The DOI matches its Crossref record; 117 of the 117 references it cites were found in a registry or an index.
Ambulatory Assessment
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
In the citing paper
“A particular advantage of mobile phone technology is its capacity to facilitate ecological momentary assessment (EMA); that is, self-monitoring of symptoms and behaviors in real-time and in real-world contexts [14,15].”
From Breaking open the black box: isolating the most potent features of a web and mobile phone-based intervention for depression, anxiety, and stress (2015) · cites this paper as [15]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene
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
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.3.022806.091415 · Cited by 6,454
Prince, S. A., Adamo, K. B., Hamel, M., Hardt, J., Connor Gorber, S., & Tremblay, M. (2008) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-5-56 · Cited by 3,162
A wandering mind is an unhappy mind
Killingsworth, M. A., & Gilbert, D. T. (2010) · Science · doi:10.1126/science.1192439 · Cited by 2,575
Handbook of research methods for studying daily life
Mehl, M. R., Conner, T. S., & Csíkszentmihályi, M. (2012) · Choice Reviews Online · doi:10.5860/choice.50-1159 · Cited by 2,121
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
Heron, K. E., & Smyth, J. M. (2010) · British Journal of Health Psychology · doi:10.1348/135910709x466063 · Cited by 1,438
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
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
Cited by
Sorted by citations
Items 601–700 of 756
When time slows down: temporal distortion and addictive social media use
Vinci, L. A., Savioni, L., & Triberti, S. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1648583 · Cited by 1
Ho, Y., Fang, C.-L., Ching, Y., Chang, H., Wang, J., & Wang, C. C. N. (2025) · JMIR Research Protocols · doi:10.2196/84024 · Cited by 1
Romeo, V. M. (2025) · Children · doi:10.3390/children12121703 · Cited by 4
Klatt, M., Lotz, C., Keßler, P., Kachel, G., & Deiglmayr, A. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1668861 · Cited by 1
Tschenett, H., Dreisoerner, A., Schäfer, K., Mewes, R., & Nater, U. M. (2026) · Internet Interventions · doi:10.1016/j.invent.2025.100901 · Cited by 1
Bourke, M., Harrison, Z., Staton, S., Rossa, K. R., & Smith, S. S. (2026) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2026.102232 · Cited by 4
Experience sampling methods require more than numbers
Bringmann, L. F., Guðmundsdóttir, G. R., Schorrlepp, L., Vogelsmeier, L. V. D. E., Smet, M. M. D., Vrijen, C., van Roekel, E., Fritz, J., Chen, J. X., Kirtley, O. J., et al. (2026) · Communications Psychology · doi:10.1038/s44271-026-00416-9 · Cited by 2
Plaitano, E. G., Frumkin, M. R., Jacobson, N. C., Gray, J. J., Panchal, A. R., Watson, P., & Marsch, L. A. (2026) · npj Mental Health Research · doi:10.1038/s44184-026-00201-w · Cited by 1
Slider versus Likert scales: Psychometric properties in ambulatory assessment
Vollbracht, D., Ottenstein, C., Ecker, S., & Lischetzke, T. (2026) · Behavior Research Methods · doi:10.3758/s13428-026-02992-4 · Cited by 2
Kairamkonda, D. D., McGinnis, E. W., Price, M., Hidalgo, J. E., Kim, J., Llorin, J., Stanton, K., Bloomfield, L. S. P., Fudolig, M. I., Ha, J., et al. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1764371 · Cited by 1
Lohmann, J. F., Zitzmann, S., Hecht, M., Niepel, C., & Ulitzsch, E. (2026) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2026.2642783 · Cited by 1
Downes, S., Krys, T., O'Hara, K., Western, M. J., Thompson, L., & Brigden, A. (2026) · medRxiv · doi:10.1371/journal.pdig.0001216
“Such methods could be appropriate for research areas such as behavioural health research, where individually complex determinant factors fluctuate over time and are strongly shaped by personal context; and where EMA designs may miss important contextual nuance or interpretation [16–18].”
Zhu, J., Pan, H., Zhou, J., Gao, Y., Xie, Z., Zhang, C., Li, Y., Liu, Q., Shen, M., & Niu, L. (2026) · Psychiatry Research · doi:10.1016/j.psychres.2026.117310 · Cited by 1
Enhancing mobile brain and body imaging: Open-source solutions for real-world research applications
Haupt, T., Maanen, P., Daeglau, M., Contreras-Altamirano, Strizke, A. S., Kiene, F., Welzel, J., Blum, S., Roheger, M., & Debener, S. (2026) · iScience · doi:10.1016/j.isci.2026.116647 · Cited by 2
“10,11 Two central technical challenges must be overcome to enable successful MoBI data acquisition.”
