Módszerek összehasonlítása

	Sport Participation Time-Budget Diary	Leisure Time-Use Sequence Analysis
Tudományterület	Sport Leisure Studies	Sport Leisure Studies
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	1998	2000
Megalkotó	Jonathan Gershuny & Oriel Sullivan (time-use diary methodology)	Andrew Abbott & Angela Tsay (optimal matching in sociology); applied to time-use leisure sequences
Típus	Episode-level diary survey pipeline for sport and leisure participation	Order-aware pipeline for clustering daily leisure activity sequences
Alapmű	Gershuny, J., & Sullivan, O. (1998). The Sociological Uses of Time-use Diary Analysis. European Sociological Review, 14(1), 69-85.	Abbott, A., & Tsay, A. (2000). Sequence Analysis and Optimal Matching Methods in Sociology: Review and Prospect. Sociological Methods & Research, 29(1), 3-33.
Alternatív nevek	Sport Time-Use Diary, Leisure Time-Budget Survey, Sport Participation Diary Method, Episode Diary of Physical Activity	Leisure Day Sequence Analysis, Optimal Matching of Leisure Episodes, Activity Sequence Analysis, Time-Use Optimal Matching
Kapcsolódó	3	3
Összefoglaló	The sport participation time-budget diary measures how much sport and leisure people actually do by asking them to record their day as a sequence of time-stamped episodes rather than answering a single recall question. Building on the time-use diary tradition formalized by Jonathan Gershuny and Oriel Sullivan, the method treats a day as an exhaustive, non-overlapping chain of activities, each with a start and end time, a location, and a record of who else was present. Applied to sport and leisure, it captures not only the duration and frequency of exercise, training, and active or passive recreation, but also the social and spatial context in which they occur. Because every minute is accounted for, the diary yields population estimates of participation that are far less prone to the over-reporting and rounding that plague stylized 'how often do you exercise?' survey items.	Leisure time-use sequence analysis treats a person's day not as a bundle of activity totals but as an ordered sequence of states, and asks which whole-day patterns of leisure recur across a population. It imports optimal matching -- the alignment technique Andrew Abbott and Angela Tsay reviewed for sociology -- into the study of time-use diaries: each day becomes a string of categorical states (sport, active leisure, passive leisure, work, sleep, and so on) sampled at regular intervals, and the dissimilarity between any two days is the minimum cost of editing one sequence into the other. Clustering the resulting dissimilarity matrix yields a typology of leisure days -- the active morning, the evening screen-leisure pattern, the fragmented weekend -- that preserves the timing and ordering of activity that simple duration tallies discard.