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Record W4399970710 · doi:10.1037/tra0001712

Family caregivers of service members in United States Department ofDefense health care report impairment in longitudinal healthoutcomes.

2024· article· en· W4399970710 on OpenAlexaff
Tracey A. Brickell, Louis M. French, Megan M. Wright, Jamie K. Sullivan, Brian Ivins, Nicole V. Varbedian, Anice M. Byrd, Rael T. Lange

Bibliographic record

VenuePsychological Trauma Theory Research Practice and Policy · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsGeneral Dynamics (Canada)
FundersTraumatic Brain Injury Center of Excellence
KeywordsEmergency departmentService memberHealth careLongitudinal studyHuman servicesService (business)GerontologyNursingFamily medicinePsychologyMedicineBusinessPolitical scienceMilitary personnel

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine elevated symptoms on health-related quality of life (HRQOL) measures over 2 years in caregivers of service members with traumatic brain injury (TBI). To compare outcomes to caregivers of veterans. METHOD: = 260). Caregivers completed 17 HRQOL measures at a baseline evaluation and follow-up evaluation 24 months later. RESULTS: = .36-.63). In the service member caregiver group, the proportion of caregivers with clinically elevated scores at baseline and follow-up was equally dispersed across persistent and newly developed symptoms, but higher for persistent symptoms compared to developed symptoms in the veteran caregiver group. CONCLUSIONS: Many caregivers of service members reported clinically elevated scores across HRQOL domains and the prevalence increased over 2 years. More services for caregivers in the Department of Defense may be helpful in reducing the trajectory of newly developed symptoms long term. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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)0.012
metaresearch head score (Gemma)0.003
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 score0.563
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.237
GPT teacher head0.550
Teacher spread0.313 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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