Title |
Comparing effects of tobacco use prevention modalities: need for complex system models
|
---|---|
Published in |
Tobacco Induced Diseases, January 2013
|
DOI | 10.1186/1617-9625-11-2 |
Pubmed ID | |
Authors |
Steve Sussman, David Levy, Kristen Hassmiller Lich, Crystal W Cené, Mimi M Kim, Louise A Rohrbach, Frank J Chaloupka |
Abstract |
Many modalities of tobacco use prevention programming have been implemented including various policy regulations (tax increases, warning labels, limits on access, smoke-free policies, and restrictions on marketing), mass media programming, school-based classroom education, family involvement, and involvement of community agents (i.e., medical, social, political). The present manuscript provides a glance at these modalities to compare relative and combined impact of them on youth tobacco use. In a majority of trials, community-wide programming, which includes multiple modalities, has not been found to achieve impacts greater than single modality programming. Possibly, the most effective means of prevention involves a careful selection of program type combinations. Also, it is likely that a mechanism for coordinating maximally across program types (e.g., staging of programming) is needed to encourage a synergistic impact. Studying tobacco use prevention as a complex system is considered as a means to maximize effects from combinations of prevention types. Future studies will need to more systematically consider the role of combined programming. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Thailand | 1 | 17% |
United Kingdom | 1 | 17% |
Unknown | 4 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 67% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Scientists | 1 | 17% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 1 | 3% |
Unknown | 35 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 6 | 17% |
Researcher | 5 | 14% |
Student > Ph. D. Student | 4 | 11% |
Student > Doctoral Student | 3 | 8% |
Student > Postgraduate | 3 | 8% |
Other | 9 | 25% |
Unknown | 6 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 7 | 19% |
Nursing and Health Professions | 7 | 19% |
Social Sciences | 7 | 19% |
Psychology | 2 | 6% |
Business, Management and Accounting | 1 | 3% |
Other | 4 | 11% |
Unknown | 8 | 22% |