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Record W2905345889 · doi:10.2196/12061

Household Surveys in the General Population and Web-Based Surveys in IQOS Users Registered at the Philip Morris International IQOS User Database: Protocols on the Use of Tobacco- and Nicotine-Containing Products in Germany, Italy, and the United Kingdom (Greater London), 2018-2020

2018· article· en· W2905345889 on OpenAlexvenueno aff
Zheng Sponsiello-Wang, P. Langer, L. Prieto, Mariia Dobrynina, Dimitra Skiada, Nathalie Camille, Rolf Weitkunat, Frank Lüdicke

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental healthContext (archaeology)PopulationMedicineNicotineNicotine replacement therapyCross-sectional studyStratified samplingGeographyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Philip Morris International (PMI) has developed a novel heat-not-burn tobacco product, Tobacco Heating System (THS), which is marketed under the brand name of IQOS with HEETS (IQOS). The aerosol generated by THS has substantially fewer toxicants than combustible cigarette smoke, although the extent of the reduction of harmful and potentially harmful constituents reported varies between studies. To evaluate the potential harm reduction associated with IQOS use, the assessment of the uptake and continued use of IQOS in the context of all other tobacco- and nicotine-containing products is crucial. In March 2018, PMI launched cross-sectional surveys in Germany, Italy, and the United Kingdom (Greater London) to estimate the prevalence and use patterns of IQOS and other tobacco- and nicotine-containing products use in these 3 markets following the commercialization of IQOS. This study describes the protocol of the surveys. OBJECTIVE: The objectives of these surveys are to estimate the prevalence of tobacco- and nicotine-containing products use; describe past and current patterns of use; and explore their associations with self-reported health, motivation to use, risk perceptions, and perceived aesthetic changes. METHODS: The overall design of the surveys is similar in all 3 countries. Repeated cross-sectional surveys are being conducted annually over 3 consecutive years (2018 to 2020) and in 2 samples: a representative sample of the general population and a sample of IQOS users. A total of 6085 adults per year will be selected from the general population for each survey through multistage stratified sampling, and participants will respond to face-to-face computer-assisted personal interviews. In addition, 1404, 1384, and 1246 IQOS users per year in Germany, Italy, and Greater London, respectively, will be randomly selected from the PMI IQOS user database and will be invited to complete the Web-based survey using computer-assisted self-interviews. The Smoking Questionnaire is used to assess the tobacco use patterns of the participants. RESULTS: The recruitment of the general population sample began in March 2018 and that of the IQOS user sample began in April 2018. The data collection is ongoing, and the results of the first year data analysis are expected to be available by June 2019. CONCLUSIONS: As the design of the 3 surveys is similar, the results will allow for cross-countries comparison of the prevalence of IQOS and other tobacco- and nicotine-containing products use as well as patterns of use and associated factors. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12061.

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)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0170.008

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 head0.410
GPT teacher head0.475
Teacher spread0.065 · 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 designNot applicable
Domainnot available
GenreProtocol

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
Published2018
Admission routes1
Has abstractyes

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