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Adult Development and Aging (6th Edition) by John C. Cavanaugh, Fredda Blanchard-Fields

By John C. Cavanaugh, Fredda Blanchard-Fields

Written inside a biopsychosocial framework, Cavanaugh and Blanchard-Fields' best-selling textual content covers the categorical ages-stages of grownup improvement and getting older. In its remarkable assurance of present learn and thought, the authors draw transparent connections among study and alertness. The book's concentrate on "positive aging" and the profits and losses humans adventure throughout maturity distinguish it from its opponents.

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Additional resources for Adult Development and Aging (6th Edition)

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All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. 1 Three Basic Building Blocks of Developmental Research Time of Measurement Cohort 2000 2010 2020 2030 1950 50 60 70 80 1960 40 50 60 70 1970 30 40 50 60 1980 20 30 40 50 Cohort is represented by the years in the first column, time of measurement by the years across the top, and age by the values in the cells. 1. Cohort is represented by the years in the first column, time of measurement is represented by the years across the top, and age is represented by the numbers in the individual cells.

Sometimes researchers cannot obtain measures directly from people and are able only to watch them carefully. In certain situations, researchers may be able to study a single individual in great detail in a case study. This technique is especially useful when researchers want to investigate very rare phenomena, such as uncommon diseases or people with extremely high ability. Identifying new diseases, for example, begins with a case study of one individual who has a pattern of symptoms that is different from any known syndrome.

G. the surviving participants may have been those who initially less healthy). The third problem with longitudinal designs is that our ability to apply the results to other groups is limited. The difficulty is that only one cohort is followed. Whether the pattern of results that is observed in one cohort can be generalized to another cohort is questionable. Thus researchers using longitudinal designs run the risk of uncovering a developmental process that is unique to that cohort. Because longitudinal designs necessarily take more time and usually are expensive, they have not been used very often.

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