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Record W4400725716 · doi:10.1080/09658211.2024.2378870

Multifactorial Memory Questionnaire: a comparison of young and older adults

2024· article· en· W4400725716 on OpenAlexafffund
Adelaide Jensen, Alex W. Castro, Rui Hu, Héloïse Drouin, Sheida Rabipour, Marie-Ève Bégin-Galarneau, Vess Stamenova, Patrick S. R. Davidson

Bibliographic record

VenueMemory · 2024
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyDevelopmental psychologyCognitive psychology

Abstract

fetched live from OpenAlex

The Multifactorial Memory Questionnaire (MMQ; Troyer & Rich, [2002]. Psychometric properties of a new metamemory questionnaire for older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 57(1), P19–P27) is a widely used measure of subjective memory consisting of three scales: Satisfaction, Ability, and Strategies. Although subjective memory complaints are prevalent across different age groups, the factor structure and psychometric properties of the MMQ have yet to be examined in young adults. Here, we independently replicated the original MMQ factor structure in N = 408 young adults (YA) recruited from undergraduate courses and N = 327 older adults (OA) and, for the first time, assessed the age-invariance of the scale using measurement invariance testing. YAs made significantly higher ratings than OAs on MMQ-Satisfaction and MMQ-Strategies, indicating greater satisfaction with their memory and greater use of strategies, but the groups were similar on MMQ-Ability. The original MMQ factor structure was replicated in OAs but not in YAs, and age invariance was not supported. Future studies seeking to compare young and older adults could therefore consider either requesting modification of the MMQ for use with young adults or using a different scale.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.328
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes2
Has abstractyes

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