including physiological, behavioral, cognitive, and social psychological outcomes. Given the law of unintended consequences, not all effects of the introduction of new technologies are likely to be planned or even anticipated when the technology is designed. Furthermore, research on human factors and aging strongly indicates that technology designers often do not consider the information processing limitations of humans, let alone their existing behavioral repertoire of skills, their attitudes, and their preferences regarding how to achieve goals (Czaja, 2001). Thus, there is a critical need for effective and reliable methods for judging the efficacy of technological interventions for improving the functioning of older persons, for assisting them in performing tasks necessary for everyday living, for enhancing their capacity to engage in desired behaviors, and for generally improving their quality of life.

Fortunately, the means for accomplishing these tasks are, by and large, available. Social scientists have engaged the generic problem of effective methods for program evaluation in a variety of domains, including education and clinical psychology (e.g., Zigler and Styfco, 2001). The pioneering efforts of scientists such as Donald T. Campbell (Bickman, 2000; Campbell and Stanley, 1966; Cook and Campbell, 1979) in the latter half of the twentieth century have produced well-established principles for conducting experimental and quasi-experimental evaluations of social trends and interventions that are intended to modify them (e.g., Berk and Rossi, 1999; Boruch, 1997; Shadish, Cook, and Leviton, 1995). The seminal study by Campbell and Stanley (1966) also had a strong influence on thinking about how to approach problems of research on aging (Nesselroade and Labouvie, 1985; Schaie, 1977). The dominant approach has been to emphasize quantitative methods for evaluating program impact, but there has also been renewed attention to and appreciation of the benefits of qualitative approaches for certain questions and problems (e.g., Patton, 2001).

A hallmark of modern approaches to program evaluation is an appreciation of the critical role that measurement quality plays in generating valid research conclusions (e.g., Campbell and Russo, 2001). Arguably, selection or development of sensitive and valid measurement techniques is the most important aspect of successful evaluation research. Finally, our sampling methods (for example, ones that achieve representativeness to a target population) have evolved considerably over the past 50 years and are widely employed in sociology, demography, and other disciplines (for an introduction, see Babbie, 2003). These issues are of course highly relevant to research on aging (Alwin and Campbell, 2001; Lawton and Herzog, 1989).

Generally speaking, research design can be viewed as a process of making compromises regarding what and when one measures so as to

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