MétaCan
Menu
Back to cohort
Record W1988513224 · doi:10.1055/s-0029-1242639

The Role of Collaborative Self-Management in Pulmonary Rehabilitation

2009· review· en· W1988513224 on OpenAlexaff
Jean Bourbeau

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2009
Typereview
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicinePulmonary rehabilitationRehabilitationIntensive care medicineSelf-managementPhysical therapy

Abstract

fetched live from OpenAlex

Self-management's key feature is to increase patients' involvement and control in their disease and improve their well-being. Self-management is not intended to replace components of patient health care such as medication and pulmonary rehabilitation. We may be enthusiastic about recent results of self-management programs in chronic obstructive pulmonary disease (COPD) patients showing a reduction in hospital admissions. However, being interested only in patients' hospital admissions is overly narrow. The pivotal objective of self-management programs is to change patients' behavior. The success should correspond to the goals of self-management (e.g., acquiring key self-management skills such as problem solving, decision making, early symptom recognition, and taking action) and self-health behaviors (maintaining comfortable breathing, implementing an action plan in the event of an exacerbation, and facilitating exercise maintenance). Pulmonary rehabilitation is increasingly becoming a realistic component of COPD patient management, but it should not stand as an isolated intervention. Pulmonary rehabilitation should be part of an integrated care process and include self-management support (i.e., aiming to achieve a shift from management by the health care provider to management by the patients themselves, which implies structural behavior change). Changing patient behavior and ensuring maintenance are complex processes and require time.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.045
GPT teacher head0.432
Teacher spread0.388 · 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 designOther design
Domainnot available
GenreReview

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

Citations31
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueSeminars in Respiratory and Critical Care MedicineSame topicFamily and Patient Care in Intensive Care UnitsFrench-language works237,207