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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...

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Related Experiment Video

Updated: Jun 22, 2026

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

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Published on: February 14, 2014

Predicting Older Adults' Mobile Payment Adoption: An Extended TAM Model.

Cheng-Chia Yang¹, Shang-Yu Yang¹, Yu-Chia Chang^1,2

¹Department of Healthcare Administration, Asia University, Taichung 41354, Taiwan.

International Journal of Environmental Research and Public Health

|January 21, 2023

Summary

Older adults

Keywords:

behavioral intention influence factor mobile payment older adults

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Area of Science:

Gerontology
Human-Computer Interaction
Information Systems

Background:

Mobile payments (M-payment) adoption is growing globally.
Understanding older adults' adoption barriers is crucial for digital inclusion.
Existing models need integration to capture specific user segments.

Purpose of the Study:

To identify key factors influencing older adults' behavioral intentions to use mobile payments.
To integrate Technology Acceptance Model, Theory of Reasoned Action, Diffusion of Innovations, and perceived risk.
To examine the role of trust in M-payment adoption among seniors.

Main Methods:

A survey of 365 older adults (aged 55+) in central Taiwan.
Utilized a combined theoretical model incorporating TAM, TRA, DOI, trust, and perceived risk.
Partial Least-Squares Structural Equation Modeling (PLS-SEM) for data analysis.

Main Results:

Attitude was the primary determinant of M-payment behavioral intention in older adults.
Perceived usefulness, ease of use, and observability positively influenced attitude towards M-payment.
Trust significantly impacted perceived usefulness and ease of use, influenced by performance and financial risks.

Conclusions:

Enhancing perceived usefulness, ease of use, and observability is key to improving older adults' M-payment adoption.
Addressing performance and financial risks is vital for building trust in M-payment systems for seniors.
Integrated models provide a robust framework for understanding technology adoption in specific demographics.