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Vícezdrojové mobilní vzorkování zážitků×Mobilní sběr zkušeností×
OborMetodologie dotazníkových šetřeníMetodologie dotazníkových šetření
RodinaProcess / pipelineProcess / pipeline
Rok vzniku2000s–2010s1983
TvůrceDeveloped from ESM (Csikszentmihalyi & Larson, 1983) and extended to multi-informant intensive longitudinal designs by Bolger, Laurenceau, and colleaguesMihaly Csikszentmihalyi & Reed Larson
TypIntensive longitudinal multi-informant data collection techniqueIntensive longitudinal data collection technique
Původní zdrojBolger, N., & Laurenceau, J.-P. (2013). Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research. Guilford Press. ISBN: 978-1462506781Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗
Další názvymulti-informant ESM, dyadic ESM, multi-respondent ecological momentary assessment, MSESMESM, Experience Sampling Method, Ecological Momentary Assessment, EMA
Příbuzné65
ShrnutíMulti-source Mobile Experience Sampling extends the standard ESM design by simultaneously collecting repeated momentary self-reports from two or more linked informant types — such as patient and caregiver, employee and supervisor, or partners in a dyad — via their smartphones. Signals are delivered concurrently across sources, enabling researchers to examine convergences and discrepancies between informants' real-time experiences and to model interpersonal dynamics at the moment they unfold in daily life.Mobile Experience Sampling (ESM) is an intensive longitudinal data-collection technique in which participants respond to brief, repeated questionnaires delivered to their smartphones at random or scheduled intervals throughout the day. By capturing thoughts, feelings, behaviors, and context at or near the moment they occur, ESM minimises retrospective recall bias and provides a high-resolution picture of psychological and behavioral fluctuations in everyday life.
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ScholarGatePorovnat metody: Multi-source Mobile Experience Sampling · Mobile Experience Sampling. Získáno 2026-06-15 z https://scholargate.app/cs/compare