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Record W26658358 · doi:10.1155/2014/738654

Similarities and Differences Between Asthma Health Care Professional and Patient Views Regarding Medication Adherence

2014· article· en· W26658358 on OpenAlexafffund
Sandra Peláez, Simon Bacon, Mark W. Aulls, Guillaume Lacoste, Kim Lavoie

Bibliographic record

VenueCanadian Respiratory Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversité du Québec à MontréalHôpital du Sacré-Cœur de MontréalMcGill UniversityMontreal Heart Institute
FundersCanadian Institutes of Health Research
KeywordsMedicineAsthmaMedication adherenceFamily medicineHealth careMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The recent literature has reported disparate views between patients and health care professionals regarding the roles of various factors affecting medication adherence. OBJECTIVE: To examine the perspectives of asthma patients, physicians and allied health professionals regarding adherence to asthma medication. METHODOLOGY: A qualitative, multiple, collective case study design with six focus-group interviews including 38 participants (13 asthma patients, 13 pulmonologist physicians and 12 allied health professionals involved in treating asthma patients) was conducted. RESULTS: Patients, physicians and allied health professionals understood adherence to be an active process. In addition, all participants believed they had a role in treatment adherence, and agreed that the cost of medication was high and that access to the health care system was restricted. Major disagreements regarding patient-related barriers to medication adherence were identified among the groups. For example, all groups referred to side effects; however, while patients expressed their legitimate concerns, health care professionals believed that patients' opinions of medication side effects were based on inadequate perceptions. CONCLUSION: Differences regarding medication adherence and barriers to adherence among the groups examined in the present study will provide insight into how disagreements may be translated to overcome barriers to optimal asthma adherence. Furthermore, when designing an intervention to enhance medication adherence, it is important to acknowledge that perceptual gaps exist and must be addressed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.033
GPT teacher head0.300
Teacher spread0.267 · 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 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

Citations21
Published2014
Admission routes2
Has abstractyes

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