A systematic review of state loneliness in daily life using intensive longitudinal methods
Xiao, Z., Ozdemir, E., Long, E., Kwong, A. S. F., Robertson, S., Murray, A., & Whalley, H. C. (2026) · Clinical Psychology Review · doi:10.1016/j.cpr.2026.102799 · Cited by 1
Suitability of Event-Based Prompts in Experience Sampling Studies Focusing on Location Changes
Exler, A., Kramer, S., Martínez, M. A. M., Navolskyi, C., Vogt, M., & Beigl, M. (2018) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-319-98551-0_19 · Cited by 1
Intensive Longitudinal Designs
Wright, A. G. C., & Hallquist, M. N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781316995808.028 · Cited by 1
Hernandez, R., Jin, H., Pyatak, E. A., Roll, S. C., Gonzalez, J. S., & Schneider, S. (2022) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2022.2149878 · Cited by 1
OpenDPMH: A Framework for Developing Mobile Sensing Applications of Digital Phenotyping
Mendes, J. P. M., Silva, F., Cardoso, A., de Moura, I. R., Coutinho, L., Viana, D., Endler, M., & Teles, A. S. (2023) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms58004.2023.00216 · Cited by 1
Baum, E., Thiel, C., Kobleder, A., Bernhardsgrütter, D., Engst, R., Maurer, C., & Koller, A. (2023) · JMIR Cancer · doi:10.2196/52985 · Cited by 1
Ambulatory assessment to advance the science of nondrug reward in addiction and recovery
Stull, S. W. (2024) · Addiction Research & Theory · doi:10.1080/16066359.2024.2376622 · Cited by 1
Mother‐Infant Covariation of Positive and Negative Emotions Across the Day
Hibel, L. C., Liu, S., & Boyer, C. J. (2024) · Infant and Child Development · doi:10.1002/icd.2562 · Cited by 2
Plaitano, E. G., Zeng, S., Emrich, M., Patton, E. E., Webb, E. K., Pacella‐LaBarbara, M. L., Barduhn, M. S., & Hruska, B. J. (2025) · Journal of Traumatic Stress · doi:10.1002/jts.23180 · Cited by 1
Byrd, A. L., Kahhalé, I., Vize, C. E., Griffith, R., Viding, E. M., & Stepp, S. D. (2025) · Aggression and Violent Behavior · doi:10.1016/j.avb.2025.102082 · Cited by 1
Keller, F., Stadnitski, T., Nützel, J., & Schepker, R. (2018) · Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie · doi:10.1024/1422-4917/a000594 · Cited by 1
Erste Schritte zu Smartphone-basierten Sportinterventionen im Alltag?
Reichert, M., Kapteinat, I., Lauvai, I., Hennig, O., Reinhard, I., Braun, U., Limberger, M. F., & Ebner‐Priemer, U. (2018) · Zeitschrift für Sportpsychologie · doi:10.1026/1612-5010/a000243 · Cited by 3
Self-citationEmotional responses to perceived haze in daily life: the moderation of dispositional mindfulness
Ding, X., An, Y., Zhou, Y., Zhou, L., & Xu, W. (2019) · Vulnerable Children and Youth Studies · doi:10.1080/17450128.2019.1612127 · Cited by 1
Trull, T. J., Hepp, J., Wycoff, A. M., Vebares, T. J., Fleming, M. N., Hua, J. P. Y., Yeung, E. W., & Kerns, J. G. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.10.031 · Cited by 2
Self-citationGesundheitspsychologische Diagnostik
Romppel, M., & Grande, G. (2016) · Springer eBooks · doi:10.1007/978-3-662-47972-8_6 · Cited by 1
Characterization of Binge Eating Days in Daily Life
Reichenberger, J., Arend, A., & Jens Blechert, A. (2023) · Springer eBooks · doi:10.1007/978-3-031-16691-4_57 · Cited by 1
Experience sampling in dementia care
van Knippenberg (2017) · doi:10.26481/dis.20170317rvk · Cited by 1
Lydon‐Staley, D. M., Kuehner, C., Zamoscik, V., Huffziger, S., Kirsch, P., & Bassett, D. S. (2018) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/5wz7c · Cited by 2
Racial discrimination and mental health : temporal dynamics and neurocognitive moderators
Volpert‐Esmond, H. I. (2020) · MOspace Institutional Repository (University of Missouri) · doi:10.32469/10355/86513 · Cited by 1
El IVA como tributo compartido
Segura, J. V. S. (1997) · Noticias de la Unión Europea · Cited by 1
Voelkle, M. C., & Hecht, M. (2020) · Springer eBooks · doi:10.1007/978-3-319-24612-3_1323 · Cited by 1
König, L. M., Allmeta, A., Christlein, N., Emmenis, M. V., & Sutton, S. R. (2021) · doi:10.31234/osf.io/xkrg5 · Cited by 1
Jamal, R., & Kullar, M. (2022) · doi:10.31234/osf.io/c957d · Cited by 1
Sameh, A., Nauha, L., Seppänen, M., Niemelä, M., Oussalah, M., Korpelainen, R., & Farrahi, V. (2025) · medRxiv · doi:10.1101/2025.09.01.25334782 · Cited by 1
