Evidence map›Paper›PMID 39075426›Full record

ArticleBMC nursing2024

Professional competencies in geriatric nursing for geriatric nurses: a latent profile analysis.

Mengxue Wang, Dongdong Li, Jingjing Li, Xiumei Zhang

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.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
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

4 authors.

Mengxue WangNursing Department, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230000, China.
Dongdong LiNursing Department, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230000, China.
Jingjing LiDepartment of Nursing, The First Affiliated Hospital of Anhui Medical University, 210 Jixi Road, Hefei, Anhui, 230000, China. 724234288@qq.com.
Xiumei ZhangDepartment of Nursing, The First Affiliated Hospital of Anhui Medical University, 210 Jixi Road, Hefei, Anhui, 230000, China. zhangxiumei@ahmu.edu.cn.

Funding

Anhui Medical University hlqml2023042Chinese Nursing Association Research Project ZHKY202211
6 · The paper itself

Abstract

backgroundAs the global population continues to age, social realities such as advanced age, disability and living alone are coming to the fore, and the demand for medical care and health services for the elderly is increasing dramatically, especially in geriatrics. Given the important role geriatric nurses play in the diagnosis and treatment of diseases and rehabilitation of elderly patients, and due to the uniqueness and complexity of geriatric work, this requires geriatric nurses not only to have the competencies that are available in general nursing, but also to ensure that they have sufficient geriatric core competencies in order to effectively meet the needs of the patients and accelerate their recovery. Although previous studies have investigated the core competencies of nursing staff, there has been little research on geriatric nurses' core geriatric nursing competencies and their predictors. The aim of this study was to investigate the current status of the geriatric nursing competency inventory (GNCI) among geriatric nurses using latent profiling, to identify potential subgroups and their population characteristics, and to explore the factors that influence the potential subgroups.

methodsFrom January to March 2024, 1,313 geriatric nurses in Hefei City were selected by stratified cluster sampling method and surveyed with general information questionnaire, geriatric nursing competency inventory, and occupational coping self-efficacy scale for nurses(OCSE-N). Potential subgroups of GNCI differences among geriatric nurses were identified by latent profile analysis (LPA). Multiple logistic regression analyses were used to explore the factors influencing the GNCI of geriatric nurses with different latent profiles.

resultsGeriatric nurses' OCSE-N was positively correlated with GNCI, and the GNCI score was 123.06(41.60), which indicated that geriatric nurses' GNCI was at an intermediate level. The OCSE-N score was 35.44(7.34), which was at a relatively high level. There was heterogeneity in the GNCI of geriatric nurses, which was classified into three subgroups i.e., Low-competency group, Medium-competency group, High-competency group. The results of multiple logistic regression analyses showed that OCSE-N, title, whether or not they attended geriatric nurse specialist training, and specialist nurse status were predictors of GNCI among geriatric nurses (P < 0.05).

conclusionThe GNCI categorical characteristics of geriatric nurses are obvious, and nursing managers should adopt targeted interventions according to the characteristics of nurses in different profiles to improve the overall quality of care.

Indexed as

Clinical nursesCompetencyGeriatric nursingLatent profile analysis

Identifiers

PMID39075426
PMCPMC11288073

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.