MétaCan
Menu
← Back to cohort
Record W2884904050 · doi:10.1017/cjn.2018.51

Trait Mindfulness and Wellness in Multiple Sclerosis

2018· article· en· W2884904050 on OpenAlexaffvenue
Ola Mioduszewski, Heather MacLean, Patricia A. Poulin, Andra Smith, Lisa A.S. Walker

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2018
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMindfulnessMoodMultiple sclerosisQuality of life (healthcare)AnxietyTraitClinical psychologyPsychologyDepression (economics)Psychological interventionTrait anxietyCognitionMedicinePsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a chronic, progressive, autoimmune, neurodegenerative disorder that can interfere with physical and psychological functioning, negatively affecting health-related quality of life (HRQoL). Fostering mindfulness may mitigate the negative consequences of MS on HRQoL. The relationship between mindfulness, mood and MS-related quality of life was investigated. In total, 52 individuals with MS completed questionnaires to examine the relationship between trait mindfulness and wellness. Higher levels of trait mindfulness were associated with better HRQoL, lower depression and anxiety, lower fatigue impact and fewer perceived cognitive deficits. Mindfulness interventions have the potential to enhance wellness in those 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 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.103
GPT teacher head0.305
Teacher spread0.201 · 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 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

Citations13
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques→Same topicMultiple Sclerosis Research Studies→French-language works237,207→