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Identifying probable post-traumatic stress disorder: applying supervised machine learning to data from a UK military cohort

Abstract:
Abstract Background: Early identification of probable post-traumatic stress disorder (PTSD) can lead to early intervention and treatment. Aims: This study aimed to evaluate supervised machine learning (ML) classifiers for the identification of probable PTSD in those who are serving, or have recently served in the United Kingdom (UK) Armed Forces. Methods: Supervised ML classification techniques were applied to a military cohort of 13,690 serving and ex-serving UK Armed Forces personnel to identify probable PTSD based on self-reported service exposures and a range of validated self-report measures. Data were collected between 2004 and 2009. Results: The predictive performance of supervised ML classifiers to detect cases of probable PTSD were encouraging when compared to a validated measure, demonstrating a capability of supervised ML to detect the cases of probable PTSD. It was possible to identify which variables contributed to the performance, including alcohol misuse, gender and deployment status. A satisfactory sensitivity was obtained across a range of supervised ML classifiers, but sensitivity was low, indicating a potential for false negative diagnoses. Conclusions: Detection of probable PTSD based on self-reported measurement data is feasible, may greatly reduce the burden on public health and improve operational efficiencies by enabling early intervention, before manifestation of symptoms.
Author Listing: Daniel Leightley;Victoria Williamson;John Darby;Nicola T Fear
Volume: 28
Pages: 34 - 41
DOI: 10.1080/09638237.2018.1521946
Language: English
Journal: Journal of Mental Health

Journal of Mental Health

J MENT HEALTH

影响因子:3.2
是否综述期刊:否
是否OA:否
是否预警:不在预警名单内
发行时间:-
ISSN:0963-8237
发刊频率:-
收录数据库:Scopus收录
出版国家/地区:-
出版社:Taylor & Francis

期刊介绍

年发文量 50
国人发稿量 3
国人发文占比 5.88%
自引率 6.2%
平均录取率 -
平均审稿周期 -
版面费 -
偏重研究方向 PSYCHOLOGY, CLINICAL-
期刊官网 https://www.tandfonline.com/toc/ijmh20/current
投稿链接 -

质量指标占比

研究类文章占比 OA被引用占比 撤稿占比 出版后修正文章占比
62.00% 40.74% 0.00% 0.00%

相关指数

影响因子
影响因子
年发文量
自引率
Cite Score

预警情况

时间 预警情况
2025年03月发布的2025版 不在预警名单中
2024年02月发布的2024版 不在预警名单中
2023年01月发布的2023版 不在预警名单中
2021年12月发布的2021版 不在预警名单中
2020年12月发布的2020版 不在预警名单中

JCR分区 WOS分区等级:Q1区

版本 按学科 分区
WOS期刊SCI分区
(2021-2022年最新版)
PSYCHIATRY Q2
PSYCHOLOGY, CLINICAL Q2

中科院分区

版本 大类学科 小类学科 Top期刊 综述期刊
医学
3区
PSYCHOLOGY, CLINICAL
心理学:临床
3区
2021年12月
升级版
医学
2区
PSYCHOLOGY, CLINICAL
心理学:临床
3区
2020年12月
旧的升级版
医学
2区
PSYCHOLOGY, CLINICAL
心理学:临床
3区
2022年12月
最新升级版
医学
4区
PSYCHOLOGY, CLINICAL
心理学:临床
4区