Our Network Executive Director, Dr. Alexandra Crosswell, walks you through the many resources available in this 15 minute video. Or read more below! 

The Stress Measurement Network has developed several tools for researchers we think will enable the advancement of stress science. These resources include:


1) Stress Typology (downloaded below) which describes common dimensions of stress exposures and responses, and can be used as a tool when describing or choosing stress measures. 

2) User Manual for the HRS Harmonization Project, which is a document that describes all stress measures that were included in the Health and Retirement Study as well as a series of similar studies used across the world. This is a detailed manual that corresponds with the actual data available in resource 3. 

3) Project description and access to the harmonized stress variables (and other harmonized variables) from the Health and Retirement Study Families of Studies Harmonization Project, led by Dr. Jinkook Lee. 


Many members of the academic community have contributed to the development of these resources. In addition to our leadership team and Scientific Advisory Board, we'd like to thank David Almeida, Sheldon Cohen, Pete Gianaros, Tara Gruenewald, Tom Kamarck, Jan Kiecolt-Glaser, Greg Miller, Eli Puterman, among many others. We welcome further input on our resources and involvement from scholars interested in the science of stress.




1. Stress Typology

Our Network has developed a taxonomy of terms (the ‘Stress Typology’) as a first step toward providing a common language, including descriptive dimensions of exposure and responses to stress. The purpose of this tool is to highlight the important conceptual dimensions of stress relevant to the study of health and well-being. Researchers describing any type of psychological stress should use this as a reference guide for how to describe the stressor exposure and response, as well as a tool during study development to make sure key aspects of the stressor of interest are being captured. Using consistent language when describing the aspects of stress and its measurement – and using a theoretical lens to do so – is important in order to build cumulative science of stress and to harmonize around critical theoretical dimensions. The Typology can be downloaded here PDF iconStress Typology for Stress Measurement_3 20 18.pdf. Version date: March 22, 2018.

2. User Manual for the HRS Family of Studies Stress Harmonization Project

This User Manuel details measures included in Health and Retirement Study (HRS) and the international HRS family of studies that capture various forms of stressor exposures and stress responses, as well as which measures of stress are harmonizable across studies. Harmonizing measures of psychosocial stress means that researchers are able to compare and contrast relationships between stress exposure, stress responses, and stress buffers, with health and aging outcomes, within and across different geographic and cultural contexts. The data is free to the public, with data from the US, Europe, Korea, Japan, China, Mexico, and Costa Rica, as part of the Health and Retirement Study family of studies. The stress types that have been harmonized across each wave of these studies are stressful life events, traumatic events, chronic stress, childhood adversity, discrimination, loneliness, social isolation, relationship strain, work stress, and neighborhood safety. This manual is a work in progress, please email [email protected]  if you have any edits to contribute. PDF iconStress Measurement in the HRS Family of Studies User Manual_12 27 19_posted.pdf

3. Data Harmonization Project Details & Webinars

The Gateway to Global Aging is a platform for population survey data on aging around the world. This site offers a digital library of survey questions, a search for finding comparable questions across surveys, and identically defined variables for cross-country analysis. To understand more about how to use this website, review this PDF iconGateway to Global Aging Data(short)_Jinkook's slides describing harmonization.pdf from Dr. Jinkook Lee. 

The Stress Measurement Network partnered with Dr. Jinkook Lee and her team to harmonize stress variables across the following studies: English Longitudinal Study of Ageing (ELSA), the Survey of Health, Ageing, and Retirement in Europe (SHARE), the Mexican Health and Aging Study (MHAS), the Costa Rican Longevity and Healthy Aging Study (CRELES), the Korean Longitudinal Study of Aging (KLoSA), the Japanese Study of Aging and Retirement (JSTAR), the Irish Longitudinal Study of Ageing (TILDA), the Chinese Health and Retirement Longitudinal Study (CHARLS), and the Longitudinal Aging Study in India (LASI)

Here is an advanced webinar on how to take advantage of this great resource. In the webinar, we walk through an example of using harmonized stress variables. 

Global Aging Data Advanced Webinar featuring Harmonized Stress Variables - Dec 4, 2018

Other webinars, including an introduction to the harmonized data available at the Gateway to Global Aging Data.


