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Component network meta-analysis identifies the most effective components of psychological preparation for adults undergoing surgery under general anaesthesia.

Component network meta-analysis identifies the most effective components of psychological preparation for adults undergoing surgery under general anaesthesia.
Author Information (click to view)

Freeman SC, Scott NW, Powell R, Johnston M, Sutton AJ, Cooper NJ,


Freeman SC, Scott NW, Powell R, Johnston M, Sutton AJ, Cooper NJ, (click to view)

Freeman SC, Scott NW, Powell R, Johnston M, Sutton AJ, Cooper NJ,

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Journal of clinical epidemiology 2018 02 21() pii S0895-4356(17)31137-X
Abstract
OBJECTIVE
To apply component network meta-analysis (CNMA) models to an existing Cochrane review of psychological preparation interventions for adults undergoing surgery and to extend the models to account for covariates to identify the most effective components for improving postoperative outcomes.

STUDY DESIGN AND SETTING
Interventions consisted of between one and four components of psychological preparation: procedural information, sensory information, behavioural instruction, cognitive interventions, relaxation and emotion-focused techniques. We used component network meta-analysis models to assess the effect of each component for three outcomes: length of stay, pain and negative affect.

RESULTS
We found evidence that the most effective component for reducing length of stay depends on the type of surgery and that relaxation may improve pain. There was insufficient evidence that individual components contributed to the overall reduction in negative affect but procedural and sensory information emerged as the most likely beneficial components. Overall, we were unable to identify any one component as the most effective across all three outcomes.

CONCLUSION
The CNMA method allowed us to address questions about the effects of specific components that could not be answered using standard Cochrane methodology.

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