Brandl Lena, Cabrita Miriam, Brodbeck Jeannette, Heylen Dirk, van Velsen Lex
Roessingh Research and Development, P.O. Box 1212, Enschede, the Netherlands.
University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Human Media Interaction, P.O. Box 217, 7500AE Enschede, the Netherlands.
Internet Interv. 2022 Apr 5;28:100534. doi: 10.1016/j.invent.2022.100534. eCollection 2022 Apr.
While much effort has been devoted to the development of mental e-health interventions, the tailoring of these applications to user characteristics and needs is a comparatively novel field of research. The premise of personalizing mental e-health interventions is that personalization increases user motivation and (thereby) mitigates intervention dropout and enhances clinical effectiveness. In this study, we selected user profile parameters for personalizing a mental e-health intervention for older adults who lost their spouse. We conducted a three-round Delphi study involving an international and interdisciplinary expert panel ( = 16) with two objectives. The first aim was to elicit adaptation strategies that can be used to dynamically readjust the intervention to the user's needs. The second aim was to identify a set of meaningful indicators for monitoring the user from within the grief intervention to escalate from self-help to blended care, whenever advisable. This Delphi study used as starting point an evaluated, text-based grief intervention composed of ten modules, including psychoeducation about grief and cognitive-behavioral exercises to support the user in adjusting their lives after bereavement. Every user follows this grief intervention in a linear fashion from beginning to end. The resulting conceptual adaptation model encompasses adjustments, as well as one-time adjustments performed at the of the service. On the level of the application structure, the adaptations affect topic module is presented to the user. The adaptations further provide strategies for adjusting the text-based content of individual intervention modules dependent on user characteristics and for selecting appropriate reactions to user input. Eighteen monitoring parameters were elicited and grouped into four categories: , , , and . Parameters that were perceived as most urgent to attend to for escalation were , , , and .
虽然在精神电子健康干预措施的开发方面投入了大量精力，但将这些应用程序根据用户特征和需求进行定制是一个相对较新的研究领域。个性化精神电子健康干预措施的前提是，个性化能够提高用户的积极性，从而减少干预措施的退出率，并提高临床效果。在本研究中，我们选择了用户概况参数，以便为失去配偶的老年人定制精神电子健康干预措施。我们开展了三轮德尔菲研究，涉及一个由16名成员组成的国际跨学科专家小组，有两个目标。第一个目标是找出可用于根据用户需求动态重新调整干预措施的适应策略。第二个目标是确定一套有意义的指标，以便在悲伤干预过程中对用户进行监测，以便在必要时从自助升级为混合护理。这项德尔菲研究以一个经过评估的、基于文本的悲伤干预措施为起点，该措施由十个模块组成，包括关于悲伤的心理教育以及认知行为练习，以帮助用户在丧亲后调整生活。每个用户从头到尾以线性方式遵循这种悲伤干预措施。由此产生的概念性适应模型包括在服务过程中进行的调整以及一次性调整。在应用结构层面，这些调整会影响向用户呈现的主题模块。这些调整还提供了根据用户特征调整各个干预模块基于文本的内容以及选择对用户输入的适当反应的策略。共引出了18个监测参数，并分为四类：[此处原文缺失具体类别内容]、[此处原文缺失具体类别内容]、[此处原文缺失具体类别内容]和[此处原文缺失具体类别内容]。被认为在升级时最需要关注的参数是[此处原文缺失具体参数内容]、[此处原文缺失具体参数内容]、[此处原文缺失具体参数内容]、[此处原文缺失具体参数内容]和[此处原文缺失具体参数内容]。
