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Abstract
Lack of knowledge about palliative care is one of the most common reasons for hindering the delivery of high-quality palliative care. Nurses play a major role in providing palliative care, and the degree of their mastery of this knowledge is crucial to whether they can effectively deliver the ideal palliative care. Therefore, it is necessary to understand the level of palliative care knowledge in this population. As of 8 November 8, 2022, we performed systematic searches in 10 databases. Meta-analysis of quantitative data that measuring the level of palliative care knowledge of nurses using the Palliative Care Quiz for Nursing (PCQN) was conducted using Stata software (version: V.15). A pooled mean score <10 indicated a low/insufficient knowledge level. The funnel plot and Egger’s regression test were used to detect publication bias, and finally, the robustness of the results was evaluated through sensitivity analysis. The pooled mean score for the level of nurses’ knowledge of palliative care was 9.68 (95% CI: 9.40 to 9.96). Among the three dimensions of the PCQN scale, the pooled mean score for the ‘“Philosophy and Principles of Palliative Care’” section was 1.73 (95% CI: 1.38 to 2.08); the ‘“Pain and Other Symptom Control’” section was 6.73 (95% CI: 6.41 to 7.05); and the ‘“Psychological, Spiritual and Social Care’” section was 1.21 (95% CI: 0.72 to 1.69). It can be seen that nurses’ mastery of palliative care knowledge is not sufficient. It is recommended that relevant departments formulate and promote the implementation of targeted measures to improve the knowledge level of this population.
- Supportive care
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
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Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
Footnotes
Contributors LiL: conceptualisation, data curation, formal analysis, investigation, methodology, project administration, software, validation, visualisation, writing—original draft, writing—review and editing, guarantor . FW: conceptualisation, data curation, formal analysis, methodology, project administration, supervision, validation, writing—review and editing. XS: data curation, investigation, methodology, writing—original draft. QL: methodology, software, visualisation. LuL: formal analysis, investigation, validation.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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