MétaCan
Menu
Back to cohort
Record W2975302602 · doi:10.1080/09540261.2019.1657384

Gender role in sleep disturbances among older adults with traumatic brain injury

2019· article· en· W2975302602 on OpenAlexaff
Conor Ledger, Wael K. Karameh, David G. Muñoz, Corinne E. Fischer, Tom A. Schweizer

Bibliographic record

VenueInternational Review of Psychiatry · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental HealthSt. Michael's Hospital
FundersNational Institute on Aging
KeywordsTraumatic brain injurySleep disorderSleep (system call)PopulationMedicinePsychologyClinical psychologyPsychiatryCognition

Abstract

fetched live from OpenAlex

Older adults are particularly vulnerable to poor long-term outcomes, and the rate of TBI in this group is increasing. Studies have shown females experience worse outcomes from TBI than males, however this research has been limited. The aim of this study is to examine gender effects on the frequency of sleep disturbances in older adults post-TBI. An analysis was conducted on data obtained from the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set. A total of 405 patients greater than 60 years of age were examined. Sleep disturbances were measured using the Nighttime Behavioural Disturbances domain of the Neuropsychiatric Inventory–Questionnaire (NPI-Q). A significant difference (p = 0.025) in reported sleep disturbance was identified in the female TBI population relative to the female non-TBI population. In the male non-TBI group, 14.8% (n = 12) experienced nighttime disturbances while 19.8% (n = 17) of those with TBI experienced nighttime disturbances. This difference was not significant (p = 0.305). These results suggest there is a greater impact from traumatic brain injury on sleep disturbances in older females than males. Further research examining gender differences in older adults related to neuropsychiatric outcomes of TBI should be considered given the implications for treatment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.018
GPT teacher head0.336
Teacher spread0.318 · 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.

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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Review of PsychiatrySame topicTraumatic Brain Injury ResearchFrench-language works237,207