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Longitudinal Research02:20

Longitudinal Research

13.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is 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...
13.0K
Cross-Sectional Research01:50

Cross-Sectional Research

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In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, 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...
12.2K
Longitudinal Studies01:26

Longitudinal Studies

402
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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Observational Studies01:11

Observational Studies

10.6K
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
10.6K
Group Design02:01

Group Design

10.0K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
10.0K
The Scientific Method02:40

The Scientific Method

64.5K
Research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.
64.5K

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Related Experiment Video

Updated: Dec 21, 2025

Enactive Phenomenological Approach to the Trier Social Stress Test: A Mixed Methods Point of View
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Integration Through Connecting in Explanatory Sequential Mixed Method Studies.

Claire Burke Draucker1, Susan M Rawl1,2, Emilee Vode1

  • 1Indiana University School of Nursing, Indianapolis, Indiana, USA.

Western Journal of Nursing Research
|May 12, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel connecting approach for explanatory sequential mixed methods research. It details a systematic sampling strategy to integrate quantitative and qualitative data for enhanced understanding of complex health behaviors.

Keywords:
connectingexplanatory sequential designsinterview guidesmixed methods

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Area of Science:

  • Mixed Methods Research
  • Health Behavior Research
  • Quantitative and Qualitative Data Integration

Background:

  • Explanatory sequential mixed methods studies require effective integration strategies.
  • Existing methods often underutilize quantitative data for qualitative sample selection.
  • Predicting health behaviors like lung cancer screening necessitates robust research designs.

Purpose of the Study:

  • To discuss integration via a connecting approach in explanatory sequential mixed methods.
  • To describe a specific connecting strategy for a lung cancer screening prediction model.
  • To present analytic products stemming from this integration strategy.

Main Methods:

  • Developed a multi-step systematic sampling strategy for qualitative participant selection.
  • Utilized quantitative data to identify specific subgroups for interviews.
  • Created tailored interview guides, narrative summaries, and case studies for integration.

Main Results:

  • A novel connecting strategy was successfully implemented.
  • An interview sample of 40 participants across eight subgroups was generated.
  • The strategy facilitated the expansion of quantitative findings through qualitative insights.

Conclusions:

  • The described connecting approach enhances mixed methods integration.
  • Systematic sampling using quantitative data improves qualitative study design.
  • This methodology offers a powerful tool for in-depth health behavior research.