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Record W4210315048 · doi:10.2196/preprints.9420

Telehealth Rehabilitation for Cognitive Impairment: Randomized Controlled Feasibility Trial (Preprint)

2017· preprint· en· W4210315048 on OpenAlexaffabout
Rachel Burton, Megan E. O’Connell

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTelehealthTelerehabilitationDementiaRehabilitationCognitive rehabilitation therapyCognitionPhysical therapyPsychological interventionIntervention (counseling)Physical medicine and rehabilitationRandomized controlled trialPsychologyMedicineTelemedicineNursingPsychiatryDiseaseHealth care

Abstract

fetched live from OpenAlex

BACKGROUND Nonpharmacological interventions are needed to support the function of older adults struggling with subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and dementia due to Alzheimer disease (AD). Telerehabilitation aims to provide rehabilitation at a distance, but cognitive rehabilitation by videoconferencing has not been explored. OBJECTIVE The objective of this study was to compare goal-oriented cognitive rehabilitation delivered in-person with videoconferencing to determine whether telehealth cognitive rehabilitation appears feasible. METHODS Random assignment to in-person or telehealth videoconferencing cognitive rehabilitation with a combined between-subjects, multiple baseline single-case experimental design, cognitive rehabilitation was delivered by a therapist to 6 participants with SCI (n=4), MCI (n=1), or dementia due to AD (n=1). RESULTS Two of the 6 participants randomly assigned to the telehealth condition withdrew before beginning the intervention. For those who participated in the intervention, 6 out of 6 goals measured with the Canadian Occupational Performance Measure improved for those in the in-person group, and 7 out of 9 goals improved for those in the telehealth group. CONCLUSIONS Delivery of cognitive rehabilitation by telehealth appeared feasible but required modifications such as greater reliance on caregivers and clients for manipulating materials.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized trialhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0200.002

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 head0.055
GPT teacher head0.424
Teacher spread0.369 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations1
Published2017
Admission routes2
Has abstractyes

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