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临床测量工具评分选项的批判性综述。

A critical review of scoring options for clinical measurement tools.

作者信息

Avila Maria Laura, Stinson Jennifer, Kiss Alex, Brandão Leonardo R, Uleryk Elizabeth, Feldman Brian M

机构信息

Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Ontario, Canada.

出版信息

BMC Res Notes. 2015 Oct 28;8:612. doi: 10.1186/s13104-015-1561-6.

DOI:10.1186/s13104-015-1561-6
PMID:26510822
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4624594/
Abstract

BACKGROUND

The aim of this paper is twofold: (1) to describe the fundamental differences between formative and reflective measurement models, and (2) to review the options proposed in the literature to obtain overall instrument summary scores, with a particular focus on formative models.

METHODS

An extensive literature search was conducted using the following databases: MEDLINE, EMBASE, PsycINFO, CINAHL and ABI/INFORM, using "formative" and "reflective" as text words; relevant articles' reference lists were hand searched.

RESULTS

Reflective models are most frequently scored by means of simple summation, which is consistent with the theory underlying these models. However, our review suggests that formative models might be better summarized using weighted combinations of indicators, since each indicator captures unique features of the underlying construct. For this purpose, indicator weights have been obtained using choice-based, statistical, researcher-based, and combined approaches.

CONCLUSION

Whereas simple summation is a theoretically justified scoring system for reflective measurement models, formative measures likely benefit from the use of weighted scores that preserve the contribution of each of the aspects of the construct.

摘要

背景

本文的目的有两个:(1)描述形成性测量模型和反思性测量模型之间的根本差异;(2)回顾文献中提出的获取总体量表汇总分数的方法,尤其侧重于形成性模型。

方法

使用以下数据库进行广泛的文献检索:MEDLINE、EMBASE、PsycINFO、CINAHL和ABI/INFORM,以“形成性”和“反思性”作为文本词;对相关文章的参考文献列表进行手工检索。

结果

反思性模型最常通过简单求和来计分,这与这些模型的基础理论一致。然而,我们的综述表明,形成性模型可能使用指标的加权组合进行更好的汇总,因为每个指标都捕捉了潜在构念的独特特征。为此,已使用基于选择、统计、基于研究者和组合的方法获得指标权重。

结论

虽然简单求和是反思性测量模型在理论上合理的计分系统,但形成性测量可能受益于使用加权分数,这种分数保留了构念各方面的贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbe/4624594/6bc464e4dfd2/13104_2015_1561_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbe/4624594/2f2fbdedaa17/13104_2015_1561_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbe/4624594/2ca3d4d46f72/13104_2015_1561_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbe/4624594/6bc464e4dfd2/13104_2015_1561_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbe/4624594/2f2fbdedaa17/13104_2015_1561_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbe/4624594/2ca3d4d46f72/13104_2015_1561_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dbe/4624594/6bc464e4dfd2/13104_2015_1561_Fig3_HTML.jpg

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