Longitudinal_studies

Longitudinal study

Longitudinal study

Study with repeated observations over time


A longitudinal study (or longitudinal survey, or panel study) is a research design that involves repeated observations of the same variables (e.g., people) over long periods of time (i.e., uses longitudinal data). It is often a type of observational study, although it can also be structured as longitudinal randomized experiment.[1]

Longitudinal studies are often used in social-personality and clinical psychology, to study rapid fluctuations in behaviors, thoughts, and emotions from moment to moment or day to day; in developmental psychology, to study developmental trends across the life span; and in sociology, to study life events throughout lifetimes or generations; and in consumer research and political polling to study consumer trends. The reason for this is that, unlike cross-sectional studies, in which different individuals with the same characteristics are compared,[2] longitudinal studies track the same people, and so the differences observed in those people are less likely to be the result of cultural differences across generations, that is, the cohort effect. Longitudinal studies thus make observing changes more accurate and are applied in various other fields. In medicine, the design is used to uncover predictors of certain diseases. In advertising, the design is used to identify the changes that advertising has produced in the attitudes and behaviors of those within the target audience who have seen the advertising campaign. Longitudinal studies allow social scientists to distinguish short from long-term phenomena, such as poverty. If the poverty rate is 10% at a point in time, this may mean that 10% of the population are always poor or that the whole population experiences poverty for 10% of the time.

Longitudinal studies can be retrospective (looking back in time, thus using existing data such as medical records or claims database) or prospective (requiring the collection of new data).[citation needed]

Cohort studies are one type of longitudinal study which sample a cohort (a group of people who share a defining characteristic, typically who experienced a common event in a selected period, such as birth or graduation) and perform cross-section observations at intervals through time. However, not all longitudinal studies are cohort studies, as longitudinal studies can instead include a group of people who do not share a common event.[3]

Advantages

When longitudinal studies are observational, in the sense that they observe the state of the world without manipulating it, it has been argued that they may have less power to detect causal relationships than experiments. However, because of the repeated observation at the individual level, they have more power than cross-sectional observational studies, by virtue of being able to exclude time-invariant unobserved individual differences and also of observing the temporal order of events.[4][failed verification]

Longitudinal studies do not require large numbers of participants (as in the examples below). Qualitative longitudinal studies may include only a handful of participants,[5] and longitudinal pilot or feasibility studies often have fewer than 100 participants.[6]

Disadvantages

Longitudinal studies are time-consuming and expensive.[7]

Longitudinal studies cannot avoid an attrition effect: that is, some subjects cannot continue to participate in the study for various reasons. Under longitudinal research methods, the reduction in the research sample will bias the remaining smaller sample.[citation needed]

Practice effect is also one of the problems: longitudinal studies tend to be influenced because subjects repeat the same procedure many times (potentially introducing autocorrelation), and this may cause their performance to improve or deteriorate.[citation needed]

Examples

More information Study name, Type ...

