Nichols Linda, Ryan Ronan, Connor Charlotte, Birchwood Max, Marshall Tom
Primary Care Clinical Sciences, University of Birmingham, Birmingham, UK.
Centre for Mental Health, Birmingham and Solihull Mental Health NHS Foundation Trust, Birmingham, UK.
Early Interv Psychiatry. 2018 Jun;12(3):444-455. doi: 10.1111/eip.12332. Epub 2016 Mar 30.
Approximately 80 000 children and young people in the UK suffer from depression, but many are untreated because of poor identification of early warning signs and risk factors.
This study aimed to derive and to investigate discrimination characteristics of a prediction model for a first recorded diagnosis of depression in young people aged 15-24 years.
This study used a matched case-control method using electronic primary care records. Stepwise conditional logistic regression modelling investigated 42 potential predictors including symptoms, co-morbidities, social factors and drug and alcohol misuse.
Of the socio-economic and symptomatic predictors identified, the strongest associations were with depression symptoms and other psychological conditions. School problems and social services involvement were prominent predictors in men aged 15-18 years, work stress in women aged 19-24 years.
Our model is a first step in the development of a predictive model identifying early warning signs of depression in young people in primary care.
英国约有8万名儿童和年轻人患有抑郁症，但由于早期预警信号和风险因素识别不足，许多人未得到治疗。
本研究旨在推导并调查15至24岁年轻人首次诊断为抑郁症的预测模型的判别特征。
本研究采用匹配病例对照法，利用电子初级保健记录。逐步条件逻辑回归模型研究了42个潜在预测因素，包括症状、共病、社会因素以及药物和酒精滥用情况。
在确定的社会经济和症状性预测因素中，最强的关联是与抑郁症状和其他心理状况相关。学校问题和社会服务参与是15至18岁男性的突出预测因素，工作压力是19至24岁女性的突出预测因素。
我们的模型是开发预测模型的第一步，该模型可识别初级保健中年轻人抑郁症的早期预警信号。
