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Record W2945207379 · doi:10.1177/0008417419832466

Meaningful occupations of young adults with muscular dystrophy and other neuromuscular disorders

2019· article· en· W2945207379 on OpenAlexvenueno aff
Sally Lindsay, Elaine Cagliostro, Laura McAdam

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMuscular dystrophyPhysical medicine and rehabilitationMedicinePsychologyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND.: Youth with Duchenne muscular dystrophy (DMD) and other neuromuscular disorders are living well into adulthood and often need help engaging in meaningful occupations. PURPOSE.: Our purpose was to explore enablers and barriers to engaging in meaningful occupations, from the perspectives of youth, parents, and practitioners. METHOD.: This qualitative study involved 26 participants (11 parents, eight youth ages 19 to 28 [mean = 22.3 years], seven practitioners). Data were obtained from semistructured interviews and analyzed using an interpretive descriptive approach. FINDINGS.: Youth with DMD and neuromuscular disorders engage in meaningful occupations in a variety of ways. Occupational enablers were supports and accommodations and self-care skills and coping strategies, while occupational barriers involved societal expectations of a normative adulthood, discrimination and inaccessible environments, lack of supports and resources, medical challenges, fatigue, lack of motivation, and social isolation and depression. IMPLICATIONS.: Practitioners should work to uncover what youth consider important and connect them to appropriate resources so they can engage in meaningful occupations.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.094
GPT teacher head0.411
Teacher spread0.317 · 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.

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
Published2019
Admission routes1
Has abstractyes

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