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Record W1830277718 · doi:10.5014/ajot.2015.016170

Managing Poststroke Fatigue Using Telehealth: A Case Report

2015· article· en· W1830277718 on OpenAlexaboutno aff
Nicole Boehm, Hannah Muehlberg, Jan Stube

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsTelehealthPhysical therapyOccupational therapyMedicineTelemedicinePsychologyPhysical medicine and rehabilitationHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to examine the effectiveness of delivering Managing Fatigue: A Six-Week Course for Energy Conservation via telehealth for a 70-yr-old man with poststroke fatigue (PSF). METHOD: For this pilot case study, a questionnaire developed by the authors and the Patient-Reported Outcomes Measurement Information System Fatigue Short Form 7a were used for screening. The study was implemented via teleconference over an 8-wk period. The Fatigue Impact Scale (FIS) and the Canadian Occupational Performance Measure (COPM) were used to gather pretest and posttest data. RESULTS: After the participant completed the course, decreased fatigue impact was noted on the FIS, and modestly improved occupational performance and satisfaction were evidenced by the COPM. CONCLUSION: For this single participant experiencing PSF, performance and satisfaction on the COPM guardedly improved and fatigue impact decreased after participation in the energy conservation course offered by teleconference, a form of telehealth delivery. Further research is recommended with larger sample sizes.

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)0.004
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 score0.450
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.439
GPT teacher head0.568
Teacher spread0.129 · 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

Citations19
Published2015
Admission routes1
Has abstractyes

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