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Record W2182495851 · doi:10.21767/2049-5471.100025

Why do Chinese people with COPD continue smoking: the attitudes and beliefs of Chinese residents of Vancouver, Canada

2015· article· en· W2182495851 on OpenAlexaffabout
Iraj Poureslami, Jessica Shum, J Mark FitzGerald

Bibliographic record

VenueDiversity & Equality in Health and Care · 2015
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsOpen access publishingCOPDChinese peopleMedicineGerontologyMedia studiesChinaPolitical scienceWorld Wide WebComputer scienceSociologyPsychiatryLaw

Abstract

fetched live from OpenAlex

Chronic obstructive pulmonary disease (COPD) is currently one of the most common chronic lung diseases and a growing cause of global morbidity and mortality.Smoking is the most important risk factor for its development, and about 20% of smokers develop COPD.This study took place in Metro Vancouver, Canada.The aim of the study was to compare and contrast the smoking habits and associated beliefs among two groups of Chinese people after receiving a diagnosis of COPD: those who successfully stopped smoking and those who continued to smoking.Ninety one Mandarin or Cantonese speaking patients with COPD, of whom 24 were current smokers and 67 were former smokers, participated in individual semi-structured interviews.Participants were recruited with the assistance of primary care physicians and respirologists in the Metro Vancouver.Data were analyzed using hand coding for qualitative content analysis.Differences between the two groups were assessed.Smoking experience, social influences, addiction/habit, and the advantages and disadvantages of smoking were identified.In particular, differences between smokers and former smokers found in terms of beliefs that smoking helps relaxation and reduces COPD anxiety and stress, and that smoking is a psychological habit that cannot give up easily.Significant information on barriers to successful smoking cessation was also elucidated.This study suggests we need to first understand Chinese smokers' internal motivations to quit and then assist with culturally and linguistically relevant smoking cessation counselling.Further research is needed to determine if communication regarding tobacco use that is targeted toward the Chinese-speaking population in North America improves cessation rates. Keywords: smoking, beliefs, attitudes, COPD, Chinese communities, differences between quitting versus non quitting subjectsWhat is known about this subject?• While most individuals understand the benefits of smoking cessation and many who are diagnosed with COPD quit smoking, some Chinese people with COPD continue to smoke.• Despite knowing about the harmful effects of smoking, Chinese people with COPD report difficulties in cutting down or quitting smoking: high nicotine dependence, breaking lifelong smoking habits, and lack of motivation.• Having respiratory symptoms is not reason enough to quit smoking.Many Chinese people with COPD continue to smoke because they feel regarded their illness as self-inflicted and believe themselves to be unworthy of smoking cessation assistance.• Long-term behavioural support increases the number of ex-smokers; interventions that promote smoking cessation may be more effective when counselling and behavioural treatments are perceived relevant to individual need. What this paper adds• Insight into Chinese people's perceptions of the consequences of smoking and their beliefs about the likelihood that they will develop COPD.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.308
Teacher spread0.281 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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