PDF(Pubmed)
Abstract：
UNASSIGNED: Diabetes is a growing global health problem. International guidelines recommend identification, screening, and referral to behavioural programmes for those at high risk of developing type 2 diabetes. Diabetes prevention programmes (DPPs) can prevent type 2 diabetes in those at high risk, however many eligible participants are not referred to these programmes. Healthcare workers (HCWs) are pivotal to the referral and recruitment processes. This study aims to identify, appraise and synthesise the evidence on barriers and facilitators to referral and recruitment to DPPs from the perspective of HCWs.
UNASSIGNED: A \"best fit\" framework synthesis method will synthesise qualitative, quantitative, and mixed methods evidence on factors that affect HCWs referral and recruitment to DPPs, with the Theoretical Domains Framework (TDF) as the a priori framework. MEDLINE, EMBASE, CINAHL, PsychINFO, Web of Science and Scopus will be searched for primary studies published in English. Year of publication will be restricted to the last 26 years (1997-2023). Quality will be assessed using the Mixed Methods Appraisal Tool. A mix of deductive coding using the TDF and inductive coding of data that does not fit the TDF will be synthesised into themes representing the whole dataset. The relationships between the final set of themes will be explored to create a new model to understand HCWs\' perspectives on referral and recruitment to DPPs. Sensitivity analysis will be carried out on this conceptual model. Confidence in the synthesised findings will be assessed using the GRADE-CERQual approach. One author will screen, extract, appraise the literature while a second author will independently verify a 20% sample at each stage.
UNASSIGNED: Participation in DPPs is key for programme impact. HCWs typically identify those at risk and refer them to DPPs. Understanding HCWs\' perspectives on the barriers and facilitators to referral and recruitment will inform future implementation of DPPs.
UNASSIGNED: A \"best fit\" framework synthesis method will synthesise qualitative, quantitative, and mixed methods evidence on factors that affect HCWs referral and recruitment to DPPs, with the Theoretical Domains Framework (TDF) as the a priori framework. MEDLINE, EMBASE, CINAHL, PsychINFO, Web of Science and Scopus will be searched for primary studies published in English. Year of publication will be restricted to the last 26 years (1997-2023). Quality will be assessed using the Mixed Methods Appraisal Tool. A mix of deductive coding using the TDF and inductive coding of data that does not fit the TDF will be synthesised into themes representing the whole dataset. The relationships between the final set of themes will be explored to create a new model to understand HCWs\' perspectives on referral and recruitment to DPPs. Sensitivity analysis will be carried out on this conceptual model. Confidence in the synthesised findings will be assessed using the GRADE-CERQual approach. One author will screen, extract, appraise the literature while a second author will independently verify a 20% sample at each stage.
UNASSIGNED: Participation in DPPs is key for programme impact. HCWs typically identify those at risk and refer them to DPPs. Understanding HCWs\' perspectives on the barriers and facilitators to referral and recruitment will inform future implementation of DPPs.
摘要：
糖尿病是一个日益严重的全球健康问题。国际准则建议识别，筛选,和转诊行为计划为那些有发展为2型糖尿病的高风险。糖尿病预防计划（DPPs）可以预防高危人群的2型糖尿病，然而，许多合格的参与者没有被推荐到这些方案。医疗保健工作者（HCWs）对于转诊和招聘流程至关重要。本研究旨在确定,从HCW的角度评估和综合有关转介和招募DPP的障碍和促进者的证据。
■“最适合”框架综合方法将综合定性，定量,以及影响HCW转介和招募DPP的因素的混合方法证据，以理论域框架(TDF)为先验框架。MEDLINE,EMBASE,CINAHL,心理信息,将搜索WebofScience和Scopus以英语发表的主要研究。出版年份将限于过去26年（1997-2023年）。质量将使用混合方法评估工具进行评估。使用TDF的演绎编码和不适合TDF的数据的归纳编码的混合将被合成为表示整个数据集的主题。将探索最终主题集之间的关系，以创建一个新的模型，以了解HCWs在推荐和招募DPP方面的观点。将对该概念模型进行敏感性分析。将使用GRADE-CERQual方法评估对综合发现的信心。一位作者将筛选，Extract,评估文献，而第二作者将在每个阶段独立验证20%的样本。
■参与DPP是方案影响的关键。HCW通常会识别有风险的人，并将其转介给DPP。了解HCWs对转诊和招聘的障碍和促进者的看法将为未来DPPs的实施提供信息。
■“最适合”框架综合方法将综合定性，定量,以及影响HCW转介和招募DPP的因素的混合方法证据，以理论域框架(TDF)为先验框架。MEDLINE,EMBASE,CINAHL,心理信息,将搜索WebofScience和Scopus以英语发表的主要研究。出版年份将限于过去26年（1997-2023年）。质量将使用混合方法评估工具进行评估。使用TDF的演绎编码和不适合TDF的数据的归纳编码的混合将被合成为表示整个数据集的主题。将探索最终主题集之间的关系，以创建一个新的模型，以了解HCWs在推荐和招募DPP方面的观点。将对该概念模型进行敏感性分析。将使用GRADE-CERQual方法评估对综合发现的信心。一位作者将筛选，Extract,评估文献，而第二作者将在每个阶段独立验证20%的样本。
■参与DPP是方案影响的关键。HCW通常会识别有风险的人，并将其转介给DPP。了解HCWs对转诊和招聘的障碍和促进者的看法将为未来DPPs的实施提供信息。
