Kaveladze Benjamin, Shkel Jane, Le Stacey, Marcotte Veronique, Rushton Kevin, Nguyen Theresa, Schueller Stephen M
Department of Preventive Medicine, Northwestern University, Chicago, IL, United States.
Department of Medical Social Sciences, Northwestern University, Chicago, IL, United States.
Internet Interv. 2024 Sep 11;38:100774. doi: 10.1016/j.invent.2024.100774. eCollection 2024 Dec.
Anxiety and depression are major public health concerns. Digital mental health interventions (DMHIs) are effective at reducing anxiety and depression, especially when they leverage human support. However, DMHIs that rely on human supporters tend to be less scalable. "Crowdsourced peer support," in which a "crowd" of many peers provides users support via structured and focused interactions, may enable DMHIs to provide some of human support's unique benefits at scale.
To conduct a pilot trial of two versions of a digital mental health intervention for anxiety and depression: one with crowdsourced peer support and one without.
We conducted a two-armed pilot randomized controlled trial examining two versions of the novel "Overcoming Thoughts" platform: crowdsourced (intervention) vs. non-crowdsourced (control). The crowdsourced version allowed participants to view and interact with other users' content. We randomly assigned 107 participants to use the crowdsourced ( = 56) or non-crowdsourced ( = 51) platform for 8 weeks. Participants completed assessments at baseline, 4 weeks, 8 weeks, and 16 weeks. At each time point, these assessments included measures of anxiety and depression, including the Depression, Anxiety, and Stress Scale (DASS, primary outcome), the Patient Health Questionnaire (PHQ-9, secondary outcome), and the Generalized Anxiety Disorder Questionnaire (GAD-7, secondary outcome). We also collected usage information, including the number of exercises started, and safety data.
Using mixed models controlling for demographic factors, we compared the conditions' effectiveness in reducing depression and anxiety over time. Although we found significant drops over time in the DASS at both Week 8 and Week 16 (s < 0.01), we did not find significant treatment x time interactions (Week 8, = 0.35; Week 16, = 0.68). The PHQ-9 and GAD-7 showed similar results. The median number of times participants used the platform was 3 (mean = 6.99, SD = 9.78). Greater platform use was not associated with a different change in DASS total score, PHQ-9 score, or GAD-7 score over eight weeks (s > 0.10).
Neither version of the "Overcoming Thoughts" platform (crowdsourced or non-crowdsourced) reduced anxiety or depression significantly more than the other. Future work should investigate how digital platforms can better leverage crowdsourced support, and if crowdsourced support may be especially useful in certain kinds of systems, populations, or target areas. Optimizing intervention engagement and obtaining the large sample sizes needed for appropriate statistical power will be key challenges for similar studies.NCT: 04226742.
焦虑和抑郁是重大的公共卫生问题。数字心理健康干预措施（DMHIs）在减轻焦虑和抑郁方面很有效，尤其是在利用人力支持时。然而，依赖人力支持者的DMHIs往往扩展性较差。“众包同伴支持”，即众多同伴组成的“群体”通过结构化且有重点的互动为用户提供支持，可能使DMHIs能够大规模提供一些人力支持的独特益处。
对两种用于焦虑和抑郁的数字心理健康干预版本进行一项试点试验：一种有众包同伴支持，另一种没有。
我们进行了一项双臂试点随机对照试验，研究新型“克服思维”平台的两个版本：众包版（干预组）与非众包版（对照组）。众包版允许参与者查看其他用户的内容并与之互动。我们随机分配107名参与者使用众包平台（n = 56）或非众包平台（n = 51），为期8周。参与者在基线、4周、8周和16周时完成评估。在每个时间点，这些评估包括焦虑和抑郁的测量指标，包括抑郁、焦虑和压力量表（DASS，主要结局）、患者健康问卷（PHQ - 9，次要结局）和广泛性焦虑障碍问卷（GAD - 7，次要结局）。我们还收集了使用信息，包括开始的练习次数以及安全数据。
使用控制人口统计学因素的混合模型，我们比较了两种情况随时间在减轻抑郁和焦虑方面的有效性。尽管我们发现8周和16周时DASS随时间均有显著下降（p < 0.01），但我们未发现显著的治疗×时间交互作用（8周时，p = 0.35；16周时，p = 0.68）。PHQ - 9和GAD - 7显示出类似结果。参与者使用平台的次数中位数为3次（均值 = 6.99，标准差 = 9.78）。在八周内，更多地使用平台与DASS总分、PHQ - 9得分或GAD - 7得分的不同变化无关（p > 0.10）。
“克服思维”平台的两个版本（众包版或非众包版）在减轻焦虑或抑郁方面均未显著优于另一个版本。未来的工作应研究数字平台如何能更好地利用众包支持，以及众包支持在某些类型的系统、人群或目标领域是否可能特别有用。优化干预参与度并获得适当统计效力所需的大样本量将是类似研究的关键挑战。试验注册号：NCT: 04226742。
