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Record W2072362958 · doi:10.1097/jtn.0b013e318275990d

The Needs Experienced by Individuals and Their Loved Ones Following a Traumatic Brain Injury

2012· article· en· W2072362958 on OpenAlexafffundabout
Hélène Lefebvre, Marie Josée Levert

Bibliographic record

VenueJournal of Trauma Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchInstitut National de la Santé et de la Recherche Médicale
KeywordsHealth careGeneral partnershipPsychologyOccupational safety and healthSuicide preventionFocus groupTraumatic brain injuryPoison controlNursingPerceptionInjury preventionHuman factors and ergonomicsMedicineMedical emergencyPsychiatryBusinessPolitical science

Abstract

fetched live from OpenAlex

Traumatic brain injury (TBI) is an important public health concern that presents real challenges for health care systems throughout the world. Through an international partnership between Canadian and French researchers, a vast qualitative study aimed to explore the needs of individuals with TBIs and their loved ones throughout the continuum of care and services. The study was first conducted in 3 regions of Quebec (Canada) and subsequently replicated in 3 regions of France. Overall, the data were collected from focus groups with 150 participants: individuals with TBIs, their loved ones, and health care professionals. Despite regional differences, the results demonstrate participants' very similar perceptions regarding the needs such as information, support, and a collaborative relationship with health care professionals experienced by individuals with TBIs and their loved ones. These needs change throughout the stages of care. The fulfillment of these needs play a determining role throughout the adaptation process of individuals with TBIs and their loved ones. Health care professionals must adopt a personalized approach to respond to needs related to the evolution of information, support, and relationships.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.066
GPT teacher head0.378
Teacher spread0.312 · 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 designOther design
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

Citations31
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Trauma NursingSame topicTraumatic Brain Injury ResearchFrench-language works237,207