انگیختگی ادراکی ایجاد حافظه های جدید اپیزودیک را بهبود می بخشد

Objectives. Our purpose is to advise those who propose to use school-based sampling frames in studying risk attributes of the adolescent population. Compared to using area sampling frames, will their estimates be biased by the fact that they do not have data from adolescents who are not enrolled in or present at school, primarily dropouts and graduates? Methods. We used a national probability sample of school enrollment rosters as a sampling frame but administered questionnaires in respondents’ homes. In this way we obtained data not only from those attending school but also from those who had dropped out or graduated between the time rosters were compiled and the time questionnaires were administered. We compare estimates of attributes with and without dropouts and graduates. Results. Estimates based on omitting those who had dropped out or graduated within the year before interview are only trivially different from estimates that include them, even though dropouts and graduates often differ significantly from those still attending school. Conclusions. Although dropouts and graduates are missing, school administration of interviews does not significantly bias population-wide estimates. This is because dropout rates at the national level are currently quite low. Although they differ significantly from the enrolled, the absence of dropouts does not bias estimates for the total population.

In planning a national survey of adolescents, decisions must be made about the population to be represented and the survey design that will best accomplish this. Generally, we assume that researchers are interested in representing the entire adolescent population at certain ages. An area sample survey would be the first choice since it can be designed to include everyone. If the survey targets ages at which most adolescents are in school, a school-based survey might be considered as an alternative since it would be much less expensive—but it would miss those not enrolled in school, i.e., those who have dropped out (not enrolled and not graduated) and those who have graduated. Other groups that one might expect to miss in a school-based survey are actually enrolled but are often in statuses of short duration. These groups are very small and include runaways and the homeless and institutionalized.1 The National Longitudinal Study of Adolescent Health (Add Health) obtained its sample from school rosters. To reduce the probability of bias because dropouts were missed, we interviewed the sample respondents at home. At the time of the home interviews (one to two years after school rosters were compiled), all sample respondents were sought, irrespective of their enrollment status. Those who were not enrolled because they had dropped out (temporarily or permanently) or had graduated were included. In this way, Add Health differs from school-based surveys that use school administration of the survey instrument. Using Add Health data, we can compare survey results with and without the not-enrolled and can determine the bias we would have experienced had we used school administration. Previous studies have examined the effects of failing to sample dropouts, but some controversy remains. Several agree that omitting dropouts does not substantially affect population estimates of drug use (GAO, 1993; Gfroerer et al., 1997; Johnston and O’Malley, 1985; Swaim et al., 1997). None of these looked at the effect of omitting high school graduates who are of an appropriate age to be enrolled in school. The methods used in this paper have the advantage of eliminating such other factors as different settings (home vs. school),2 question wordings, modes of data collection, and the impact of non-response that might contribute to differences in high risk behaviors estimated from a school-based rather than an area survey.