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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...
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.
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...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Qualitative Analysis03:46

Qualitative Analysis

For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
For instance, group IV...
Qualitative Analysis01:10

Qualitative Analysis

Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
There are two main approaches to qualitative analysis:...

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Related Experiment Video

Updated: May 15, 2026

High-Throughput Behavioral Aging and Lifespan Assays Using the Lifespan Machine
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Afterward: keeping analysis alive over time.

Judy L Kantrowitz1

  • 1Boston Institute for Psychoanalysis, MA, USA. Judy_Kantrowitz@hms.harvard.edu

The Psychoanalytic Quarterly
|January 19, 2013
PubMed
Summary

Psychoanalysis aims to foster self-analytic function. Post-analysis, self-exploration varies among former analysands, but continued growth is possible regardless of ongoing self-analysis, challenging its role as a success metric.

Area of Science:

  • Psychology
  • Psychoanalysis
  • Psychotherapy Research

Background:

  • The development of a self-analytic function has long been a central objective in psychoanalysis.
  • Understanding how individuals engage in self-exploration after formal psychoanalytic treatment is crucial for evaluating therapeutic outcomes.

Purpose of the Study:

  • To examine the diverse ways former psychoanalytic patients continued self-exploration after their analysis concluded.
  • To reconsider the significance of ongoing self-analysis as a primary measure of successful psychoanalytic outcomes.

Main Methods:

  • Qualitative analysis of interviews conducted with former psychoanalytic patients (analysands).
  • Exploration of participants' experiences of self-exploration and personal growth post-analysis.

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Main Results:

  • Not all former analysands reported continued, active self-exploration after their psychoanalytic treatment ended.
  • Absence of ongoing self-exploration did not correlate with a lack of benefit or continued personal growth post-analysis.
  • Diverse patterns of assimilating the analytic process and relationship were observed.

Conclusions:

  • Self-analysis should not be the sole criterion for judging the success of psychoanalytic outcomes.
  • Psychoanalysis can facilitate lasting benefits and growth even when formal self-analysis ceases.
  • The integration of the analytic experience is multifaceted and extends beyond continuous self-analytic practice.