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Record W3094950515 · doi:10.1080/17483107.2020.1833093

Potential advantages, barriers, and facilitators of implementing a cognitive orthosis for cooking for individuals with traumatic brain injury: the healthcare providers’ perspective

2020· article· en· W3094950515 on OpenAlexaff
Sareh Zarshenas, Mélanie Couture, Nathalie Bier, Sylvain Giroux, Hélène Pigot, Deirdre Dawson, Emily Nalder, Mireille Gagnon‐Roy, Guylaine Le Dorze, Frédérique Poncet, Suzanne McKenna, Karl Zabjek, Carolina Bottari

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2020
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre de réadaptation Lethbridge-Layton-MackayBaycrest HospitalToronto Rehabilitation InstituteChamplain Regional CollegeMarch of Dimes CanadaInstitut Universitaire de Gériatrie de MontréalUniversity of TorontoUniversité de SherbrookeUniversité de MontréalUniversity Health NetworkCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsCognitionHealth careRehabilitationQualitative researchMeal preparationAcquired brain injuryTraumatic brain injuryFocus groupPerspective (graphical)PsychologyMedicineNursingPsychiatryPhysical therapyBusiness

Abstract

fetched live from OpenAlex

Purpose Considering the key role of health care providers in integrating assistive technologies into clinical settings (e.g., in/outpatient rehabilitation) and home, this study explored the care providers’ perspectives on benefits, barriers and facilitators to the implementation of the Cognitive Orthosis for coOking (COOK) for adults with traumatic brain injury (TBI) within clinical contexts and homes.Methods Using a qualitative descriptive approach, semi-structured individual interviews and focus groups were carried out with experienced care providers of adults with TBI (n = 30) in Ontario-Canada. Qualitative analysis based on the Miles et al approach was used.Results According to the participants, COOK could potentially be used with individuals with cognitive impairments (TBI and non-TBI) to increase safety and independence in meal preparation and support healthcare providers. However, limited access to funding, clients’ lack of motivation/knowledge, and the severity of their cognitive and motor impairments were perceived as potential barriers. Facilitators to the use of COOK include training sessions, availability of private/provincial financing, and comprehensive assessments by a clinical team prior to use.Conclusions Health care providers’ perspectives will help develop implementation strategies to facilitate the adoption of COOK within homes and clinical contexts for individuals with TBI and improve the next version of this technology.IMPLICATIONS FOR REHABILITATIONCOOK shows a high potential for increasing independence and safety during meal preparation with its sensor-based monitoring of the environment and cognitive-based assistance, for adults with TBI.Comprehensive clinical assessments to identify individuals’ therapeutic goals, clinical characteristics, and living environments are necessary to facilitate the deployment of COOK.

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.370
Teacher spread0.337 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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