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Record W2899987738 · doi:10.1093/heapro/day084

Individual-level determinants of waterpipe smoking demand in four Eastern-Mediterranean countries

2018· article· en· W2899987738 on OpenAlexfundno aff
Ramzi G. Salloum, Rima Nakkash, Niveen M. E. Abu-Rmeileh, Randah R Hamadeh, Muhammad W. Darawad, Khalid Kheirallah, Yahya Al‐Farsi, Afzalhussein Yusufali, Justin Thomas, Aya Mostafa, Mohamed Salama, Lama El Kadi, Sukaina Alzyoud, Nihaya Al-Sheyab, James F. Thrasher

Bibliographic record

VenueHealth Promotion International · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
FundersInternational Development Research CentreAl Jalila Foundation
KeywordsMultinomial logistic regressionTobacco controlEnvironmental healthNicotineMedicineSmokeLogistic regressionDemographyPublic healthGeography

Abstract

fetched live from OpenAlex

The prevalence of waterpipe tobacco smoking in the Eastern Mediterranean Region is at alarmingly high levels, especially among young people. The objective of this research was to evaluate the preferences of young adult waterpipe smokers with respect to potential individual-level determinants of waterpipe smoking using discrete choice experiment methodology. Participants were young adult university students (18-29 years) who were ever waterpipe smokers, recruited from universities across four Eastern Mediterranean countries: Jordan, Oman, Palestine and the United Arab Emirates. The Internet-based discrete choice experiment, with 6 × 3 × 2 block design, evaluated preferences for choices of waterpipe smoking sessions, presented on hypothetical waterpipe café menus. Participants evaluated nine choice sets, each with five fruit-flavored options, a tobacco flavored option (non-flavored), and an opt-out option. Choices also varied based on nicotine content (0.0% vs. 0.05% vs. 0.5%) and price (low vs. high). Participants were randomized to receive menus with either a pictorial + text health-warning message or no message (between-subjects attribute). Multinomial logit regression models evaluated the influence of these attributes on waterpipe smoking choices. Across all four samples (n = 1859), participants preferred fruit-flavored varieties to tobacco flavor, lower nicotine content and lower prices. Exposure to the health warning did not significantly predict likelihood to opt-out. Flavor accounted for 81.4% of waterpipe smoking decisions. Limiting the use of fruit flavors in waterpipe tobacco, in addition to accurate nicotine content labeling and higher pricing may be effective at curbing the demand for waterpipe smoking among young adults.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.263
GPT teacher head0.319
Teacher spread0.056 · 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.

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

Citations20
Published2018
Admission routes1
Has abstractyes

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