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AimsTo explore decision control preferences and decisional conflicts and to analyse their association among the surrogate decision makers in the intensive care unit.DesignThe study carried out a cross‐sectional survey among the surrogates.MethodsThe participants were 115 surrogate decision makers of critical patients, from August to September 2019. A Chi‐squared test and logistic regression were used to assess decision control preferences and decisional conflicts, and Spearman's rank correlation coefficient was employed to examine their association.ResultsOf the 115 surrogate decision makers, 51.3% preferred a collaborative role, and 63.48% were somewhat unsure about making decisions. Logistic regression analysis identified decision control preferences was associated with surrogates’ age, education level, and personality traits, while decisional conflicts was associated with surrogates’ age, education level, character, medical expense burden, and Acute Physiology and Chronic Health Evaluation‐II score. Cohen's kappa statistics showed a bad concordance of decision‐making expectations and actuality, with kappa values of 0.158 (p < .05). Wherein surrogates who experienced discordance between their preferred and actual roles, have relatively higher decisional conflicts.ConclusionThis study identified individual differences of surrogate decision makers in decision control preferences and decisional conflicts. These results imply that incorporation of the individual decision preferences and communication styles into care plans is an important first step to develop high quality decision support.ImpactThis research is a contribution to the limited study on decision control preferences and decisional conflicts among surrogate decision makers of critically ill patients. Moreover based on the investigation of understanding the status and related factors of decision preferences and decisional conflicts set the stage for developing effective decision support interventions.

Background: An emerging approach to prevent delirium in an intensive care unit is the use of risk prediction models. At present, there is no scientific comparison of the predictive effect of the prediction model. This systematic review and meta-analysis aimed to compare the performance of available delirium risk prediction models for intensive care units.Methods: As of June 1st, 2019, articles on delirium prediction models of the intensive care patients were