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Record W3200648262 · doi:10.1111/phn.12971

Cigarette smokers’ perceptions of smoking cessation and associated factors in Karachi, Pakistan

2021· article· en· W3200648262 on OpenAlexaff
Rubina Barolia, Sajid Iqbal, Salim S. Virani, Faris Farooq Saeed Khan, Pammla Petrucka

Bibliographic record

VenuePublic Health Nursing · 2021
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsThematic analysisSmoking cessationMedicineQualitative researchPerceptionExploratory researchHealth careFamily medicinePsychologyNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: The study explored the perceptions of adult smokers with cardiovascular and respiratory diseases regarding cigarette smoking cessation. We also explored factors that may hinder or facilitate smoking cessation process. DESIGN: Qualitative descriptive exploratory design SAMPLE: Purposive sample of 13 adult smokers with cardiovascular or respiratory diseases visiting outpatient cardiac and respiratory clinics at a private tertiary care hospital MEASUREMENTS: In-depth, face-to-face, and semi-structured interviews were conducted. The interviews were digitally recorded and transcribed verbatim followed by a six steps process of manual thematic analysis of data. RESULTS: Meaningful statements were assigned codes and grouped into categories. Categories were clustered under three themes representing individual factors, socio-cultural factors, and institutional factors. CONCLUSIONS: Smoking cessation is influenced by personal, cultural, as well as social aspects. Institutionally, there is a need to recognize that smoking is a learned behavior; hence, prohibiting public smoking will potentially contribute to non-smoking behaviors. Although the nature of misconceptions varies, this is imperative to ensure consistency in messaging, programming, and supports led by healthcare professionals.

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)0.001
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 score0.032
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.064
GPT teacher head0.375
Teacher spread0.311 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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