Evidence map›Paper›PMID 37886046›Full record

ArticleFrontiers in public health2023

Perceptions of registered nurses on facilitators and barriers of implementing the AI-IoT-based healthcare pilot project for older adults during the COVID-19 pandemic in South Korea.

Sunjoo Boo, Hyunjin Oh

Abstract read
In one paragraph

Article in Frontiers in public health, 2023. 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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
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

2 authors.

Sunjoo BooCollege of Nursing Research Institute of Nursing Science, Suwon, Republic of Korea.
Hyunjin OhCollege of Nursing, Gachon University, Incheon, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study explored the perceptions of registered nurses on the facilitators and barriers to implementing an AI/IoT (Artificial Intelligence/Internet of Things)-based healthcare pilot project, designed to prevent frailty and improve health behaviors by providing Bluetooth-enabled smart devices (including blood pressure and blood glucose meters) for the older adults aged over 65 years and above in South Korea. Methods: Using a qualitative descriptive methodology, interviews and qualitative surveys were conducted with 15 registered nurses from 11 public health centers. Data were analyzed using qualitative content analysis. Results: The study found that the AI·IoT-based healthcare pilot project was well received by participants, leading to increased client satisfaction and improved health behaviors. Government support and funding were crucial facilitators of project implementation. However, technical challenges and disparities in digital literacy among older adults pose significant barriers. Conclusion: The findings highlight the potential of AI·IoT technologies in improving the healthcare of older adults. Efforts to address technological challenges and enhance digital literacy among vulnerable populations are necessary for successfully implementing such interventions. Government support and ongoing training for healthcare professionals can help optimize the AI·IoT-based healthcare services for older adults.

Indexed as

COVID-19NursesAgedArtificial IntelligenceHumansPandemicsPatient SatisfactionPilot ProjectsRepublic of KoreaAI·IoT-based healthcarebarriersdigital literacyfacilitatorsolder adultspublic health

Identifiers

PMID37886046
PMCPMC10598465

What OpenQuestion holds

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LicenceCC BY
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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.