Consensus statement on assessment of waterpipe smoking in epidemiological studies
Bibliographic record
Abstract
Numerous epidemiological accounts suggest that waterpipe smoking (aka hookah, shisha, narghile) has become a global phenomenon, especially among youth. The alarming spread of waterpipe and accumulating evidence of its addictive and harmful effects represent a new threat in the global fight to limit tobacco-related morbidity and mortality. In response to waterpipe's alarming trends, major public health and tobacco control organisations have started or are considering systematic collection of data about waterpipe smoking to monitor its trends and assess its harmful effects in different societies. Such plans require coordination and agreement on epidemiological measurement tools that reflect the uniqueness of this tobacco use method, and at the same time allow comparison of waterpipe trends across time and place, and with other tobacco use methods. We started a decade ago our work to develop standardised measures and definitions for the assessment of waterpipe smoking in epidemiological studies. In this communication, we try to expand and update these assessment tools in light of our increased knowledge and understanding of waterpipe use patterns, its context and marketing, as well as the need for evidence-guided policies and regulations to curb its spread. We have assembled for this purpose a group of leading waterpipe researchers worldwide, and worked through an iterative process to develop the suggested instruments and definitions based on what we know currently about the waterpipe epidemic. While the suggested measures are by no means comprehensive, we hope that they can provide the building blocks for standard and comparable surveillance of waterpipe smoking globally.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".