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| Мобилно задълбочено интервю× | Мобилно събиране на преживявания× | |
|---|---|---|
| Област | Методология на проучванията | Методология на проучванията |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2010s | 1983 |
| Създател≠ | Adapted from traditional in-depth interviewing; mobile application popularised in qualitative research from the 2010s onward | Mihaly Csikszentmihalyi & Reed Larson |
| Тип≠ | Qualitative data collection technique | Intensive longitudinal data collection technique |
| Основополагащ източник≠ | Galletta, A. (2013). Mastering the Semi-Structured Interview and Beyond. New York University Press. ISBN: 978-0814732595 | Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗ |
| Други названия | mobile IDI, smartphone in-depth interview, mobile qualitative interview, mIDI | ESM, Experience Sampling Method, Ecological Momentary Assessment, EMA |
| Свързани≠ | 4 | 5 |
| Резюме≠ | A mobile in-depth interview (mIDI) is a qualitative data collection technique in which a researcher conducts an extended, exploratory conversation with a participant using a smartphone or tablet, either synchronously (voice or video call) or asynchronously (voice-message or text exchange). The approach retains the probing, open-ended character of traditional in-depth interviewing while leveraging the ubiquity and convenience of mobile technology to reach participants in naturalistic, everyday settings. | 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. |
| ScholarGateНабор от данни ↗ |
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