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建立美国医生常见倦怠测量指标的转换标准。

Establishing Crosswalks Between Common Measures of Burnout in US Physicians.

机构信息

Health Law, Policy & Management Department, Boston University School of Public Health, Boston, MA, USA.

Biostatistics & Epidemiology Data Analytic Center, Boston University School of Public Health, Boston, MA, USA.

出版信息

J Gen Intern Med. 2022 Mar;37(4):777-784. doi: 10.1007/s11606-021-06661-4. Epub 2021 Mar 31.

Abstract

BACKGROUND

Physician burnout is often assessed by healthcare organizations. Yet, scores from different burnout measures cannot currently be directly compared, limiting the interpretation of results across organizations or studies.

OBJECTIVE

To link common measures of burnout to a single metric in psychometric analyses such that group-level scores from different assessments can be compared.

DESIGN

Cross-sectional survey.

SETTING

US practices.

PARTICIPANTS

A total of 1355 physicians sampled from the American Medical Association Physician Masterfile.

MAIN MEASURES

We linked the Stanford Professional Fulfillment Index (PFI) and Mini-Z Single-Item Burnout (MZSIB) scale to the Maslach Burnout Inventory (MBI) in item response theory (IRT) fixed-calibration and equipercentile analyses and created crosswalks mapping PFI and MZSIB scores to corresponding MBI scores. We evaluated the accuracy of the results by comparing physicians' actual MBI scores to those predicted by linking and described the closest cut-point equivalencies across scales linked to the same MBI subscale using the resulting crosswalks.

KEY RESULTS

IRT linking produced the most accurate results and was used to create crosswalks mapping (1) PFI Work Exhaustion (PFI-WE) and MZSIB scores to MBI Emotional Exhaustion (MBI-EE) scores and (2) PFI Interpersonal Disengagement (PFI-ID) scores to MBI Depersonalization (MBI-DP) scores. The commonly used MBI-EE raw score cut-point of ≥27 corresponded most closely with respective PFI-WE and MZSIB raw score cut-points of ≥7 and ≥3. The commonly used MBI-DP raw score cut-point of ≥10 corresponded most closely with a PFI-ID raw score cut-point of ≥9.

CONCLUSIONS

Our findings allow healthcare organizations using the PFI or MZSIB to compare group-level scores to historical, regional, or national MBI scores (and vice-versa).

摘要

背景

医生倦怠通常由医疗机构进行评估。然而,目前不同倦怠测量工具的分数无法直接比较,限制了在不同组织或研究之间解释结果。

目的

在心理测量分析中将常见的倦怠测量工具与单一指标联系起来,以便比较不同评估的群体得分。

设计

横断面调查。

设置

美国的实践。

参与者

从美国医学协会医师主文件中抽取的总共 1355 名医生。

主要措施

我们在项目反应理论(IRT)固定校准和等百分位分析中将斯坦福职业满意度指数(PFI)和迷你-Z 单项倦怠量表(MZSIB)与 Maslach 倦怠量表(MBI)联系起来,并创建了将 PFI 和 MZSIB 分数映射到相应 MBI 分数的交叉表。我们通过将医生的实际 MBI 分数与通过联系预测的分数进行比较来评估结果的准确性,并使用生成的交叉表描述与相同 MBI 子量表相关联的量表中最接近的切点等价物。

主要结果

IRT 联系产生了最准确的结果,并用于创建将(1)PFI 工作倦怠(PFI-WE)和 MZSIB 分数映射到 MBI 情绪耗竭(MBI-EE)分数,以及(2)PFI 人际脱节(PFI-ID)分数映射到 MBI 去人格化(MBI-DP)分数的交叉表。常用的 MBI-EE 原始分数切点≥27 与各自的 PFI-WE 和 MZSIB 原始分数切点≥7 和≥3 最接近。常用的 MBI-DP 原始分数切点≥10 与 PFI-ID 原始分数切点≥9 最接近。

结论

我们的研究结果使使用 PFI 或 MZSIB 的医疗机构能够将群体得分与历史、地区或国家 MBI 得分进行比较(反之亦然)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91cd/8904666/78c0b9121897/11606_2021_6661_Fig1_HTML.jpg

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