Community stakeholder preferences for evidence-based practice implementation strategies in behavioral health: a best-worst scaling choice experiment.
Community stakeholder preferences for evidence-based practice implementation strategies in behavioral health: a best-worst scaling choice experiment.
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社区利益相关者对行为健康循证实践实施策略的偏好：最佳-最差比例选择实验。
DOI：
10.1186/s12888-021-03072-x
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发表时间：
2021-02-04
期刊：
影响因子：
4.4
通讯作者：
Beidas RS
中科院分区：
文献类型：
--
作者：
Williams NJ;Candon M;Stewart RE;Byeon YV;Bewtra M;Buttenheim AM;Zentgraf K;Comeau C;Shoyinka S;Beidas RS
社区行为健康临床医生，监督员和管理人员在实施新的心理社会循证实践（EBP）的患者接受精神科护理中发挥着至关重要的作用，但是，很少有人知道这些利益相关者的价值观和偏好的实施策略，支持EBP的使用，也不知道如何最好地引出，量化，或细分他们的喜好。本研究试图量化这些利益相关者的偏好的实施战略，并确定利益相关者的部分不同的偏好，使用严格的选择实验方法称为最好的最坏的缩放。共有240名临床医生，74名临床主管，和29名管理人员在诊所内提供公共资助的行为健康服务，在一个大都市的行为健康系统参加了最佳最差的缩放选择实验。与会者评价了通过在目标系统内广泛征求意见和试点工作制定的14项执行战略。使用分层贝叶斯估计为每个策略生成偏好权重。潜在类别分析确定了具有独特偏好的利益相关者部分。平均而言，利益相关者更喜欢两种策略，即每次使用EBP的补偿和使用EBP的准备时间的补偿（P <0.05）;两种策略的偏好显著低于所有其他策略，即通过电子邮件和通过排行榜进行绩效反馈（P <0.05）。然而，潜在类别分析确定了具有独特偏好的利益相关者的四个不同部分：（n = 121，35%）强烈倾向于经济激励，而不是所有其他方法，并包括更多的管理人员;（n = 80，23%）更喜欢基于技术的策略，平均年龄更小;段3（n = 52，15%）更喜欢改善候诊室，以提高客户的准备，强烈不喜欢任何类型的临床咨询，并在当地EBP培训计划的参与率最低;第4部分（n = 90，26%）强烈倾向于临床咨询策略，包括更多的临床医生在物质使用诊所。在这个庞大的临床医生，主管和管理人员群体中存在四个异质亚群，这表明通过利益相关者偏好的启发获得的有针对性的策略可以实现最佳实施。最佳-最差缩放是一种可行且严格的方法，用于引出利益相关者的实施偏好并识别行为健康环境中具有独特偏好的亚群。在线版本包含补充材料，可通过10.1186/s12888-021-03072-x获得。
Community behavioral health clinicians, supervisors, and administrators play an essential role in implementing new psychosocial evidence-based practices (EBP) for patients receiving psychiatric care; however, little is known about these stakeholders’ values and preferences for implementation strategies that support EBP use, nor how best to elicit, quantify, or segment their preferences. This study sought to quantify these stakeholders’ preferences for implementation strategies and to identify segments of stakeholders with distinct preferences using a rigorous choice experiment method called best-worst scaling. A total of 240 clinicians, 74 clinical supervisors, and 29 administrators employed within clinics delivering publicly-funded behavioral health services in a large metropolitan behavioral health system participated in a best-worst scaling choice experiment. Participants evaluated 14 implementation strategies developed through extensive elicitation and pilot work within the target system. Preference weights were generated for each strategy using hierarchical Bayesian estimation. Latent class analysis identified segments of stakeholders with unique preference profiles. On average, stakeholders preferred two strategies significantly more than all others—compensation for use of EBP per session and compensation for preparation time to use the EBP (P < .05); two strategies were preferred significantly less than all others—performance feedback via email and performance feedback via leaderboard (P < .05). However, latent class analysis identified four distinct segments of stakeholders with unique preferences: Segment 1 (n = 121, 35%) strongly preferred financial incentives over all other approaches and included more administrators; Segment 2 (n = 80, 23%) preferred technology-based strategies and was younger, on average; Segment 3 (n = 52, 15%) preferred an improved waiting room to enhance client readiness, strongly disliked any type of clinical consultation, and had the lowest participation in local EBP training initiatives; Segment 4 (n = 90, 26%) strongly preferred clinical consultation strategies and included more clinicians in substance use clinics. The presence of four heterogeneous subpopulations within this large group of clinicians, supervisors, and administrators suggests optimal implementation may be achieved through targeted strategies derived via elicitation of stakeholder preferences. Best-worst scaling is a feasible and rigorous method for eliciting stakeholders’ implementation preferences and identifying subpopulations with unique preferences in behavioral health settings. The online version contains supplementary material available at 10.1186/s12888-021-03072-x.
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影响因子：
64.8
作者：
Collins, Pamela Y.;Patel, Vikram;Joestl, Sarah S.;March, Dana;Insel, Thomas R.;Daar, Abdallah S.
通讯作者：
Daar, Abdallah S.
影响因子：
4.5
作者：
Bridges, John F. P.;Hauber, A. Brett;Mauskopf, Josephine
通讯作者：
Mauskopf, Josephine
影响因子：
7.2
作者：
Beidas, Rinad S.;Williams, Nathaniel J.;Mandell, David S.
通讯作者：
Mandell, David S.
DOI：
10.1007/s10488-012-0450-8
发表时间：
2013-01
影响因子：
2.6
作者：
Garland, Ann F.;Haine-Schlagel, Rachel;Brookman-Frazee, Lauren;Baker-Ericzen, Mary;Trask, Emily;Fawley-King, Kya
通讯作者：
Fawley-King, Kya
DOI：
10.1111/j.1754-9434.2010.01309.x
发表时间：
2011-03-01
影响因子：
15.8
作者：
Foti, Roseanne J.;Thompson, Nicole J.;Allgood, Sarah F.
通讯作者：
Allgood, Sarah F.