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Record W2134537851 · doi:10.1177/2333393614548762

Living With Chronic Lower Pulmonary Disease

2014· article· en· W2134537851 on OpenAlexaff
Charlotte Pooler

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEmbodied cognitionPhenomenology (philosophy)Thematic analysisPulmonary diseaseMedicineLived experienceDiseaseExperiential learningPsychologyHermeneutic phenomenologyQualitative researchPsychotherapistSociologyPathologyPedagogyInternal medicineSocial scienceEpistemology

Abstract

fetched live from OpenAlex

In this article, I present a phenomenological study of individuals' experiences of living with moderate to very severe chronic lower pulmonary disease (chronic obstructive pulmonary disease, asthma, or both). Phenomenology is a philosophy, distinct from descriptive or thematic research, which is useful as a foundation for scientific inquiry. In this study, I used the lens of Merleau-Ponty to understand and interpret participants' experiences of living with pulmonary disease, and the approach of van Manen for analysis. I conclude that in chronic pulmonary disease, awareness of breathing and the body is experienced in the sounds, sensations, and signals of breathing and the body, and in the experiences of the body-in-the-world. Central themes of being-in-the-world from the study describe the disruption of the embodied phenomenological self: Participants experienced slowing down, doing less, and having to stop due to shortness of breath. Both chronic and acute dyspnea were prevalent and the taken-for-granted aspects of daily activities were disrupted. Findings of this study have implications for public and patient education, and opportunities for integration of experiential aspects within nursing education and practice.

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)0.013
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.152
GPT teacher head0.602
Teacher spread0.450 · 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

Citations11
Published2014
Admission routes1
Has abstractyes

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