A Model of Cross-Disciplinary Communication for Collaborative Statisticians: Implications for Curriculum Design

Autor/inn/en	Samsa, Gregory P.; LeBlanc, Thomas W.; Locke, Susan C.; Troy, Jesse D.; Pomann, Gina-Maria
Titel	A Model of Cross-Disciplinary Communication for Collaborative Statisticians: Implications for Curriculum Design
Quelle	In: Journal of Curriculum and Teaching, 7 (2018) 2, S.1-11 (11 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1927-2677
Schlagwörter	Curriculum Design; Interdisciplinary Approach; Statistics; Biomedicine; Case Studies; Cooperation; Communication (Thought Transfer); Patients; Physicians; Medical Services; Cancer; Drug Therapy; Interpersonal Communication; Teaching Methods + Suchen Sie Ihr Suchwort? Lehrplangestaltung; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Statistik; Biomedizin; Case study; Fallstudie; Case Study; Co-operation; Kooperation; Communication; thought; Kommunikation; Gedanke; Patient; Physician; Doctor; Arzt; Carcinoma; Karzinom; Krebs (med); Krebserkrankung; Interpersonale Kommunikation; Teaching method; Lehrmethode; Unterrichtsmethode
Abstract	The ability to bridge multiple disciplines is critical to the successful practice of collaborative statistics, yet the literature on statistical education devotes relatively little attention to how this skill can be taught. Our goal here is to describe a general conceptual framework within which a curriculum on communication and leadership could ultimately be organized. The primary research question pertains to whether an actionable model of cross-disciplinary communication for collaborative statisticians can be developed, and our task here is to describe such a model and also to illustrate its use. Within this model most communications either share or request information. For example, statisticians might provide information about statistics (e.g., specific statistical approaches, general statistical principles), comment on the clinician's understanding of statistics, share their understanding of clinical content, and request information (e.g., about clinical content, the design and execution of the study being discussed, etc.). Clinical investigators contribute an analogous set of components. In addition, a critical element to the interaction is the higher-level task of developing a mutually understood agreement about the work to be performed: in essence, proposing and negotiating such an agreement. The model is illustrated using a case study, and general qualitative feedback from investigators who performed the case study was obtained, commenting on both successful and unsuccessful interactions with statisticians. Implications for curriculum development are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01