一个系统的预测和调节器的系统审查治疗结果在互联网和移动基于抑郁症干预措施的预测和调节器
Theresa Sextl-Plötz1,2, Maria Steinhoff3, Harald Baumeister3
1Professorship for Psychology & Digital Mental Health Care, Technical University of Munich, Germany.
Internet interventions
|August 14, 2024
概括
在抑郁症治疗中,基于互联网和移动的干预措施 (IMI) 的预测因素正在出现. 基线抑郁症严重程度和坚持表现有希望,但需要更多高质量的研究来实现个性化护理.
科学领域:
- 数字心理健康数字心理健康
- 精神病学是一个精神病学.
- 临床心理学 临床心理学
背景情况:
- 基于互联网和移动的干预 (IMI) 提供可访问的心理健康支持.
- 预测IMI中的治疗结果对于个性化护理至关重要.
- 需要综合证据来识别关键预测因素和调节者.
研究的目的:
- 系统地审查抑郁症IMI治疗结果的预测因素和调节因素.
- 为个人化数字心理健康战略的发展提供信息.
- 评估现有证据的质量和意义.
主要方法:
- 在PubMed,PsycInfo和Cochrane数据库中进行系统搜索.
- 独立的选,数据提取,以及由两名审稿人进行偏差风险评估.
- 包括58个单个研究和6个个体患者数据元分析.
主要成果:
- 很少有分析 (24.0%在单个研究中,15.1%在元分析中) 是显著的.
- 基线抑郁症严重程度是最强的预测因素,较高的得分与更好的结果有关.
- 坚持,年龄,教育,种族,关系状况,治疗史和行为变量显示出潜在的预测价值.
结论:
- 目前关于IMI中抑郁症预测因子和调节因子的证据基本上不足.
- 基线抑郁症严重程度和变化过程指标是有希望的预测指标.
- 高质量,强大的研究对于验证发现和指导个性化的数字心理健康干预至关重要.
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