#3105 How does self-report of mood symptoms compare with observer assessments after acquired brain injury
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".