Summary
Objective
Shared decision making (SDM) between patient and physician is an interpersonal process.
Most SDM measures use the view of one party (patient, physician or observer) as a
proxy to capture this process although these views typically diverge. This study suggests
the compound measure SDMMASS (SDM Meeting its concept's ASSumptions) integrating these three perspectives in one single index.
Methods
SDMMASS was derived theoretically and compared empirically to unilateral perspectives of
patients, physicians and observers by application to a data set of 10 physicians (40
consultations) receiving an SDM training.
Results
The constituting parts of SDMMASS were highly reliable (Cronbach's alpha .94; interrater reliability .74-.87). Unilateral
appraisal of training effects was divergent. SDMMASS revealed no effect.
Conclusion
SDMMASS combines noteworthy information about SDM processes from different viewpoints and
thereby delivers plausible assessments. It could overcome immanent shortcomings of
unilateral approaches. However, it is a complex measure needing further validation.
Zusammenfassung
Ziel
Shared Decision Making (SDM) zwischen Patient und Arzt ist ein interpersonaler Prozess.
Die meisten SDM-Messinstrumente verwenden die Sichtweise einer der Parteien Patient,
Arzt und Beobachter als Surrogatparameter für diesen Prozess, obwohl die unilateralen
Maße typischerweise divergieren. Diese Studie stellt das SDM-Verbundmaß SDMMASS (SDM Meeting its concept's ASSumptions) vor, das diese drei Perspektiven in einem einzigen Index bündelt.
Methoden
SDMMASS wurde theoretisch hergeleitet und anhand eines bestehenden Datensatzes von 10 Ärzten
(40 Konsultationen), die ein SDM-Training durchliefen, mit den unilateralen Perspektiven
von Patient, Arzt und Beobachter empirisch verglichen.
Ergebnisse
Die konstituierenden Teile von SDMMASS waren hoch reliabel (Cronbach's alpha .94; Interrater-Reliabilität .74 bis .87).
Die unilaterale Bewertung von Trainingseffekten war divergent. SDMMASS offenbarte keinen Effekt.
Schlussfolgerung
SDMMASS kombiniert notwendige Informationen über SDM-Prozesse aus unterschiedlichen Blickwinkeln
und liefert damit plausible Ergebnisse. Es könnte immanente Schwächen unilateraler
Ansätze überwinden. Allerdings ist es ein in der Anwendung komplexes Maß, das weiterer
Validierung bedarf.
Key words
Schlüsselwörter
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© 2012 Published by Elsevier Inc.
