当前位置: X-MOL 学术BMC Nurs. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Bibliometric mapping of intensive care nurses’ wellbeing: development and application of the new iAnalysis model
BMC Nursing ( IF 3.1 ) Pub Date : 2019-06-03 , DOI: 10.1186/s12912-019-0343-1
Rebecca J Jarden 1, 2 , Ajit Narayanan 3 , Margaret Sandham 2 , Richard J Siegert 4 , Jane Koziol-McLain 2
Affiliation  

Intensive care nurse wellbeing is essential to a healthy healthcare workforce. Enhanced wellbeing has widespread benefits for workers. Bibliometrics enables quantitative analysis of bourgeoning online data. Here, a new model is developed and applied to explore empirical knowledge underpinning wellbeing and intensive care nurse wellbeing in terms of size and impact, disciplinary reach, and semantics. Mixed methods bibliometric study. Firstly, a new model coined ‘iAnalysis’ was developed for the analysis of published data. Secondly, iAnalysis was applied in two studies to examine wellbeing and ICU nurse wellbeing. Study one explored data from a title search with search terms [wellbeing OR well-being], identifying 17,543 records with bibliographic data. This dataset included 20,526 keywords. Of the identified records, 10,715 full-text manuscripts were retrieved. Study two explored data from a topic search with search terms [(intensive OR critical) AND (nurs*) AND (wellbeing OR well-being)], identifying 383 records with bibliographic data. This dataset included 1223 author keywords. Of the identified records, 328 full-text manuscripts were retrieved. Once data were collected, for size and impact, WoS Clarivate Analytics™ and RStudio™ were used to explore publication dates, frequencies, and citation performance. For disciplinary reach, RStudio™ (with the Bibliometrics™ package & Vosviewer™ plugin) was used to explore the records in terms of country of publication, journal presence, and mapping of authors. For semantics, once the bibliographic data was imported to RStudio™ (with the Bibliometrics™ package & Vosviewer™ plugin) keyword co-occurrences were identified and visualised. Full-text manuscripts were imported to NVivo™ to explore word frequencies of both the keywords and full-text manuscripts using the word frequency search. For both studies, records were predominantly published in the past 5 years, in English language, and from USA. The highest keyword co-occurrence for study one was “health and well-being”, and for study two, “family and model”. Terms commonly associated with ‘illbeing’, as opposed to ‘wellbeing’, were highly prevalent in both study datasets, but more so in intensive care nurse wellbeing data. Intensive care nurse wellbeing was virtually absent in this literature. The iAnalysis model provided a practice-friendly tool to explore a large source of online published literature.

中文翻译:

重症监护护士幸福感的文献计量映射:新 iAnalysis 模型的开发和应用

重症监护护士的福祉对于健康的医疗保健队伍至关重要。增强的幸福感为工人带来了广泛的好处。文献计量学可以对蓬勃发展的在线数据进行定量分析。在这里,开发并应用了一个新模型,以探索在规模和影响、学科范围和语义方面支持福祉和重症监护护士福祉的经验知识。混合方法文献计量研究。首先,开发了一种名为“iAnalysis”的新模型,用于分析已发布的数据。其次,iAnalysis 被应用于两项研究,以检查幸福感和 ICU 护士的幸福感。一项研究使用搜索词 [wellbeing OR wellbeing] 探索了来自标题搜索的数据,确定了 17,543 条带有书目数据的记录。该数据集包括 20,526 个关键字。在已识别的记录中,有 10 个,检索到全文稿件715篇。使用搜索词[(密集或关键)AND(护士*)AND(幸福或幸福)]研究来自主题搜索的两个探索数据,用书目数据识别 383 条记录。该数据集包括 1223 个作者关键词。在确定的记录中,检索到 328 篇全文手稿。一旦收集到数据,就规模和影响而言,WoS Clarivate Analytics™ 和 RStudio™ 被用于探索出版日期、频率和引用性能。对于学科范围,RStudio™(带有 Bibliometrics™ 包和 Vosviewer™ 插件)用于根据出版国家、期刊存在和作者映射来探索记录。对于语义,一旦将书目数据导入 RStudio™(使用 Bibliometrics™ 包和 Vosviewer™ 插件)关键字共现被识别和可视化。将全文手稿导入 NVivo™ 以使用词频搜索来探索关键字和全文手稿的词频。这两项研究的记录主要在过去 5 年以英语和美国出版。研究一的关键词共现率最高的是“健康和幸福”,研究二的关键词共现率最高的是“家庭和模特”。通常与“不适”相关的术语,而不是“幸福”,在两个研究数据集中都非常普遍,但在重症监护护士幸福数据中更是如此。该文献中几乎没有重症监护护士的幸福感。iAnalysis 模型提供了一种便于实践的工具来探索大量在线出版文献。将全文手稿导入 NVivo™ 以使用词频搜索来探索关键字和全文手稿的词频。这两项研究的记录主要在过去 5 年以英语和美国出版。研究一的关键词共现率最高的是“健康和幸福”,研究二的关键词共现率最高的是“家庭和模特”。通常与“不适”相关的术语,而不是“幸福”,在两个研究数据集中都非常普遍,但在重症监护护士幸福数据中更是如此。该文献中几乎没有重症监护护士的幸福感。iAnalysis 模型提供了一种便于实践的工具来探索大量在线出版文献。将全文手稿导入 NVivo™ 以使用词频搜索来探索关键字和全文手稿的词频。这两项研究的记录主要在过去 5 年以英语和美国出版。研究一的关键词共现率最高的是“健康和幸福”,研究二的关键词共现率最高的是“家庭和模特”。通常与“不适”相关的术语,而不是“幸福”,在两个研究数据集中都非常普遍,但在重症监护护士幸福数据中更是如此。该文献中几乎没有重症监护护士的幸福感。iAnalysis 模型提供了一种便于实践的工具来探索大量在线出版文献。这两项研究的记录主要在过去 5 年以英语和美国出版。研究一的关键词共现率最高的是“健康和幸福”,研究二的关键词共现率最高的是“家庭和模特”。通常与“不适”相关的术语,而不是“幸福”,在两个研究数据集中都非常普遍,但在重症监护护士幸福数据中更是如此。该文献中几乎没有重症监护护士的幸福感。iAnalysis 模型提供了一种便于实践的工具来探索大量在线出版文献。这两项研究的记录主要在过去 5 年以英语和美国出版。研究一的关键词共现率最高的是“健康和幸福”,研究二的关键词共现率最高的是“家庭和模特”。通常与“不适”相关的术语,而不是“幸福”,在两个研究数据集中都非常普遍,但在重症监护护士幸福数据中更是如此。该文献中几乎没有重症监护护士的幸福感。iAnalysis 模型提供了一种便于实践的工具来探索大量在线出版文献。与“健康”相反,在两个研究数据集中都非常普遍,但在重症监护护士健康数据中更为普遍。该文献中几乎没有重症监护护士的幸福感。iAnalysis 模型提供了一种便于实践的工具来探索大量在线出版文献。与“健康”相反,在两个研究数据集中都非常普遍,但在重症监护护士健康数据中更为普遍。该文献中几乎没有重症监护护士的幸福感。iAnalysis 模型提供了一种便于实践的工具来探索大量在线出版文献。
更新日期:2019-06-03
down
wechat
bug