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Record W4391806815 · doi:10.1080/02699052.2024.2311332

Healthcare perceptions of persons with traumatic brain injuries across providers: shortcomings in the chronic phase of care

2024· article· en· W4391806815 on OpenAlexaboutno aff
Jerry K. Hoepner, Kathleen A. Dahl, Louise C. Keegan, Daniel N. Proud

Bibliographic record

VenueBrain Injury · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsTraumatic brain injuryHealth careMedicinePerceptionRehabilitationMedical emergencyPsychologyNursingPsychiatryPhysical therapyNeuroscience

Abstract

fetched live from OpenAlex

Objective This investigation sought to examine the perceptions of individuals with mild, moderate, and severe traumatic brain injury (TBIs) toward healthcare providers across rehabilitation contexts (acute, rehabilitation, and chronic).Methods The mCARE-TBI survey was distributed via Qualtrics throughout the US and Canada. Sixty-four survey responses met criteria for analysis. Participants were ≥18 years old, one-year post onset, reported no unrelated neurological deficits prior to the single TBI, and reported no prior diagnosed psychiatric disorders. The mCARE was the primary outcome measure. Comparisons were made between provider ratings on each question.Results Significant differences were found between chronic-phase care, compared to acute care and rehabilitation. Group differences were found in transitioning home after discharge and in between each therapy discipline and both nurses and doctors, as well as for really listening and pairwise differences between therapy disciplines and both nurses and doctors. Group effects were found for showing compassion and care and being positive.Conclusions All disciplines need to improve communication, and transition care/discharge planning. Dismissal of ongoing impairments continues to be an area of perceived concern with doctors in particular. Communication training is needed, particularly for nurses and doctors.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.067
GPT teacher head0.431
Teacher spread0.363 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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