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Hong L, Yang A, Liang Q, He Y, Wang Y, Tao S, Chen L. Wife-Mother Role Conflict at the Critical Child-Rearing Stage: A Machine-Learning Approach to Identify What and How Matters in Maternal Depression Symptoms in China. PREVENTION SCIENCE : THE OFFICIAL JOURNAL OF THE SOCIETY FOR PREVENTION RESEARCH 2024; 25:699-710. [PMID: 37897552 DOI: 10.1007/s11121-023-01610-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2023] [Indexed: 10/30/2023]
Abstract
Maternal depression (MD) was one of the most prevalent psychiatric problems worldwide. However, it easily remains untreated and misses the best time to prevent the emergence or worsening of major depressive symptoms due to under-observed stigma and the lack of effective screening tools. Thus, this study aims to develop and validate a machine learning-based MD symptoms prediction model integrating more observable and objective factors to early detect and monitor MD risk. A cross-sectional study was conducted in 10 community vaccination centers in Wenzhou, China, and a total of 1099 mothers were surveyed by using purposive sampling. A questionnaire containing questions regarding socio-demographic variables, psychophysiological variables, wife role-related variables, and mother role-related variables was used to collect data. A framework of data preprocessing, feature selection, and model evaluation was implemented to develop an optimal risk prediction model. Results demonstrated that the XG-Boost algorithm provided robust performance with the highest AUC and well-balanced sensitivity and specificity (AUC = 0.90, sensitivity = 0.74, specificity = 0.90). Furthermore, the causal mediation analysis indicated that wife-mother role conflict positively predicted MD symptoms, and it also exerted influence on mothers suffering through the mediation of anxiety and insomnia. Findings from the present study may help guide the development of MD screening tools to early detect and provide the modifiable risk factor information for timely tailored prevention.
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Affiliation(s)
- Liuzhi Hong
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China
| | - Ai Yang
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China
| | - Qi Liang
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China
| | - Yuhan He
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China
| | - Yulin Wang
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China
| | - Shuhan Tao
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China
| | - Li Chen
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China.
- The Affiliated Kangning Hospital, Wenzhou Medical University, Wenzhou, 325035, China.
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Qin Y, Han H, Li Y, Cui J, Jia H, Ge X, Ma Y, Bai W, Zhang R, Chen D, Yi F, Yu H. Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment. Neurology 2023; 100:e297-e307. [PMID: 36220593 PMCID: PMC9869761 DOI: 10.1212/wnl.0000000000201386] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 08/26/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Various resources exist for treating mild cognitive impairment (MCI) or dementia separately as terminal events or for focusing solely on a 1-way path from MCI to dementia without taking into account heterogeneous transitions. Little is known about the trajectory of reversion from MCI to normal cognition (NC) or near-NC and patterns of postreversion, which refers to cognitive trajectories of patients who have reversed from MCI to NC. Our objectives were to (1) quantitatively predict bidirectional transitions of MCI (reversion and progression), (2) explore patterns of future cognitive trajectories for postreversion, and (3) estimate the effects of demographic characteristics, APOE, cognition, daily activity ability, depression, and neuropsychiatric symptoms on transition probabilities. METHODS We constructed a retrospective cohort by reviewing patients with an MCI diagnosis at study entry and at least 2 follow-up visits between June 2005 and February 2021. Defining NC or near-NC and MCI as transient states and dementia as an absorbing state, we used continuous-time multistate Markov models to estimate instantaneous transition intensity between states, transition probabilities from one state to another at any given time during follow-up, and hazard ratios of reversion-related variables. RESULTS Among 24,220 observations from 6,651 participants, there were 2,729 transitions to dementia and 1,785 reversions. As for postreversion, there were 630 and 73 transitions of progression to MCI and dementia, respectively. The transition intensity of progression to MCI for postreversion was 0.317 (2.48-fold greater than that for MCI progression or reversion). For postreversion participants, the probability of progressing to dementia increased by 2% yearly. Participants who progressed to MCI were likely to reverse again (probability of 40% over 15 years). Age, independence level, APOE, cognition, daily activity ability, depression, and neuropsychiatric symptoms were significant predictors of bidirectional transitions. DISCUSSION The nature of bidirectional transitions cannot be ignored in multidimensional MCI research. We found that postreversion participants remained at an increased risk of progression to MCI or dementia over the longer term and experienced recurrent reversions. Our findings may serve as a valuable reference for future research and enable health care professionals to better develop proactive management plans and targeted interventions.
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Affiliation(s)
- Yao Qin
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Hongjuan Han
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Yang Li
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Jing Cui
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Haixia Jia
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Xiaoyan Ge
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Yifei Ma
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Wenlin Bai
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Rong Zhang
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Durong Chen
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Fuliang Yi
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China
| | - Hongmei Yu
- From the Department of Health Statistics (Y.Q., H.H., J.C., X.G., Y.M., W.B., R.Z., D.C., F.Y., H.Y.), School of Public Health, Shanxi Medical University, Taiyuan; Department of Medical Device Ethics (Y.L.), Shanxi Province Cancer Hospital, Taiyuan; Department of Neurology (H.J.), First Hospital of Shanxi Medical University, Taiyuan; and Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment (H.Y.), Taiyuan, China.
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