Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/22991
Appears in Collections:Faculty of Health Sciences and Sport Journal Articles
Peer Review Status: Refereed
Title: Optimisation of complex health interventions prior to a randomised controlled trial: a scoping review of strategies used
Authors: Levati, Sara
Campbell, Pauline
Frost, Rachael
Dougall, Nadine
Wells, Mary
Donaldson, Cam
Hagen, Suzanne
Contact Email: nadine.dougall@stir.ac.uk
Keywords: Complex interventions
Intervention development
Pre-trial
Optimisation
Modelling
Scoping review
Effectiveness
Acceptability
Issue Date: 15-Mar-2016
Publisher: BioMed Central
Citation: Levati S, Campbell P, Frost R, Dougall N, Wells M, Donaldson C & Hagen S (2016) Optimisation of complex health interventions prior to a randomised controlled trial: a scoping review of strategies used, Pilot and Feasibility Studies, 2, Art. No.: 17.
Abstract: Background  Many complex intervention trials fail to show an intervention effect. Although this may be due to genuine ineffectiveness, it may also be the result of sub-optimal intervention design, implementation failure or a combination of these. Given current financial constraints and the pressure to reduce waste and increase value in health services research, pre-trial strategies are needed to reduce the likelihood of design or implementation failure and to maximise the intervention’s potential for effectiveness. In this scoping review, we aimed to identify and synthesise the available evidence relating to the strategies and methods used to ‘optimise’ complex interventions at the pre-trial stage.  Methods  We searched MEDLINE, CINAHL, AMED, PsycINFO and ProQuest Nursing & Allied Health Source for papers published between January 2000 and March 2015. We included intervention development and optimisation studies that explored potential intervention weaknesses and limitations before moving to a definitive randomised controlled trial (RCT). Two reviewers independently applied selection criteria and systematically extracted information relating to the following: study characteristics; intervention under development; framework used to guide the development process; areas of focus of the optimisation process, methods used and outcomes of the optimisation process. Data were tabulated and summarised in a narrative format.  Results  We screened 3968 titles and 231 abstracts for eligibility. Eighty-nine full-text papers were retrieved; 27 studies met our selection criteria. Optimisation strategies were used for a range of reasons: to explore the feasibility and acceptability of the intervention to patients and healthcare professionals; to estimate the effectiveness and cost-effectiveness of different combinations of intervention components; and to identify potential barriers to implementation. Methods varied widely across studies, from interviews and focus groups to economic modelling and probability analysis.  Conclusions  The review identifies a range of optimisation strategies currently used. Although a preliminary classification of these strategies can be proposed, a series of questions remain as to which methods to use for different interventions and how to determine when the intervention is ready or ‘optimised enough’ to be tested in a RCT. Future research should explore potential answers to the questions raised, to guide researchers in the development and evaluation of more effective interventions.
Type: Journal Article
URI: http://hdl.handle.net/1893/22991
DOI Link: http://dx.doi.org/10.1186/s40814-016-0058-y
Rights: © Levati et al. 2016 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
Affiliation: Glasgow Caledonian University
Glasgow Caledonian University
Glasgow Caledonian University
NMAHP Research
NMAHP Research
Glasgow Caledonian University
Glasgow Caledonian University

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