Personalized cognitive training: Protocol for individual-level meta-analysis implementing machine learning methods.
Personalized cognitive training: Protocol for individual-level meta-analysis implementing machine learning methods.
复制标题
个性化认知训练：实施机器学习方法的个人级元分析协议。
DOI：
10.1016/j.jpsychires.2021.03.043
复制
发表时间：
2021
影响因子：
4.8
通讯作者：
Shani R
中科院分区：
文献类型：
--
作者：
Shani R
越来越多的证据表明，认知训练可以提高幸福感。然而，混合的研究结果意味着，个体差异和训练特征可能会相互作用，以适度的训练效果。为了研究这种可能性，本文描述了一个数据驱动的个人层面的荟萃分析研究，旨在开发个性化的认知训练的协议。为了便于全面分析，本方案提出了数据检索、选择和预处理的标准，并沿着了每个决策的依据。收集了包括1544名参与者的22个认知训练数据集。这些数据集纳入了各种培训方法，所有这些方法都旨在改善福祉。这些训练方案在训练特征方面不同，例如目标领域（例如，工作记忆、注意偏差、解释偏差、抑制控制）和训练持续时间，而被试在诊断状态、年龄和性别上存在差异。计划中的分析包括机器学习算法，旨在确定哪些人对一般认知训练最敏感，并辨别哪些方法可能更适合某些人。
Accumulating evidence suggests that cognitive training may enhance well-being. Yet, mixed findings imply that individual differences and training characteristics may interact to moderate training efficacy. To investigate this possibility, the current paper describes a protocol for a data-driven individual-level meta-analysis study aimed at developing personalized cognitive training. To facilitate comprehensive analysis, this protocol proposes criteria for data search, selection and pre-processing along with the rationale for each decision. Twenty-two cognitive training datasets comprising 1544 participants were collected. The datasets incorporated diverse training methods, all aimed at improving well-being. These training regimes differed in training characteristics such as targeted domain (e.g., working memory, attentional bias, interpretation bias, inhibitory control) and training duration, while participants differed in diagnostic status, age and sex. The planned analyses incorporate machine learning algorithms designed to identify which individuals will be most responsive to cognitive training in general and to discern which methods may be a better fit for certain individuals.
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训练认知控制以减少乳腺癌患者的情绪脆弱性
影响因子：
3.6
作者：
Jessica Swainston;N. Derakshan
通讯作者：
N. Derakshan
影响因子：
3.7
作者：
Owens, Max;Koster, Ernst H. W.;Derakshan, Nazanin
通讯作者：
Derakshan, Nazanin
影响因子：
6.6
作者：
Williams AD;O'Moore K;Blackwell SE;Smith J;Holmes EA;Andrews G
通讯作者：
Andrews G
影响因子：
4.6
作者：
Beevers CG;Clasen PC;Enock PM;Schnyer DM
通讯作者：
Schnyer DM
DOI：
10.1146/annurev-clinpsy-050817-084746
发表时间：
2018-01-01
期刊：
ANNUAL REVIEW OF CLINICAL PSYCHOLOGY, VOL 14
影响因子：
--
作者：
Cohen, Zachary D.;DeRubeis, Robert J.
通讯作者：
DeRubeis, Robert J.