Evidence map›Paper›PMID 35381955›Full record

ArticleBehavior research methods2023

Measuring affect dynamics: An empirical framework.

Sergio Pirla, Maxime Taquet, Jordi Quoidbach

Abstract read
In one paragraph

Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  13. The affective dynamics of parenting: Inertia of emotional distance characterizes severe parental burnout.Journal of family psychology : JFP : journal of the Division of Family Psychology of the American Psychological Association (Division 43) · 2025
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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

3 authors.

Sergio Pirla *Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain. sergio.pirla@upf.edu.ORCID http://orcid.org/0000-0001-5979-4528
Maxime Taquet *Department of Psychiatry, University of Oxford, Oxford, UK.
Jordi QuoidbachUniversitat Ramon Llul, ESADE Business School, Barcelona, Spain.

Funding

Ministerio de Economía, Industria y Competitividad, Gobierno de España RYC-2016-21020National Institute for Health Research BRC-1215-20005
6 · The paper itself

Abstract

A fast-growing body of evidence from experience sampling studies suggests that affect dynamics are associated with well-being and health. But heterogeneity in experience sampling approaches impedes reproducibility and scientific progress. Leveraging a large dataset of 7016 individuals, each providing over 50 affect reports, we introduce an empirically derived framework to help researchers design well-powered and efficient experience sampling studies. Our research reveals three general principles. First, a sample of 200 participants and 20 observations per person yields sufficient power to detect medium-sized associations for most affect dynamic measures. Second, for trait- and time-independent variability measures of affect (e.g., SD), distant sampling study designs (i.e., a few daily measurements spread out over several weeks) lead to more accurate estimates than close sampling study designs (i.e., many daily measurements concentrated over a few days), although differences in accuracy across sampling methods were inconsistent and of little practical significance for temporally dependent affect dynamic measures (i.e., RMSSD, autocorrelation coefficient, TKEO, and PAC). Third, across all affect dynamics measures, sampling exclusively on specific days or time windows leads to little to no improvement over sampling at random times. Because the ideal sampling approach varies for each affect dynamics measure, we provide a companion R package, an online calculator ( https://sergiopirla.shinyapps.io/powerADapp ), and a series of benchmark effect sizes to help researchers address three fundamental hows of experience sampling: How many participants to recruit? How often to solicit them? And for how long?

Indexed as

AffectEcological Momentary AssessmentHumansReproducibility of ResultsAffect dynamicsAmbulatory assessmentExperience sampling method

Identifiers

PMID35381955
PMCPMC9918585

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.