers, and health workers to promote the elderly population's use of mobile phones to manage their long-term illnesses in Uganda.

Indexed as

Cell PhoneAgedAged, 80 and overChronic DiseaseCross-Sectional StudiesFemaleFocus GroupsHumansMaleMiddle AgedPerceptionSelf-ManagementUgandaHealthcare technologymobile phoneolder persons

Identifiers

PMID38962354
PMCPMC11217833

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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.