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A Review of Ambulatory Health Data Collection Methods for Employee Experience Sampling Research
Author(s) -
Eatough Erin,
Shockley Kristen,
Yu Peter
Publication year - 2016
Publication title -
applied psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.497
H-Index - 88
eISSN - 1464-0597
pISSN - 0269-994X
DOI - 10.1111/apps.12068
Subject(s) - experience sampling method , actigraphy , popularity , sampling (signal processing) , variety (cybernetics) , applied psychology , tracking (education) , data science , data collection , computer science , psychology , social psychology , sociology , artificial intelligence , social science , pedagogy , filter (signal processing) , neuroscience , circadian rhythm , computer vision
Experience sampling research can offer unique insight into state conditions of employee health. Over the past several years, there has been a surge of popularity for such designs in work and organisational psychology, especially with regard to employee health measurement. Experience sampling health measurement can be executed using a variety of different methods including various objective health metrics such as cardiovascular activity measurement, cortisol response tracking, and actigraphy. Furthermore, recent innovations with personal fitness tracking devices open up many possibilities for researchers to continuously monitor activity and health patterns over many days. Technological advances in self‐reporting methods, especially in combination with innovations in objective health measurement, can offer modern researchers richer sets of data. We summarise and describe these methods, offering insight into their advantages and disadvantages for contemporary health researchers interested in experience sampling designs.