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Record W2047579046 · doi:10.1186/s12890-015-0044-9

Patients’ perspective of barriers and facilitators to taking long-term controller medication for asthma: a novel taxonomy

2015· article· en· W2047579046 on OpenAlexafffund
Sandra Peláez, Alexandrine J. Lamontagne, Johanne Collin, Annie Gauthier, Roland Grad, Lucie Blais, Kim Lavoie, Simon Bacon, Pierre Ernst, Hélène Guay, Martha L. McKinney, Francine M. Ducharme

Bibliographic record

VenueBMC Pulmonary Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcGill UniversityConcordia UniversityJewish General HospitalUniversité du Québec à MontréalCentre Hospitalier Universitaire Sainte-JustineInstitut National d'Excellence en Santé et en Services SociauxUniversité de MontréalMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsMedicineAsthmaMedical prescriptionFamily medicineThematic analysisPsychological interventionQualitative researchNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although asthma morbidity can be prevented through long-term controller medication, most patients with persistent asthma do not take their daily inhaled corticosteroid. The objective of this study was to gather patients' insights into barriers and facilitators to taking long-term daily inhaled corticosteroids as basis for future knowledge translation interventions. METHODS: We conducted a collective qualitative case study. We interviewed 24 adults, adolescents, or parents of children, with asthma who had received a prescription of long-term inhaled corticosteroids in the previous year. The one-hour face-to-face interviews revolved around patients' perceptions of asthma, use of asthma medications, current self-management, prior changes in self-management, as well as patient-physician relationship. We sought barriers and facilitators to optimal asthma management. Interviews were transcribed verbatim and transcripts were analyzed using a thematic approach. RESULTS: Patients were aged 2-76 years old and 58% were female. Nine patients were followed by an asthma specialist (pulmonologist or allergist), 13 patients by family doctors or pediatricians, and two patients had no regular follow-up. Barriers and facilitators to long-term daily inhaled corticosteroids were classified into the following loci of responsibility and its corresponding domains: (1) patient (cognition; motivation, attitudes and preferences; practical implementation; and parental support); (2) patient-physician interaction (communication and patient-physician relationship); and (3) health care system (resources and services). Patients recognized that several barriers and facilitators fell within their own responsibility. They also underlined the crucial impact (positive or negative) on their adherence of the quality of patient-physician interaction and health care system accessibility. CONCLUSIONS: We identified a close relationship between reported barriers and facilitators to adherence to long-term daily controller medication for asthma within three loci of responsibility. As such, patients' adherence must be approached as a multi-level phenomenon; moreover, interventions targeting the patient, the patient-physician interaction, and the health care system are recommended. The present study offers a potential taxonomy of barriers and facilitators to adherence to long-term daily inhaled corticosteroids therapy that, once validated, may be used for planning a knowledge translation intervention and may be applicable to other chronic conditions.

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)0.009
metaresearch head score (Gemma)0.016
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 score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.008
Scholarly communication0.0060.007
Open science0.0020.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.309
Teacher spread0.262 · 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".

Quick stats

Citations80
Published2015
Admission routes2
Has abstractyes

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