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Record W2326260110 · doi:10.1089/neu.2014.3799

Resilience Is Associated with Outcome from Mild Traumatic Brain Injury

2015· article· en· W2326260110 on OpenAlexaff
Heidi Losoi, Noah D. Silverberg, Minna Wäljas, Senni Turunen, Eija Rosti‐Otajärvi, Mika Helminen, Teemu M. Luoto, Juhani Julkunen, Juha Öhman, Grant L. Iverson

Bibliographic record

VenueJournal of Neurotrauma · 2015
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTraumatic brain injuryResilience (materials science)PsychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Resilient individuals manifest adaptive behavior and are better able to recover from adversity. The association between resilience and outcome from mild traumatic brain injury (mTBI) is examined, and the reliability and validity of the Resilience Scale and its short form in mTBI research is evaluated. Patients with mTBI (n=74) and orthopedic controls (n=39) completed the Resilience Scale at one, six, and 12 months after injury. Additionally, self-reported post-concussion symptoms, fatigue, insomnia, pain, post-traumatic stress, and depression, as well as quality of life, were evaluated. The internal consistency of the Resilience Scale and the short form ranged from 0.91 to 0.93 for the mTBI group and from 0.86 to 0.95 for controls. The test-retest reliability ranged from 0.70 to 0.82. Patients with mTBI and moderate-to-high resilience reported significantly fewer post-concussion symptoms, less fatigue, insomnia, traumatic stress, and depressive symptoms, and better quality of life, than the patients with low resilience. No association between resilience and time to return to work was found. Resilience was associated with self-reported outcome from mTBI, and based on this preliminary study, can be reliably evaluated with Resilience Scale and its short form in those with mTBIs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.512

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 integrity0.0000.001
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 head0.200
GPT teacher head0.452
Teacher spread0.252 · 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

Citations84
Published2015
Admission routes1
Has abstractyes

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