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| Online Dagbogsmetode× | Longitudinal Dag Metode× | |
|---|---|---|
| Fagområde | Surveymetodologi | Surveymetodologi |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | 2000s (online adaptation); diary method roots in social research circa 1970s–1990s | 1942 (diary method); longitudinal variant formalised 1980s–2000s |
| Ophavsperson≠ | Adaptation of the traditional diary method; Bolger, Davis & Rafaeli (2003) systematized the daily diary design; online delivery emerged through web survey tools in the early 2000s | Allport (1942); systematic longitudinal extension developed by Bolger, Davis & Rafaeli (2003) |
| Type≠ | Longitudinal self-report data collection technique | Longitudinal qualitative/quantitative data collection |
| Oprindelig kilde≠ | Alaszewski, A. (2006). Using Diaries for Social Research. Sage Publications. ISBN: 978-0761942764 | Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54(1), 579–616. DOI ↗ |
| Aliasser | e-diary method, digital diary study, web-based diary method, online daily diary study | diary study (longitudinal), daily diary method, repeated-measures diary, longitudinal self-report diary |
| Relaterede≠ | 5 | 3 |
| Resumé≠ | The online diary method is a longitudinal data collection technique in which participants record their thoughts, experiences, behaviors, or events in structured or semi-structured entries submitted via digital platforms — such as web forms, email, or dedicated apps — at regular or event-contingent intervals. It combines the ecological validity of traditional diary research with the logistical advantages of remote, automated data collection. | 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. |
| ScholarGateDatasæt ↗ |
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