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Longitudinal Research

Longitudinal Research

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...

Cross-Sectional Research

Cross-Sectional Research

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...

Reliability and Validity

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.

Longitudinal Studies

Longitudinal Studies

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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Related Experiment Video

Updated: Jul 5, 2026

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Published on: February 11, 2014

Evaluation of cross-sectional and longitudinal construct validity of two vision-related quality of life

M R de Boer¹, C B Terwee, H C W de Vet

¹Department of Ophthalmology, VU University Medical Center, Amsterdam, The Netherlands. michiel.deboer@vumc.nl

Quality of Life Research : an International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation

|February 10, 2006

Summary

The Low Vision Quality of Life (LVQOL) questionnaire shows satisfactory cross-sectional validity, but the Vision-related Quality of Life Core Measure (VCM1) appears poor. Longitudinal validity for both is moderate to poor.

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Last Updated: Jul 5, 2026

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

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Published on: February 11, 2014

Development of a Virtual Reality Assessment of Everyday Living Skills

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Published on: April 23, 2014

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Published on: August 29, 2025

Area of Science:

Ophthalmology
Psychometrics
Health Outcomes Research

Background:

Vision-related quality of life (QOL) questionnaires are crucial for assessing patient well-being.
The Low Vision Quality of Life (LVQOL) and Vision-related Quality of Life Core Measure (VCM1) are prominent QOL instruments.
While their general psychometric properties are comparable, construct and longitudinal validity require thorough examination.

Purpose of the Study:

To evaluate the cross-sectional and longitudinal construct validity of the LVQOL and VCM1 questionnaires.
To test pre-specified hypotheses regarding the relationship between these QOL measures and other relevant assessments.

Main Methods:

Cross-sectional and longitudinal design employed.
Hypothesis testing was used to assess construct validity.
Specific hypotheses were formulated regarding the interrelations of LVQOL and VCM1 with other measures.

Main Results:

Cross-sectional construct validity: 22-50% of hypotheses refuted for LVQOL subscales; 57% for VCM1.
Longitudinal construct validity: 33-75% of hypotheses refuted for LVQOL subscales; 50% for VCM1.
LVQOL demonstrated satisfactory cross-sectional validity, while VCM1 showed poor cross-sectional validity.

Conclusions:

The LVQOL questionnaire exhibits satisfactory cross-sectional construct validity.
The VCM1 questionnaire demonstrates poor cross-sectional construct validity.
Both questionnaires show poor to moderate longitudinal construct validity, indicating limitations in capturing changes over time.