Longitudinal and Cross Sectional Studies

The most straightforward approach to assessing physical and behavioral changes in people over time is to conduct a longitudinal study in which the same group of individuals are followed up over a long period of time and periodically reevaluated. Unfortunately, due to carryover effects and mortality, this approach does not always yield valid information. Carryover effects result in measurements taken at time B being affected by the same measurements taken previously at time A. Mortality refers to the loss of subjects due to moving, dying, or refusing to participate further in the study. The result may be that the persons who are assessed at later periods is different in significant ways from those with whom the study began. Finally, the fact that a longitudinal study may continue for many years can result in the study not being completed by the same researchers who began it.

An alternative to the longitudinal approach to developmental research is a cross-sectional study, in which groups of people of different chronological ages are measured at the same point in time. For example, a cross-sectional study of changes in cognitive abilities during adulthood might involve administering appropriate measures of these abilities to groups of individuals of different ages from 20 to 80. The cross-sectional approach, which was firs; used by Adolphe Quetelet in 1838, is less expensive and more efficient than the longitudinal approach but has its own drawbacks. One drawback is that the different age groups must be matched initially on variables that might confound the relationship between age and the variable of interest (the criterion variable). For example, in a study of changes in cognitive abilities over the life span, the investigator should match various age groups on education before comparing them on measures of cognitive abilities. This matching process is not always easy to do, and even so, it may still not be clear whether differences among selected age groups on the criterion variable are a result of the developmental process, cohort (generational, cultural, etc.) differences, or other variables associated with chronological age. Thus, the researchers may not be able to tell whether the observed differences among the age groups on the criterion variable are caused by the aging process itself, by generational or cultural differences (cohort differences), or by time-related changes in the attitudes and values of society. In short, whereas the longitudinal approach confounds chronological age with the times at which the physical and behavioral characteristics are assessed, the cross-sectional approach confounds chronological age with cohort (generational) differences.

To obtain a clearer picture of the effects of age, apart from cohort and time-of-measurement effects, investigators have employed research designs consisting of a combination of the longitudinal and cross-sectional procedures. One approach, proposed by Warner Schaie (1967) is the three-component model in Figure 1-2. As depicted in the figure, a simple cross-sectional study might involve comparing the characteristics of behaviors of representative samples of 25-, 35-, 45-, and 55-year-olds (A, E, H, and J in the figure). On the other hand, a simple longitudinal design might involve comparing the characteristics or behaviors of the same group of individuals at ages 25,35,45, and 55 (A, B, C, and D in the figure). A third type of age-related comparison is a time-lag design, in which several cohorts are examined, each at a different time period. As depicted by the letters M, J, G, and D in the figure, the subjects in this design are all of the same chronological age (55) when they are assessed, but they were born in different years and are assessed in different years. Unfortunately, like the cross-sectional and longitudinal designs, the time-lag design does not enable the investigator to evaluate the true effects of aging, free from the confounding effects of cohort differences and the time at which the assessments are made.

Other proposals for separating differences in characteristics or behaviors due to age from those due to cohort and time-of-measurement differences were made by Baltes (1968) and Schaie (1977). One of these proposals, Schaie's (1977) most efficient design, involves a combination of three different research strategies. To begin, a cross-sectional study is conducted, in which two or more age groups are measured at the same point in time.

Cross-sectional

Cross-sequential

Time-lag

Year of Birth

1945

1935

1925

1915

Cross-sectional

Cross-sequential

Time-lag

Year of Birth

1945

1935

1925

1915

Cohort-sequential

Time-sequential

Longitudinal

1970

1980

1990

Yearof Measurement

2000

Figure 1-2 Schematic Representation of Cross-Sectional, Longitudinal, and Sequential Designs for Developmental Research. Ages in years are above letters in table. See text for further explanation.

1970

1980

1990

Yearof Measurement

2000

Cohort-sequential

Time-sequential

Longitudinal

Figure 1-2 Schematic Representation of Cross-Sectional, Longitudinal, and Sequential Designs for Developmental Research. Ages in years are above letters in table. See text for further explanation.

Longitudinal data on several cohorts are provided by retesting these groups after several years. In addition, two or more new age groups are tested to form a second cross-sectional study. The longitudinal data can be added to by retesting previously tested age groups every 5-10 years, and the cross-sectional data can be added to by testing new age groups.

There are three ways of analyzing the results of a study employing a most-efficient design—cohort-sequential, cross-sequential, and time-sequential. The interactive effect of cohort and age on the dependent variable is of concern in a cohort-sequential analysis. For example, changes in cognitive abilities from age 45 to 55 in a group of people born in 1945 may be compared with such changes from age 45 to 55 in a group born in 1935. Referring to Figure 1-2, the difference between C and D is compared with the difference between F and G. In the second or cross-sequential analysis, the interaction between cohort and time of measurement is of concern. For example, changes in cognitive abilities from 1980 to 1990 in a group born in 1945 are compared with the changes in abilities during the same period in a group born in 1935. Referring to Figure 1 -2,the difference between B and C is compared with the difference between F and G. Finally, the interaction between age and time of measurement is of concern in a time-sequential analysis. For example, the cognitive abilities of 65-year-olds are compared with those of 75-year-olds, both in 1990 and 2000. Referring to Figure 1-2, the difference between K and O is compared with the difference between H and L. An abstract of a study

Abstract of a Study with Cross-Sectional, Longitudinal, and Sequential Research Designs

Whitbourne, S. K., Zuschlag, M. K., Elliot, L. B., & Waterman, A. S. (1992). Psychosocial development in adulthood: A 22-year sequential study. Journal of Personality and Social Psychology, 63 (2), 260—271.

Data supporting the notion of adult personality stability are challenged by the present findings, in which developmental change was demonstrated using the Eriksonian-stage-based Inventory of Psychosocial Development (A. Constantinople, 1969). A sequential design over the ages 20-42 was used on 2 cohorts of college students and alumni originally tested in 1966 and 1976-1977 (ns in 1988 = 99 and 83, respectively), and a 3rd cohort of college students in 19881989 (n = 292). Results of longitudinal, cross-sectional, and sequential analyses challenged ideas about personality stability, with evidence of increasingly favorable resolutions of the early Eriksonian psychosocial stages up through the oldest age studied. There was evidence of a trend over the past decade toward less favorable resolution of ego integrity vs. despair. The findings were interpreted in terms of developmental change processes during the adult years interacting with culturally based environmental effects on psychosocial development (Reprinted with permission of the American Psychological Association, publisher of Psychological Abstracts and the PsycLIT database. All rights reserved.)

that employed several types of developmental research designs—cross-sectional, longitudinal, and sequential—is given in Report 1-3.

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