Staley Kristina
TwoCan Associates, Wallace House, 45 Portland Road, Hove, BN3 5DQ UK.
Res Involv Engagem. 2015 Jul 31;1:6. doi: 10.1186/s40900-015-0008-5. eCollection 2015.
Much of the current debate around the impact of patient/public involvement on research focuses on the lack of empirical data. While a number of systematic literature reviews have reported the various ways in which involvement makes a difference to research and the people involved, this evidence has been criticised as being weak and anecdotal. It is argued that robust evidence is still required. This review reflects on the use of quantitative approaches to evaluating impact. It concludes that the statistical evidence is weakened by not paying sufficient attention to the context in which involvement takes place and the way it is carried out. However, if scientific (systematic, quantitative, empirical) approaches are designed in a way to take these factors into account, they might not generate knowledge that is useful beyond the original context. Such approaches might not therefore enhance our understanding of when, why and how involvement makes a difference. In the context of individual research projects where researchers collaborate with patients/the public, researchers often acquire 'new' knowledge about life with a health condition. This new understanding can be described as experiential knowledge-'knowledge in context'-that researchers gain through direct experience of working with patients/the public. On this basis, researchers' accounts of their experience potentially provide a source of insight and learning to influence others, in the same way that the patient experience helps to shape research. These accounts could be improved by increasing the detail provided about context and mechanism. One of the most important contextual factors that influence the outcome of involvement is the researchers themselves and the skills, assumptions, values and priorities they start with. At the beginning of any research project, the researchers 'don't know what they don't know' until they involve patients/the public. This means that the impact of involvement is somewhat unpredictable. The answer to the question 'Is involvement worth doing?' will always be 'It depends'. Further exploration of the contextual and mechanistic factors which influence outcomes could give a stronger steer to researchers but may never accurately predict any specific impact.
In recent years, there has been considerable interest in finding out what difference patient and public involvement makes to research projects. The evidence published so far has been criticised for being weak and anecdotal. Some people argue we need robust evidence of impact from scientific studies of involvement. In this review, I consider examples of where impact has been measured using statistical methods. I conclude that the statistical evidence is weak, if the studies do not consider the context in which involvement takes place and the way that it is done. Studies designed to take this into account give us more confidence that the involvement did make a difference . They do not tell us whether the same impact will occur in the same way in other projects and therefore have limited value. Researchers gain an understanding of involvement through their direct experience of working with patients and the public. This is 'knowledge in context' or 'insight' gained in the same way that patients gain expertise through their direct experience of a health condition. This means that detailed accounts of involvement from researchers already provide valuable learning to others, in the same way that patients' insights help shape research. However, the impact of involvement will always be somewhat unpredictable, because at the start of any project researchers 'don't know what they don't know'-they do not know precisely what problems they might anticipate, until the patients/public tell them.
当前关于患者/公众参与对研究的影响的许多争论都集中在缺乏实证数据上。虽然一些系统的文献综述报告了参与对研究及相关人员产生影响的各种方式,但这些证据被批评为薄弱且多为轶事性的。有人认为仍需要有力的证据。本综述反思了使用定量方法评估影响的情况。结论是,由于没有充分关注参与发生的背景及其实施方式,统计证据的说服力被削弱。然而,如果科学(系统、定量、实证)方法的设计能考虑到这些因素,它们可能无法产生超出原始背景仍有用的知识。因此,此类方法可能无法增进我们对参与何时、为何以及如何产生影响的理解。在研究人员与患者/公众合作的单个研究项目中,研究人员常常会获得有关健康状况下生活的“新”知识。这种新的理解可被描述为经验性知识——“情境中的知识”——研究人员通过与患者/公众直接合作的经验而获得。在此基础上,研究人员对自身经历的描述有可能为他人提供见解和学习的来源,就如同患者经历有助于塑造研究一样。通过增加所提供的关于背景和机制的细节,这些描述可以得到改进。影响参与结果的最重要背景因素之一是研究人员自身以及他们初始所具备的技能、假设、价值观和优先事项。在任何研究项目开始时,研究人员“不知道自己不知道什么”,直到他们让患者/公众参与进来。这意味着参与的影响在一定程度上是不可预测的。“参与是否值得做?”这个问题的答案永远是“视情况而定”。对影响结果的背景和机制因素进行进一步探索,可能会给研究人员提供更强有力的指导,但可能永远无法准确预测任何具体影响。
近年来,人们对弄清楚患者和公众参与对研究项目有何影响产生了浓厚兴趣。迄今为止发表的证据因薄弱且多为轶事性而受到批评。一些人认为我们需要来自参与的科学研究的有力影响证据。在本综述中,我考虑了使用统计方法衡量影响的例子。我得出结论,如果研究没有考虑参与发生的背景及其实施方式,统计证据就很薄弱。旨在考虑这一点的研究让我们更有信心认为参与确实产生了影响。但它们没有告诉我们同样的影响在其他项目中是否会以同样方式出现,因此价值有限。研究人员通过与患者和公众直接合作的经验来理解参与。这是“情境中的知识”或“见解”,就如同患者通过对健康状况的直接体验获得专业知识一样。这意味着研究人员对参与的详细描述已经为他人提供了有价值的学习内容,就如同患者的见解有助于塑造研究一样。然而,参与的影响在一定程度上总是不可预测的,因为在任何项目开始时,研究人员“不知道自己不知道什么”——他们直到患者/公众告诉他们,才确切知道可能会遇到什么问题。