Evidence map›Paper›PMID 38152498›Full record

ArticleData in brief2024

Lifespan trajectories of risk preference, impulsivity, and self-control: A dataset containing self-report, informant-report, behavioral, hormone and functional neuroimaging measures from a cross-sectional human sample.

Loreen Tisdall, Simon Mugume, David Kellen, Rui Mata

Abstract read
In one paragraph

Article in Data in brief, 2024. 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. Increased Brain-Age Gap in Young Adults With Psychotic Experiences.Biological psychiatry global open science · 2026
    Article
  2. Convergence of Age Differences in Risk Preference, Impulsivity, and Self-Control: A Multiverse Analysis.The journals of gerontology. Series B, Psychological sciences and social sciences · 2024
    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

4 authors.

Loreen TisdallCenter for Cognitive and Decision Sciences, Faculty of Psychology, University of Basel, Switzerland.
Simon MugumeCenter for Cognitive and Decision Sciences, Faculty of Psychology, University of Basel, Switzerland.
David KellenCollege of Arts & Sciences, Syracuse University, USA.
Rui MataCenter for Cognitive and Decision Sciences, Faculty of Psychology, University of Basel, Switzerland.

Funding

Research Network on Decision Neuroscience and AgingR24AG076847 · NIA · UNIVERSITY OF TEXAS DALLAS · PI Nichole Lighthall, Kendra Leigh Seaman · 2022 to 2026
$1.9M
NIA NIH HHS R24 AG076847
6 · The paper itself

Abstract

This paper describes data collected from a cross-sectional convenience sample of 200 healthy human volunteers between 16 and 81 years of age. We assembled an extensive battery of measures of risk preference, impulsivity, and self-control, as well as a range of demographic and cognitive measures, Crucially, we adopted different measure categories, including self-reports, informant reports, behavioral measures, and biological measures (hormones, brain function) to capture individual differences, and adopted a within-participant design. Data collection took place over multiple sessions. First, participants completed a laboratory session at the university during which we collected computer-assisted self-report measures (i.e., standardized questionnaires) as well as behavioral measures using computerized tasks. Second, participants independently completed a home session that included the completion of self-report measures, and the collection of saliva samples. In parallel, we acquired informant reports from up to three individuals nominated by the study participants. Third, participants completed a final session at the local hospital during which we collected structural and functional neuroimaging data, as well as further self-report measures. The data was collected to address questions concerning the developmental trajectories of risk preference and related constructs while assessing the impact of the assessment method; however, we invite fellow researchers to benefit from and further explore the data for research on decision-making under risk and uncertainty in general, and to apply novel analytical approaches (e.g., machine-learning applications to the neuroimaging data). Combining a large set of measures with a within-participant design affords a wealth of opportunities for further insights and a more robust evidence base supporting current theorizing on (age-related) differences in risk preference, impulsivity, and self-control.

Indexed as

AgingBalloon analogue risk taskDelay discountingfMRIMixed gamblesPropensityRisk takingTaskTestosterone

Identifiers

PMID38152498
PMCPMC10751829

What OpenQuestion holds

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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.