Leading Predictors of COVID-19-Related Poor Mental Health in Adult Asian Indians: An Application of Extreme Gradient Boosting and Shapley Additive Explanations.
Leading Predictors of COVID-19-Related Poor Mental Health in Adult Asian Indians: An Application of Extreme Gradient Boosting and Shapley Additive Explanations.
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DOI：
10.3390/ijerph20010775
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发表时间：
2022-12-31
影响因子：
--
通讯作者：
Sambamoorthi, Usha
中科院分区：
文献类型：
--
作者：
Ikram, Mohammad;Shaikh, Nazneen Fatima;Vishwanatha, Jamboor K.;Sambamoorthi, Usha
关键词：
在2019冠状病毒病大流行期间，在美国观察到亚裔印度人心理健康状况不佳的情况有所增加。然而，在2019冠状病毒病大流行期间，亚洲印度人心理健康状况不佳的主要预测因素仍然未知。一个横断面的在线调查进行了自我认定的亚洲印度人年龄在18岁及以上（N = 289）。调查收集有关人口及社会经济特征以及COVID-19负担的资料。两种新的机器学习技术eXtreme Gradient Boosting和Shapley Additive Explanations（SHAP）被用来识别主要的预测因子，并解释它们与心理健康状况不佳的关系。大多数研究参与者为女性（65.1%），年龄低于50岁（73.3%），收入≥ 75，000美元（81.0%）。亚裔印度人心理健康状况不佳的六个主要预测因素是睡眠障碍、年龄、一般健康状况、收入、戴口罩和自我报告的歧视。SHAP图表明，较高的年龄，戴口罩，并保持社交距离的所有时间与心理健康状况不佳呈负相关，而睡眠障碍和估算的收入水平与心理健康状况不佳呈正相关。模型性能指标显示高准确度（0.77），精确度（0.78），F1评分（0.77），召回率（0.77）和AUROC（0.87）。近二分之一的成年人报告心理健康状况不佳，五分之一的人报告睡眠障碍。我们的研究结果表明，收入和心理健康状况不佳之间存在矛盾的关系;需要进一步的研究来证实我们的研究结果。可以通过量身定制的干预措施来针对睡眠障碍和感知歧视，以降低亚洲印度人心理健康状况不佳的风险。
During the COVID-19 pandemic, an increase in poor mental health among Asian Indians was observed in the United States. However, the leading predictors of poor mental health during the COVID-19 pandemic in Asian Indians remained unknown. A cross-sectional online survey was administered to self-identified Asian Indians aged 18 and older (N = 289). Survey collected information on demographic and socio-economic characteristics and the COVID-19 burden. Two novel machine learning techniques-eXtreme Gradient Boosting and Shapley Additive exPlanations (SHAP) were used to identify the leading predictors and explain their associations with poor mental health. A majority of the study participants were female (65.1%), below 50 years of age (73.3%), and had income ≥ $75,000 (81.0%). The six leading predictors of poor mental health among Asian Indians were sleep disturbance, age, general health, income, wearing a mask, and self-reported discrimination. SHAP plots indicated that higher age, wearing a mask, and maintaining social distancing all the time were negatively associated with poor mental health while having sleep disturbance and imputed income levels were positively associated with poor mental health. The model performance metrics indicated high accuracy (0.77), precision (0.78), F1 score (0.77), recall (0.77), and AUROC (0.87). Nearly one in two adults reported poor mental health, and one in five reported sleep disturbance. Findings from our study suggest a paradoxical relationship between income and poor mental health; further studies are needed to confirm our study findings. Sleep disturbance and perceived discrimination can be targeted through tailored intervention to reduce the risk of poor mental health in Asian Indians.
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DOI：
10.1007/s00018-022-04303-4
发表时间：
2022-05-03
期刊：
Cellular and molecular life sciences : CMLS
影响因子：
--
作者：
通讯作者：
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影响因子：
3.4
作者：
Ayalon, Liat;Gum, Amber M.
通讯作者：
Gum, Amber M.
影响因子：
6.6
作者：
Diaz F;Cornelius T;Bramley S;Venner H;Shaw K;Dong M;Pham P;McMurry CL;Cannone DE;Sullivan AM;Lee SAJ;Schwartz JE;Shechter A;Abdalla M
通讯作者：
Abdalla M
影响因子：
3.9
作者：
Assari, Shervin;Caldwell, Cleopatra H.
通讯作者：
Caldwell, Cleopatra H.
影响因子：
4.4
作者：
Alvarez, Kiara;Fillbrunn, Mirko;Alegria, Margarita
通讯作者：
Alegria, Margarita