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Record W2333553665 · doi:10.1097/pep.0b013e3181eabc0f

Growing Older With Cerebral Palsy

2010· article· en· W2333553665 on OpenAlexaff
Marylyn Horsman, Melinda Suto, Brian J. Dudgeon, Susan R. Harris

Bibliographic record

VenuePediatric Physical Therapy · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCerebral palsyPsychologyPhenomenology (philosophy)Hermeneutic phenomenologyLived experienceQuality of life (healthcare)Developmental psychologyGerontologyMedicinePsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

In Brief Purpose: Research has shown that adults with cerebral palsy (CP) lose functional abilities earlier than persons who are able-bodied. Because CP is a lifespan disability, developmental therapists should be aware of these changes. Methods: We used descriptive phenomenology to understand the unique, lived experiences of adults growing older with CP. Data were gathered through in-depth, semistructured interviews. Open-ended questions asked what it was like to age with CP, how these experiences were understood, how strategies were used to cope with changes, and what are the meanings of these experiences. Results: A theme, Awareness, Acceptance, and Action, emerged from the data analysis. Participants were aware that their bodies were deteriorating quicker than those of peers who are able-bodied. They developed acceptance that hastened actions toward improving their quality of life. Conclusions: These findings provide insights for pediatric therapists who work with children with CP about what may be important to their clients as they grow older. This phenomenological study of the perspectives of adults with CP on growing older provides pediatric physical therapists with issues to consider as they work with children with CP and their families.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.151
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.011
GPT teacher head0.264
Teacher spread0.253 · 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

Citations28
Published2010
Admission routes1
Has abstractyes

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