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Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Δειγματοληψία Εμπειριών από Πολλαπλές Πηγές μέσω Κινητών Συσκευών× | Δειγματοληψία Εμπειρίας μέσω Κινητού× | |
|---|---|---|
| Πεδίο | Μεθοδολογία Επισκοπήσεων | Μεθοδολογία Επισκοπήσεων |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 2000s–2010s | 1983 |
| Δημιουργός≠ | Developed from ESM (Csikszentmihalyi & Larson, 1983) and extended to multi-informant intensive longitudinal designs by Bolger, Laurenceau, and colleagues | Mihaly Csikszentmihalyi & Reed Larson |
| Τύπος≠ | Intensive longitudinal multi-informant data collection technique | Intensive longitudinal 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 | Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗ |
| Εναλλακτικές ονομασίες | multi-informant ESM, dyadic ESM, multi-respondent ecological momentary assessment, MSESM | ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA |
| Συναφείς≠ | 6 | 5 |
| 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. | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
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