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Record W2016239322 · doi:10.3109/17549507.2011.549240

Experiences of care: Perspectives of carers of adults with traumatic brain injury

2011· article· en· W2016239322 on OpenAlexaboutno aff
Anna O’Callaghan, Lindy McAllister, Linda Wilson

Bibliographic record

VenueInternational Journal of Speech-Language Pathology · 2011
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationQuarter (Canadian coin)MedicineNursingFamily memberService (business)Health careFamily medicinePhysical therapy

Abstract

fetched live from OpenAlex

This paper describes the results of a survey that explored the experiences of carers when accessing rehabilitative services alongside their family member with a moderate-severe TBI. The 184 carers who completed these surveys reflected retrospectively on the care they received. The results of this study indicated that 61% of the carer respondents recollected accessing inpatient rehabilitation following their acute care. However, following inpatient discharge only 33% of carers reported receiving ongoing services. One quarter of carers stated they received inadequate information while transitioning through their healthcare journey and fewer than 20% of carers recollected receiving any formal support service. The results of this study showed that as carers transitioned through the healthcare journey with their family member with TBI, health services progressively declined. As this occurred, carers' satisfaction with services reduced, while their responsibilities for caring increased. This trend is concerning given the needs of carers have been shown to change over time and increase if not addressed. This paper describes both carer experience following TBI in Australia and encourages clinicians to advocate for carers needs when planning and providing rehabilitation services.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.003
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 head0.024
GPT teacher head0.377
Teacher spread0.353 · 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 source (direct Gemma or distilled Codex), 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

Citations35
Published2011
Admission routes1
Has abstractyes

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