Iyngkaran Pupalan, Usmani Wania, Bahmani Zahra, Hanna Fahad
Department of Health and Education, Torrens University Australia, Melbourne, VIC 3000, Australia.
HeartWest, Hoppers Crossing, VIC 3029, Australia.
J Cardiovasc Dev Dis. 2024 Mar 24;11(4):96. doi: 10.3390/jcdd11040096.
Mixed methods research forms the backbone of translational research methodologies. Qualitative research and subjective data lead to hypothesis generation and ideas that are then proven via quantitative methodologies and gathering objective data. In this vein, clinical trials that generate subjective data may have limitations, when they are not followed through with quantitative data, in terms of their ability to be considered gold standard evidence and inform guidelines and clinical management. However, since many research methods utilise qualitative tools, an initial factor is that such tools can create a burden on patients and researchers. In addition, the quantity of data and its storage contributes to noise and quality issues for its primary and post hoc use. This paper discusses the issue of the burden of subjective data collected and fatigue in the context of congestive heart failure (CHF) research. The CHF population has a high baseline morbidity, so no doubt the focus should be on the content; however, the lengths of the instruments are a product of their vigorous validation processes. Nonetheless, as an important source of hypothesis generation, if a choice of follow-up qualitative assessment is required for a clinical trial, shorter versions of the questionnaire should be used, without compromising the data collection requirements; otherwise, we need to invest in this area and find suitable solutions.
混合方法研究构成了转化研究方法的核心。定性研究和主观数据有助于生成假设和观点,随后通过定量方法和收集客观数据来加以验证。就此而言,产生主观数据的临床试验若不继以定量数据,在被视为金标准证据以及为指南和临床管理提供信息方面可能存在局限性。然而,由于许多研究方法都使用定性工具,一个首要因素是此类工具可能给患者和研究人员带来负担。此外,数据的数量及其存储会给其初次使用和事后使用带来噪声和质量问题。本文探讨了在充血性心力衰竭(CHF)研究背景下收集主观数据的负担和疲劳问题。CHF人群的基线发病率很高,所以毫无疑问重点应放在内容上;然而,这些工具的篇幅是其严格验证过程的结果。尽管如此,作为假设生成的重要来源,如果临床试验需要选择后续的定性评估,应使用问卷的简短版本,同时不影响数据收集要求;否则,我们需要在这一领域投入并找到合适的解决方案。