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物理康复治疗中治疗联盟的评估:RASCH 分析。

Assessment of the therapeutic alliance in physical rehabilitation: a RASCH analysis.

机构信息

Musculoskeletal Division, The George Institute for Global Health, Sydney, Australia.

出版信息

Disabil Rehabil. 2012;34(3):257-66. doi: 10.3109/09638288.2011.606344.

DOI:10.3109/09638288.2011.606344
PMID:21999716
Abstract

PURPOSE

To investigate the psychometric properties of the Working Alliance Inventory Theory of Change Inventory (WATOCI) in physical rehabilitation.

METHODS

RASCH analysis was used to examine the validity, internal consistency, reliability and discriminative properties of the 16-item WATOCI. Data was obtained from a randomized controlled trial, which employed the WATOCI to measure the alliance between physical therapists and patients with chronic low back pain.

RESULTS

The results indicated that 7 items on the 16-item WATOCI should need to be improved for use in physiotherapy settings. The resulting 9-item version of the WATOCI was found to be a uni-dimensional tool for measuring alliance, however, demonstrated a ceiling effect.

CONCLUSIONS

There are several items in the WATOCI that require re-wording and/or re-contextualization prior to its use in clinical practice. Specifically, items relating more to the element social interaction did not discriminate well in this population and one solution may be to provide a therapy-specific context. Items regarding how well the patient understood the purpose of the treatment discriminated best between patients and this area is recommended for further development in the tool's assessment. It is recommended that future research address these issues prior to its use in clinical settings.

摘要

目的

调查工作联盟量表变化理论量表(WATOCI)在物理康复中的心理测量特性。

方法

使用 RASCH 分析来检验 16 项 WATOCI 的有效性、内部一致性、可靠性和区分特性。数据来自一项随机对照试验,该试验使用 WATOCI 来衡量物理治疗师与慢性腰痛患者之间的联盟。

结果

结果表明,16 项 WATOCI 中的 7 项需要改进,以便在物理治疗环境中使用。由此产生的 9 项 WATOCI 版本被认为是一种用于测量联盟的单维工具,但表现出上限效应。

结论

WATOCI 中有几个项目需要重新措辞和/或重新调整语境,然后才能在临床实践中使用。具体来说,与社会互动元素更相关的项目在该人群中区分度不高,一个解决方案可能是提供治疗特定的背景。关于患者对治疗目的理解程度的项目在患者之间的区分度最好,建议在工具评估中进一步开发这一领域。建议在将其用于临床环境之前,未来的研究解决这些问题。

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