ArticleBMC medical informatics and decision making2023
Identifying factors that affect the use of health information technology in the treatment and management of hypertension.
Article in BMC medical informatics and decision making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed.
- Cardiovascular and renal effects of 5-aminoimidazole-4-carboxyribonucleoside (AICAR) in the deoxycorticosterone acetate (DOCA)-salt rat model of hypertension.Life sciences · 2025Article
- Mobile solution and chronic diseases: development and implementation of a mobile application and digital platform for collecting, analyzing data, monitoring and managing health care.BMC health services research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe conducted this study with the aim of identifying factors that affect the use of health information technology in the treatment and management of hypertension.
methodsThis paper is a descriptive-analytic study conducted in 2022. To obtain relevant articles, databases including Scopus, Web of Science, IEEE, and PubMed were searched and the time period was between 2013 and 2022. Based on the review of similar articles, a five-point Likert scale checklist was developed in the second phase. The statistical population of the present study was specialist physicians (N = 40) and patients (N = 384). In order to analyze the data, SPSS Statistics 24 was used. To analyze the data obtained from the checklist, we used summary statistics (mean and standard deviation).
resultsAs a result of the review literature process, 50 papers were screened, that based we can distinguish motivational and inhibitory factors affecting the use of health information technology in hypertension management. Indeed, Motivational factors and inhibitory factors can be classified into five groups: organizational, economic, technical, personal, and legal/moral factors. Based on the results of the checklist, the factors that were identified as most influential on motivation and inhibitory patients and specialist physicians' to use of health information technology to manage and treat hypertension.
conclusionUtilizing technologies for hypertension, its management can be improved by identifying motivating and inhibiting factors. Our approach can improve the acceptability of these technologies, save costs, reduce long-term complications of hypertension, and improve patient quality of life.
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Registered trials
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.