Evidence map›Paper›PMID 33140229›Full record

ArticlePsychonomic bulletin & review2021

Default sensitivity in attempts at social influence.

Craig R M McKenzie, Lim M Leong, Shlomi Sher

Abstract read
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In one paragraph

Article in Psychonomic bulletin & review, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Craig R M McKenzieRady School of Management, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0553, USA. cmckenzie@ucsd.edu.
Lim M LeongDepartment of Psychology, University of California San Diego, La Jolla, CA, 92093, USA.ORCID https://orcid.org/0000-0002-9098-9718
Shlomi SherDepartment of Psychological Science, Pomona College, Claremont, CA, 91711, USA.

Funding

James S. McDonnell Foundation Scholar Award
6 · The paper itself

Abstract

While past research has demonstrated the power of defaults to nudge decision makers toward desired outcomes, few studies have examined whether people understand how to strategically set defaults to influence others' choices. A recent paper (Zlatev et al. Proceedings of the National Academy of Sciences, 114, 13643-13648, 2017) found that participants exhibited "default neglect," or the failure to set optimal defaults at better than chance levels. However, we show that this poor performance is specific to the complex and potentially confusing paradigms they used, and does not reflect a general lack of understanding regarding defaults. Using simple scenarios, Experiments 1A and 1B provide clear evidence that people can optimally set defaults given their goals. In Experiment 2, we conducted a direct and conceptual replication of one of Zlatev et al.'s original studies, which found that participants selected the optimal default significantly less than chance. While our direct replication found results similar to those in the original study, our conceptual replication, which simplified the task, instead found the opposite. Experiment 3 manipulated the framing of the option attributes, which were confounded with the default in the original study, and found that the original framing led to below-chance performance while the alternate framing led to above-chance performance. Together, our results cast doubt on the prevalence and generalizability of default neglect, and instead suggest that people are capable of setting optimal defaults in attempts at social influence.

Indexed as

Choice BehaviorGoalsSocial BehaviorAdultFemaleHumansMaleChoice architectureDecision makingDefault effectNudge

Identifiers

What OpenQuestion holds

Textmetadata
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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.