Evidence map›Paper›PMID 35411629›Full record

ArticleJournal of nursing management2022

Experiences and perceptions of final-year nursing students of using a chatbot in a simulated emergency situation: A qualitative study.

Miguel Rodriguez-Arrastia, Adrian Martinez-Ortigosa, Cristofer Ruiz-Gonzalez, Carmen Ropero-Padilla, Pablo Roman, Nuria Sanchez-Labraca

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of nursing management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 4 pooled it
6.6field-weighted citation impact, top 3% of its field
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

18 citing papers in PubMed, 4 syntheses or guidelines pooled it, 54 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

6 authors at 3 institutions in 1 country.

Miguel Rodriguez-ArrastiaPre-Department of Nursing, Jaume I University, Castello de la Plana, Spain.ORCID https://orcid.org/0000-0001-9430-4272
Adrian Martinez-OrtigosaEmergency Department, La Inmaculada Hospital, Huercal-Overal, Almeria, Spain.ORCID https://orcid.org/0000-0001-9624-0081
Cristofer Ruiz-GonzalezDepartment of Nursing Science, Physiotherapy and Medicine, University of Almeria, Almeria, Spain.ORCID https://orcid.org/0000-0001-9037-6439
Carmen Ropero-PadillaPre-Department of Nursing, Jaume I University, Castello de la Plana, Spain.ORCID https://orcid.org/0000-0001-5883-767X
Pablo RomanDepartment of Nursing Science, Physiotherapy and Medicine, University of Almeria, Almeria, Spain.ORCID https://orcid.org/0000-0002-5966-0498
Nuria Sanchez-LabracaDepartment of Nursing Science, Physiotherapy and Medicine, University of Almeria, Almeria, Spain.ORCID https://orcid.org/0000-0002-5867-2817
University of Almería · ESUniversitat Jaume I · ESHospital La Inmaculada · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThe aim of this study is to explore the experiences and perceptions of final-year nursing students on the acceptability and feasibility of using a chatbot for clinical decision-making and patient safety.

backgroundThe effective and inclusive use of new technologies such as conversational agents or chatbots could support nurses in increasing evidence-based care and decreasing low-quality services.

methodsA descriptive qualitative study was used through focus group interviews. The data analysis was conducted using a thematic analysis.

resultsThis study included 114 participants. After our data analysis, two main themes emerged: (i) experiences in the use of a chatbot service for clinical decision-making and and (ii) integrating conversational agents into the organizational safety culture.

conclusionsThe findings of our study provide preliminary support for the acceptability and feasibility of adopting SafeBot, a chatbot for clinical decision-making and patient safety. Our results revealed substantial recommendations for refining navigation, layout and content, as well as useful insights to support its acceptance in real nursing practice. IMPLICATIONS FOR NURSING MANAGEMENT: Leaders and managers may well see artificial intelligence-based conversational agents like SafeBot as a potential solution in modern nursing practice for effective problem-solving resolution, innovative staffing and nursing care delivery models at the bedside and criteria for measuring and ensure quality and patient safety.

Indexed as

Students, NursingArtificial IntelligenceDelivery of Health CareHumansProblem SolvingQualitative Researchartificial intelligencechatbotevidence-based practicenursingpatient safety

Identifiers

PMID35411629
PMCPMC10084062
OpenAlexW4223574528

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.