Reducing plastic waste: A meta-analysis of influences on behaviour and interventions

塑料废料 荟萃分析 心理干预 废物管理 环境科学 工程类 心理学 医学 精神科 内科学
作者
Ayşe Lisa Allison,Harriet M. Baird,Fabiana Lorencatto,Thomas L. Webb,Susan Michie
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:380: 134860-134860 被引量:34
标识
DOI:10.1016/j.jclepro.2022.134860
摘要

Eliminating plastic waste relies, in part, on changing human behaviour. This review aimed to (a) use the AACTT (Action-Actor-Context-Target-Time) framework to identify and categorise relevant behaviours, (b) use the COM-B (Capability-Opportunity-Motivation-Behaviour) model to identify, categorise and evaluate variables that might be associated with these behaviours, (c) use the Behaviour Change Wheel and the Behaviour Change Techniques Taxonomy to identify, categorise and evaluate the nature of interventions. A systematic literature search identified 60 studies of behaviour relating to plastic waste. Meta-analysis was used to quantify (i) the strength and direction of the relationship between variables and behaviour and (ii) the impact of intervention components on changes in behaviour. Studies focused predominantly on the general public (actors), recycling (action), shopping (context), and a limited range of plastic waste items. Variables reflecting capability, opportunity, and motivation all had medium-strength associations with behaviour. The intervention types associated with the strongest changes in behaviour were 'persuasion', 'enablement' and 'environmental restructuring'. The policy options associated with strongest changes in behaviour were 'communications and marketing', 'environmental and social planning' and 'service provision'. Interventions targeting 'psychological capability' had a negative effect on plastic waste reducing behaviours while interventions targeting 'physical opportunity' and 'reflective motivation' had the strongest positive effects. All identified behaviour change techniques had medium to large effects on changes in behaviour. Taken together, the findings provide clear directions for future research and efforts to reduce plastic waste.
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