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Record W2061441741 · doi:10.1080/09595230701710829

What does it mean to want to quit?

2007· article· en· W2061441741 on OpenAlexaboutno aff
James Balmford, Ron Borland

Bibliographic record

VenueDrug and Alcohol Review · 2007
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersGlaxoSmithKline
KeywordsSmoking cessationQuarter (Canadian coin)Quit smokingAmbivalenceMedicinePsychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: To report on the prevalence of attitudes and beliefs about the importance of wanting to quit and need for use of cessation assistance, that may act as barriers to quitting smoking and adopting cessation assistance. DESIGN AND METHODS: National telephone survey of 802 randomly selected adults (685 smokers, 117 recent quitters). RESULTS: Seventy per cent of smokers believed that 'wanting to quit' was both a necessary and sufficient condition for being able to quit. While only one-third of smokers believed that they were too addicted to be able to quit, only a quarter believed they could quit any time they want to. Belief that use of cessation assistance is a sign of weakness was endorsed by 35% of participants, and related to stage of change. DISCUSSION AND CONCLUSIONS: Beliefs about the importance of wanting to quit are commonly held. Many smokers appear to believe that a rational, unambivalent desire to quit is needed before it is worthwhile trying. Short-term impulses to act are not perceived as sufficient. The role of cessation assistance in helping smokers form a rational desire to quit appears to be poorly understood by the majority of smokers. There is a need to engender greater understanding of the potential value of cessation aids to smokers experiencing ambivalence about wanting to quit.

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)0.003
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.044
GPT teacher head0.378
Teacher spread0.334 · 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

Citations62
Published2007
Admission routes1
Has abstractyes

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