{"id":38,"date":"2023-01-19T17:09:44","date_gmt":"2023-01-19T17:09:44","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/introductiontopsychology\/chapter\/reading-research\/"},"modified":"2025-10-31T16:19:08","modified_gmt":"2025-10-31T16:19:08","slug":"reading-research","status":"publish","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/introductiontopsychology\/chapter\/reading-research\/","title":{"raw":"Types of Research: Learn It 5\u2014Archival, Longitudinal, and Cross-Sectional Research","rendered":"Types of Research: Learn It 5\u2014Archival, Longitudinal, and Cross-Sectional Research"},"content":{"raw":"

Archival Research<\/h2>\r\n

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research.<\/p>\r\n

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archival research<\/h3>\r\n

Research that relies on looking at past records or data sets to look for interesting patterns or relationships.<\/p>\r\n<\/section>\r\n

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students.<\/p>\r\n

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.<\/p>\r\n

[ohm2_question height=\"185\"]3415[\/ohm2_question]<\/section>\r\n
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Cross-Sectional Research<\/h2>\r\n

Sometimes we want to see how people change over time, as in studies of human development and lifespan.\u00a0One approach is cross-sectional<\/strong> research.<\/p>\r\n

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cross-sectional research<\/h3>\r\n

When a researcher compares multiple segments of the population at the same time.<\/p>\r\n<\/section>\r\n

Imagine that a researcher wants to know how eating habits vary by age range. To do this, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations, also called cohorts, that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations.<\/p>\r\n

Longitudinal Research<\/h2>\r\n

When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research.<\/p>\r\n

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longitudinal research<\/h3>\r\n

A research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.<\/p>\r\n<\/section>\r\n

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population.<\/p>\r\n

\r\n[caption id=\"\" align=\"alignright\" width=\"325\"]\"A Figure 2<\/strong>. Longitudinal research like the CPS-3 help us to better understand how smoking is associated with cancer and other diseases. (credit: CDC\/Debora Cartagena)[\/caption]\r\n\r\n

The Cancer Prevention Study-3 (CPS-3)<\/b><\/h3>\r\n

The American Cancer Society\u2019s Cancer Prevention Study-3<\/a> (CPS-3)<\/b><\/span>is a large-scale longitudinal study tracking hundreds of thousands of adults<\/span> for over two decades.<\/p>\r\n

Participants complete detailed surveys about health behaviors, family history, and environmental factors. Follow-up surveys every few years help researchers identify patterns\u2014such as which habits or exposures predict cancer risk.<\/p>\r\n

Earlier Cancer Prevention Studies were among the first to link smoking to cancer<\/span>, providing groundbreaking evidence for public health policy.<\/p>\r\n<\/section>\r\n

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.<\/p>\r\n

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition<\/strong> rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increase over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.<\/p>\r\n

[ohm2_question height=\"500\"]3416[\/ohm2_question]<\/section>\r\n<\/section>","rendered":"

Archival Research<\/h2>\n

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research.<\/p>\n

\n

archival research<\/h3>\n

Research that relies on looking at past records or data sets to look for interesting patterns or relationships.<\/p>\n<\/section>\n

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students.<\/p>\n

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.<\/p>\n