See also


References

  1. Shadish, William R.; Cook, Thomas D.; Campbell, Donald T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference (2nd ed.). Boston, Massachusetts: Houghton Mifflin. p. 267. ISBN 0-395-61556-9.
  2. Carlson, Neil R.; Miller, Harold L. Jr.; Heth, Donald S.; Donahoe, John W.; Martin, G. Neil (2009). Psychology: the Science of Behavior (7th ed.). Boston, Massachusetts: Allyn & Bacon. p. 361. ISBN 978-0-205-54786-9.
  3. "What is the difference between a Panel Study and a Cohort Study?". Academia Stack Exchange. Retrieved 3 February 2016.
  4. van der Krieke, Lian; Blaauw, Frank J.; Emerencia, Ando C.; Schenk, Hendrika M.; Slaets, Joris P.J.; Bos, Elisabeth H.; de Jonge, Peter; Jeronimus, Bertus F. (August 2016). "Temporal Dynamics of Health and Well-Being: A Crowdsourcing Approach to Momentary Assessments and Automated Generation of Personalized Feedback" (PDF). Psychosomatic Medicine. 79 (2). Philadelphia, Pennsylvania: Lippincott Williams & Wilkins: 213–223. doi:10.1097/PSY.0000000000000378. PMID 27551988. S2CID 10955232.
  5. Wood, Jennifer P.; Connelly, Denise M.; Maly, Monica R. (November 2010). "'Getting back to real living': A qualitative study of the process of community reintegration after stroke". Clinical Rehabilitation. 24 (11). Thousand Oaks, California: SAGE Publications: 1045–56. doi:10.1177/0269215510375901. PMID 20713436. S2CID 40295472.
  6. Freeman, Joshua R.; Whitcomb, Brian W.; Roy, Amrita; Bertone-Johnson, Elizabeth R.; Reich, Nicholas G.; Healy, Andrew J. (August 2018). "A pilot longitudinal study of anti-Müllerian hormone levels throughout gestation in low risk pregnancy". Health Science Reports. 1 (8). Hoboken, New Jersey: Wiley: e53. doi:10.1002/hsr2.53. PMC 6266452. PMID 30623089.
  7. Cherry, Kendra. "What Is Longitudinal Research?". About.com. Archived from the original on 4 March 2016. Retrieved 22 February 2012.
  8. "Building a New Life in Australia (BNLA): The Longitudinal Study of Humanitarian Migrants". Department of Social Services, Australian Government. Retrieved 1 December 2016.
  9. "Busselton Health Study – Past Projects". BPMRI. 14 May 2014. Retrieved 1 December 2016.
  10. "Canadian Longitudinal Study on Aging". Retrieved 1 December 2016.
  11. Raina, Parminder; Wolfson, Christina; Kirkland, Susan; Griffith, Lauren E.; Balion, Cynthia; Cossette, Benoît; Dionne, Isabelle; Hofer, Scott; Hogan, David; van den Heuvel, Edwin R (Dec 2019). "Cohort profile: the Canadian Longitudinal Study on Aging (CLSA)". International Journal of Epidemiology. 48 (6): 1753. doi:10.1093/ije/dyz173. PMC 6929533. PMID 31633757.
  12. Raina, Parminder; Wolfson, Christina; Kirkland, Susan; Giffith, Lauren E.; Balion, Cynthia; Cossette, Benoît; Dionne, Isabelle; Hofer, Scott; Hogan, David; van den Heuvel, Edwin R. (Dec 2019). "Cohort profile: the Canadian Longitudinal Study on Aging (CLSA)". International Journal of Epidemiology. 48 (6): 1753. doi:10.1093/ije/dyz173. PMC 6929533. PMID 31633757.
  13. "Child Development Project – Developmental Pathways to Adjustment and Well-being in Early Adulthood". Durham, North Carolina: Center for Child & Family Policy – Duke University. Archived from the original on 28 February 2014. Retrieved 1 December 2016.
  14. "Overview of Footprints in Time – The Longitudinal Study of Indigenous Children (LSIC)". Department of Social Services, Australian Government. Retrieved 1 December 2016.
  15. Walters, Laura (15 May 2018). "Budget 2018: $2m for NZ's biggest longitudinal study about growing up in NZ". Stuff. Retrieved 8 April 2021.
  16. Studies, Australian Institute of Family. "Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC)". Australian Institute of Family Studies (AIFS). Retrieved 1 December 2016.
  17. "Adoption study records of the Child Development Center Finding Aid". Archives at Yale. New Haven, Connecticut: Yale University. Retrieved 1 December 2019.
  18. "Panel Study of Belgian Households". Archived from the original on 2007-02-09. Retrieved 2020-03-17.
  19. Panel Study of Belgian Households, Survey summary
  20. Newnham, J.P.; Evans, S.F.; Michael, C.A.; Stanley, F.J.; Landau, L.I. (1993-10-09). "Effects of frequent ultrasound during pregnancy: a randomised controlled trial". The Lancet. 342 (8876): 887–891. doi:10.1016/0140-6736(93)91944-H. ISSN 0140-6736. PMID 8105165. S2CID 11763088.
  21. McKnight, Charlotte M.; Newnham, John P.; Stanley, Fiona J.; Mountain, Jenny A.; Landau, Louis I.; Beilin, Lawrence J.; Puddey, Ian B.; Pennell, Craig E.; Mackey, David A. (2012). "Birth of a cohort — the first 20 years of the Raine study". Medical Journal of Australia. 197 (11–12): 608–610. doi:10.5694/mja12.10698. ISSN 1326-5377. PMID 23230915. S2CID 43704496.
  22. Murphy, Jane M.; Laird, Nan McKenzie; Monson, Richard R.; Sobol, Arthur M.; Leighton, Alexander H. (May 2000). "Incidence of depression in the Stirling County Study: historical and comparative perspectives". Psychological Medicine. 30 (3). Cambridge, Massachusetts: Cambridge University Press: 505–14. doi:10.1017/s0033291799002044. PMID 10883707. S2CID 40645927.
  23. "About the Seattle Longitudinal Study". Archived from the original on 14 September 2015. Retrieved 1 December 2016.
  24. "ONS Longitudinal Study". Archived from the original on 2015-10-10. Retrieved 2015-12-08.
  25. Shelton, Nicola; Marshall, Chris E.; Stuchbury, Rachel; Grundy, Emily; Dennett, Adam; Tomlinson, Jo; Duke-Williams, Oliver; Xun, Wei (April 2019). "Cohort Profile: the Office for National Statistics Longitudinal Study (The LS)". International Journal of Epidemiology. 48 (2). Oxford, England: Oxford University Press: 383–384g. doi:10.1093/ije/dyy243. PMC 6469306. PMID 30541026.

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