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Framework for describing community integration for people with acquired brain injury

2012· article· en· W2052138697 on OpenAlexaff
Shahriar Parvaneh, Errol Cocks

Bibliographic record

VenueAustralian Occupational Therapy Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAcquired brain injuryCommunity integrationFocus groupDelphi methodStakeholderPsychologyPopulationVulnerability (computing)Descriptive statisticsProcess (computing)RehabilitationApplied psychologyMedicinePublic relationsPolitical scienceSociologyComputer scienceComputer security

Abstract

fetched live from OpenAlex

BACKGROUND/AIM: Community integration is the ultimate goal of rehabilitation of adults with acquired brain injury which has a high incidence in the Australian population. The literature shows a need for a more comprehensive framework for community integration. This study developed a descriptive community integration framework drawn from views of five stakeholder groups and was compared with four similar frameworks. METHODS: Thirty-seven experts in acquired brain injury, including practitioners, researchers, policy makers, people with acquired brain injury and family members participated. Using a Delphi method, an iterative process of surveys, interviews, and focus groups sought their views on community integration. Responses were analysed in three stages systematically to reduce a large quantity of raw data into a core set of descriptive themes. A final member checking process rated participants' agreement with the importance of each theme. RESULTS: Seven themes were identified and described: Relationships, Community Access, Acceptance, Occupation, Being at Home, Picking up Life Again, and Heightened Risks and Vulnerability. Themes were congruent with elements of the frameworks from the literature. CONCLUSIONS: Rich data came from the diverse stakeholders in the participant groups. Two unique themes reflected the importance of re-integration and recovering important aspects of previous lives, and identifying risks and vulnerabilities and providing safeguards. The framework reflected emphases that may be specific to acquired brain injury. It can be used as a basis for development of community integration programmes and outcome measures.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.384
GPT teacher head0.461
Teacher spread0.078 · 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

Citations22
Published2012
Admission routes1
Has abstractyes

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