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Record W4390078755 · doi:10.1017/s1355617723002242

20 The Influence of Brain Injury Severity, Anxiety, and Depression on Objective and Subjective Prospective Memory Problems

2023· article· en· W4390078755 on OpenAlexaff
Gabrielle Tétreault, Sarah-Jade Roy, Julie Audy, Isabelle Rouleau, Marie-Julie Potvin

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsHôpital du Sacré-Cœur de MontréalCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre Intégré de Santé et de Services Sociaux des LaurentidesUniversité du Québec à Montréal
Fundersnot available
KeywordsTraumatic brain injuryDepression (economics)AnxietyProspective cohort studyCorrelationMedicinePsychologyClinical psychologyPhysical therapyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Objective: Following a traumatic brain injury (TBI), the majority of patients report difficulties with prospective memory (PM). However, there is not always a significant relationship between subjective and objective PM measures. Several variables may influence the degree of severity of perceived difficulties, including the severity of the injury and psychoemotional status. The aim of this study was to determine whether the severity of the TBI and anxiety and depressive symptoms were related to objective and subjective difficulties of PM. Participants and Methods: 50 patients (mean age = 31,3 years old) with a TBI (20 mild and 30 moderate/severe) in the post-acute phase of recovery and 15 matched healthy control participants (mean age = 32,3 years old) were recruited. They completed inventories assessing the presence of anxiety (BAI) and depressive (BDI) symptoms and performed the Ecological test of prospective memory (TEMP), an objective measure of PM. The Comprehensive Assessment of PM (CAPM), a subjective measure of PM, was also filled out by participants and their relatives. Results: In patients with moderate/severe TBI, significant correlations were found between the CAPM and the BDI (r =.601, p<.001) and the BAI (r =.507, p=.004). A negative correlation was also observed between the relatives’ CAPM scores and the performance of the patients on the TEMP (r= -.374, p=.042). In patients with mild TBI, there was only a strong significant correlation between the CAPM and the BAI scores (r =.574, p=.008). However, no other correlation was significant between this group of patients and their relatives. Additionally, results on the TEMP were not significantly correlated with the CAMP completed by healthy control participants or their relatives. A linear regression conducted in the group of participants with TBI showed that BAI and BDI scores are the only significant predictors of the results on the CAPM (31% of the variance), while TBI severity is the only significant predictor of the results on the TEMP (37% of the variance). Conclusions: The perception of PM difficulties in patients with a TBI does not seem to be related to their objective performance. Anxiety and depressive symptoms appear to influence their perception more than their objective performance. As suggested by their relatives, a decrease in self-awareness could explain the lack of relationship between subjective PM difficulties of patients with moderate/severe TBI and their objective performance. On the other hand, TBI severity is more strongly related to objective performance on PM tests. These results highlight the importance of using different measures to accurately assess PM and the various factors influencing this construct.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.310
Teacher spread0.291 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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