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Longitudinal Study

A longitudinal study captures data over a period of time (days, week, months, or years) to understand the long-term effects of changes in products, processes, or environment.

Many usability methods like usability testing focus on initial use (learnability). Longitudinal studies focus on long-term effectiveness and satisfaction. A longitudinal study involves the repeated observations or examination of a group of users over time, at regular intervals, with respect to one or more study variables. Longitudinal studies are mainly done in order to follow changes in perception, behaviors, attitudes, and motivation of use. Such studies may be conducted over the duration of anywhere from a few days to several decades. Longitudinal studies can employ a range of methods including diaries, participant observation, critical incident reports, data logging, and repeated interviews.

 

Related Links

Web Resources

Wikipedia
http://en.wikipedia.org/wiki/Longitudinal_study

This Wikipedia entry describes the characteristics of longitudinal studies and provides a description of different types of studies including retrospective studies, panel studies, and cohort studies.

Vaughan, M. & Courage, C. (2007). SIG: capturing longitudinal usability: what really affects user performance over time?”, In CHI '07 Extended Abstracts on Human Factors in Computing Systems, New York: ACM Press, p. 2149-2152, 2007.
http://delivery.acm.org/10.1145/1250000/1240970/p2149-vaughan.pdf?key1=1240970&a...

An overview of the issues.

Gorlenko, Lada. Long-term (longitudinal) research and usability. UPA 2005 Conference.
http://www.upassoc.org/usability_resources/conference/2005/gorlenko_longitudinal...

Formal Publications

Gerken, J., Bak, P. & Reiterer, H. (2007). Longitudinal evaluation methods in Human-Computer Studies and visual analytics. Paper presented at the Metrics for the Evaluation of Visual Analytics Workshop, Vis-2007.
http://www.cs.umd.edu/hcil/InfoVisworkshop/papers/VIS_Workshop_gerken_bak.pdf

Argues for applying longitudinal research methods in human-computer studies and suggests a methodological research framework.

Taris, T.W. (2000). A Primer in longitudinal data analysis. London: SAGE Publications, 2000.

An introduction to the theory and practice of longitudinal research including the strengths and weaknesses of this kind of research; how to design a longitudinal study; how to collect data most effectively; how to make the best use of statistical techniqu

Other

Menard, S. (2002) Longitudinal Research, Newbury Park: Sage Publications.

Research design strategies; methods of data collection; and how longitudinal and cross-sectional research compares in terms of consistency and accuracy of results.

Kjeldskov, M. B. Skov, & J. Stage (2005). Does time heal?: a longitudinal study of usability. In Proceedings of the 19th Conference of the Computer-Human interaction Special interest Group (Chisig) of Australia on Computer-Human interaction: Citizens onli

A longitudinal laboratory-based usability evaluation of an interactive system investigating the nature of usability problems experienced by novice and expert users over time, and to see to what extends usability problems may or may not disappear over time

Mendoza, V., and Novick, D. G. (2005). Usability over time. In ACM 23rd International Conference on Computer Documentation, ACM Press (2005), 151-158.
http://digitalcommons.utep.edu/cs_papers/11/

A longitudinal study of usability among middle-school teachers creating Web sites. The study looked at the use both the use of documentation and the underlying software, tracking the causes and extent of user frustration over eight weeks.

Peters, O. and Ben Allouch, S. (2005). Always connected: a longitudinal field study of mobile communication. Telemat. Inf. 22, 3 (Aug. 2005), 239-256.
http://doc.utwente.nl/59776/1/Peters04always.pdf

The results of this longitudinal field study suggest that people’s motivations for using mobile communication technology are initially influenced more strongly by their perceptions about the expected use, which is more task-oriented.

Shneiderman, B. & Plaisant, C. (2006). Strategies for evaluating information visualization tools: multi-dimensional in-depth long-term case studies.

In Proceedings of the 2006 AVI Workshop on Beyond Time and Errors: Novel Evaluation Methods For information Visualization, BELIV '06, New York: ACM Press, p. 1-7, 2006.

How To

In order to do a longitudinal study, the following general steps should be followed:

  • Identify research questions, which are not well addressed in current cross-sectional studies or even not considered at all.
  • Derive a hypothesis from this research question.
  • Choose a methodology to test the hypothesis. Longitudinal studies can employ a variety of methods including diaries, participant observation, critical incident reports, data logging, repeated interviews, and repeated controlled experiments in laboratory setting.
  • Collect data.
  • Define relevant methods for data analysis and analyse data. It is important to note that data in longitudinal studies may be more voluminous than in cross-sectional studies.
  • Repeat the study at least two times, at a given time interval.

Tips

  • Ensure that variables are kept consistent during the whole duration of the longitudinal study. Otherwise all that will be tested will be the learnability of the system.

 

Facts

Lifecycle: User research, Evaluation
Sources and contributors: 
Margarita Anastassova, Chauncey Wilson.
Released: 2011-03
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