4. Expert Opinion: How do I chose the right stress measure? 

We often get emails asking what stress measures to use. If you are a researcher, we'd be happy to chat with you about your specific project, so reach out to [email protected] to schedule a consultation. In the meantime, here is our first response to this tough question:
Choosing the right stress measure

There is no ideal measure of stress, and due to constraints on participant burden and other considerations, difficult choices about which “type” of stress to capture need to be made. The choice of which measure to use depends on the research question and study population. Some types of stress will be more or less relevant for different groups based on that sample’s demographic make-up. To capture a wide-range of stress types in an observational study using self-report questionnaires in adult community samples, we suggest measuring the following categories of stress that were selected based on the evidence linking each to worse health: major life events, traumatic events, early life adversity, current experiences of chronic stress, current social stress (i.e. loneliness, social isolation, marital discord), experiences of discrimination, work stress, financial strain, neighborhood safety and cohesion, and global perceived stress. This list can and should be expanded to account for the uniqueness in the sample. For example, international cohorts may choose to include measures that capture political strife, religious persecution, overcrowding in living quarters, noise pollution, or combat exposure because of the known exposures..


5. Further resources: 


Manuscript in Frontiers in Neuroendocrinology, "More than a feeling: A unified view of stress measurement for population science"

This paper lays out the Stress Measurement Network leadership team's perspective on stress measurement, and presents a comprehensive model of relationships between stress, aging, and health that emphasizes the importance of the context in which stressor is experienced. The paper can be found here: PDF iconEpel_More than a feeling_2018.pdf

Figure 1: Transdisciplinary model of stress: Integrating contextual, historical, habitual, and acute stress processes.

Legend: Figure 1 presents a transdisciplinary model that describes “stress” as a set of interactive and emergent processes. The figure illustrates that stressors are experienced within the context of a person’s life, represented by the contextual factors in the blue triangle. These contextual factors include individual-level characteristics such as personality and demographic factors, current and past stressor exposures, the environment in which one lives, and protective factors; all of which combine to determine the baseline allostatic state, and the lens through which stressors are perceived and assigned meaning. Contextual factors and habitual processes together influence psychological and physiological responses to acute and daily stressors. These responses, if dysregulated, are thought to lead to allostatic load and ultimately biological aging and early disease.

Citation: Epel ES, Crosswell AD, Mayer SE, Prather AA, Slavich GM, Puterman E, Mendes WB. (2018). More than a feeling: An integrative review of stress measurement for population science. Frontiers in Neuroendocrinology, 49, 146-169.


Biomarker Network

The NIA funded Biomarker Network is a group of scientists dedicated to improving the measurement of biological risk for late life health outcomes in large representative samples of populations. See their website and resources at

Relevant article: Djuric Z, Bird CE, Furumoto-Dawson A, Rauscher GH, Ruffin MT, Stowe RP, Tucker KL, Masi CM. (2008). Biomarkers of psychological stress in health disparaties reseraach. Open Biork J,1(1), 7-19. PDF iconBiomarkers of stress in health disparaties research_2010.pdf


Science of Behavior Change (SOBC) Grand Rounds Speaker Series

The Stress Measurement Network leadership presented to SOBC researchers during a grand rounds presentation in September 2016 on stress measurement and our response to Jerome Kagan’s recent (2016) article in Perspectives on Psychological Science. The conversation and corresponding slides were recorded. The presentation can be found hereFileNetwork summary slides Oct 2016.pptxFileSOBC slides from Stress Measurement Network_Sept 2016_to post.pptx


Psychosocial Measurement Recommendations for Obesity Research 

An NIH working group, ADOPT, has compiled a short battery of measures of stress, affect, and eating behavior that are strongly recommended to investigators for inclusion in clinical trials of obesity (as well as relevant mechanistic studies in humans).

ADOPT Core Measures project also has a home on the NHLBI website: This page serves as a landing page and resource for those looking to learn about the project and hoping to find all relevant information in one place. The above website ( the GEM website) hosts detailed information on the measures, and hosts “working lists” that anyone can edit or add to. The .gov site links to GEM as well as to each individual recommended measure.