Evidence map›Paper›PMID 31193710›Full record

ArticleHeliyon2019

Health Information Technology Acceptance Framework for diabetes management.

O S Ayanlade, T O Oyebisi, B A Kolawole

Abstract read
In one paragraph

Article in Heliyon, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. 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

3 authors.

O S AyanladeAfrican Institute for Science Policy and Innovation (AISPI), Obafemi Awolowo University, Ile-Ife, Nigeria.
T O OyebisiAfrican Institute for Science Policy and Innovation (AISPI), Obafemi Awolowo University, Ile-Ife, Nigeria.
B A KolawoleDepartment of Medicine, Faculty of Clinical Sciences, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examined the level of acceptance of Health Information Technology (HIT) as tools for diabetes care and management, in six selected tertiary hospitals in southwestern zone of Nigeria. Using both quantitative and qualitative methods, this study was conducted amongst selected healthcare stakeholders namely Nurses, Doctors, Laboratory Scientists, Pharmacists, ICT unit Professionals, Medical Record Officers, and Type-2 diabetes out-patients available in the designated hospitals. Adapting Technology Acceptance and Chronic Care Models, the level of HIT acceptance by the respondents in the study area was measured in terms of Perceived Ease-of-Use, Perceived Usefulness, and the Perceived Unintended Consequences relating to HIT, while also considering the roles of the government, community and healthcare organizations. One hundred and fifty (150) respondents were examined, each for both Staff and Patients, and the factor variables studied on a 5-point Likert rating scale of measurement from 1 (Strongly Disagree) to 5 (Strongly Agree). The results revealed strong perception of Staff and Patients about HIT implementation and acceptance and showed that in some cases, the perception of Staff and patients about HIT acceptance are the same, while different in some. The study concluded that for acceptability of HIT, hospitals have to embark on 'continuous' training for the HIT users, so that users would familiarize themselves with the system, and it will be fully incorporated into their workflow. Based on the findings, a conceptual Health Information Technology Acceptance Framework for Chronic diseases' management, especially for diabetes mellitus was developed.

Indexed as

Health professionInformation science

Identifiers

PMID31193710
PMCPMC6539785

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.