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Cited by 349Pro-Environmental Behavior and AttitudesClimate Change Communication and PerceptionDecision-Making and Behavioral Economics

The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.

Meta-analysis of randomised controlled trials testing behavioural interventions to promote household action on climate change

Open access
Nisa, Claudia F., Bélanger, Jocelyn J., Schumpe, Birga M., Faller, Daiane G.·2019·Nature Communications
DOI 10.1038/s41467-019-12457-2PMC PMC6778105
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Abstract

No consensus exists regarding which are the most effective mechanisms to promote household action on climate change. We present a meta-analysis of randomised controlled trials comprising 3,092,678 observations, which estimates the effects of behavioural interventions holding other factors constant. Here we show that behavioural interventions promote climate change mitigation to a very small degree while the intervention lasts ( d = −0.093 95% CI −0.160, −0.055), with no evidence of sustained positive effects once the intervention ends. With the exception of recycling, most household mitigation behaviours show a low behavioural plasticity. The intervention with the highest average effect size is choice architecture (nudges) but this strategy has been tested in a limited number of behaviours. Our results do not imply behavioural interventions are less effective than alternative strategies such as financial incentives or regulations, nor exclude the possibility that behavioural interventions could have stronger effects when used in combination with alternative strategies.

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Crossref · 10.1038/s41467-019-12457-2

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Figures

Fig. 1 Duration of the behavioural interventions in weeks. Shows the distribution of intervention duration according to the number of weeks from the beginning to the conclusion of the experimental period
Fig. 1 Duration of the behavioural interventions in weeks. Shows the distribution of intervention duration according to the number of weeks from the beginning to the conclusion of the experimental periodCC BY · PubMed Central
Fig. 2 Funnel plot displaying the relationship between estimate quality and effect size. Each dot represents a study (e.g. measuring the effect of a certain behavioural intervention); the y-axis represents study precision (standard error) and the x-axis shows the study’s result (effect estimate). This scatterplot is used for the visual detection of systematic heterogeneity between studies. It assumes that studies with high precision will be plotted near the average (red line), and studies with low precision will be spread evenly on both sides of the average, creating a roughly funnel-shaped distribution. Deviation from this shape suggest small-study bias, which is the case here, with lower precision studies reporting stronger effects
Fig. 2 Funnel plot displaying the relationship between estimate quality and effect size. Each dot represents a study (e.g. measuring the effect of a certain behavioural intervention); the y-axis represents study precision (standard error) and the x-axis shows the study’s result (effect estimate). This scatterplot is used for the visual detection of systematic heterogeneity between studies. It assumes that studies with high precision will be plotted near the average (red line), and studies with low precision will be spread evenly on both sides of the average, creating a roughly funnel-shaped distribution. Deviation from this shape suggest small-study bias, which is the case here, with lower precision studies reporting stronger effectsCC BY · PubMed Central
Fig. 3 Cumulative meta-analysis. In cumulative meta-analysis, the pooled estimate of the treatment effect is updated each time the result from a new study is included. The circles in the plot represent the cumulative effect size at any given moment, that is, the average effect size resulting from the inclusion of studies up to a certain point. This allows tracking the accumulation of evidence on the effect of behavioural interventions over time
Fig. 3 Cumulative meta-analysis. In cumulative meta-analysis, the pooled estimate of the treatment effect is updated each time the result from a new study is included. The circles in the plot represent the cumulative effect size at any given moment, that is, the average effect size resulting from the inclusion of studies up to a certain point. This allows tracking the accumulation of evidence on the effect of behavioural interventions over timeCC BY · PubMed Central
Fig. 4 Sample size per experimental group in behavioural interventions targeting different types of behaviour. Shows how different household mitigation behaviours have been tested with interventions with a distinct number of observations
Fig. 4 Sample size per experimental group in behavioural interventions targeting different types of behaviour. Shows how different household mitigation behaviours have been tested with interventions with a distinct number of observationsCC BY · PubMed Central
Fig. 5 Sample size per experimental group in behavioural interventions using different strategies. Shows how different behavioural stimuli have been tested in interventions with a distinct number of observations
Fig. 5 Sample size per experimental group in behavioural interventions using different strategies. Shows how different behavioural stimuli have been tested in interventions with a distinct number of observationsCC BY · PubMed Central
Fig. 6 Type of intervention tested per mitigation behaviour. Shows how different mitigation behaviours have been targeted by distinct behavioural stimuli
Fig. 6 Type of intervention tested per mitigation behaviour. Shows how different mitigation behaviours have been targeted by distinct behavioural stimuliCC BY · PubMed Central

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Research works printed but not linked: 3

  1. US Department of Energy. Saving Water Saves Energy. Technical Report. https://www.osti.gov/servlets/purl/927020 (2006).
  2. Steichen, T. J., Egger, M. & Sterne, J. Modification of the metabias program. Stata Tech. Bull. 44, 3 (1998).
  3. Higgins, J. P. T. & Green, S. Cochrane Handbook for Systematic Reviews of Interventions, Vol. 4. Version 5.1.0 updated March 2011 (The Cochrane Collaboration, 2011).

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Metadata

Authors
Nisa, C. F., Bélanger, J. J., Schumpe, B. M., & Faller, D. G.
Affiliations
New York University Abu Dhabi (AE)
Corresponding author
Nisa, Claudia F.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-10-04
Volume
10
Issue
1
Pages
4545-4545
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-019-12457-2
PMC
PMC6778105
OpenAlex
W2978033587
Cited by
349
References
68
Citations by year
2026: 43 · 2025: 63 · 2024: 59 · 2023: 61 · 2022: 53 · 2021: 42 · 2020: 26 · 2019: 1
FWCI
3.93
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
York University
Topics
  • Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Pro-Environmental Behavior and Attitudes
  • Social Sciences › Sociology and Political Science › Climate Change Communication and Perception
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
Keywords
behavioral interventions, nudging, choice architecture, recycling, behavioral plasticity, intervention effectiveness, sustainable behavior, financial incentives, environmental regulation
MeSH terms
Adaptation, Psychological, Family Characteristics, Humans, Motivation, Randomized Controlled Trials as Topic, Behavior Control, Information Dissemination, Climate Change, Recycling

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