Evidence map›Paper›PMID 39530726›Full record

ArticleStress and health : journal of the International Society for the Investigation of Stress2024

Exploring the Utility of a Real-Time Approach to Characterising Within-Person Fluctuations in Everyday Stress Responses.

Meynard John L Toledo, Matthew J Zawadzki, Stacey B Scott, Jillian A Johnson, David Marcusson-Clavertz, Jinhyuk Kim, Stephanie Lanza, David M Almeida, Martin J Sliwinski, Joshua M Smyth

Abstract read
In one paragraph

Article in Stress and health : journal of the International Society for the Investigation of Stress, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Meynard John L ToledoCenter for Self-Report Science, University of Southern California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-0215-003X
Matthew J ZawadzkiPsychological Sciences, University of California, Merced, California, USA.ORCID https://orcid.org/0000-0001-6968-084X
Stacey B ScottDepartment of Psychology, Stony Brook University, Stony Brook, New York, USA.ORCID https://orcid.org/0000-0002-7060-4964
Jillian A JohnsonComprehensive Cancer Center, Atrium Health Wake Forest Baptist, Winston-Salem, North Carolina, USA.
David Marcusson-ClavertzDepartment of Psychology, Linnaeus University, Växjö, Sweden.
Jinhyuk KimDepartment of Informatics, Shizuoka University, Shizuoka, Japan.ORCID https://orcid.org/0000-0003-4218-1631
Stephanie LanzaBiobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, USA.
David M AlmeidaHuman Development and Family Studies, The Pennsylvania State University, University Park, Pennsylvania, USA.
Martin J SliwinskiHuman Development and Family Studies, The Pennsylvania State University, University Park, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-9611-7558
Joshua M SmythDepartment of Psychology, The Ohio State University, Columbus, Ohio, USA.ORCID https://orcid.org/0000-0002-0904-5390

Funding

Everyday Stress Response Targets in the Science of Behavior ChangeUH3AG052167 · NIA · PENNSYLVANIA STATE UNIVERSITY, THE · PI SMYTH, JOSHUA M · 2018 to 2019
$2.5M
Everyday Stress Response Targets in the Science of Behavior ChangeUH2AG052167 · NIA · PENNSYLVANIA STATE UNIVERSITY, THE · PI ALMEIDA, DAVID M., SMYTH, JOSHUA M · 2015 to 2017
$2.5M
NIA NIH HHS UH2 AG052167NIA NIH HHS UH3 AG052167NIH HHS
6 · The paper itself

Abstract

Few studies have measured components of stress responses in real time-an essential step in designing just-in-time interventions targeting moments of risk. Using ecological momentary assessment (EMA), we characterised stress response components to everyday stressors, including reactivity (the response following a stressor), recovery (the return towards baseline), and pile-up (the accumulation of stressors) (RRPs) by quantifying the dynamics of response indicators (i.e., subjective stress, negative affect, and perseverative cognition). To determine the utility of these novel measures in capturing and characterising acute moments of the stress response, this study evaluated the proportion of variance in RRPs attributed to (1) between-person, (2) between-days, and (3) within-day (momentary) levels. Healthy adults (n = 123; aged 35-65, 79% women, 91% non-Hispanic White) participated in a 14-day study assessing stress response via EMA 6 times a day. RRPs were constructed from 10,065 EMA reports. Multilevel models with moments nested within days nested within persons were used to partition variance in the RRPs. Reactivity and recovery indicators captured the most variation within-days (i.e., across moments; range 76%-80% and 87%-89%, respectively), with small amounts of variance between-person. For pile-up, variation was mostly observed between-days (range 60%-63%) and between-persons (range 27%-31%). In contrast, raw measures of stress response reflected substantial between-person (range 32%-54%) and within-day (range 34%-53%) variance. These results demonstrated that a person-specific approach to measuring stress response components (i.e., RRPs) can capture the dynamic within-person variation in stress response, as it occurs in real time, making it well-suited for use in novel just-in-time interventions targeting moments of risk.

Indexed as

Ecological Momentary AssessmentStress, PsychologicalAdultAgedFemaleHumansMaleMiddle Agedecological momentary assessmentreal‐time stress responsestress response assayvariance partitioningwithin‐person variability

Identifiers

PMID39530726
PMCPMC11636429

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.