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International Programs and Perspectives

2007· article· en· W2047050115 on OpenAlexaboutno aff
Jan Lexell

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2007
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationHealth careHealthcare systemPopulationWorld populationStrengths and weaknessesMedicinePolitical sciencePsychologyEnvironmental healthPhysical therapy

Abstract

fetched live from OpenAlex

Traumatic brain injury (TBI) is an important public health problem. Throughout the world, TBI is one of the leading causes of life-long disability. The impact on the injured person, his or her family, friends, as well as society, and the healthcare system is well known, and so is the need for prevention, efficient acute care, rehabilitation, and follow-up. This special issue brings together articles from 5 countries—Canada, Denmark, Sweden, the Netherlands, and the United Kingdom—and provides a comprehensive insight into TBI rehabilitation within different healthcare systems around the world. Each article focuses on specific aspects of TBI rehabilitation, strengths and weaknesses, and future areas of interest as well as problems to address. In the first article, the Canadian system is described. Canada is the second largest country in the world with a population of only 31 million. The country has many similarities but it also differs substantially from its North American counterparts as it has a healthcare system based on principles of universal access to healthcare, making basic healthcare services available to all residents of the country. Even though TBI rehabilitation has developed greatly over the last 20 years in Canada, several areas of improvement are listed. Interestingly, many of them are similar to those listed in the other countries in this issue, emphasizing the similarities rather than the differences between TBI rehabilitation across the world. In the second article, the experiences from Denmark and the establishment of a national strategy for treatment and rehabilitation of TBI are presented. The vision was to create a system for tax-financed rehabilitation, centralized to 2 units, each with half the country as uptake area. The advantages gained by this centralization are described together with the results for the first 3 years, which indicate that outcome is improved. In the third article, TBI rehabilitation in Sweden is described. Demographics and injury characteristics of TBI in Sweden follow those of Europe in general. Several new developments, among them the decision to recommend that all rehabilitation departments in Sweden go through the accreditation process of the Commission of Accreditation of Rehabilitation Facilities, are expected to lead to improved services. In the fourth article, the system in the Netherlands is presented. Awareness of the impact of TBI has grown rapidly in the last 15 years in the Netherlands, and initiatives to improve services have been taken. Cognitive rehabilitation is such an example, and since 1993, healthcare insurers have agreed to pay for cognitive rehabilitation programs. However, like those of many other countries, several issues that need to be resolved are also described. In the fifth and final article, TBI rehabilitation in United Kingdom is presented. Rehabilitation has grown over the last 20 years. Various actions, some fairly recent, have been taken by the UK Government, which, as is described, means that it is essentially the first time that rehabilitation has featured in any major policy development. At the same time, new funding arrangements pose a considerable threat for rehabilitation services as currently set up in the United Kingdom. This special issue intends to present and compare rehabilitation of persons with TBI in different parts of the world. It is our hope that the articles will broaden our knowledge and that they may serve as an inspiration for clinicians and researchers in their ambition to develop efficient TBI rehabilitation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.234

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.069
GPT teacher head0.396
Teacher spread0.327 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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