MétaCan
Menu
Back to cohort
Record W2791392953 · doi:10.1177/0008417417727298

Sensory processing, cognitive fatigue, and quality of life in multiple sclerosis

2018· article· en· W2791392953 on OpenAlexfundvenueno aff
Melissa Colbeck

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2018
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersAssociation for Applied Sport PsychologyHealth Sciences Centre Foundation
KeywordsSensory processingQuality of life (healthcare)CognitionPsychologySensory systemPopulationSensationPhysical therapyPhysical medicine and rehabilitationMedicineClinical psychologyPsychiatryCognitive psychologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Quality of life for persons living with multiple sclerosis (MS) is significantly lower than population norms. Fatigue, both physical and cognitive, is one of the most prevalent and debilitating symptoms of MS that decrease quality of life. Cognitive fatigue presents similarly to sensory overresponsiveness, but the connection has not been explored. PURPOSE: This study aims to describe how sensory-processing preferences and cognitive fatigue relate to variances in quality of life for people with MS. METHOD: A cross-sectional design was used with 30 people living with MS to complete the Adolescent/Adult Sensory Profile (AASP), Modified Fatigue Impact Scale, and RAND-36. Spearman's coefficient measured nonparametric correlations between variables. FINDINGS: People with MS who have high scores in low registration, sensory sensitivity, and sensation avoidant quadrants of the AASP also have higher levels of cognitive fatigue and poorer quality of life. Those with high scores in sensory seeking experience greater quality of life and less cognitive fatigue. IMPLICATIONS: The findings shape clinical practice by supporting the assessment of sensory processing alongside fatigue, offering individualized intervention planning to shape fatigue management, and fostering hope and quality of life for persons living with MS.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.525
GPT teacher head0.451
Teacher spread0.074 · 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

Citations18
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Occupational TherapySame topicMultiple Sclerosis Research StudiesFrench-language works237,207