The National Study of Daily Experiences: Protocol for Assessments of Daily Stress, Well-Being, Health, and Salivary Biomarkers in a Longitudinal Cohort
Bibliographic record
Abstract
BACKGROUND: Modern psychology has long recognized that understanding human behavior requires knowledge about a person's current context, which is often examined through daily diary studies. These studies offer ecologically valid insights into how everyday experiences-particularly stressors-affect health and well-being. The National Study of Daily Experiences (NSDE) addresses a critical gap by applying this approach in a large, longitudinal, and publicly accessible study that captures daily life across adulthood. OBJECTIVE: The NSDE is the largest and longest-running publicly accessible daily diary study in the United States. The purpose of this paper is to provide a guide for researchers interested in initiating similar naturalistic studies and to facilitate research using the existing NSDE data. METHODS: The NSDE includes 3510 adults (aged 24-97 years), yielding over 42,000 days of information to capture how daily life changes with age, over time, and across different cohorts, and how these daily experiences predict later health and well-being. This intensive longitudinal dataset includes an 8-day daily diary collected via phone survey, spans more than 20 years, and consists of 2 longitudinal datasets. During the daily phone interviews, participants provide reports of their experiences regarding daily events, including their stressors (Daily Inventory of Stressful Events), as well as their physical health indices, emotional experiences, and cognitive health. In addition, saliva is collected concurrently with days 2-5 of the daily phone interviews (4 collections per day for 4 consecutive days) and is used to measure biomarkers such as cortisol and alpha amylase. RESULTS: Recruitment began in 1995, with data collection occurring every 9-10 years. The most recent data collection is ongoing through 2027. All NSDE data are housed under the Midlife in the United States (MIDUS) study umbrella, with archived and updated datasets made available to the public on the online portal, MIDUS Colectica. CONCLUSIONS: Results from the NSDE have refined our understanding of daily stress processes. The study's timescale has provided insight into daily life for hundreds of studies, yet much more can be learned from using these data. Microlongitudinal measures and combinations of factors provide for new avenues of research and promise for better understanding of health and aging. Moreover, NSDE data can be combined with datasets from neuroscience, biomarker, and macrolongitudinal subprojects from MIDUS to examine health-related processes. In addition to offering information on how to use the NSDE, this protocol serves as a resource for secondary data analyses and an outline for investigators wishing to replicate an intensive assessment design to other populations and research questions to continue to refine our understanding of how daily stress processes influence health and well-being. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/76453.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".