Lawrence S, Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada.
Implement Sci. 2010 Nov 20;5:90. doi: 10.1186/1748-5908-5-90.
Appreciative inquiry (AI) is an innovative knowledge translation (KT) intervention that is compatible with the Promoting Action on Research in Health Services (PARiHS) framework. This study explored the innovative use of AI as a theoretically based KT intervention applied to a clinical issue in an inpatient pediatric care setting. The implementation of AI was explored in terms of its acceptability, fidelity, and feasibility as a KT intervention in pain management.
A mixed-methods case study design was used. The case was a surgical unit in a pediatric academic-affiliated hospital. The sample consisted of nurses in leadership positions and staff nurses interested in the study. Data on the AI intervention implementation were collected by digitally recording the AI sessions, maintaining logs, and conducting individual semistructured interviews. Data were analysed using qualitative and quantitative content analyses and descriptive statistics. Findings were triangulated in the discussion.
Three nurse leaders and nine staff members participated in the study. Participants were generally satisfied with the intervention, which consisted of four 3-hour, interactive AI sessions delivered over two weeks to promote change based on positive examples of pain management in the unit and staff implementation of an action plan. The AI sessions were delivered with high fidelity and 11 of 12 participants attended all four sessions, where they developed an action plan to enhance evidence-based pain assessment documentation. Participants labeled AI a 'refreshing approach to change' because it was positive, democratic, and built on existing practices. Several barriers affected their implementation of the action plan, including a context of change overload, logistics, busyness, and a lack of organised follow-up.
Results of this case study supported the acceptability, fidelity, and feasibility of AI as a KT intervention in pain management. The AI intervention requires minor refinements (e.g., incorporating continued follow-up meetings) to enhance its clinical utility and sustainability. The implementation process and effectiveness of the modified AI intervention require evaluation in a larger multisite study.
欣赏式探询（Appreciative Inquiry，AI）是一种创新的知识转化（Knowledge Translation，KT）干预措施，与促进卫生服务研究行动（Promoting Action on Research in Health Services，PARiHS）框架相兼容。本研究探讨了将 AI 作为一种基于理论的 KT 干预措施应用于住院儿科护理环境中的临床问题的创新用法。该研究从接受度、保真度和可行性方面探讨了 AI 在疼痛管理中的 KT 干预措施的应用。
采用混合方法案例研究设计。案例为一家儿童医院的外科病房。样本由具有领导职位的护士和对研究感兴趣的工作人员护士组成。通过数字记录 AI 会议、维护日志和进行个人半结构化访谈来收集有关 AI 干预实施的数据。使用定性和定量内容分析以及描述性统计来分析数据。在讨论中对发现进行了三角验证。
三名护士领导和九名工作人员参与了研究。参与者对干预措施总体感到满意，该干预措施包括在两周内进行四次为期 3 小时的互动式 AI 会议，以促进基于该单位在疼痛管理方面的积极范例和工作人员实施行动计划的变革。AI 会议的实施保真度很高，12 名参与者中有 11 名参加了全部四次会议，在会议中他们制定了增强基于证据的疼痛评估文件记录的行动计划。参与者将 AI 标记为“变革的令人耳目一新的方法”，因为它是积极的、民主的，并且建立在现有实践基础上。一些障碍影响了他们行动计划的实施，包括变革过载、后勤、忙碌和缺乏有组织的后续行动等。
本案例研究结果支持 AI 作为疼痛管理 KT 干预措施的接受度、保真度和可行性。AI 干预措施需要进行细微调整（例如，纳入持续的跟进会议），以提高其临床实用性和可持续性。在更大的多地点研究中需要评估修改后的 AI 干预措施的实施过程和效果。
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