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Derivation of a prediction model for a diagnosis of depression in young adults: a matched case–control study using electronic primary care records
Author(s) -
Nichols Linda,
Ryan Ronan,
Connor Charlotte,
Birchwood Max,
Marshall Tom
Publication year - 2018
Publication title -
early intervention in psychiatry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.087
H-Index - 45
eISSN - 1751-7893
pISSN - 1751-7885
DOI - 10.1111/eip.12332
Subject(s) - depression (economics) , logistic regression , conditional logistic regression , primary care , medical record , medicine , stepwise regression , psychiatry , psychology , clinical psychology , case control study , family medicine , economics , macroeconomics
Background 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. Aims 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. Method 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. Results 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. Conclusion 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.