Evidence map›Paper›PMID 31601590›Full record

ArticleBMJ open2019

Psychometric properties of the Chinese version of the spiritual care competency scale in nursing practice: a methodological study.

Yanli Hu, René Van Leeuwen, Fan Li

Abstract read
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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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

13 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

3 authors.

Yanli HuSchool of Nursing, Jilin University, Changchun, China.
René Van LeeuwenHealth Care, Viaa Christian University of Applied Sciences, Zwolle, The Netherlands.
Fan LiSchool of Nursing, Jilin University, Changchun, China lifan@jlu.edu.cn.ORCID 0000-0002-1517-616X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the validity and reliability of the Spiritual Care Competency Scale (SCCS) among nurses in China.

designMethodological research.

methodsAfter the SCCS was translated into Chinese, the validity and reliability of the Chinese version of the SCCS (C-SCCS) were evaluated using a convenience sample of 800 nurses recruited from different healthcare centres. The construct validity of the C-SCCS was determined by an exploratory factor analysis (EFA) with promax rotation. Pearson's correlation coefficients of the C-SCCS and the Palliative Care Spiritual Care Competency Scale (PCSCCS-M) were computed to assess the concurrent validity and construct validity of the C-SCCS. To verify the quality of the component structure, we conducted a confirmatory factor analysis (CFA). We tested the internal consistency and stability of the measure using Cronbach's alpha coefficient and the Guttman split-half coefficient, respectively, and a factorial analysis was performed.

resultsA total of 709 participants completed the questionnaire (response rate: 88.63%), and all completed questionnaires were suitable for analysis. Three factors were abstracted from the EFA and explained 58.19% of the total variance. The Cronbach's alpha coefficients of the three subscales were .93, .92, and .89, and the Guttman split-half coefficient for the C-SCCS was .84. The CFA indicated a well-fitting model, and the significant correlations between the C-SCCS and the PCSCCS-M (r=0.67, p<0.01) showed adequate concurrent validity. Nurses' education and income level showed a significant association with the C-SCCS score.

conclusionThe C-SCCS was shown to be a psychometrically sound instrument for evaluating Chinese nurses' spiritual care competencies.

Indexed as

Clinical CompetenceSpiritualityAdolescentAdultChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedNursesNursing CarePsychometricsReproducibility of ResultsSurveys and QuestionnairesYoung Adultcompetencynursesspiritual carevalidity and reliability

Identifiers

PMID31601590
PMCPMC6797272

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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.