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Record W4229054338 · doi:10.1111/hex.13513

Attitudes towards the integration of smoking cessation into lung cancer screening in the United Kingdom: A qualitative study of individuals eligible to attend

2022· article· en· W4229054338 on OpenAlexaff
Samantha Groves, Grace McCutchan, Samantha L. Quaife, Rachael L Murray, Jamie S. Ostroff, Kate Brain, Philip Crosbie, Janelle Yorke, David Baldwin, John K. Field, Lorna McWilliams

Bibliographic record

VenueHealth Expectations · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsInstitute of Infection and Immunity
FundersManchester Biomedical Research CentreNational Cancer InstituteNational Institute for Health and Care ResearchCancer Research UK
KeywordsSmoking cessationMedicineFocus groupCancer screeningThematic analysisFamily medicineLung cancer screeningQualitative researchOutreachLung cancerNursingCancerOncologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: There is limited research exploring how smoking cessation treatment should be implemented into lung cancer screening in the United Kingdom. This study aimed to understand attitudes and preferences regarding the integration of smoking cessation support within lung cancer screening from the perspective of those eligible. METHODS: Thirty-one lung cancer screening eligible individuals aged 55-80 years with current or former smoking histories were recruited using community outreach and social media. Two focus groups (three participants each) and 25 individual telephone interviews were conducted. Data were analysed using the framework approach to thematic analysis. RESULTS: Three themes were generated: (1) bringing lung cancer closer to home, where screening was viewed as providing an opportunity to motivate smoking cessation, depending on perceived personal risk and screening result; (2) a sensitive approach to cessation with the uptake of cessation support considered to be largely dependent on screening practitioners' communication style and expectations of stigma and (3) creating an equitable service that focuses on ease of access as a key determinant of uptake, where integrating cessation within the screening appointment may sustain increased quit motivation and prevent loss to follow-up. CONCLUSIONS: The integration of smoking cessation into lung cancer screening was viewed positively by those eligible to attend. Screening appointments providing personalized lung health information may increase cessation motivation. Services should proactively support participants with possible fatalistic views regarding risk and decreased cessation motivation upon receiving a good screening result. To increase engagement in cessation, services need to be person-centred. PATIENT OR PUBLIC CONTRIBUTION: This study has included patient and public involvement throughout, including input regarding study design, research materials, recruitment strategies and research summaries.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.945

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 head0.172
GPT teacher head0.502
Teacher spread0.330 · 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 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

Citations8
Published2022
Admission routes1
Has abstractyes

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