Cited by 761Mental Health Research TopicsDigital Mental Health InterventionsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

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Ambulatory Assessment

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Trull, Timothy J., Ebner-Priemer, Ulrich·2013·Annual Review of Clinical Psychology

DOI 10.1146/annurev-clinpsy-050212-185510PMC PMC4249763

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Abstract

Ambulatory assessment (AA) covers a wide range of assessment methods to study people in their natural environment, including self-report, observational, and biological/physiological/behavioral. AA methods minimize retrospective biases while gathering ecologically valid data from patients' everyday life in real time or near real time. Here, we report on the major characteristics of AA, and we provide examples of applications of AA in clinical psychology (a) to investigate mechanisms and dynamics of symptoms, (b) to predict the future recurrence or onset of symptoms, (c) to monitor treatment effects, (d) to predict treatment success, (e) to prevent relapse, and (f) as interventions. In addition, we present and discuss the most pressing and compelling future AA applications: technological developments (the smartphone), improved ecological validity of laboratory results by combined lab-field studies, and investigating gene-environment interactions. We conclude with a discussion of acceptability, compliance, privacy, and ethical issues.

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Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I. W., Harrington, H., McClay, J., Mill, J., Martin, J., Braithwaite, A., et al. (2003) · Science · doi:10.1126/science.1083968 · Cited by 8,120
Ecological momentary assessment
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A wandering mind is an unhappy mind
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Handbook of research methods for studying daily life
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Ecological Momentary Assessment (Ema) in Behavioral Medicine
Stone, A. A., & Shiffman, S. (1994) · Annals of Behavioral Medicine · doi:10.1093/abm/16.3.199 · Cited by 1,931
Ecological momentary interventions: incorporating mobile technology into psychosocial and health behaviour treatments
Heron, K. E., & Smyth, J. M. (2010) · British Journal of Health Psychology · doi:10.1348/135910709x466063 · Cited by 1,438
A Critical Review of the First 10 Years of Candidate Gene-by-Environment Interaction Research in Psychiatry
Duncan, L. E., & Keller, M. C. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.11020191 · Cited by 1,032
Experience sampling research in psychopathology: opening the black box of daily life
Myin-Germeys, I., Oorschot, M., Collip, D., Lataster, J., Delespaul, P., & van Os, J. (2009) · Psychological Medicine · doi:10.1017/s0033291708004947 · Cited by 817
Patient non-compliance with paper diaries
Stone, A. A., Shiffman, S., Schwartz, J. E., Broderick, J. E., & Hufford, M. R. (2002) · BMJ · doi:10.1136/bmj.324.7347.1193 · Cited by 810

Show all 112 references

Research works printed but not linked: 12

Bussmann JBJ, Ebner-Priemer UW. 2011. Ambulatory activity monitoring: assessing activity, posture, and motion patterns in daily life. See Mehl & Conner 2011, pp. 235–50
Conner TS, Lehman BJ. 2011. Getting started: launching a study in daily life. See Mehl & Conner 2011, pp. 89–107
Eid M, Courvoisier DS, Lischetzke T. 2011. Structural equation modeling of ambulatory assessment data. See Mehl & Conner 2011, pp. 384–406
Goodwin MS. 2011. Passive telemetric monitoring: novel methods. See Mehl & Conner 2011, pp. 251–66
Grassi A, 2007, Annu. Rev. CyberTherapy Telemed., 5, 123
Mehl MR, Robbins ML. 2011. Naturalistic observation sampling: the Electronically Activated Recorder (EAR). See Mehl & Conner 2011, pp. 176–92
Portio Res., 2012, Portio Research Mobile Factbook 2012.
10.1037//0022-006X.64.2.366 · DOI · Paper page
Smith A, 2012, 46% of American Adults Are Smartphone Owners.
Solzbacher S, 2007, Frontiers in Stepped eCare—eHealth Methods in Behavioural and Psychosomatic Medicine, 111
Wilhelm FH, Grossman P, Mueller M. 2011. Bridging the gap between laboratory and the real word: integrative ambulatory psychophysiology. See Mehl & Conner 2011, pp. 210–34
Wilhelm P, Perrez M, Pawlik K. 2011. Conducting research in daily life: a historical overview. See Mehl & Conner, pp. 62–86

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Authors: Trull, T. J., & Ebner-Priemer, U.
Affiliations: University of Missouri (US)
Institute for Sport and Sport Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany; Central Institute of Mental Health, 68072 Mannheim, Germany
ORCID: Trull, Timothy J.
Venue: Annual Review of Clinical Psychology
Publisher: Annual Reviews
Published: 2013-03-28
Volume: 9
Issue: 1
Pages: 151-176
ISSN: 1548-5943 (ISSN-L)
1548-5951
DOI: 10.1146/annurev-clinpsy-050212-185510
PMC: PMC4249763
OpenAlex: W4235675284
Cited by: 761
References: 112
Citations by year: 2026: 82 · 2025: 72 · 2024: 67 · 2023: 61 · 2022: 56 · 2021: 77 · 2020: 85 · 2019: 61 · 2018: 52 · 2017: 44 · 2016: 34 · 2015: 37 · 2014: 20 · 2013: 9
FWCI: 3.07
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Annual Review of Clinical Psychology (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: National Institute on Alcohol Abuse and Alcoholism (P60AA011998)
Topics: Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Keywords: ambulatory assessment, ecological validity, self-report, observational assessment, physiological assessment, symptom dynamics, recurrence prediction, treatment monitoring, treatment response prediction, relapse prevention, smartphone technology, gene-environment interaction, research ethics, participant compliance, privacy
MeSH terms: Mental Disorders, Data Collection, Humans, Psychology, Clinical, Monitoring, Ambulatory

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