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Record W2995712348 · doi:10.30773/pi.2019.0116

Combined Measures of Psychomotor and Cognitive Alterations as a Potential Hallmark for Bipolar Depression

2019· article· en· W2995712348 on OpenAlexaboutno aff
Alison Robin, Anne Sauvaget, Thibault Deschamps, Samuel Bulteau, Véronique Thomas-Ollivier

Bibliographic record

VenuePsychiatry Investigation · 2019
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsnot available
FundersUniversité de Nantes
KeywordsDepression (economics)Psychomotor learningCognitionBipolar disorderPsychologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: The current study aimed to examine whether specific features of psychomotor retardation (PMR) and cognitive functioning established different profiles in unipolar (UD) and bipolar depression (BD). METHODS: Two groups of age-matched patients with UD (n=54) and BD (n=20) completed the Montgomery-Asberg Depression Rating Scale (MADRS/60), the Montreal Cognitive Assessment (MoCA/30), and the Salpêtrière Retardation Rating Scale (SRRS/60). We analyzed the group effect and then performed intra-group analyses. RESULTS: The BD patients have higher SRRS score, and lower MoCA score than UD despite no difference on the level of depression between UD and BD. Our results show that PMR can be predicted by the level of depression in UD and by the cognitive alteration and onset of disease in BD. CONCLUSION: PMR is a relevant marker of depression. Our results highlight the importance of concomitant evaluation of psychomotor and cognitive functions in the distinction of UD and BD symptoms.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.271
Teacher spread0.255 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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