Slade Mike, Rennick-Egglestone Stefan, Llewellyn-Beardsley Joy, Yeo Caroline, Roe James, Bailey Sylvia, Smith Roger Andrew, Booth Susie, Harrison Julian, Bhogal Adaresh, Penas Morán Patricia, Hui Ada, Quadri Dania, Robinson Clare, Smuk Melanie, Farkas Marianne, Davidson Larry, van der Krieke Lian, Slade Emily, Bond Carmel, Nicholson Joe, Grundy Andrew, Charles Ashleigh, Hare-Duke Laurie, Pollock Kristian, Ng Fiona
School of Health Sciences, Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom.
National Institute for Health Research, ARC East Midlands, University of Nottingham, Nottingham, United Kingdom.
JMIR Form Res. 2021 May 27;5(5):e24417. doi: 10.2196/24417.
The internet enables sharing of narratives about health concerns on a substantial scale, and some digital health narratives have been integrated into digital health interventions. Narratives describing recovery from health problems are a focus of research, including those presented in recorded (eg, invariant) form. No clinical trial has been conducted on a web-based intervention providing access to a collection of Recorded Recovery Narratives (RRNs).
This study presents knowledge produced through the development of the Narrative Experiences Online (NEON) Intervention, a web-based intervention incorporating the algorithmic recommendation of RRNs.
Knowledge was gathered through knowledge integration (KI) activities. KI1 synthesized previous studies to produce the NEON Impact Model describing how accessing RRNs produces health-related outcomes. KI2 developed curation principles for the NEON Collection of RRNs through consultation with the NEON Lived Experience Advisory Panel and the curation of a preliminary collection. KI3 identified harm minimization strategies for the NEON Intervention through consultation with the NEON International Advisory Board and Lived Experience Advisory Panel. The NEON Intervention was finalized through 2 research studies (RS). In RS1, mental health service users (N=40) rated the immediate impact of randomly presented narratives to validate narrative feedback questions used to inform the recommendation algorithm. In RS2, mental health service users (n=25) were interviewed about their immediate response to a prototype of the NEON Intervention and trial procedures and then were interviewed again after 1 month of use. The usability and acceptability of the prototype and trial procedures were evaluated and refinements were made.
KI1 produced the NEON Impact Model, which identifies moderators (recipient and context), mechanisms of connection (reflection, comparison, learning, and empathy), processes (identification of change from narrative structure or content and internalization of observed change), and outcomes (helpful and unhelpful). KI2 identified 22 curation principles, including a mission to build a large, heterogeneous collection to maximize opportunities for connection. KI3 identified seven harm minimization strategies, including content warnings, proactive and reactive blocking of narratives, and providing resources for the self-management of emotional distress. RS1 found variation in the impact of narratives on different participants, indicating that participant-level feedback on individual narratives is needed to inform a recommender system. The order of presentation did not predict narrative feedback. RS2 identified amendments to web-based trial procedures and the NEON Intervention. Participants accessed some narratives multiple times, use reduced over the 4-week period, and narrative feedback was provided for 31.8% (105/330) of narrative accesses.
RRNs can be integrated into web-based interventions. Evaluating the NEON Intervention in a clinical trial is feasible. The mixed methods design for developing the NEON Intervention can guide its extension to other clinical populations, the design of other web-based mental health interventions, and the development of narrative-based interventions in mental health.
互联网使得人们能够大规模分享有关健康问题的叙述,并且一些数字健康叙述已被纳入数字健康干预措施。描述从健康问题中康复的叙述是研究的重点,包括那些以记录(如固定不变)形式呈现的叙述。尚未对提供访问记录康复叙述(RRN)集合的基于网络的干预措施进行临床试验。
本研究展示了通过开发在线叙事体验(NEON)干预措施所产生的知识,这是一种基于网络的干预措施,纳入了RRN的算法推荐。
通过知识整合(KI)活动收集知识。KI1综合先前的研究成果,生成NEON影响模型,描述访问RRN如何产生与健康相关的结果。KI2通过与NEON生活体验咨询小组协商以及对初步集合的策划,为NEON RRN集合制定策划原则。KI3通过与NEON国际咨询委员会和生活体验咨询小组协商,确定NEON干预措施的危害最小化策略。NEON干预措施通过两项研究(RS)最终确定。在RS1中,心理健康服务使用者(N = 40)对随机呈现的叙述的即时影响进行评分,以验证用于为推荐算法提供信息的叙述反馈问题。在RS2中,对心理健康服务使用者(n = 25)进行访谈,了解他们对NEON干预措施原型和试验程序的即时反应,然后在使用1个月后再次进行访谈。对原型和试验程序的可用性和可接受性进行评估并进行改进。
KI1生成了NEON影响模型,该模型确定了调节因素(接受者和背景)、连接机制(反思、比较、学习和同理心)、过程(从叙述结构或内容中识别变化以及观察到的变化的内化)和结果(有益和无益)。KI2确定了22条策划原则,包括建立一个大型、多样化集合以最大化连接机会的使命。KI3确定了七种危害最小化策略,包括内容警告、对叙述的主动和被动屏蔽,以及为情绪困扰的自我管理提供资源。RS1发现叙述对不同参与者的影响存在差异,表明需要参与者对单个叙述的反馈来为推荐系统提供信息。呈现顺序并不能预测叙述反馈。RS2确定了对基于网络的试验程序和NEON干预措施的修正。参与者多次访问一些叙述,在4周期间使用量减少,并且对31.8%(105/330)的叙述访问提供了叙述反馈。
RRN可以整合到基于网络的干预措施中。在临床试验中评估NEON干预措施是可行的。开发NEON干预措施的混合方法设计可以指导其扩展到其他临床人群、其他基于网络的心理健康干预措施的设计以及心理健康中基于叙述的干预措施的开发。