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Record W2079075519 · doi:10.5014/ajot.2015.015370

Goals Set After Completing a Teleconference-Delivered Program for Managing Multiple Sclerosis Fatigue

2015· article· en· W2079075519 on OpenAlexaff
Miho Asano, Katharine Preissner, R Lamar Duffy, Maggie Meixell, Marcia Finlayson

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2015
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsSet (abstract data type)Psychological interventionGoal settingTeleconferencePsychologyMedical educationTime managementApplied psychologyMedicineNursingComputer scienceMultimediaSocial psychology

Abstract

fetched live from OpenAlex

Setting goals can be a valuable skill to self-manage multiple sclerosis (MS) fatigue. A better understanding of the goals set by people with MS after completing a fatigue management program can assist health care professionals with tailoring interventions for clients. This study aimed to describe the focus of goals set by people with MS after a teleconference-delivered fatigue management program and to evaluate the extent to which participants were able to achieve their goals over time. In total, 485 goals were set by 81 participants. Over a follow-up period, 64 participants rated 284 goals regarding progress made toward goal achievement. Approximately 50% of the rated goals were considered achieved. The most common type of goal achieved was that of instrumental activities of daily living. Short-term goals were more likely to be achieved. This study highlights the need for and importance of promoting and teaching goal-setting skills to people 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)0.001
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 score0.562
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.353
GPT teacher head0.435
Teacher spread0.082 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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