ArticleBig data2015
How Genetic and Other Biological Factors Interact with Smoking Decisions.
Article in Big data, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- The Interplay between Maternal Smoking and Genes in Offspring Birth Weight.medRxiv : the preprint server for health sciences · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite clear links between genes and smoking, effective public policy requires far richer measurement of the feedback between biological, behavioral, and environmental factors. The Kavli HUMAN Project (KHP) plans to exploit the plummeting costs of data gathering and to make creative use of new technologies to construct a longitudinal panel data set that would compare favorably to existing longitudinal surveys, both in terms of the richness of the behavioral measures and the cost-effectiveness of the data collection. By developing a more comprehensive approach to characterizing behavior than traditional methods, KHP will allow researchers to paint a much richer picture of an individual's life-cycle trajectory of smoking, alcohol, and drug use, and interactions with other choices and environmental factors. The longitudinal nature of KHP will be particularly valuable in light of the increasing evidence for how smoking behavior affects physiology and health. The KHP could have a transformative impact on the understanding of the biology of addictive behaviors such as smoking, and of a rich range of prevention and amelioration policies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.