Cited by 3,843Mental Health Research TopicsPsychometric Methodologies and TestingAttachment and Relationship Dynamics

Diary Methods: Capturing Life as it is Lived

Bolger, Niall, Davis, Angelina, Rafaeli, Eshkol·2003·Annual Review of Psychology

Abstract

In diary studies, people provide frequent reports on the events and experiences of their daily lives. These reports capture the particulars of experience in a way that is not possible using traditional designs. We review the types of research questions that diary methods are best equipped to answer, the main designs that can be used, current technology for obtaining diary reports, and appropriate data analysis strategies. Major recent developments include the use of electronic forms of data collection and multilevel models in data analysis. We identify several areas of research opportunities: 1. in technology, combining electronic diary reports with collateral measures such as ambulatory heart rate; 2. in measurement, switching from measures based on between-person differences to those based on within-person changes; and 3. in research questions, using diaries to (a) explain why people differ in variability rather than mean level, (b) study change processes during major events and transitions, and (c) study interpersonal processes using dyadic and group diary methods.

Integrity signals

Registry

Crossref · 10.1146/annurev.psych.54.101601.145030

Cites

0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Research works printed but not linked: 30

  1. Allport GW, 1942, The Use of Personal Documents in Psychological Science.
  2. Bentler PM, 1995, EQS Structural Equations Program Manual.
  3. Borsboom D, 2002, Psychol. Rev.
  4. Bryk AS, 1996, HLM: Hierarchical Linear and Nonlinear Modeling with the HLM/2L and HLM/3L Programs.
  5. Diggle P, 2001, Analyses of Longitudinal Data.
  6. Fahrenberg J, 1996, Ambulatory Assessment: Computer Assisted Psychological and Psychophysiological Methods in Monitoring and Field Studies.
  7. Feldman Barrett L, Jamner LD. 2000. Capturing the vicissitudes of life: electronic experience sampling . Workshop presented at Annu. Meet. Soc. Personal. Soc. Psychol., 1st, Nashville, TN
  8. Jamner LD, Shapiro D, Alberts J. 1998. Mood, blood pressure, and heart rate: strategies for developing a more effective ambulatory mood diary. In Technology and Methods in Behavioral Medicine , ed. DS Krantz, A Baum, pp. 195–220. Mahwah, NJ: Erlbaum
  9. Jöreskog KG, 1996, LISREL 8 User's Reference Guide.
  10. Kashy DA, Kenny DA. 2000. The analysis of data from dyads and groups. In Handbook of Research Methods in Social Psychology , ed. HT Reis, CM Judd, pp. 451–77. New York: Cambridge Univ. Press
  11. Kenny D, Kashy D, Bolger N. 1998. Data analysis in social psychology. In Handbook of Social Psychology , ed. D Gilbert, S Fiske, G Lindzey, pp. 233–65. New York: McGraw-Hill
  12. Larsen RJ. 1990. Spectral analysis of longitudinal data. In Statistical Methods in Longitudinal Research: Time Series and Categorical Longitudinal Data. Vol. 2: Statistical Modeling and Decision Science , ed. A von Eye, pp. 319–50. San Diego, CA: Academic
  13. Larson R, 1994, Divergent Realities: The Emotional Lives of Mothers, Fathers, and Adolescents.
  14. Moskowitz DS, 2002, Modeling Intraindividual Variability with Repeated Measures Data: Methods and Applications.
  15. Muthén B, 2002, Mplus Version 2 User's Guide.
  16. Nesselroade JR, McArdle JJ, Aggen SH, Meyers JM. 2002. Dynamic factor analysis models for representing process in multivariate time-series. SeeMoskowitz & Hershberger 2002, pp. 235–65
  17. Perrez M, Reicherts M. 1996. A computer-assisted self-monitoring procedure for assessing stress-related behavior under real life conditions. SeeFahrenberg & Myrtek 1996, pp. 51–67
  18. Perrez M, Wilhelm P, Schoebi D, Horner M. 2001. Simultaneous computer assisted assessment of causal attribution and social coping in families. SeeFahrenberg & Myrtek 2001, pp. 25–43
  19. Prosser R, 1996, MLn User's Guide.
  20. Raudenbush SW, 2002, Hierarchical Linear Models: Applications and Data Analysis Methods.
  21. Reis HT. 1994. Domains of experience: investigating relationship processes from three perspectives. In Theoretical Frameworks in Personal Relationships , ed. R Erber, R Gilmore, pp. 87–110. Mahwah, NJ: Erlbaum
  22. Reis HT, Gable SL. 2000. Event-sampling and other methods for studying everyday experience. In Handbook of Research Methods in Social and Personality Psychology , ed. TH Reis, MC Judd, pp. 190–222. New York: Cambridge Univ. Press
  23. Reis HT, Shaver P. 1988. Intimacy as an interpersonal process. In Handbook of Relationships , ed. SW Duck, pp. 367–389. Chichester, UK: Wiley
  24. SAS Inst., 1999, SAS/STAT User's Guide, Version 7.
  25. Shiffman S. 2000. Real-time self-report of momentary states in the natural environment: computerized ecological momentary assessment. In The Science of Self-reports: Implications for Research and Practice , ed. AA Stone, JS Turkkan, CA Bachrach, JB Jobe, HS Kurtzman, VS Cain, pp. 277–96. Mahwah, NJ: Erlbaum
  26. Shiffman S, Stone AA. 1998. Ecological momentary assessment: a new tool for behavioral medicine research. In Technology and Methods in Behavioral Medicine , ed. DS Krantz, A Baum, pp. 117–31. Mahwah, NJ: Erlbaum
  27. Singer JD. 2002. Fitting individual growth models using SAS PROC MIXED. SeeMoskowitz & Hershberger 2002, pp. 135–70
  28. Snijders TAB, 1999, Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling.
  29. Stonborough THW, 1942, Appl. Anthropol., 2, 37
  30. Wilhelm P. 2001. A multi-level approach to analyze ambulatory assessment data: an examination of family members' emotional states in daily life. In Progress in Ambulatory Assessment: Computer-assisted Psychological and Psychophysiological Methods in Monitoring and Field Studies , ed. J Fahrenberg, M Myrtek, pp. 173–89. Kirkland, WA: Hogrefe & Huber

Cited by

Sorted by citations

Authors
Bolger, N., Davis, A., & Rafaeli, E.
Affiliations
New York University (US)
Venue
Annual Review of Psychology
Published
2003-02
Volume
54
Issue
1
Pages
579-616
ISSN
  • 0066-4308 (ISSN-L)
  • 1545-2085
OpenAlex
W2166190112
Cited by
3,843
References
0
Citations by year
2026: 210 · 2025: 205 · 2024: 203 · 2023: 161 · 2022: 212 · 2021: 257 · 2020: 282 · 2019: 207 · 2018: 204 · 2017: 214 · 2016: 177 · 2015: 215 · 2014: 180 · 2013: 206 · 2012: 195
FWCI
5.68
Type
journal article
Language
en
Open access
closed
Locations
  • Annual Review of Psychology (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Institute of Mental Health (R01MH060366)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Social Sciences › Psychology › Social Psychology › Attachment and Relationship Dynamics
Keywords
diary method, everyday experience, within-person variability, ambulatory heart rate, multilevel models, within-person change, interpersonal processes, life transitions, data collection technology
MeSH terms
Data Collection, Humans, Individuality, Life Change Events, Medical Records, Personality Assessment, Software, User-Computer Interface, Writing

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review