Evidence map›Paper›PMID 35421151›Full record

ArticlePloS one2022

Profiling dynamic decision-makers.

Konrad Grabiszewski, Alex Horenstein

Abstract read
In one paragraph

Article in PloS one, 2022. 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

2 authors.

Konrad GrabiszewskiMohammed Bin Salman College, King Abdullah Economic City, Saudi Arabia.
Alex HorensteinDepartment of Economics, University of Miami, Coral Gables, FL, United States of America.ORCID 0000-0002-6044-4266

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

From CEOs confronting competition to children playing board games, our professional and personal lives are full of dynamic decisions. Naturally, while playing the role of a decision-maker, people differ. To comprehend and analyze how they differ, first it is necessary to construct a profiling method that classifies dynamic decision-makers. Developing such a method is the main objective of our article. We equate dynamic decision-making with backward inducting. We rely on response times to construct the profiles. Our method has both descriptive power and predictive power: a subject's profile resembles her reasoning process and forecasts the likelihood of her correctly backward inducting. To test the proposed profiling method, we use data generated by 22 different finite dynamic scenarios from the mobile app Blues and Reds. Our sample consists of 35,826 observations from 6,463 subjects located in 141 countries. We construct the profiles of our subjects, and, in a variety of exercises supported by an array of robustness checks, we successfully establish the predictive power of our profiling method.

Indexed as

Decision MakingHealth ServicesChildFemaleHumans

Identifiers

PMID35421151
PMCPMC9009624

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.