Evidence map›Paper›PMID 39334099›Full record

ArticleBMC nursing2024

Construction of an index system of core competence assessment for sleep medicine nurse specialists in China: a Delphi study.

Nan Jiang, Wei Bin Liu, YanHong Zong, Li Yu, ShuHua Cheng

Abstract read
In one paragraph

Article in BMC nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

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12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

12 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

5 authors.

Nan JiangAffiliated Rehabilitation Hospital of Nanchang University, Nanchang, China.
Wei Bin LiuAffiliated Rehabilitation Hospital of Nanchang University, Nanchang, China.
YanHong ZongAffiliated Rehabilitation Hospital of Nanchang University, Nanchang, China.
Li YuAffiliated Rehabilitation Hospital of Nanchang University, Nanchang, China.
ShuHua ChengAffiliated Rehabilitation Hospital of Nanchang University, Nanchang, China. chengsh29@163.com.

Funding

The Science and Technology Program of Jiangxi Provincial Health and Wellness Commission No. 202410294
6 · The paper itself

Abstract

aimTo construct an evaluation index system for the core competence of nurses in sleep medicine specialties.

backgroundSpecialized nurses in sleep medicine must handle treatment, nursing, and management well, which requires nurses to have excellent competence in knowledge, skills, and ability. However, a competency evaluation system for sleep medicine nurses has not been established in China.

methodsWe used a literature review and an expert meeting to establish a draft indicator system. Subsequently, two rounds of correspondence were conducted with 27 experts from 5 provinces using the Delphi method to solicit their opinions on the core competency evaluation indicators for sleep medicine nurse specialists and to qualitatively evaluate the experts' scores. The consensus was defined in advance as a mean score of 4.0 or above, with at least 75% agreement among participants. In this way, the final indicator framework was determined.

resultsThe final evaluation indexes of the core competencies for sleep medicine Nurse Specialists included 6 first-level indexes (Practical ability, Theoretical Knowledge, Critical thinking, Communication and coordination, Nursing Management, and Professional Development), 16 s-level indexes, and 64 third-level indexes. The effective response rates of the two expert consultation rounds were 100%. The expert authority coefficients were 0.878 and 0.865 in the first and second rounds of consultation, respectively. In the second round of consultation, the first, second, and third indexes of Kendall's coefficient of concordance were 0.373, 0.351, and 0.286, respectively (P < 0.05).

conclusionThe core competence evaluation index system for sleep medicine nurses established in this study is scientific and reliable and can provide a theoretical reference for the training, assessment, and evaluation of sleep medicine nurses in the future. IMPLICATIONS FOR NURSING MANAGEMENT: The evaluation index system of sleep medicine nurses' core competence will provide an effective practical framework for nursing management to evaluate, train, and examine the core competence of sleep medicine nurses.

Indexed as

Core competenceDelphi studyEvaluation indexSleep medicineSpecialist nurse

Identifiers

PMID39334099
PMCPMC11438144

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LicenceCC BY-NC-ND
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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.