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Record W7056586532

Guided asthma self-management or patient self-adjustment? Using patients’ narratives to better understand adherence to asthma treatment

2019· other· en· W7056586532 on OpenAlexaboutno aff

Bibliographic record

VenueDove Medical Press (Taylor and Francis Group) · 2019
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisAsthmaNarrativeContext (archaeology)Perspective (graphical)Qualitative researchMedical prescriptionNarrative inquiry
DOInot available

Abstract

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Biagina-Carla Farnesi,1 Francine M Ducharme,2,3 Lucie Blais,4 Johanne Collin,4 Kim L Lavoie,5,6 Simon L Bacon,1,6 Martha L McKinney,7 Sandra Peláez3,8 1Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montreal, QC Canada; 2Departments of Pediatrics and of Social and Preventive Sciences, University of Montreal, Montreal, QC Canada; 3Research Centre, CHU Sainte-Justine, University of Montreal, Montreal, QC Canada; 4Faculty of Pharmacy, University of Montreal, Montreal, QC Canada; 5Psychology Department, University of Quebec at Montreal, Montreal, QC Canada; 6Research Center, Sacré-Cœur de Montréal Hospital, CIUSSS du Nord-de-l’Ile-de-Montréal, Montreal, QC Canada; 7CHU Ste-Justine, University of Montreal, Montreal, QC Canada; 8School of Kinesiology and Physical Activity Sciences, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada Purpose: The purpose of this study was to better understand patients’ perspective of asthma self-management by focusing on the sociocultural and medical context shaping patients’ illness representations and individual decisions. Patients and methods: We conducted a secondary analysis of semi-structured interviews carried out as part of a multicentered collective qualitative case study. In total, 24 patients, aged 2–76 years with a confirmed diagnosis of asthma (or were parents of a child), who renewed the prescription for inhaled corticosteroids in the past year, participated in this study. The thematic analysis focused on asthma-related events and experiences reported by the patients. Consistent with narrative inquiry, similar patterns were grouped together, and three vignettes representing the different realities experienced by the patients were created. Results: The comparison of experiences and events reported by the patients suggested that patients’ perceptions and beliefs regarding asthma and treatment goals influenced their self-management-related behaviors. More specifically, the medical context in which the patients were followed (ie, frame in which the medical encounter takes place, medical recommendations provided) contributed to shape their understanding of the disease and the associated treatment goals. In turn, a patient’s perception of the disease and the treatment goals influenced asthma self-management behaviors related to environmental control, lifestyle habits, and medication intake. Conclusion: Current medical recommendations regarding asthma self-management highlight the importance of the physicians’ guidance through the provision of a detailed written action plan and asthma education. These data suggest that while physicians contribute to shaping patients’ beliefs and perceptions about the disease and treatment goals, patients tend to listen to their own experience and manage the disease accordingly. Thus, a medical encounter between the patient and the physician, aiming at enhancing a meaningful conversation about the disease, may lead the patient to approach the disease in a more effective manner, which goes beyond taking preventative paths to avoid symptoms. Keywords: asthma, adherence, self-management, written action plan, patient-physician relationship, narrative inquiry

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.297
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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