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Record W4387719900

Asthma impacts on workplace productivity in employed patients who are symptomatic despite background therapy: a multinational survey

2019· article· en· W4387719900 on OpenAlexaboutno aff
Kevin Gruffydd‐Jones, Mike Thomas, Miguel Román-Rodríguez, Antonio Infantino, FitzGerald Jm, Ian Pavord, Haddon JM, U Elsasser, Christian Vogelberg

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsnot available
Fundersnot available
KeywordsMultinational corporationAsthmaProductivityMedicineSurvey researchBusinessAgricultural economicsIntensive care medicinePhysical therapyEconomic growthSocioeconomicsEconomicsInternal medicineFinance
DOInot available

Abstract

fetched live from OpenAlex

Kevin Gruffydd-Jones,1 Mike Thomas,2 Miguel Roman-Rodríguez,3 Antonio Infantino,4 J Mark FitzGerald,5 Ian Pavord,6 Jennifer M Haddon,7 Ulrich Elsasser,8 Christian Vogelberg91Box Surgery, Box, Wiltshire, UK; 2Primary Care and Population Sciences, University of Southampton, Southampton, UK; 3Son Pisà Primary Health Care Centre, Balearic Health Centre, Palma de Mallorca, Spain; 4Società Italiana Interdisciplinare per le Cure Primarie (SIICP), Bari, Italy; 5Institute for Heart and Lung Health, University of British Columbia, Vancouver, British Columbia, Canada; 6Respiratory Medicine Unit and Oxford Respiratory NIHR Biomedical Research Centre, Nuffield Department of Medicine, University of Oxford, Oxford, UK; 7TA Dig Excellence + Healthcare Inno Med, Boehringer Ingelheim International GmbH, Ingelheim am Rhein, Germany; 8Biostatistics and Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany; 9Department of Pediatric Pneumology and Allergology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, GermanyBackground: Asthma affects millions of people worldwide, with many patients experiencing symptoms that affect their daily lives despite receiving long-term controller medication.Purpose: Work is a large part of most people’s lives, hence this study investigated the impact of uncontrolled asthma on work productivity in adults receiving asthma maintenance therapy.Patients and methods: An online survey was completed by employed adults in Brazil, Canada, Germany, Japan, Spain and the UK. Participants were confirmed as symptomatic using questions from the Royal College of Physicians’ 3 Questions for Asthma tool. The survey contained the Work Productivity and Activity Impairment – Specific Health Problem questionnaire and an open-ended question on the effect of asthma at work.Results: Of the 2,055 patients on long-term maintenance therapy screened, 1,598 were symptomatic and completed the survey. The average percentage of work hours missed in a single week due to asthma symptoms was 9.3%, ranging from 3.5% (UK) to 17.4% (Brazil). Nearly three-quarters of patients reported an impact on their productivity at work caused by asthma. Overall work productivity loss (both time off and productivity whilst at work) due to asthma was 36%, ranging from 21% (UK) to 59% (Brazil). When asked how asthma made participants feel at work, many respondents highlighted how their respiratory symptoms affect them. Tiredness, weakness and mental strain were also identified as particular challenges, with respondents describing concerns about the perception of colleagues and feelings of inferiority.Conclusions: This study emphasizes the extent to which work time is adversely affected by asthma in patients despite the use of long-term maintenance medication, and provides unique personal insights. Strategies to improve patients’ lives may include asthma education, optimizing asthma management plans and running workplace well-being programs. Clinicians, employers and occupational health teams should be more aware of the impact of asthma symptoms on employees, and work together to help overcome these challenges.Keywords: work productivity, asthma, burden, costs

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.176
GPT teacher head0.513
Teacher spread0.337 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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