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探索可能影响计划生育诊所中暴露前预防(PrEP)实施的因素的异质性:一项潜在剖面分析。

Exploring the heterogeneity of factors that may influence implementation of PrEP in family planning clinics: a latent profile analysis.

作者信息

Piper Kaitlin N, Haardörfer Regine, Escoffery Cam, Sheth Anandi N, Sales Jessica

机构信息

Department of Behavioral, Social, and Health Education Science, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, USA.

出版信息

Implement Sci Commun. 2021 May 4;2(1):48. doi: 10.1186/s43058-021-00148-3.

Abstract

BACKGROUND

Title X-funded family planning clinics have been identified as optimal sites for delivery of pre-exposure prophylaxis (PrEP) for HIV prevention. However, PrEP has not been widely integrated into family planning services, especially in the Southern US, and data suggest there may be significant implementation challenges in this setting. Because Title X clinics vary greatly in provider-, organizational-, and systems-level characteristics, there is likely variation in capacity to implement PrEP across clinics.

METHODS

We conducted a survey from February to June 2018 among providers and administrators of non-PrEP-providing Title X-funded clinics across 18 southern states. Survey items were designed using the Consolidated Framework for Implementation Research (CFIR) to assess constructs relevant to PrEP implementation. To explore the heterogeneity of CFIR-related implementation determinants and identify distinct sub-groups of Title X clinics, a latent profile analysis was conducted using nine CFIR constructs: complexity, relative advantage, cost, attitudes, implementation climate, compatibility, leadership engagement, available resources, and cosmopolitanism. We then conducted a multi-level analysis (accounting for nesting of participants within clinics) to test whether group membership was associated with readiness for implementation of PrEP, controlling for key sociodemographic characteristics.

RESULTS

Four hundred and fourteen healthcare providers/administrators from 227 non-PrEP-providing Title X clinics participated in the study. We identified six sub-groups of clinics that each had distinct patterns of PrEP implementation determinants. Clinic sub-groups included "Highest Capacity for Implementation", "Favorable Conditions for Implementation", "Mixed Implementation Context", "Neutral Implementation Context", "Incompatible Setting for Implementation", and "Resource-Strained Setting". Group membership was related to numerous provider-level (i.e., ability to prescribe medication) and clinic-level (i.e., provision of primary care) characteristics. In comparison to the "Neutral" group (which held neutral perceptions across the implementation determinants), the "Highest Capacity" and "Favorable Conditions" groups had significantly higher levels of implementation readiness, and the "Resource-Strained" group had a significantly lower level of implementation readiness.

CONCLUSIONS

Latent profile analyses can help researchers understand how implementation readiness varies across healthcare settings, promoting tailoring of implementation strategies to unique contexts.

摘要

背景

获得第十类计划(Title X)资助的计划生育诊所已被确定为提供暴露前预防(PrEP)以预防艾滋病毒的理想场所。然而,PrEP尚未广泛纳入计划生育服务,尤其是在美国南部,并且数据表明在这种情况下可能存在重大的实施挑战。由于获得第十类计划资助的诊所在提供者、组织和系统层面的特征差异很大,因此各诊所实施PrEP的能力可能存在差异。

方法

2018年2月至6月,我们对18个南部州未提供PrEP的获得第十类计划资助的诊所的提供者和管理人员进行了一项调查。调查项目采用实施研究综合框架(CFIR)设计,以评估与PrEP实施相关的构念。为了探讨与CFIR相关的实施决定因素的异质性,并确定获得第十类计划资助的诊所的不同亚组,我们使用九个CFIR构念进行了潜在剖面分析:复杂性、相对优势、成本、态度、实施氛围、兼容性、领导参与度、可用资源和国际性。然后,我们进行了多层次分析(考虑参与者在诊所内的嵌套情况),以测试组成员身份是否与PrEP实施准备情况相关,并控制关键的社会人口特征。

结果

来自227家未提供PrEP的获得第十类计划资助的诊所的414名医疗保健提供者/管理人员参与了该研究。我们确定了六个诊所亚组,每个亚组都有不同的PrEP实施决定因素模式。诊所亚组包括“最高实施能力”、“有利实施条件”、“混合实施背景”、“中性实施背景”、“不兼容实施环境”和“资源紧张环境”。组成员身份与许多提供者层面(即开药能力)和诊所层面(即提供初级保健)的特征相关。与“中性”组(在实施决定因素方面持中立看法)相比,“最高能力”组和“有利条件”组的实施准备水平明显更高,而“资源紧张”组的实施准备水平明显更低。

结论

潜在剖面分析可以帮助研究人员了解不同医疗保健环境下实施准备情况的差异,促进根据独特背景调整实施策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9f/8097793/a590e4b9ed70/43058_2021_148_Fig1_HTML.jpg

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