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Record W4388342099 · doi:10.1016/j.pnpbp.2023.110891

Verbal memory impairments in mood disorders and psychotic disorders: A systematic review of comparative studies

2023· review· en· W4388342099 on OpenAlexafffund
Bryce J. M. Bogie, Chelsea Noël, Ahmad Alftieh, Julia R. MacDonald, Ya Ting Lei, Jamie Mongeon, Claire Mayaud, Patrick Dans, Synthia Guimond

Bibliographic record

VenueProgress in Neuro-Psychopharmacology and Biological Psychiatry · 2023
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsCentre for Addiction and Mental HealthCarleton UniversityRoyal Ottawa Mental Health CentreUniversité du Québec en OutaouaisLakehead UniversityUniversity of Ottawa
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsVerbal memoryMoodPsychologyBipolar disorderNeurocognitiveMood disordersRecallSchizophrenia (object-oriented programming)Clinical psychologyMajor depressive disorderPsychosisPsychiatryCognitionCognitive psychologyAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: Mood and psychotic disorders are both associated with verbal memory impairments. Verbal memory represents an important treatment target for both disorders. However, whether the neurocognitive and neurophysiological profiles of verbal memory impairments differ between specific disorders within these two diagnostic categories and healthy controls remains unclear. The current systematic review synthesized findings from comparative studies which used behavioural and neuroimaging tasks to investigate verbal memory impairments between: (1) mood disorder, psychotic disorder, and healthy control groups; and (2) mood disorder without psychotic features, mood disorder with psychotic features, and healthy control groups. METHODS: The search strategy combined terms related to three main concepts: 'mood disorders', 'psychotic disorders', and 'verbal memory'. Searches were executed in Embase, MEDLINE, PsycInfo, and PubMed databases. A total of 38 articles met the full eligibility criteria and were included in the final narrative synthesis. Findings were stratified by memory domain (overall composite score, verbal working memory, immediate recall, delayed recall, and recognition memory) and by illness phase (acute and non-acute). RESULTS: Mood and psychotic disorders displayed consistent verbal memory impairments compared to healthy controls during the acute and non-acute phases. Few significant differences were identified in the literature between mood and psychotic disorders, and between mood disorders with and without psychotic features. Individuals with schizophrenia were found to have decreased immediate and delayed verbal recall performance compared to bipolar disorder groups during the acute phase. Major depressive disorder groups with psychotic features were also found to have decreased delayed verbal recall performance compared to those without psychosis during the acute phase. No consistent differences were identified between mood and psychotic disorders during the non-acute phase. Finally, preliminary evidence suggests there may be functional abnormalities in important frontal and temporal brain regions related to verbal memory difficulties in both mood and psychotic disorders. DISCUSSION: The current findings have potential implications for the diagnosis and treatment of cognitive impairments in mood and psychotic disorders. Verbal recall memory may serve as a sensitive tool in the risk stratification of cognitive impairments for certain mood and psychotic disorders. Moreover, since no widespread differences between clinical groups were identified, the evidence supports providing targeted interventions for verbal memory, such as pharmacological and non-pharmacological interventions, through a trans-diagnostic approach in mood and psychotic disorders.

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)0.007
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0120.013
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.097
GPT teacher head0.468
Teacher spread0.371 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations6
Published2023
Admission routes2
Has abstractyes

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