Evidence map›Paper›PMID 32882904›Full record

ArticleJournal of Intelligence2020

Do Non-Decision Times Mediate the Association between Age and Intelligence across Different Content and Process Domains?

Mischa von Krause, Veronika Lerche, Anna-Lena Schubert, Andreas Voss

Abstract read
In one paragraph

Article in Journal of Intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Mischa von KrauseDepartment of Psychology, Heidelberg University, 69117 Heidelberg, Germany.ORCID 0000-0001-7424-1454
Veronika LercheDepartment of Psychology, Heidelberg University, 69117 Heidelberg, Germany.ORCID 0000-0002-4551-2339
Anna-Lena SchubertDepartment of Psychology, Heidelberg University, 69117 Heidelberg, Germany.ORCID 0000-0001-7248-0662
Andreas VossDepartment of Psychology, Heidelberg University, 69117 Heidelberg, Germany.

Funding

Deutsche Forschungsgemeinschaft GRK 2277Deutsche Forschungsgemeinschaft VO1288/2-2
6 · The paper itself

Abstract

In comparison to young adults, middle-aged and old people show lower scores in intelligence tests and slower response times in elementary cognitive tasks. Whether these well-documented findings can both be attributed to a general cognitive slow-down across the life-span has become subject to debate in the last years. The drift diffusion model can disentangle three main process components of binary decisions, namely the speed of information processing, the conservatism of the decision criterion and the non-decision time (i.e., time needed for processes such as encoding and motor response execution). All three components provide possible explanations for the association between response times and age. We present data from a broad study using 18 different response time tasks from three different content domains (figural, numeric, verbal). Our sample included people between 18 to 62 years of age, thus allowing us to study age differences across young-adulthood and mid-adulthood. Older adults generally showed longer non-decision times and more conservative decision criteria. For speed of information processing, we found a more complex pattern that differed between tasks. We estimated mediation models to investigate whether age differences in diffusion model parameters account for the negative relation between age and intelligence, across different intelligence process domains (processing capacity, memory, psychometric speed) and different intelligence content domains (figural, numeric, verbal). In most cases, age differences in intelligence were accounted for by age differences in non-decision time. Content domain-general, but not content domain-specific aspects of non-decision time were related to age. We discuss the implications of these findings on how cognitive decline and age differences in mental speed might be related.

Indexed as

cognitive agingdiffusion modelingintelligenceresponse time

Identifiers

PMID32882904
PMCPMC7555164

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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.