ORCID Profile
0000-0001-7933-0667
Current Organisations
University of Oxford
,
University of Oxford Nuffield Department of Population Health
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Publisher: BMJ
Date: 07-2021
DOI: 10.1136/BMJOPEN-2020-048554
Abstract: This study aims to explore the association between maternal depression and the loss of the only child under the family-planning (FP) policy. Cross-sectional data from a Chinese population-based study were analysed. Population from 10 (5 rural and 5 urban) areas in China. Around 300 000 females were included in the study. The FP group was defined as women with one or two live births. Those with no surviving child were classified into the loss-of-only-child group. The non-FP group included women who had more than two live births. Logistic regression was used to assess the relationship between major depressive disorder (MDD) and family types, after stratification and adjustment. MDD was assessed using the Composite International Diagnostic Inventory. The odds of MDD are 1.42 times higher in the FP group in general (OR=1.42, 95% CI: 1.28 to 1.57), as opposed to the non-FP group. In particular, the odds of MDD are 1.36 times greater in the non-loss-of-only-child group (OR=1.36, 95% CI: 1.21 to 1.51) and 2.80 (OR=2.80, 95% CI: 0.88 to 8.94) times greater in the loss-of-only-child group, compared with the non-FP group. The associations between FP groups and MDD appeared to be stronger in the elderly population, in those who were married, less educated and those with a higher household income. The association was found progressively stronger in those who lost their only child. People in the FP group, especially those who lost their only child, are more susceptible to MDD than their counterparts in the non-FP group. Mental health programmes should give special care to those who lost their only child and take existing social policies and norms, such as FP policies, into consideration.
Publisher: JMIR Publications Inc.
Date: 30-01-2023
DOI: 10.2196/38397
Abstract: Imbalanced health care resource distribution has been central to unequal health outcomes and political tension around the world. Artificial intelligence (AI) has emerged as a promising tool for facilitating resource distribution, especially during emergencies. However, no comprehensive review exists on the use and ethics of AI in health care resource distribution. This study aims to conduct a scoping review of the application of AI in health care resource distribution, and explore the ethical and political issues in such situations. A scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A comprehensive search of relevant literature was conducted in MEDLINE (Ovid), PubMed, Web of Science, and Embase from inception to February 2022. The review included qualitative and quantitative studies investigating the application of AI in health care resource allocation. The review involved 22 articles, including 9 on model development and 13 on theoretical discussions, qualitative studies, or review studies. Of the 9 on model development and validation, 5 were conducted in emerging economies, 3 in developed countries, and 1 in a global context. In terms of content, 4 focused on resource distribution at the health system level and 5 focused on resource allocation at the hospital level. Of the 13 qualitative studies, 8 were discussions on the COVID-19 pandemic and the rest were on hospital resources, outbreaks, screening, human resources, and digitalization. This scoping review synthesized evidence on AI in health resource distribution, focusing on the COVID-19 pandemic. The results suggest that the application of AI has the potential to improve efficacy in resource distribution, especially during emergencies. Efficient data sharing and collecting structures are needed to make reliable and evidence-based decisions. Health inequality, distributive justice, and transparency must be considered when deploying AI models in real-world situations.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Hanyu Wang.