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Record W6907869611 · doi:10.25384/sage.c.6098071.v1

Development and validation of the Music Cognitive Test: A music-based cognitive screening test

2022· other· en· W6907869611 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionReliability (semiconductor)Cognitive testTest (biology)Cognitive InterventionIntervention (counseling)Cognitive remediation therapy

Abstract

fetched live from OpenAlex

Specific tools to measure the cognitive benefits of music therapy and music-rehabilitation training available to music therapists are few and empirically weak: they are mostly psychometrically unrefined or based on unclear tasks and scoring protocols; they do not take into consideration distinct cognitive functions or are based on exclusively observational protocols. To overcome these limitations, we developed a 15-min cognitive screening tool suitable for music therapists, Music Cognitive Test (MCT), which assesses cognitive abilities stimulated by music-making activities (e.g., attentional, verbal, and executive functions, short- and long-term memory) by including music-based items. MCT was validated with 335 participants (aged 18–100 years old) presenting a range of cognitive levels, from healthy cognition to severe impairment. MCT correlated strongly and positively with well-known tests: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Severe Mini-Mental State Examination (SMMSE). MCT also displayed excellent sensitivity in identifying impaired individuals according to both MMSE and MoCA diagnostic criteria (99.4% and 93.0%, respectively), and excellent specificity in identifying healthy participants based on MMSE (93.5%) and MoCA (97.8%) criteria. Overall, results highlight the reliability of this novel brief music-focused cognitive screening test, to enable music therapists to independently and consistently monitor the effectiveness of their intervention on cognitive functions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0450.000

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 head0.114
GPT teacher head0.318
Teacher spread0.205 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207