Evidence map›Paper›PMID 39698133›Full record

ReviewInternational journal of nursing sciences2024

Nurses' job embeddedness and turnover intention: A systematic review and meta-analysis.

Xin Wang, Ming Liu, Angela Y M Leung, Xiaoyan Jin, Hongxia Dai, Shaomei Shang

Abstract readReview
In one paragraph

Review in International journal of nursing sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 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

6 authors.

Xin WangFaculty of Health Sciences and Sports, Macao Polytechnic University, Macao SAR, China.
Ming LiuPeking University Health Science Center - Macao Polytechnic University Nursing Academy, Macao Polytechnic University, Macao SAR, China.
Angela Y M LeungSchool of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Xiaoyan JinPeking University Health Science Center - Macao Polytechnic University Nursing Academy, Macao Polytechnic University, Macao SAR, China.
Hongxia DaiPeking University Health Science Center - Macao Polytechnic University Nursing Academy, Macao Polytechnic University, Macao SAR, China.
Shaomei ShangSchool of Nursing, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to review the relationship between job embeddedness and turnover intentions among nurses and explore the effects of the Job Embeddedness Scale, number of years in the career, education, and marital status on this relationship. Methods: The review was conducted by searching the China Knowledge Resource Integrated Database (CNKI), Weipu Database (CQVIP), China Biology Medicine (CBM), Wanfang Database, PubMed, Web of Science, Embase, CINAHL, and APA-PsycNet for articles on nurses' job embeddedness and turnover from intention up to March 2024. The research quality was evaluated using the Agency for Healthcare Research and Quality (AHRQ) assessment criteria. The review protocol has been registered on PROSPERO [CRD42023483947]. Results: The results of this review included 47 studies consisting of 15,742 nurses from seven countries worldwide. A moderate negative correlation was found between job embeddedness and turnover intention ( Conclusion: This systematic review and meta-analysis analyzed the relationships between nurses' job embeddedness, dimensions, and turnover intention. Meanwhile, subgroup analysis and meta-regression explored the factors influencing these relationships. It is an important reference for nurse managers to promote nurse retention.

Indexed as

Job embeddednessMeta-analysisNursesTurnover intention

Identifiers

PMID39698133
PMCPMC11650684

What OpenQuestion holds

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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.