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| Mobile Diary Method× | Pitkittäinen päiväkirjamenetelmä× | |
|---|---|---|
| Tieteenala | Kyselytutkimuksen metodologia | Kyselytutkimuksen metodologia |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1987 (ESM roots); mobile form ~2007–2010 | 1942 (diary method); longitudinal variant formalised 1980s–2000s |
| Kehittäjä≠ | Csikszentmihalyi & Larson (ESM foundation); mobile adaptation through 2000s smartphone proliferation | Allport (1942); systematic longitudinal extension developed by Bolger, Davis & Rafaeli (2003) |
| Tyyppi≠ | Longitudinal self-report data collection technique | Longitudinal qualitative/quantitative data collection |
| Alkuperäislähde≠ | Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the Experience-Sampling Method. Journal of Nervous and Mental Disease, 175(9), 526–536. DOI ↗ | Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54(1), 579–616. DOI ↗ |
| Rinnakkaisnimet | mobile diary study, smartphone diary method, mobile ESM diary, ecological momentary diary | diary study (longitudinal), daily diary method, repeated-measures diary, longitudinal self-report diary |
| Liittyvät≠ | 4 | 3 |
| Tiivistelmä≠ | The Mobile Diary Method is a longitudinal self-report technique in which participants record their thoughts, feelings, behaviors, or events using a smartphone app or mobile platform over a defined study period — ranging from days to months. Rooted in the classic diary method and the Experience Sampling Method, its mobile form enables real-time, in-context capture of experience, dramatically reducing retrospective recall bias compared to one-shot surveys or end-of-day questionnaires. | The Longitudinal Diary Method is a data collection technique in which participants record experiences, thoughts, feelings, or behaviors in structured diary entries repeatedly over an extended period — from days to months or even years. Unlike a one-shot survey, it tracks within-person change, daily fluctuation, and temporal processes in natural settings, making it especially powerful for studying how phenomena evolve over time. |
| ScholarGateAineisto ↗ |
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