Effectiveness of an Online Personalized Intervention Based on a Risk Algorithm for the Universal Prevention of Anxiety: Randomized Controlled Trial. The prevANS Study.
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 2,000
- 试验地点
- 2
- 主要终点
- Primary Outcome Measure
研究概览
简要总结
Objective: To design, develop and evaluate an online personalized intervention based on a risk algorithm for the universal prevention of anxiety disorders in the general population.
Methods: Randomized controlled trial, with two parallel arms and 12 months follow-up. The entire process of recruitment, randomization, intervention and follow-up will be carried out from a web platform designed for the study (web prevANS). Through a communication campaign, where announcements and informative videos will be produced, and through the dissemination on prevANS website, 2,000 Spanish and Portuguese adult participants without anxiety in the baseline of the study will be recruited. The participants will be randomly assigned to the prevANS intervention, which will be self-guided and can be implemented from the prevANS web or from the participants' Smartphone (through an APP), or to a control group. The prevANS intervention will have different intensities depending on the risk level of the population, evaluated from the already validated risk algorithm for anxiety: predictA. Participants with a low risk of anxiety will receive information on their level and profile (risk factors) of anxiety and psychoeducational information periodically. Participants with moderate and high risk of anxiety will also receive information on their risk level and profile, but will also include a cognitive-behavioral training (problem solving, decision-making, handling thoughts / concerns and emotions and communicational skills). Both groups of risk will work towards manage stressors and enhance protective factors. The control group will not receive any intervention, but they will fill out the same questionnaires as in the intervention group. The main result will be the incidence of new cases of anxiety disorders measured by CIDI, and the secondary results will be the reduction of anxiety (GAD-7) and depression (PHQ-9) symptoms, of the risk probability of anxiety and depression (predictA and predictD algorithms) and improvement of quality of life measured by SF-12 and EuroQol, and cost-effectiveness and cost-utility.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Prevention
- 盲法
- Double (Investigator, Outcomes Assessor)
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •GAD-7 <10 at baseline
- •GAD-7 ≥10 at baseline and a negative diagnosis of anxiety disorders by CIDI
排除标准
- •Not have a smartphone and internet for personal use
- •Unable to speak Spanish
- •Documented terminal illness
- •Documented cognitive impairment
- •Documented serious mental illness (psychosis, bipolar, addictions, etc.)
- •Being involved in any psychological intervention or treatment
结局指标
主要结局
Primary Outcome Measure
时间窗: 12 months
Rate of anxiety disorders measured by the Composite International Diagnostic Interview (CIDI). CIDI is a structured diagnostic interview that provides current diagnoses of anxiety disorders according to DSM.
次要结局
- Mediator of the intervention: cognitive change(12 months)
- Subgroup analysis according to depressive symptoms at baseline (through the PHQ-9 questionnaire)(12 months)
- Probability of anxiety measured by the Spanish predictA risk algorithm(12 months)
- Cost-utility(12 months)
- Acceptability and satisfaction with the intervention (prevANS intervention) measured by u-MARS scale(12 months)
- Subgroup analysis according to age(12 months)
- Subgroup analysis according to anxiety symptoms at baseline (through the GAD-7 questionnaire)(12 months)
- Subgroup analysis according to risk level of anxiety (through the predictA risk algorithm)(12 months)
- Anxious symptoms measured by the General Anxiety Questionnaire (GAD-7)(12 months)
- Depressive symptoms measured by the Patient Health Questionnaire-9 (PHQ-9)(12 months)
- Probability of depression measured by the Spanish predictD risk algorithm(12 months)
- Quality of life measured by SF-12(12 months)
- Cost-effectiveness(12 months)
- Subgroup analysis according to sex(12 months)
- Subgroup analysis according to education level(12 months)
- Subgroup analysis according to risk level of depression (through the predictD risk algorithm)(12 months)
研究者
Patricia Moreno Peral
PhD
University of Malaga