# Advancing the measurement of emotional well-being with the Day Reconstruction Method

> **NIH NIH R21** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2020 · $206,250

## Abstract

7. Project Summary/Abstract
The Day Reconstruction Method (DRM) has found widespread attention as a survey method for the
measurement of daily emotional well-being experiences in large-scale population-based research. The DRM
collects granular information about affective experiences as they unfold over the course of a day. Typically, the
overall (“average”) level of emotions serves as an indicator of a person’s emotional well-being from the DRM.
However, many aspects of people’s emotional lives are not captured by how they feel on average. The proposed
application seeks to utilize the rich information inherent in the DRM for the construction of measures
capturing dynamic aspects of emotional well-being, involving the intensity, frequency, variability, regulation,
and complexity of a person’s everyday emotional experiences. Drawing on a rich repertoire of existing metrics
of intrapersonal emotion dynamics developed in laboratory and ambulatory assessment research, we take the
approach of examining whether these metrics can be successfully applied to population-level research afforded
by the DRM. The psychometric properties of the new DRM metrics will be systematically evaluated and
compared in a probability-based Internet panel of 1000 respondents 50 years or older, including their
reliability, their correspondence with parallel indices derived from ecological momentary assessments, and
their susceptibility to response style artifacts. Cognitive interviews with DRM respondents will shed light on
cognitive strategies for completing the instrument that could either facilitate or impede the content validity of
the new DRM metrics. To evaluate the extent to which the new DRM metrics can augment understanding of
well-being and health disparities in older ages, we will examine the ability of the new DRM metrics to
discriminate between demographic subgroups (age, sex, education, race/ethnicity, disability); we will further
examine which of the metrics are predictive of changes in health outcomes. New metrics of emotional well-
being derived from the DRM could facilitate large-scale analyses of disparities of emotional health and
dysfunction, refine understanding of the development and determinants of well-being in the aging population,
and augment options for evaluating policy decisions.

## Key facts

- **NIH application ID:** 9912084
- **Project number:** 5R21AG061364-02
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Doerte Ulrike Junghaenel
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $206,250
- **Award type:** 5
- **Project period:** 2019-06-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9912084

## Citation

> US National Institutes of Health, RePORTER application 9912084, Advancing the measurement of emotional well-being with the Day Reconstruction Method (5R21AG061364-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9912084. Licensed CC0.

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