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Record W3186808620 · doi:10.1136/jnnp-2021-bnpa.35

#3105 How does self-report of mood symptoms compare with observer assessments after acquired brain injury

2021· article· en· W3186808620 on OpenAlexaboutno aff
Mark Paramlall, Ida Bakar, Rohan Kandasamy, Anna Gadhvi, Cameron Holloway, Sam Harding, Himanshu Tyagi

Bibliographic record

VenueJournal of Neurology Neurosurgery & Psychiatry · 2021
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentNeuropsychiatryAcquired brain injuryMoodCognitionDepression (economics)PsychologyClinical psychologyRating scalePsychiatryPhysical therapyMedicineRehabilitationCognitive impairmentDevelopmental psychology

Abstract

fetched live from OpenAlex

Objectives Post acquired brain injury (ABI) depression has been implicated in different patient outcomes such as prospective cognition, cognitive impairment, rehabilitation outcome, and quality of life. However, there have been no studies identified in the literature, investigating post ABI insight into depression across varied cognitive abilities. Here we looked at ABI patient insight into their depression across a range of cognitive abilities and compared this to an observed or an objective measure of depression. Methods A retrospective cohort of 24 individuals with ABI (depressed and non-depressed) seen in a neuropsychiatry outpatient clinic between 2019 and 2020 completed a Patient Health Questionnaire-9 (PHQ-9), self-reported depression scale and had a Neuropsychiatry Inventory Questionnaire(NPI-Q), an observer assessment with a depression domain. The patients also underwent a formal cognitive examination using the Montreal Cognitive Assessment (MoCA). Results Non-depressed ABI and depressed ABI individuals with a wide range of cognitive abilities demonstrated good insight into their depression when matched to the observer rating. Chi-Square Test showed little variation between the PHQ-9 and NPI-Q Depression data sets; Wilcoxon Signed Ranks Test: Z Test -4.08, p<0.001, Effect Size 0.87 and Spearman’s rho showed positive correlation between the two data sets (Correlation Coefficient 0.527, P<0.008). Therefore, there was a statistically significant agreement between the subjective measure (PHQ-9) and the observed (objective) measure NPIQD and that there was a positive correlation between the two measurement scales for patients with ABI regardless of cognition (as measured by MoCAz score; range -6 to 2.21, mean: -1.17) Conclusions These findings indicate (1) self-reported measures of depression in ABI are consistent with observed (objective measures) thus can be used to assess depression in this cohort and (2) ABI patients with a wide range of cognitive abilities would appear to have good insight into their depression.

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)0.009
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.325
Teacher spread0.298 · 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.

Study designObservational
DomainMethods
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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