ScholarGate
Assistente

Confronta i metodi

Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.

Campionamento Triangolato dell'Esperienza Mobile×Campionamento di Esperienze da Fonti Multiple su Dispositivi Mobili×
CampoMetodologia delle indaginiMetodologia delle indagini
FamigliaProcess / pipelineProcess / pipeline
Anno di origine2000s–present (as an integrated mobile ESM variant)2000s–2010s
IdeatoreCsikszentmihalyi & Larson (ESM, 1983); Denzin (triangulation, 1978); integrated in HCI/health informatics research from the 2000s onwardDeveloped from ESM (Csikszentmihalyi & Larson, 1983) and extended to multi-informant intensive longitudinal designs by Bolger, Laurenceau, and colleagues
TipoMixed/multi-source data collection techniqueIntensive longitudinal multi-informant data collection technique
Fonte seminaleCsikszentmihalyi, M., & Larson, R. (1983). The Experience Sampling Method. In H. T. Reis (Ed.), Naturalistic Approaches to Studying Social Interaction (pp. 41–56). Jossey-Bass. link ↗Bolger, N., & Laurenceau, J.-P. (2013). Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research. Guilford Press. ISBN: 978-1462506781
Aliastriangulated ESM, multi-source mobile ESM, triangulated ecological momentary assessment, triangulated mobile EMAmulti-informant ESM, dyadic ESM, multi-respondent ecological momentary assessment, MSESM
Correlati46
SintesiTriangulated Mobile Experience Sampling combines the Experience Sampling Method (ESM) — repeated, real-time self-reports delivered via smartphone — with deliberate triangulation across two or more data sources, instruments, or methods. By converging mobile survey prompts with passive sensor streams, behavioral logs, or complementary qualitative probes, the technique strengthens construct validity and enables cross-verification of findings collected in participants' natural environments.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.
ScholarGateInsieme di dati
  1. v1
  2. 2 Fonti
  3. PUBLISHED
  1. v1
  2. 2 Fonti
  3. PUBLISHED

Vai alla ricerca Scarica le diapositive

ScholarGateConfronta i metodi: Triangulated Mobile Experience Sampling · Multi-source Mobile Experience Sampling. Consultato il 2026-06-15 da https://scholargate.app/it/compare