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| Mẫu thu thập trải nghiệm di động được tam giác hóa× | Lấy mẫu trải nghiệm di động đa nguồn× | |
|---|---|---|
| Lĩnh vực | Phương pháp luận khảo sát | Phương pháp luận khảo sát |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 2000s–present (as an integrated mobile ESM variant) | 2000s–2010s |
| Người khởi xướng≠ | 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 |
| Loại≠ | Mixed/multi-source data collection technique | Intensive longitudinal multi-informant data collection technique |
| Công trình gốc≠ | 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. link ↗ | Bolger, N., & Laurenceau, J.-P. (2013). Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research. Guilford Press. ISBN: 978-1462506781 |
| Tên gọi khác | triangulated ESM, multi-source mobile ESM, triangulated ecological momentary assessment, triangulated mobile EMA | multi-informant ESM, dyadic ESM, multi-respondent ecological momentary assessment, MSESM |
| Liên quan≠ | 4 | 6 |
| Tóm tắt≠ | 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. |
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