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Record W4313458596 · doi:10.1097/htr.0000000000000837

INCOG 2.0 Guidelines for Cognitive Rehabilitation Following Traumatic Brain Injury, Part V: Memory

2023· article· en· W4313458596 on OpenAlexaff
Diana Velikonja, Jennie Ponsford, Shannon Janzen, Amber Harnett, Eleni Patsakos, Mary Kennedy, Leanne Togher, Robert Teasell, Amanda McIntyre, Penny Welch‐West, Ailene Kua, Mark Bayley

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsHamilton Health Sciences
Fundersnot available
KeywordsCognitionProspective memoryRehabilitationTraumatic brain injuryCognitive rehabilitation therapyMemory impairmentIntervention (counseling)MedicineEpisodic memoryAuditPhysical medicine and rehabilitationCognitive trainingPsychologyPhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Memory impairments affecting encoding, acquisition, and retrieval of information after moderate-to-severe traumatic brain injury (TBI) have debilitating and enduring functional consequences. The interventional research reviewed primarily focused on mild to severe memory impairments in episodic and prospective memory. As memory is a common focus of cognitive rehabilitation, clinicians should understand and use the latest evidence. Therefore, the INCOG ("International Cognitive") 2014 clinical practice guidelines were updated. METHODS: An expert panel of clinicians/researchers reviewed evidence published since 2014 and developed updated recommendations for intervention for memory impairments post-TBI, a decision-making algorithm, and an audit tool for review of clinical practice. RESULTS: The interventional research approaches for episodic and prospective memory from 2014 are synthesized into 8 recommendations (6 updated and 2 new). Six recommendations are based on level A evidence and 2 on level B. In summary, they include the efficacy of choosing individual or multiple internal compensatory strategies, which can be delivered in a structured or individualized program. Of the external compensatory strategies, which should be the primary strategy for severe memory impairment, electronic reminder systems such as smartphone technology are preferred, with technological advances increasing their viability over traditional systems. Furthermore, microprompting personal digital assistant technology is recommended to cue completion of complex tasks. Memory strategies should be taught using instruction that considers the individual's functional and contextual needs while constraining errors. Memory rehabilitation programs can be delivered in an individualized or mixed format using group instruction. Computer cognitive training should be conducted with therapist guidance. Limited evidence exists to suggest that acetylcholinesterase inhibitors improve memory, so trials should include measures to assess impact. The use of transcranial direct current stimulation (tDCS) is not recommended for memory rehabilitation. CONCLUSION: These recommendations for memory rehabilitation post-TBI reflect the current evidence and highlight the limitations of group instruction with heterogeneous populations of TBI. Further research is needed on the role of medications and tDCS to enhance memory.

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)0.019
metaresearch head score (Gemma)0.070
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.070
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0100.005
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0070.005
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0090.008

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 head0.177
GPT teacher head0.473
Teacher spread0.296 · 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
GenreMethods

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

Citations52
Published2023
Admission routes1
Has abstractyes

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