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Related Concept Videos

Longitudinal Research02:20

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...
Longitudinal Studies01:26

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...
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
Data Collection by Observations01:08

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...

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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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Persistence pays off: follow-up methods for difficult-to-track longitudinal samples.

John H Kleschinsky1, Leslie B Bosworth, Sarah E Nelson

  • 1Division on Addictions, Cambridge Health Alliance, Medford, Massachusetts 02155, USA. jkleschinsky@challiance.org

Journal of Studies on Alcohol and Drugs
|September 10, 2009
PubMed
Summary

Maximizing participant retention in longitudinal studies requires extensive follow-up. For difficult-to-track substance-using populations, over 10 calls are needed, with diminishing returns around 40 calls.

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Area of Science:

  • Clinical Psychology
  • Public Health Research
  • Substance Abuse Treatment

Background:

  • Longitudinal studies face challenges in participant retention due to privacy regulations.
  • Repeat driving-under-the-influence (DUI) offenders often have high rates of substance use and psychiatric disorders, complicating follow-up.
  • Effective participant tracking methods are crucial for study validity.

Purpose of the Study:

  • To review and assess the effectiveness of various methods for maximizing participant completion rates in a 1-year longitudinal study.
  • To identify optimal strategies for retaining participants with complex needs in research.

Main Methods:

  • Follow-up attempts were made with 704 repeat DUI offenders over 21 months.
  • Methods included obtaining baseline information, contacting collaterals, mailed reminders, internet searches, and monetary incentives.
  • Participant location and interview completion were tracked, with an average of 8.6 calls per participant.

Main Results:

  • Interviews were completed with 488 participants (70.1% of the eligible sample).
  • 87.4% of participants had active telephone numbers.
  • Participant completion rates increased with more calls, but returns diminished significantly after approximately 40 calls.

Conclusions:

  • Researchers should utilize over 10 telephone calls for tracking substance-using populations.
  • A subset of participants will require extensive contact efforts.
  • Empirical guidelines are essential for estimating necessary contact numbers to ensure adequate follow-up rates.