定量数据质量保证、分析和展示。

IF 2.6 4区医学 Q1 NURSING

Journal of Psychiatric and Mental Health Nursing Pub Date : 2024-12-19 DOI:10.1111/jpm.13143

Paul Slater, Felicity Hasson

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引用次数: 0

摘要

定量数据质量保证是用于确保整个研究过程中数据的准确性、一致性、可靠性和完整性的系统过程和程序。有效的质量保证有助于识别和纠正错误，减少偏差，并确保数据符合分析和报告所需的标准。本文概述了处理数据和报告发现时要考虑的关键问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Quantitative Data Quality Assurance, Analysis and Presentation.

Quantitative data quality assurance is the systematic process and procedures used to ensure the accuracy, consistency, reliability, and integrity of data throughout the research process. Effective quality assurance helps identify and correct errors, reduce biases, and ensure the data meets the standards needed for analysis and reporting. This paper provides an overview of key issues to consider when working with data and reporting findings.

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来源期刊

Journal of Psychiatric and Mental Health Nursing 医学-护理

CiteScore

4.70

自引率

3.70%

发文量

审稿时长

4-8 weeks

期刊介绍： The Journal of Psychiatric and Mental Health Nursing is an international journal which publishes research and scholarly papers that advance the development of policy, practice, research and education in all aspects of mental health nursing. We publish rigorously conducted research, literature reviews, essays and debates, and consumer practitioner narratives; all of which add new knowledge and advance practice globally. All papers must have clear implications for mental health nursing either solely or part of multidisciplinary practice. Papers are welcomed which draw on single or multiple research and academic disciplines. We give space to practitioner and consumer perspectives and ensure research published in the journal can be understood by a wide audience. We encourage critical debate and exchange of ideas and therefore welcome letters to the editor and essays and debates in mental health.