Experience sampling method

Abstract: The Day Reconstruction Method (DRM) assesses how people spend their time and how they experience the various activities and settings of their lives, combining features of time-budget measurement and experience sampling. Participants systematically reconstruct their activities and experiences of the preceding day with procedures designed to reduce recall biases. The DRM's utility is shown by documenting close correspondences between the DRM reports of 909 employed women and established results from experience sampling. An analysis of the hedonic treadmill shows the DRM's potential for well-being research.

Abstract: To understand the dynamics of mental health, it is essential to develop measures for the frequency and the patterning of mental processes in every-day-life situations. The Experience-Sampling Method (ESM) is an attempt to provide a valid instrument to describe variations in self-reports of mental processes. It can be used to obtain empirical data on the following types of variables: (a) frequency and patterning of daily activity, social interaction, and changes in location; (b) frequency, intensity, and patterning of psychological states, i.e., emotional, cognitive, and conative dimensions of experience; (c) frequency and patterning of thoughts, including quality and intensity of thought disturbance. The article reviews practical and methodological issues of the ESM and presents evidence for its short-and long-term reliability when used as an instrument for assessing the variables outlined above.

Abstract: To understand the dynamics of mental health, it is essential to develop measures for the frequency and the patterning of mental processes in every-day-life situations. The Experience-Sampling Method (ESM) is an attempt to provide a valid instrument to describe variations in self-reports of mental processes. It can be used to obtain empirical data on the following types of variables: a) frequency and patterning of daily activity, social interaction, and changes in location; b) frequency, intensity, and patterning of psychological states, i.e., emotional, cognitive, and conative dimensions of experience; c) frequency and patterning of thoughts, including quality and intensity of thought disturbance. The article reviews pratical and methodological issues of the ESM and presents evidence for its short-and long-term reliability when used as an instrument for assessing the variables outlined above. It also presents evidence for validity by showing correlation between ESM measures on the one hand and physiological measures, one-time psychological tests, and behavioral indices on the other. A number of studies with normal and clinical populations that have used the ESM are reviewed to demonstrate the range of issues to which the technique can be usefully applied.

Abstract: Part 1. Theoretical Background. H.T. Reis, Why Researchers Should Think "Real World": A Conceptual Rationale. N. Schwarz, Why Researchers Should Think "Real Time": A Cognitive Rationale. E.L. Hamaker, Why Researchers Should Think "Within Person": A Paradigmatic Rationale. P. Wilhelm, M. Perrez, K. Pawlik, Conducting Research in Daily Life: A Historical Review. Part 2. Study Design Considerations and Methods of Data Collection. T.S. Conner, B.J. Lehman, Getting Started: Launching a Study in Daily Life. W.D. Barta, H. Tennen, M.D. Litt, S. Armeli, Measurement Reactivity in Diary Research. T. Kubiak, K. Krog, Computerized Sampling of Experience and Behavior. K.C. Gunthert, S.J. Wenze, Daily Diary Methods. D.S. Moskowitz, G. Sadikaj, Event-Contingent Recording. M.R. Mehl, M.L. Robbins, Naturalistic Observation Sampling: The Electronically Activated Recorder (EAR). W. Schlotz, Ambulatory Psychoneuroendocrinology: Assessing Salivary Cortisol and Other Hormones in Daily Life. F.H. Wilhelm, P. Grossman, M.I. Muller, Bridging the Gap between the Laboratory and the Real World: Integrative Ambulatory Psychophysiology. J.B.J. Bussmann, U.W. Ebner-Priemer, Ambulatory Assessment of Movement Behavior: Methodology, Measurement, and Application. M.S. Goodwin, Passive Telemetric Monitoring: Novel Methods for Real-World Behavioral Assessment. S.S. Intille, Emerging Technology for Studying Daily Life. Part 3. Data-Analytic Methods. N. Bolger, G. Stadler, J.P. Laurenceau, Power Analysis for Intensive Longitudinal Studies. P.E. Shrout, S.P. Lane, Psychometrics. K.O. McCabe, L. Mack, W. Fleeson, A Guide for Data Cleaning in Experience Sampling Studies. A.C. Black, O. Harel, G. Matthews, Techniques for Analyzing Intensive Longitudinal Data with Missing Values. J.B. Nezlek, Multilevel Modeling Analysis of Diary-Style Data. M. Eid, D.S. Courvoisier, T. Lischetzke, Structural Equation Modeling of Ambulatory Assessment Data. J.P. Laurenceau, N. Bolger, Analyzing Diary and Intensive Longitudinal Data from Dyads. U.W. Ebner-Priemer, T.J. Trull, Investigating Temporal Instability in Psychological Variables: Understanding the Real World as Time Dependent. P.R. Deboeck, Modeling Nonlinear Dynamics in Intraindividual Variability. A. Brose, N. Ram, Within-Person Factor Analysis: Modeling How the Individual Fluctuates and Changes across Time. N.A. Card, Multilevel Mediational Analysis in the Study of Daily Lives. Part 4. Research Applications: Perspectives from the Different Fields. A.A. Augustine, R.J. Larsen, Emotion Research. S.L. Gable, C.L. Gosnell, T. Prok, Close Relationships. W. Fleeson, E.E. Noftle, Personality Research. W. Tov, C.N. Scollon, Cross-Cultural Research. J.L. Kurtz, S. Lyubomirsky, Positive Psychology. J.M. Smyth, K.E. Heron, Health Psychology. J.M. Hektner, Developmental Psychology. D.J. Beal, Industrial/Organizational Psychology. T.J. Trull, U.W. Ebner-Priemer, W.C. Brown, R.L. Tomko, E.M. Scheiderer, Clinical Psychology. I. Myin-Germeys, Psychiatry.