Σύγκριση μεθόδων

	Δειγματοληψία Εμπειριών από Πολλαπλές Πηγές μέσω Κινητών Συσκευών	Διαχρονική Δειγματοληψία Εμπειρίας μέσω Κινητών
Πεδίο	Μεθοδολογία Επισκοπήσεων	Μεθοδολογία Επισκοπήσεων
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	2000s–2010s	1983 (ESM origins); 2000s onward (mobile longitudinal variants)
Δημιουργός	Developed from ESM (Csikszentmihalyi & Larson, 1983) and extended to multi-informant intensive longitudinal designs by Bolger, Laurenceau, and colleagues	Csikszentmihalyi & Larson (ESM, 1983); Shiffman, Stone & Hufford (EMA, 2008); extended to longitudinal mobile designs by Hamaker and colleagues
Τύπος	Intensive longitudinal multi-informant data collection technique	Longitudinal intensive data collection technique
Θεμελιώδης πηγή	Bolger, N., & Laurenceau, J.-P. (2013). Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research. Guilford Press. ISBN: 978-1462506781	Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1–32.
Εναλλακτικές ονομασίες	multi-informant ESM, dyadic ESM, multi-respondent ecological momentary assessment, MSESM	Longitudinal ESM, Longitudinal EMA, Longitudinal Ecological Momentary Assessment, Long-term mESM
Συναφείς	6	4
Σύνοψη	Multi-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.	Longitudinal Mobile Experience Sampling combines the real-time, in-context signal capture of Experience Sampling Method (ESM) with a longitudinal design spanning weeks, months, or longer. Participants respond to repeated prompts delivered to their smartphones across multiple time waves, enabling researchers to observe within-person change, stability, and dynamic processes as they unfold in daily life rather than in retrospective recall.