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Record W2791725499 · doi:10.1080/09638288.2018.1451560

Managing cognitive difficulties after traumatic brain injury: a review of online resources for families

2018· review· en· W2791725499 on OpenAlexaff
Valérie Poulin, Deirdre Dawson, Carolina Bottari, Cynthia Verreault, Samantha Turcotte, Alexandra Jean

Bibliographic record

VenueDisability and Rehabilitation · 2018
Typereview
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsUniversité LavalUniversité de MontréalToronto Rehabilitation InstituteUniversity of TorontoUniversité du Québec à Trois-RivièresBaycrest HospitalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsReadabilityUsabilityCognitionChecklistApplied psychologyReliability (semiconductor)HyperlinkPsychologyThe InternetWeb usabilityQuality (philosophy)MedicineMedical educationComputer scienceWorld Wide WebWeb pagePsychiatry

Abstract

fetched live from OpenAlex

Purpose: To identify and critically appraise the content, readability, reliability and usability of websites providing information for managing cognitive difficulties in everyday life for the families of adults with moderate to severe traumatic brain injury.Method: Systematic searches on the Internet for relevant websites were conducted using five search engines, and through consultation of the lists of resources published on websites of traumatic brain injury organizations. Two team members assessed eligibility of the websites. To be included, they had to provide information related to management of cognitive difficulties following moderate to severe traumatic brain injury, to be in English or French and available free of charge. Two reviewers evaluated each website according to: (1) its readability using Flesch–Kincaid Grade Level; (2) the quality of its content using a checklist of eight recommendations for managing memory, attention and executive function problems; (3) its usability (e.g., clear design) and reliability (e.g., currency of information) using the Minervation Validation Instrument for Health Care Web Sites.Results: Of the 38 websites included, 10 provide specific tips for families that cover several domains of cognitive function, including memory, attention and executive function. The most frequent recommendations focused on the use of environmental supports for memory problems (n = 33 websites). The readability of information is below the recommended grade 7 for only nine of the websites. All sites show acceptable usability, but their quality is variable in terms of reliability of the information.Conclusions: This review provides useful information for selecting online resources to educate families about the management of cognitive difficulties following moderate to severe traumatic brain injury, as a complement to information and training provided by the rehabilitation team.Implications for rehabilitationThis review describes standardized criteria for the evaluation of the content, readability, reliability and usability of websites for family education post-TBI.Given the variability in the content, the readability and the reliability of websites providing information for families about the management of cognitive difficulties post-TBI, careful attention to the selection of appropriate resources is required.Findings from this review may facilitate clinicians’ identification of relevant websites to educate families about the management of cognitive difficulties post-TBI, as a complement to other information and training from the rehabilitation team.

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)0.008
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0110.010
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
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 head0.085
GPT teacher head0.487
Teacher spread0.402 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations12
Published2018
Admission routes1
Has abstractyes

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