Learning differences between two decades of mental health related emergency department visits by youth via recurrent events data analyses

Yi Xiong et al.

Journal of the Royal Statistical Society. Series C: Applied Statistics2026https://doi.org/10.1093/jrsssc/qlag001article
AJG 3
Weight
0.37

Abstract

Administrative health data contain rich information for investigating public health issues; however, many restrictions and regulations apply to their use. Such data are usually not in the conventional format for statistical analysis since the databases are created and maintained to serve non-research purposes and only information for people who seek health services is recorded. Analysis of administrative health data is thus challenging in general. We aim to develop a tool for understanding how the mental health of youth aged younger than 18 years evolves over time through administrative records of mental health related emergency department (MHED) visits. The MHED records, a set of zero-truncated recurrent events data, are integrated with relevant population census information, and framed into a set of doubly censored recurrent events data. We present innovative strategies for overcoming the zero-truncation induced by the data collection and for processing doubly censored recurrent events data. We compare the dynamic patterns and exposure impacts of the MHED visits in two decades with a loosely structured model. The findings are verified empirically via simulation. The asymptotic properties of the proposed estimator are established. Through exploring the paediatric MHED visit records, we provide new insights into children/youths mental health changes over time.

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https://doi.org/https://doi.org/10.1093/jrsssc/qlag001

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@article{yi2026,
  title        = {{Learning differences between two decades of mental health related emergency department visits by youth via recurrent events data analyses}},
  author       = {Yi Xiong et al.},
  journal      = {Journal of the Royal Statistical Society. Series C: Applied Statistics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/jrsssc/qlag001},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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