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.
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.
| Original language | English |
|---|---|
| Pages (from-to) | 105-116 |
| Number of pages | 12 |
| Journal | Journal of Clinical Epidemiology |
| Volume | 98 |
| Early online date | 21 Feb 2018 |
| DOIs | |
| Publication status | Published - 1 Jun 2018 |
Bibliographical note
The Complex Reviews Support Unit is funded by the National Institute for Health Research (project number 14/178/29). The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health.Acknowledgments
Research assistant costs for data collection on the original Cochrane review were supported by small grants from the British Academy, UK and Manchester Center for Health Psychology, University of Manchester, UK.
The authors would like to thank our co-authors on the original Cochrane review who contributed to the collection of data used in the present secondary analysis: Anne Manyande, Julie Bruce, Claus V€ogele, Lucie Byrne-Davis, Mary Unsworth and Christian Osmer.
Keywords
- network meta-analysis
- complex interventions
- psychological preparation
- surgery
- Bayesian
- Component
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Neil Scott
- School of Medicine, Medical Sciences & Nutrition, Applied Health Sciences - Senior Research Fellow
- School of Medicine, Medical Sciences & Nutrition, Medical Statistics
- Institute of Applied Health Sciences
Person: Academic Related - Research