e. managerial, social, political, economic benefits are linked to the study's results) the proposed helpful outcomes are realistic (i.e. dealing with questions that can actually be answered through the type of data gathering and analysis you're proposing. The suggested helpful outcomes do not go beyond the data that's to be collected).
The increase in teen smoking may be abating, or may be taking a pause before it continues the climb seen in the past 10 years, from 1996 to 2005. In either case, reducing smoking at an early age has a lifelong effect on individuals' health, and can lead to better quality of life for millions of people who might otherwise take up smoking. A secondary benefit is that lessons learned may help to reduce the current 3.1 million teen smokers, many of whom try smoking and quit -- it would be useful to know why they started in the first place, and why they quit.
The objective of this information is to apply the information learned to future ad campaigns, most of which are funded by state tobacco settlement money.
The study will focus on a high school in a mid-sized Texas town, but also include those who started high school, stayed in the same town, but dropped out before their senior year. In order to provide significant statistical results, the study will focus on over 1,000 students in the primary study, plus a control group of at least 400 students. It is hoped that findings in the control group (African-American teens) can be compared to the entire 1,000-student cohort, and to sub-cohorts of Hispanic and white teens.
This survey will be performed with questionnaires which ask the students about the following independent variables:
Body Mass Index -- the hypothesis is that there is a high correlation between high BMI and starting smoking. Does it also correlate with continuing to smoke?
Gender -- the hypothesis is that more boys than girls will take up smoking and continue to smoke; these numbers have changed in the past, so it would be useful to understand how they relate in this group studied.
Sexual behavior -- it may be that there are enough teen pregnancies to study that sub-group's smoking...
If not, the survey will cover some sexual behaviors, attempting to learn if the students engaged in sexual behavior prior to or during their high school years. The hypothesis is that early sexual behavior is a predictor for starting and continuing smoking, as is teen pregnancy.
Dropping out of high school -- the hypothesis is that dropping out of high school results in a higher propensity to start and continue smoking.
Home status -- the hypothesis is that those teens who come from single-parent households are more likely to start and continue smoking habits.
Church attendance -- the hypothesis is that church attendance frequency is negatively correlated with smoking initiation and continuation.
Exercise -- how much they exercise may be related to BMI
School sports participation -- may be related to BMI
It is not known if dropping out of high school is related to the 'problem syndrome,' as outlined in the literature review, above.
It may be that the students' self-declared behaviors are not true, despite assurances that the results will be kept confidential. The study will poll 10% of the students' parents in order to verify some of the claims, such as regular church attendance, single- versus dual-parent households, and known smoking behavior. Although the parents may not be aware of all their children's activities, this will provide a useful cross-check of teen behaviors.
The surveys will be made anonymous. A code will be used to tie together those students' results who also have results from parents, but these will be double-blinded for the study scorers.
In addition to straight correlations, a regression analysis will be used in order to break students into specific groups of behavior. It may be found, for example, that those who are or have been pregnant participate in a number of other behaviors. By controlling for these variables, one may be able to establish influences of specific behaviors or demographic factors on the likelihood of smoking.
Statistical significance will depend on the number in the sample corresponding to specific correlations. if, for example, 100 of the 1,000 surveyed are heavy drinkers (over 1 drink per day), the 2 SD variation will be about 6%. The standard used for statistical significance will be a P
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