Martínez-Vispo Carmela, García-Huércano Cristina, Conejo-Cerón Sonia, Rodríguez-Morejón Alberto, Moreno-Peral Patricia
Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela (USC), Santiago de Compostela, Spain.
Institute of Research in Psychology (IPsiUS), University of Santiago de Compostela(USC), Santiago de Compostela, Spain.
Digit Health. 2024 Oct 25;10:20552076241292418. doi: 10.1177/20552076241292418. eCollection 2024 Jan-Dec.
To describe the design and development of prevANS, a personalized online intervention for the universal prevention of anxiety disorders based on a predictive risk algorithm. A user-centered approach was followed, considering the feedback of potential users and mental health professionals.
The study had three phases: (a) designing the intervention based on existing scientific literature; (b) piloting and evaluating the beta version involving potential users and health professionals; and (c) refining the intervention based on participants' suggestions. This iterative process aimed to refine the prevANS intervention before testing in a randomized controlled trial.
The prevANS intervention provides personalized anxiety risk reports and components tailored to individuals' needs. Participants at low risk receive psychoeducation had access to a set of tools enhance protective factors. Moderate/high-risk individuals also receive cognitive-behavioral training. Both groups have access to a reward system and forum. Results from the design evaluation indicate that the prevANS interface is attractive and user-friendly and the psychoeducational materials helpful and engaging. The cognitive-behavioral training module received positive feedback. Participants suggested changes related to usability, content clarity, attractiveness, and engagement, which were implemented afterwards.
This article describes the development of a personalized intervention for preventing anxiety disorders using a validated risk prediction algorithm. The prevANS intervention was designed based on current scientific literature by a team of experts employing a user-centered approach. Research on the effectiveness of information and communication technologies in mental health prevention interventions considering user needs and preferences is warranted.
描述prevANS的设计与开发，这是一种基于预测风险算法的用于广泛性焦虑症预防的个性化在线干预措施。遵循以用户为中心的方法，考虑了潜在用户和心理健康专业人员的反馈。
该研究有三个阶段：(a) 基于现有科学文献设计干预措施；(b) 对涉及潜在用户和健康专业人员的测试版进行试点和评估；(c) 根据参与者的建议完善干预措施。这个迭代过程旨在在随机对照试验测试之前完善prevANS干预措施。
prevANS干预提供个性化的焦虑风险报告以及根据个人需求量身定制的组件。低风险参与者接受心理教育，可使用一套工具来增强保护因素。中度/高风险个体还接受认知行为训练。两组都可使用奖励系统和论坛。设计评估结果表明，prevANS界面具有吸引力且用户友好，心理教育材料有用且引人入胜。认知行为训练模块得到了积极反馈。参与者提出了与可用性、内容清晰度、吸引力和参与度相关的改进建议，随后均得以实施。
本文描述了一种使用经过验证的风险预测算法来预防焦虑症的个性化干预措施的开发。prevANS干预措施是由一组专家基于当前科学文献并采用以用户为中心的方法设计的。有必要对考虑用户需求和偏好的信息通信技术在心理健康预防干预中的有效性进行研究。
