MétaCan
Menu
Back to cohort
Record W2793542685 · doi:10.18332/tid/83944

Low knowledge among Zambian smokers and the need for large pictorial health warnings: findings from the ITC Zambia Wave 2 survey

2018· article· en· W2793542685 on OpenAlexaff
Susan Kaai, Fastone Goma, Richard Zulu, Masauso Moses Phiri, Kondwani Chirwa, Lorraine Craig, Anne C K Quah, Geoffrey T. Fong

Bibliographic record

VenueTobacco Induced Diseases · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEnvironmental healthMedicineSocioeconomicsSociology

Abstract

fetched live from OpenAlex

Background Many studies have shown that pictorial health warnings (PHWs) are more effective in increasing knowledge about the many harms of cigarettes. Zambia currently has a single text-only English warning covering less than 3% of pack. This study is the first to assess health knowledge and the effectiveness of warnings in Zambia. Methods Data were from 1,171 smokers in the International Tobacco Control (ITC) Zambia Wave 2 Survey (2014), a longitudinal survey of a nationally representative sample of Zambian adults. Key variables analyzed were knowledge of specific harms of smoking and validated indicators of warning effectiveness. Results Knowledge among Zambian smokers was very low compared to other ITC countries: only 45% knew that smoking causes stroke (2 nd lowest among 20 ITC countries), heart disease (74%--3 rd lowest among 14 ITC countries), and lung cancer (79%--lowest among 12 ITC countries). The Zambian text-only warning was very ineffective: 58% of Zambian smokers reported “never” or “hardly ever” noticing the warning; only 24% reported closely reading the warning. 75% reported that warning “never” stopped them from smoking; 70% reported that warning did not make them more likely to think about health risks; 66% reported that warning “never” made them think about quitting. When shown the warning, 55% of smokers were not able to easily read it. And yet 71% thought the packs should have more health information and 86% wanted the government to do more about harms of tobacco use. Conclusions Knowledge of tobacco-related harms is very poor among Zambian smokers and the single-text only warning provides no help, particularly among the many low literacy smokers in Zambia. There is a clear need for Zambia to implement pictorial health warnings, as they are obligated to do as a Party to the FCTC and as other African countries - Mauritius and Kenya - have already done successfully.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.039
GPT teacher head0.318
Teacher spread0.279 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueTobacco Induced DiseasesSame topicVaccine Coverage and HesitancyFrench-language works237,207