Evidence map›Paper›PMID 37856553›Full record

Trial reportPloS one2023

Nudging policymakers on gendered impacts of policy.

Lindsay Blair Bochon, Janet Dean, Tanja Rosteck, Jiaying Zhao

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lindsay Blair BochonSauder School of Business, University of British Columbia, Vancouver, British Columbia, Canada.ORCID 0000-0002-6735-6453
Janet DeanSauder School of Business, University of British Columbia, Vancouver, British Columbia, Canada.
Tanja RosteckSauder School of Business, University of British Columbia, Vancouver, British Columbia, Canada.
Jiaying ZhaoDepartment of Psychology, University of British Columbia, Vancouver, British Columbia, Canada.ORCID 0000-0003-0902-4343

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the proliferation of nudge research in the last few decades, very little published work aims to nudge the behavior of policymakers. Here we explore the impact of a well-established nudge on policymakers in the Northwest Territories of Canada. In a pre-registered randomized controlled trial, we emailed an invitation to policymakers (N = 263) to attend an online briefing on gendered impacts of policy. In the treatment condition (N = 133), the invitation contained personal stories of two women whose lives were disproportionally impacted by public policies more than men. In the control condition (N = 130), the invitation did not contain such stories. After the briefing, we sent all participants in both conditions a link to a public pledge that they could sign. The pledge was to lead and advocate for equity-oriented policymaking. Contrary to our prediction, there was a small backfiring effect where policymakers in the treatment condition (3.0%) were less likely to attend the briefing than the control condition (7.7%). However, two policymakers (1.5%) in the treatment condition signed the public pledge compared to one (0.8%) in the control condition. The current findings reveal the limits of using personal stories as a nudge to influence policymakers. We discuss insights gained from this experiment and follow-up debriefings with policymakers on how to improve future behavioral interventions designed to nudge policymakers.

Indexed as

Public PolicyCanadaFemaleHumansMaleNorthwest Territories

Identifiers

PMID37856553
PMCPMC10586654

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.