A scoping review of approaches for measuring ‘interdependent’ collaborative performances

二元体 中心性 心理学 相互依存 医疗保健 医学教育 领域(数学) 应用心理学 社会心理学 医学 社会学 社会科学 经济增长 数学 组合数学 经济 纯数学
作者
Stefanie S. Sebok‐Syer,Jennifer M. Shaw,Farah Asghar,Michael J. Panza,Mark D. Syer,Lorelei Lingard
出处
期刊:Medical Education [Wiley]
卷期号:55 (10): 1123-1130 被引量:21
标识
DOI:10.1111/medu.14531
摘要

Individual assessment disregards the team aspect of clinical work. Team assessment collapses the individual into the group. Neither is sufficient for medical education, where measures need to attend to the individual while also accounting for interactions with others. Valid and reliable measures of interdependence are critical within medical education given the collaborative manner in which patient care is provided. Medical education currently lacks a consistent approach to measuring the performance between individuals working together as part of larger healthcare team. This review's objective was to identify existing approaches to measuring this interdependence.Following Arksey & O'Malley's methodology, we conducted a scoping review in 2018 and updated it to 2020. A search strategy involving five databases located >12 000 citations. At least two reviewers independently screened titles and abstracts, screened full texts (n = 161) and performed data extraction on twenty-seven included articles. Interviews were also conducted with key informants to check if any literature was missing and assess that our interpretations made sense.Eighteen of the twenty-seven articles were empirical; nine conceptual with an empirical illustration. Eighteen were quantitative; nine used mixed methods. The articles spanned five disciplines and various application contexts, from online learning to sports performance. Only two of the included articles were from the field of Medical Education. The articles conceptualised interdependence of a group, using theoretical constructs such as collaboration synergy; of a network, using constructs such as degree centrality; and of a dyad, using constructs such as synchrony. Both descriptive (eg social network analysis) and inferential (eg multi-level modelling) approaches were described.Efforts to measure interdependence are scarce and scattered across disciplines. Multiple theoretical concepts and inconsistent terminology may be limiting programmatic work. This review motivates the need for further study of measurement techniques, particularly those combining multiple approaches, to capture interdependence in medical education.
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