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Ambulatory Assessment

Overview
Publisher Annual Reviews
Specialty Psychology
Date 2012 Nov 20
PMID 23157450
Citations 239
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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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References
1.
Berkman E, Falk E, Lieberman M . In the trenches of real-world self-control: neural correlates of breaking the link between craving and smoking. Psychol Sci. 2011; 22(4):498-506. PMC: 3076513. DOI: 10.1177/0956797611400918. View

2.
Hufford M, Shields A, Shiffman S, Paty J, Balabanis M . Reactivity to ecological momentary assessment: an example using undergraduate problem drinkers. Psychol Addict Behav. 2002; 16(3):205-11. View

3.
Shapiro J, Bauer S, Andrews E, Pisetsky E, Bulik-Sullivan B, Hamer R . Mobile therapy: Use of text-messaging in the treatment of bulimia nervosa. Int J Eat Disord. 2009; 43(6):513-9. DOI: 10.1002/eat.20744. View

4.
Ebner-Priemer U, Kuo J, Kleindienst N, Welch S, Reisch T, Reinhard I . State affective instability in borderline personality disorder assessed by ambulatory monitoring. Psychol Med. 2007; 37(7):961-70. DOI: 10.1017/S0033291706009706. View

5.
Razavi N, Horn H, Koschorke P, Hugli S, Hofle O, Muller T . Measuring motor activity in major depression: the association between the Hamilton Depression Rating Scale and actigraphy. Psychiatry Res. 2011; 190(2-3):212-6. DOI: 10.1016/j.psychres.2011.05.028. View