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Longitudinal research involves the collection and analysis of comparable data at more than one point in time. The exact number of time points and the interval between time points depend on the nature of the investigation. A longitudinal design is desirable for many research investigations because it enables an assessment of change over time. The history of research methods in industrial/organizational psychology shows the increasing importance of longitudinal designs (although they are still relatively rare) and advances in associated analytical methods. Experience sampling is one method of longitudinal research in which people are asked to report on particular aspects of their everyday experiences at frequent intervals (which may be more than once a day). This form of longitudinal research has become more commonplace in industrial/organizational psychology in recent years because of its potential for capturing the dynamic nature of work experiences.

Longitudinal Research

The defining characteristic of longitudinal research is that it examines how data change over time. This contrasts with cross-sectional research, in which data are collected and analyzed at only one point in time in order to provide a single snapshot of the variables being studied. Research in which cross-sectional data collection is repeated over time—for example, when a survey is readministered in an organization—is considered longitudinal only if the analysis compares the data from different time points (rather than examining the data from each time point in isolation).

Data can be collected over time from the same sample or from different samples in longitudinal research. Retaining the same sample can be difficult from a practical viewpoint, but it allows the researcher to identify how individuals change over time and eliminates the possibility that identified changes are attributable to differences between samples rather than changes over time. Longitudinal data can be quantitative, qualitative, or both. There are many methods for collecting longitudinal data, but the measures used should be consistent over time so that identified changes cannot be attributed to changes in instrumentation. There are a variety of techniques for analyzing longitudinal data, including time-series analysis, longitudinal multilevel modeling, and latent variable modeling. Usually, studies that sample a large number of equally spaced time points (time-series analysis) offer the greatest potential for identifying the causes and nature of effects.

Types of Longitudinal Research

Five main types of longitudinal research study can be identified:

  • A trend study compares different groups from the same population at different points in time. It can provide information about net change but not individual change.
  • A panel study tracks the same individuals at fixed intervals over a period of time, which often covers many years.
  • A cohort study follows a sample of individuals from a particular group (e.g., an age or an employment group) at fixed intervals over a period of time. It is usually a form of panel study, but it becomes a trend study if a new sample is observed at each time point. A number of cohorts can be simultaneously observed and compared over time, which can be useful for separating the effects of maturational and external influences. For example, comparing different age cohorts measured at the same point in time and the same age cohorts measured at different points in time can help distinguish changes that normally occur as people get older from changes resulting from shifts in employment. If a cohort has received a treatment or intervention, the study is also a quasi-experiment because the individuals have not been assigned randomly to the groups being compared.
  • An intervention study—which is also a form of quasi-experiment—examines the effects of a naturally occurring intervention (e.g., occupational retirement) or an imposed intervention (e.g., a stress-prevention program) by comparing data collected from a group on one or more occasions, both before and after it receives the intervention. Collecting data at the same times from a comparison or control group that has not received the intervention can help to establish whether the changes resulted from the intervention.
  • An experience sampling study obtains reports from the same individuals on many occasions at frequent intervals. It is distinguished by its focus on individuals' immediate experiences in their natural environment and its high frequency of reporting.

Retrospective studies, in which participants recall aspects of their life histories or recent past, are sometimes also labeled longitudinal, but this is not strictly accurate because, although they cover periods of time, they do not usually involve real-time sampling at more than one time point. In genuinely longitudinal retrospective studies, participants report at consecutive time points on their experiences since the last time point. Prospective studies are often preferred, however, because they are less susceptible to the problem of memory recall.

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