Predicting Decisional Conflict: Anxiety and Depression in Shared Decision Making

Item Type:	Dataset
Title:	Predicting Decisional Conflict: Anxiety and Depression in Shared Decision Making
Date:	5 November 2020
Creator:	Köther, Anja K. ; Alpers, Georg W. ; Büdenbender, Björn ; Lenhart, Maximilian ; Michel, Maurice S. ; Kriegmair, Maximilian C.
Divisions:	School of Social Sciences > Klinische u. Biologische Psychologie u. Psychotherapie (Alpers 2010-)

DDC Classification:	150 Psychology 610 Medicine and health
Keywords:	shared decision making, emotional distress, decisional conflict, anxiety, depression
Abstract:	Emotional distress can be a potential barrier to shared decision making (SDM), yet affect is typically not systematically assessed in medical consultation. We examined whether urological patients report anxiety or depression prior to a consultation and if emotional distress predicts decisional conflict thereafter. We recruited a large sample of urological outpatients (N = 397) with a range of different diagnoses (42% oncological). Prior to a medical consultation, patients filled in questionnaires, including the Hospital Anxiety and Depression Scale. After the consultation, patients completed the Decisional Conflict Scale. We scored the rate of anxiety and depression in our sample and conducted multiple regression analysis to examine if emotional distress before the consultation predicts decisional conflict thereafter. About a quarter of patients reported values at or above cut-off for clinically relevant emotional distress. Emotional distress significantly predicted a higher degree of decisional conflict. There were no differences in emotional distress between patients with and without uro-oncological diagnosis. Emotional distress is common in urology patients – oncological as well as non-oncological. It predicts decisional conflict after physician consultation. Emotional distress should be systematically assessed in clinical consultations. This may improve the process and outcome of SDM.

URL:	https://madata.bib.uni-mannheim.de/347/
DOI:	https://doi.org/10.7801/347
Availability (Controlled):	Delivery
Availability:	Send a request to alpers@uni-mannheim.de

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Depositing User:	osidata
Date Deposited:	07 Nov 2020 19:15
Last Modified:	29 Feb 2024 20:33

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