Evidence map›Paper›PMID 33834382›Full record

ArticleMemory & cognition2021

The simultaneous recognition of multiple words: A process analysis.

Anne Voormann, Mikhail S Spektor, Karl Christoph Klauer

Abstract read
In one paragraph

Article in Memory & cognition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Anne VoormannDepartment of Psychology, University of Freiburg, Engelbergerstraße 41, Freiburg, 79106, Germany. anne.voormann@psychologie.uni-freiburg.de.ORCID http://orcid.org/0000-0002-5024-5116
Mikhail S SpektorDepartment of Psychology, University of Freiburg, Engelbergerstraße 41, Freiburg, 79106, Germany.
Karl Christoph KlauerDepartment of Psychology, University of Freiburg, Engelbergerstraße 41, Freiburg, 79106, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In everyday life, recognition decisions often have to be made for multiple objects simultaneously. In contrast, research on recognition memory has predominantly relied on single-item recognition paradigms. We present a first systematic investigation into the cognitive processes that differ between single-word and paired-word tests of recognition memory. In a single-word test, participants categorize previously presented words and new words as having been studied before (old) or not (new). In a paired-word test, however, the test words are randomly paired, and participants provide joint old-new categorizations of both words for each pair. Across two experiments (N = 170), we found better memory performance for words tested singly rather than in pairs and, more importantly, dependencies between the two single-word decisions implied by the paired-word test. We extended two popular model classes of single-item recognition to paired-word recognition, a discrete-state model and a continuous model. Both models attribute performance differences between single-word and paired-word recognition to differences in memory-evidence strength. Discrete-state models account for the dependencies in paired-word decisions in terms of dependencies in guessing. In contrast, continuous models map the dependencies on mnemonic (Experiment 1 & 2) as well as on decisional processes (Experiment 2). However, in both experiments, model comparison favored the discrete-state model, indicating that memory decisions for word pairs seem to be mediated by discrete states. Our work suggests that individuals tackle multiple-item recognition fundamentally differently from single-item recognition, and it provides both a behavioral and model-based paradigm for studying multiple-item recognition.

Indexed as

Recognition, PsychologyHumansMemoryMental RecallCognitive modelingContinuous modelsDiscrete-state modelsRecognition memory

Identifiers

PMID33834382
PMCPMC8081710

What OpenQuestion holds

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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.