教练忠诚量表(CFS)

IF 1.1 4区 医学 Q3 EDUCATION, SPECIAL Infants & Young Children Pub Date : 2023-01-01 DOI:10.1097/IYC.0000000000000231
H. Meadan, James D. Lee, Michelle M. Sands, Moon Y. Chung, Pau García-Grau
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引用次数: 0

摘要

对发育障碍或发育迟缓儿童的有效支助取决于家庭与专业人员之间以及专业人员之间的成功合作。多年来,研究人员和专业人员一直在指导护理人员和其他专业人员对残疾儿童实施循证实践。然而,相关文献的空白表明,需要一个有效的、可靠的、基于观察的测量工具来准确评估不同学科、内容和背景的教练。教练保真度量表(CFS)旨在评估专业人员实施一套教练实践的保真程度。本探索性研究的目的是介绍CFS作为教练忠诚度的观察工具,并试点其心理测量学。在分析的基础上,中心制定了有效和可靠的措施,以衡量为残疾家庭和儿童提供服务的不同专业人员的指导忠实度。
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The Coaching Fidelity Scale (CFS)
Effective support for children with developmental disabilities or delays is dependent on the successful collaboration between families and professionals and among professionals. For years, researchers and professionals have been coaching caregivers and other professionals to implement evidence-based practices with children with disabilities. However, a gap in the relevant literature suggests that a valid, reliable, and observation-based measurement tool is needed to accurately assess coaching across different disciplines, contents, and contexts. The Coaching Fidelity Scale (CFS) was designed to evaluate the extent to which professionals implement a set of coaching practices with fidelity. The purpose of this exploratory study was to introduce the CFS as an observational tool for coaching fidelity and to pilot its psychometrics. On the basis of the analyses, the CFS produced valid and reliable measures of coaching fidelity of different professionals who provide services to families and children with disabilities.
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来源期刊
CiteScore
1.90
自引率
9.10%
发文量
24
期刊介绍: Infants & Young Children is an interdisciplinary journal focusing on vulnerable children from birth to five years of age and their families. Of special interest are articles involving innovative interventions, summaries of important research developments and their implications for practice, updates for high priority topic areas, balanced presentations of controversial issues, and articles that address issues involving policy, professional training, new conceptual models, and related matters. Although data are often presented primarily to illustrate points, some types of data-based articles may be appropriate.
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