Evidence map›Paper›PMID 40201532›Full record

ArticleAsia-Pacific journal of oncology nursing2025

An ideal portrait of the professional competence of clinical research nurses: A qualitative study.

Heng Yang, Yipei Chen, Xin Peng

Abstract read
In one paragraph

Article in Asia-Pacific journal of oncology nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Canadian oncology nursing journal = Revue canadienne de nursing oncologique · 2026
    Article
  3. Scoping review of oncology clinical trials nursing: Roles, competencies, and evolving practice in cancer research.Canadian oncology nursing journal = Revue canadienne de nursing oncologique · 2026
    Article
  4. 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

3 authors.

Heng YangNursing Department, Union Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Yipei ChenNursing Department, Union Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Xin PengNursing Department, Union Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to identify and define the ideal professional competencies of Clinical Research Nurses (CRNs) in China, focusing on the essential knowledge, skills, and personal attributes required for effective practice in clinical trials. Methods: Interviews were conducted with CRNs, Nurse Managers (NMs), Principal Investigators (PIs), Sub-Investigators (SIs), Clinical Research Coordinators (CRCs), Clinical Research Associates (CRAs), and subjects. Thematic analysis was performed using Colaizzi's seven-step method to analyze interview data and identify key competencies. Results: The study identified four primary themes that characterize the ideal CRN profile: (1) theoretical knowledge ability, (2) practical technical ability, (3) professional quality and ability, and (4) personal traits. A total of 21 specific indicators were delineated, reflecting the diverse expectations of various stakeholders in clinical trials. Conclusions: The findings highlight the multifaceted nature of CRN competencies, emphasizing the importance of comprehensive training programs tailored to the needs of CRNs. This study provides a foundational framework for enhancing CRN training and professional development in China.

Indexed as

Clinical trialNursesProfessional competenceQualitative research

Identifiers

PMID40201532
PMCPMC11976228

What OpenQuestion holds

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LicenceCC BY
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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.