Linganisha mbinu

	Uchanganuzi wa Sampuli za Uzoefu za Simu kwa Mfumo wa Pembetatu	Uchunguzi wa Sampuli ya Uzoefu wa Simu za Mkononi kutoka Vyanzo Vingi
Nyanja	Metodolojia ya Dodoso	Metodolojia ya Dodoso
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2000s–present (as an integrated mobile ESM variant)	2000s–2010s
Mwanzilishi	Csikszentmihalyi & Larson (ESM, 1983); Denzin (triangulation, 1978); integrated in HCI/health informatics research from the 2000s onward	Developed from ESM (Csikszentmihalyi & Larson, 1983) and extended to multi-informant intensive longitudinal designs by Bolger, Laurenceau, and colleagues
Aina	Mixed/multi-source data collection technique	Intensive longitudinal multi-informant data collection technique
Chanzo asilia	Csikszentmihalyi, M., & Larson, R. (1983). The Experience Sampling Method. In H. T. Reis (Ed.), Naturalistic Approaches to Studying Social Interaction (pp. 41–56). Jossey-Bass.	Bolger, N., & Laurenceau, J.-P. (2013). Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research. Guilford Press. ISBN: 978-1462506781
Majina mbadala	triangulated ESM, multi-source mobile ESM, triangulated ecological momentary assessment, triangulated mobile EMA	multi-informant ESM, dyadic ESM, multi-respondent ecological momentary assessment, MSESM
Zinazohusiana	4	6
Muhtasari	Triangulated 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.