Methodological Innovations in Gerontology: Advances in Psychosocial Research

Extract

Forty years ago, Baltes, Reese, and Nesselroade (1977) published their path-breaking textbook Life-span Developmental Psychology: Introduction to Research Methods, which delineated methods for studying individual differences and changes over the life course. The textbook’s focus was explicitly interdisciplinary, emphasizing linkages among individual development, social contexts, and historical change. It is fitting that the articles featured in this special issue Methodological Innovations in Gerontology: Advances in Psychosocial Research bridge psychological and sociological principles. These papers exemplify the directive by Baltes and colleagues that “the complexity of the historical study of behavioral development within a changing biocultural context calls for unique methodologies and a heightened sensitivity to the pitfalls, blind alleys, and frustrations produced by malignant data” (1977: 13).

Since the publication of the text, the data, methods, and technologies available to scholars of aging have expanded dramatically, enabling explorations of new areas of study, or more sophisticated investigations of questions at the core of social gerontology. Researchers have moved beyond data resources focused on one individual at a single or two points in time, and instead investigate the experiences of individuals embedded in dyads, families, social networks, and neighborhoods, at multiple points in time. Technological advances such as portable devices for experience sampling and daily diary studies have led to an increased volume of individual-, meta-, and macro-level data, necessitating the development and application of statistical techniques to appropriately model psychosocial phenomena. Merging traditional longitudinal designs, a hallmark of life course sociology, and within-person designs, the foundation of life-span psychology, has yielded measurement burst designs which allow for examinations of short-term fluctuations within the context of long-term changes. Detailed longitudinal data on large population-based samples enable scholars to explore the effects of complex life histories and trajectories on later-life outcomes.