Evidence map›Paper›PMID 31222630›Full record

ArticleMemory & cognition2019

Validating the relation-monitoring task as a measure of relational integration and predictor of fluid intelligence.

Joel E Bateman, Kate A Thompson, Damian P Birney

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Memory & cognition, 2019. 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

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Joel E BatemanSchool of Psychology, University of Sydney, Sydney, New South Wales, Australia. jbat2136@uni.sydney.edu.au.ORCID http://orcid.org/0000-0001-8083-4213
Kate A ThompsonSchool of Psychology, University of Sydney, Sydney, New South Wales, Australia.
Damian P BirneySchool of Psychology, University of Sydney, Sydney, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relation-monitoring task (RMT) has demonstrated a remarkable ability to predict higher-order cognitive abilities such as fluid intelligence, despite its apparent simplicity: It requires no storage over time and no advanced mental manipulation. Instead, the task is theorized to measure relational integration: the process of constructing mental relations between independent elements. Although several studies have established a link between the RMT and fluid intelligence, few studies have investigated the task parameters that contribute to the task's ability to predict higher-order performance. In the present experiment, we manipulated relational complexity and attentional-control demands by varying visual interference and the amount of new information presented on each trial. Even the most basic version of the task (loading primarily on relational integration) explained substantial variance in fluid intelligence, above and beyond the variance already predicted by traditional working memory tasks. We extended prior results by suggesting an incremental effect of attentional-control demands that contributes (but is not imperative) to the RMT's relationship with fluid intelligence. These findings support the relational integration hypothesis, the theory that what fundamentally limits fluid intelligence is the capacity for relational integration.

Indexed as

AdolescentAdultAttentionExecutive FunctionFemaleHumansIntelligenceMaleMemory, Short-TermNeuropsychological TestsPattern Recognition, VisualThinkingYoung AdultAttentionFluid intelligenceReasoningRelational integrationWorking memory

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.