Abstract
BackgroundTranslational Medicine focuses on “bench to bedside”, converting experimental results into clinical use. The “bedside to bench” transition remains challenging, requiring clinicians to define true clinical need for laboratory study. In this study, we show how observational data (an eleven-year data survey program on adolescent smoking behaviours), can identify knowledge gaps and research questions leading directly to clinical implementation and improved health care. We studied gender-specific trends (2000–2010) in Italian students to evaluate the specific impact of various anti-smoking programs, including evaluation of perceptions of access to cigarettes and health risk.MethodsThe study used, ESPAD-Italia® (European School Survey Project on Alcohol and other Drugs), is a nationally representative sample of high-school students. The permutation test for joinpoint regression was used to calculate the annual percent change in smoking. Changes in smoking habits by age, perceived availability and risk over a 11-year period were tested using a gender-specific logistic model and a multinomial model.ResultsGender-stratified analysis showed 1) decrease of lifetime prevalence, then stabilization (both genders); 2) decrease in last month and occasional use (both genders); 3) reduction of moderate use (females); 4) no significant change in moderate use (males) and in heavy use (both genders). Perceived availability positively associates with prevalence, while perceived risk negatively associates, but interact with different effects depending on smoking patterns. In addition, government implementation of public policies concerning access to tobacco products in this age group during this period presented a unique background to examine their specific impact on behaviours.ConclusionLarge observational databases are a rich resource in support of translational research. From these observations, key clinically relevant issues can be identified and form the basis for further clinical studies. The ability to identify patterns of behaviour and gaps in available data translates into new experiments, but also impacts development of public policy and reveals patterns of clinical reality. The observed global decrease in use is countered by stabilization in number of heavy smokers. Increased cigarette cost has not reduced use. While perceived risk of smoking may prevent initial experimentation, how government policies impact the perception of risk is not easily quantifiable.
Highlights
The challenges and opportunities for translational medicine (TM) were well described in an editorial in 2003 [1], where the difference between the “bench to bedside” and “bedside to bench” paradigms were described
Our analysis further examines the impact of specific programs and recognizes the difference between experimentation and its progressive conversion to long-term smoking habits, including evaluation of self-perception of access to cigarettes and health risk, especially in years when the programs have been applied
The current study has uniquely analyzed changes in the early smoking habits of Italian adolescents (330,000 students) from 2000 to 2010. We present this detailed analysis as the basis for examining the specific impact of various anti-smoking programs to evaluate their differences in altering experimentation and long-term smoking behaviours, under the hypothesis that there exists a strict association among each intervention program, perceived availability and perceived health risk, and smoking habits
Summary
The challenges and opportunities for translational medicine (TM) were well described in an editorial in 2003 [1], where the difference between the “bench to bedside” and “bedside to bench” paradigms were described. There are at least two approaches to drive the bedside to bench paradigm that could increase the potential that research outcome will have direct clinical application: 1) apply knowledge engineering approaches to identify concerns, gaps and critical need from the clinician, possibly using a natural language interface [3]; and 2) appropriately data-mine and utilize the ex vivo data that exist in well-designed observational studies. We show how observational data (an eleven-year data survey program on adolescent smoking behaviours), can identify knowledge gaps and research questions leading directly to clinical implementation and improved health care. We studied gender-specific trends (2000–2010) in Italian students to evaluate the specific impact of various anti-smoking programs, including evaluation of perceptions of access to cigarettes and health risk. Changes in smoking habits by age, perceived availability and risk over a 11-year period were tested using a gender-specific logistic model and a multinomial model
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