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Record W2120329374 · doi:10.2217/npy.13.3

Systematic review of neurocognition and occupational functioning in major depressive disorder

2013· article· en· W2120329374 on OpenAlexaff
Vanessa Evans, Sarah SL Chan, Grant L. Iverson, David J. Bond, Lakshmi N. Yatham, Raymond W. Lam

Bibliographic record

VenueNeuropsychiatry · 2013
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeurocognitivePsychologyMajor depressive disorderClinical psychologyPsychiatryCognition

Abstract

fetched live from OpenAlex

Occupational impairment accounts for much of the burden and economic costs associated with major depressive disorder (MDD). Many studies have documented neurocognitive deficits in MDD, and depression-associated cognitive dysfunction would be expected to have significant effects on occupational functioning. We systematically reviewed the literature for studies on neurocognition and occupational functioning in MDD. Electronic databases (e.g., MEDLINE, PsychInfo and Cochrane Clinical Trials) were searched using appropriate terms and bibliographies of relevant publications were scanned for additional citations. Two reviewers independently reviewed papers for inclusion and data extraction, with conflicts resolved by consensus. Inclusion criteria were diagnosis of MDD using validated criteria (e.g., DSM‑IV or ICD‑10), use of objective neuropsychological tests and use of a specific measure of occupational functioning. Of 630 citations identified in the initial search, only two studies met inclusion criteria and were included in a qualitative review. Both had significant methodological limitations. Nonetheless, the depressed samples had significant neurocognitive deficits that were associated with employment status and work impairment. Neurocognitive dysfunction is probably associated with impairment in occupational functioning in individuals with MDD, but the evidence is limited. Further research should examine specific cognitive domains, and use validated measures of work functioning and productivity.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.329
Teacher spread0.316 · 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.

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

Citations41
Published2013
Admission routes1
Has abstractyes

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