Systematic reviews are difficult to keep up to date, but failure to do so leads to a decay in review currency, accuracy, and utility. We are developing a novel approach to systematic review updating termed "Living systematic review" (LSR): systematic reviews that are continually updated, incorporating relevant new evidence as it becomes available. LSRs may be particularly important in fields where research evidence is emerging rapidly, current evidence is uncertain, and new research may change policy or practice decisions. We hypothesize that a continual approach to updating will achieve greater currency and validity, and increase the benefits to end users, with feasible resource requirements over time.

BackgroundOvereating and harmful alcohol and tobacco use have been linked to the aetiology of various non-communicable diseases, which are among the leading global causes of morbidity and premature mortality. As people are repeatedly exposed to varying sizes and shapes of food, alcohol and tobacco products in environments such as shops, restaurants, bars and homes, this has stimulated public health policy interest in product size and shape as potential targets for intervention.Objectives1) To assess the effects of interventions involving exposure to different sizes or sets of physical dimensions of a portion, package, individual unit or item of tableware on unregulated selection or consumption of food, alcohol or tobacco products in adults and children.2) To assess the extent to which these effects may be modified by study, intervention and participant characteristics.Search methodsWe searched CENTRAL, MEDLINE, EMBASE, PsycINFO, eight other published or grey literature databases, trial registries and key websites up to November 2012, followed by citation searches and contacts with study authors. This original search identified eligible studies published up to July 2013, which are fully incorporated into the review. We conducted an updated search up to 30 January 2015 but further eligible studies are not yet fully incorporated due to their minimal potential to change the conclusions.Selection criteriaRandomised controlled trials with between-subjects (parallel-group) or within-subjects (cross-over) designs, conducted in laboratory or field settings, in adults or children. Eligible studies compared at least two groups of participants, each exposed to a different size or shape of a portion of a food (including non-alcoholic beverages), alcohol or tobacco product, its package or individual unit size, or of an item of tableware used to consume it, and included a measure of unregulated selection or consumption of food, alcohol or tobacco.Data collection and analysisWe applied standard Cochrane methods to select eligible studies for inclusion and to collect data and assess risk of bias. We calculated study-level effect sizes as standardised mean differences (SMDs) between comparison groups, measured as quantities selected or consumed. We combined these results using random-effects meta-analysis models to estimate summary effect sizes (SMDs with 95% confidence intervals (CIs)) for each outcome for size and shape comparisons. We rated the overall quality of evidence using the GRADE system. Finally, we used meta-regression analysis to investigate statistical associations between summary effect sizes and variant study, intervention or participant characteristics.Main resultsThe current version of this review includes 72 studies, published between 1978 and July 2013, assessed as being at overall unclear or high risk of bias with respect to selection and consumption outcomes. Ninety-six per cent of included studies (69/72) manipulated food products and 4% (3/72) manipulated cigarettes. No included studies manipulated alcohol ...

BackgroundThe idea that behaviour can be influenced at population level by altering the environments within which people make choices (choice architecture) has gained traction in policy circles. However, empirical evidence to support this idea is limited, especially its application to changing health behaviour. We propose an evidence-based definition and typology of choice architecture interventions that have been implemented within small-scale micro-environments and evaluated for their effects on four key sets of health behaviours: diet, physical activity, alcohol and tobacco use.DiscussionWe argue that the limitations of the evidence base are due not simply to an absence of evidence, but also to a prior lack of definitional and conceptual clarity concerning applications of choice architecture to public health intervention. This has hampered the potential for systematic assessment of existing evidence. By seeking to address this issue, we demonstrate how our definition and typology have enabled systematic identification and preliminary mapping of a large body of available evidence for the effects of choice architecture interventions. We discuss key implications for further primary research, evidence synthesis and conceptual development to support the design and evaluation of such interventions.SummaryThis conceptual groundwork provides a foundation for future research to investigate the effectiveness of choice architecture interventions within micro-environments for changing health behaviour. The approach we used may also serve as a template for mapping other under-explored fields of enquiry.

This is a repository copy of The TIPPME intervention typology for changing environments to change behaviour.

Objective: To develop a web-based tool to automate the adjustment of estimates of costs drawn from previously published or unpublished studies to a specified target currency and price year. Methods: A web-based tool was programmed using C#, utilising GDP deflator index values and Purchasing Power Parities conversion rates produced by the International Monetary Fund and the Organisation for Economic Co-operation and Development. Results: Version 1.0 is available at http://eppi.ioe.ac.uk/costconversion/default.aspx Conclusions: The tool can be used as a first-line approach to cost adjustment in non-healthcare applications and as an optional approach in healthcare applications when use of more sophisticated methods is not feasible.