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Record W2078480589 · doi:10.4236/ojpm.2011.13016

"CF chatters": the development of a theoretically informed physical activity intervention for youth with cystic fibrosis

2011· article· en· W2078480589 on OpenAlexaff
Fiona J. Moola, Guy Faulkner, Jane E. Schneiderman

Bibliographic record

VenueOpen Journal of Preventive Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsIntervention (counseling)Physical activityPopulationPsychological interventionCystic fibrosisQuality of life (healthcare)PsychologyPsychotherapistMedicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

Despite the benefits of physical activity for youth living with cystic fibrosis (CF), the majority of patients are insufficiently active to meet physical activity recommendations. Existing physical activity interventions are atheoretical and tend to prescribe standardized exercise regimes which are often not appealing for children and compromise long term adherence. Following recent calls for counselling based physical activity approaches in the CF population, this study describes the development of a theoretically informed, parent-mediated, behavioural counselling intervention for CF youth―“CF Chatters”. We first a) describe the development of a grounded theory of physical activity in youth with CF; b) explain how this theory informed the development and implementation of the CF Chatters program and c) reflect on the findings of our pilot intervention using a case study research design. CF Chatters participants demonstrated self reported increases in physical activity and quality of life. While further development and more robust objective measures are needed to extend this investigative pilot work, our findings suggest that behavioural counselling is an effective modality for enhancing physical activity participation and quality of life in this life limited group of children and youth.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.081
GPT teacher head0.385
Teacher spread0.304 · 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 designBench or experimental
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

Citations11
Published2011
Admission routes1
Has abstractyes

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