How and why do financial incentives contribute to helping people stop smoking? A realist review protocol

Abstract

IntroductionSmoking is harmful to human health and programmes to help people stop smoking are key public health efforts that improve individual and population health outcomes. Research shows that financial incentives improve the success of stop smoking programmes. However, a better understanding of how they work is needed to better inform policy and to support building capability for implementation.The aims of this study: (1) To review the international literature to understand: How, why, in what circumstances and for whom financial incentives improve the success of stop smoking interventions among general population groups and among pregnant women. (2) To provide recommendations for how to best use financial incentives in efforts to promote smoking cessation.Methods and analysisA realist review of published international literature will be undertaken to understand how, why, for whom and in which circumstances financial incentives contribute to success in stopping smoking for general population groups and among pregnant women. Systematic searches were undertaken on 16 February 2022 of five academic databases: MEDLINE (ovid), Embase.com, CIHAHL, Scopus and PsycINFO. Iterative searching using citation tracking and of grey literature will be undertaken as needed. Using Pawson and Tilley’s iterative realist review approach, data collected will be screened, selected, coded, analysed and synthesised into a set of explanatory theoretical findings.Ethics and disseminationEthical approval is not required for this review as data sources to be included are previously published. The study will provide important findings for policy-makers and health system leaders to guide the development of stop smoking services which use incentives, for example, as part of the Health Service Executive’s Tobacco Free Programme in Ireland. Understanding how contextual factors impact implementation and programmatic success is key to developing a more effective public health approach to stop smoking. Our dissemination strategy will be developed with our stakeholders.PROSPERO registration numberCRD42022298941.

Application of cloud accounting in enterprise financial forecasting and decision making in the era of big data

“…In contrast to single-view clustering algorithms, extant multi-view clustering techniques are divided into three categories based on multi-view learning methods: standard co-training cloud accounting clustering algorithms, multi-core learning clustering algorithms, and subspace cloud accounting data learning clustering algorithms. Although there are significant differences between the different approaches that combine multiple perspectives with improving learning performance, they all have in common the use of consensus criteria or complementary criteria to ensure that multiperspective learning can be successful [23][24]. Therefore, combining multi-view clustering techniques with cloud accounting, which considers both information from individual views and complementary information that depends on each other, can make clustering results more accurate.…”