The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Measuring the Heaviness of Smoking: using self‐reported time to the first cigarette of the day and number of cigarettes smoked per day
Abstract
Summary: Two simple self‐report measures have been used to assess the heaviness of smoking,‘number of cigarettes per day’(CPD) and‘time to the first cigarette of the day’(TTF). Little attention, however, has been given to the precise method of scoring this information. Using biochemical indicators of heaviness of smoking (alveolar carbon monoxide and cotinine), we explore the optimum data transformations for regression analysis and categorical analysis. We suggest a four category scoring scheme for both time to the first cigarette of the day (5, 6–30, 31–60 and 61 + mm) and average daily consumption of cigarettes (1–10, 11–20, 21–30, 31 + cigarettes) as the most powerful and practical categorical scoring of these variables. Due to possible ceiling effects on biochemical measures, we suggest using logarithmic transformations of CPD or TTF for regression or correlation analyses.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Cohen, P., Cohen, P., West, S. G., & Aiken, L. S. (2014) · Psychology Press eBooks · doi:10.4324/9781410606266 · Cited by 20,737
(2005) · Technometrics · doi:10.1198/tech.2005.s303 · Cited by 17,923
Applied Linear Statistical Models
Ziegel, E. R., Neter, J., Wasserman, W., & Kutner, M. (1992) · Technometrics · doi:10.2307/1269588 · Cited by 9,907
Applied Linear Statistical Models
(1997) · Technometrics · doi:10.1080/00401706.1997.10485141 · Cited by 7,185
Hahn, G. J., Draper, N., & Smith, H. (1982) · Technometrics · doi:10.2307/1267833 · Cited by 5,773
Applied Linear Statistical Models.
Lorenz, F., Neter, J., Wasserman, W., & Kutner, M. H. (1986) · Journal of the American Statistical Association · doi:10.2307/2289108 · Cited by 5,565
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences.
Fong, G. T., Cohen, J., & Cohen, P. (1985) · Journal of the American Statistical Association · doi:10.2307/2287930 · Cited by 4,475
Bowman, P. W. (1963) · AIBS Bulletin · doi:10.2307/1292957 · Cited by 3,638
Applied Regression Analysis (2nd ed).
de Carvalho, J. F., Draper, N. R., & Smith, H. (1981) · Journal of the American Statistical Association · doi:10.2307/2287608 · Cited by 3,044
Fagerström, K.-O. (1978) · Addictive Behaviors · doi:10.1016/0306-4603(78)90024-2 · Cited by 2,221
Cited by
The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire
HEATHERTON, T. F., KOZLOWSKI, L. T., FRECKER, R. C., & FAGERSTROM, K. (1991) · British Journal of Addiction · doi:10.1111/j.1360-0443.1991.tb01879.x · Cited by 10,738
Self-citationWebb, T. L., & Sheeran, P. (2006) · Psychological Bulletin · doi:10.1037/0033-2909.132.2.249 · Cited by 3,732
de Leon, J., & Diaz, F. J. (2005) · Schizophrenia Research · doi:10.1016/j.schres.2005.02.010 · Cited by 1,276
Novel genes identified in a high-density genome wide association study for nicotine dependence
Bierut, L. J., Madden, P. A. F., Breslau, N., Johnson, E. O., Hatsukami, D., Pomerleau, O. F., Swan, G. E., Rutter, J., Bertelsen, S., Fox, L., et al. (2007) · Human Molecular Genetics · doi:10.1093/hmg/ddl441 · Cited by 622
Planned missing data designs in psychological research.
Graham, J. W., Taylor, B. J., Olchowski, A. E., & Cumsille, P. E. (2006) · Psychological Methods · doi:10.1037/1082-989x.11.4.323 · Cited by 573
Metadata
- Authors
- HEATHERTON, T. F., KOZLOWSKI, L. T., FRECKER, R. C., RICKERT, W., & ROBINSON, J.
- Venue
- British Journal of Addiction
- Publisher
- Wiley
- Published
- 1989-07
- Volume
- 84
- Issue
- 7
- Pages
- 791-800
- ISSN
- 0952-0481 (ISSN-L)
- 2056-5178
- OpenAlex
- W2035501540
- Cited by
- 1,313
- References
- 33
- FWCI
- 0.96
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Measuring the Heaviness of Smoking: using self‐reported time to the first cigarette of the day and number of cigarettes smoked per day. https://app.cochat.ai/papers/10.1111/j.1360-0443.1989.tb03059.x
- The paper
- HEATHERTON, T. F., KOZLOWSKI, L. T., FRECKER, R. C., RICKERT, W., & ROBINSON, J. (1989). Measuring the Heaviness of Smoking: using self‐reported time to the first cigarette of the day and number of cigarettes smoked per day. British Journal of Addiction. https://doi.org/10.1111/j.1360-0443.1989.tb03059.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.