Related Experiment Video
Updated: Jul 24, 2026

06:15
A Modified Trier Social Stress Test for Vulnerable Mexican American Adolescents
Published on: July 10, 2017
12.9K
The Subjective Impact and Timing of Adversity Scale: A Feasibility Study Using Cross-Sectional and Longitudinal Data
Michael T McKay1, Colm Healy1, Derek Chambers2
1RCSI University of Medicine and Health Sciences, Dublin, Ireland.
Assessment
|August 23, 2022
Summary
The Subjective Impact and Timing of Adversity Scale (SITA) shows promise in measuring childhood psychological adversity. Findings suggest both the impact and timing of adversity are crucial for understanding psychiatric diagnoses.
Area of Science:
- Psychology
- Psychiatry
- Developmental Psychology
Background:
- Childhood psychological adversity is a significant risk factor for mental health issues.
- Existing measures may not fully capture the nuances of adversity exposure.
- A comprehensive tool is needed to assess the occurrence, impact, and timing of adversity.
Purpose of the Study:
- To assess the feasibility of the Subjective Impact and Timing of Adversity Scale (SITA).
- To evaluate the SITA's reliability and validity in measuring psychological adversity.
- To explore the relationship between adversity exposure and psychiatric diagnoses.
Main Methods:
- Utilized data from participants previously assessed at ages 14 and 21.
- Administered the SITA across online and interview formats.
- Analyzed internal consistency, convergent validity, and group differences based on psychiatric diagnoses.
Main Results:
- The SITA demonstrated acceptable internal consistency across most domains.
- SITA scores showed meaningful correlations with other psychological measures, supporting convergent validity.
- Individuals with lifetime psychiatric diagnoses reported significantly higher SITA domain scores.
Conclusions:
- The SITA is a viable tool for assessing the subjective impact and timing of childhood adversity.
- Both the subjective impact and timing of adversity appear important for psychiatric outcomes.
- Further research with larger samples is recommended to confirm these findings.
More Related Videos
Related Concept Videos
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...
Cross-Sectional Research
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
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...
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...
The primary goal of survival analysis is to estimate survival time—the time until a...

