Identifying individuals at risk of developing psychosis: A systematic review of the literature in primary care services

EARLY INTERVENTION IN PSYCHIATRY(2023)

引用 0|浏览9
暂无评分
摘要
AimPsychosis and related disorders are a major public health issue. Early identification and prevention for those at high risk (at-risk-mental-state, ARMS) is important. General practitioners (GPs) are often the first point of contact for health services. In this review we aim to identify (1) the most common methods for identifying individuals with an ARMS in primary care, (2) the methods for improving identification of individuals with an ARMS in primary care, and (3) the most common barriers that prevent GPs from screening for individuals with an ARMS. MethodsWe conducted a systematic review (PROSPERO 42021245095) of quantitative and qualitative studies with no date restriction. Searches were performed in September 2021. Studies' quality was appraised using Mixed Methods Appraisal tool (MMAT). ResultsWe identified 16 eligible studies, and all but one provided quantitative data. Nearly two-thirds of studies were classified as 'medium' quality. Employing narrative synthesis, we identified three themes relating to (1) improving GP knowledge and confidence in identifying individuals with an ARMS, (2) balancing the over- and under-identification of individuals with an ARMS in primary care, and (3) supporting GPs as significant stakeholders in early diagnosis and treatment of individuals with an ARMS. ConclusionsImproved identification of individuals with an ARMS is needed. We identified various strategies, including development and implementation of identification methods (e.g., screening measures), educational interventions for GPs (e.g., workshops), and systemic interventions (e.g., simplifying referrals to secondary care, developing integrated services). When implemented successfully, these interventions may help facilitate the access to appropriate care for individuals with an ARMS.
更多
查看译文
关键词
at-risk mental state,general practitioner,primary care,screening
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要