Qualitative Methoden der Psychologischen Online-Forschung
Gnambs, T., & Batinic, B. (2017) · Springer eBooks · doi:10.1007/978-3-658-18387-5_24-1
Sport tut gut?! Bewegung und Wohlbefinden
Brand, R., & Kanning, M. K. (2018) · Springer eBooks · doi:10.1007/978-3-662-53385-7_36-1
Merrill, A. M. (2018) · MOspace Institutional Repository (University of Missouri) · doi:10.32469/10355/66774
Samuel, D. B., Bucher, M. A., & Suzuki, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781316995808.007
Possible applications of companion systems in psychotherapy - perspectives on a new technology
Walter, S., Haase, M., Oschlies-Strobel, A., Jerg‐Bretzke, L., Traue, H. C., & Limbrecht-Ecklundt, K. (2017) · doi:10.1109/icct42709.2017.9151910
Social Behaviour and Cognitive Monitoring in Healthy Ageing
Röcke, C., Guye, S., Girolami, M., & Kniestedt, I. (2021) · Research for development · doi:10.1007/978-3-030-72663-8_6
Hong, D., Zhu, Y., Chen, R., Xiao, B., Huang, Y., & Meng, Y. (2021) · Research Square · doi:10.21203/rs.3.rs-886323/v1
Data to Information: Computational Models and Analytic Methods
Visweswaran, S., & Tajgardoon, M. (2021) · Health informatics · doi:10.1007/978-3-030-70558-9_10
Capograssi, Leopardi e il pianto dell'essere
Biancu, S. (2009) · IRIS
(2021) · Cambridge University Press eBooks · doi:10.1017/9781108976213.013
Wright, A. G. C., & Hallquist, M. N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781316995808.005
Zänkert, S., Lindl, A., Schmitz, A., Kudielka, B. M., Mühlberger, A., & Wüst, S. (2022) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2022.02.009 · Cited by 1
Tomasik, M. J., & Moser, U. (2019) · Psychologische Rundschau · doi:10.1026/0033-3042/a000438
Approaching Academic Adjustment on Multiple Time ScalesPreprint
Neubauer, A. B., & Schmiedek, F. (2022) · doi:10.31234/osf.io/n7srz
Characterization of Binge Eating Days in Daily Life
Reichenberger, J., Arend, A., & Jens Blechert, A. (2022) · Springer eBooks · doi:10.1007/978-3-030-67929-3_57-1
Chapter 25. Use of Technology in Geriatric Psychiatry
Kim, H., Skurla, M. D., Rahman, A. T., & Vahia, I. V. (2022) · American Psychiatric Association Publishing eBooks · doi:10.1176/appi.books.9781615375196.ds25
Lukka, L., Karhulahti, V., Bergman, V.-R., & Palva, J. M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4578807
Ebling, S., Johnson, S. U., Hoffart, A., Pallesen, S., & Ebrahimi, O. V. (2023) · doi:10.31234/osf.io/kjqg8
Time-Series Signals of Affect and Neural Dynamics with Technology to Identify Depression Risk
Jamal, R., & Kullar, M. (2023) · Journal of Student Research · doi:10.47611/jsrhs.v12i4.5142 · Cited by 1
Szaszkó, B., Tschenett, H., Ulrich Ansorge, A., & Nater, U. M. (2024) · doi:10.31234/osf.io/dmqpt
Feneberg, A. C., Hirsch, S., Mewes, R., & Nater, U. M. (2024) · Springer eBooks · doi:10.1007/978-3-662-67506-9_18
Koenig, J., Steiner, S., Reichl, C., Cavelti, M., Zimmermann, R., Schmeck, K., & Kaess, M. (2024) · Psychotherapy Research · doi:10.1080/10503307.2024.2385396
Qiao, L., Xu, S., Zhang, W.-R., Liu, S., & Lin, X.-Y. (2024) · Psychology and Health · doi:10.1080/08870446.2024.2395867
Gajos, J. M., Giménez-Santana, A., Walker, J. T., Cropsey, K. L., Walters, S. T., & Businelle, M. S. (2024) · Journal of Crime and Justice · doi:10.1080/0735648x.2024.2396406
Fernández‐García, X., Inchausti, F., Pérez‐Albéniz, A., Sierra, J. O., Falcó, R., & Fonseca‐Pedrero, E. (2024) · International Journal of Methods in Psychiatric Research · doi:10.1002/mpr.2035
Li, J., Zhu, J., Guan, C., Shen, T., & Zhou, B. (2024) · Stress and Health · doi:10.1002/smi.3510
Mullick, K., Tidwell, C. A., & Mehl, M. R. (2024) · Social and Personality Psychology Compass · doi:10.1111/spc3.70019
Moldavski, A., Benedyk, A., Reichert, M., Meyer‐Lindenberg, A., & Tost, H. (2024) · Nervenheilkunde · doi:10.1055/a-2426-9420
Utilizing ecological momentary assessment in nursing research
Choi, M. (2024) · Women s Health Nursing · doi:10.4069/whn.2024.12.14.1
Griffith, J. M., Long, E. E., & Hankin, B. L. (2025) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-025-01306-0
Olfermann, R., & Reichert, M. (2025) · Springer eBooks · doi:10.1007/978-3-662-68241-8_29-1
Hannibal, S., Behrendt, D., Wessa, M., Schäfer, S. K., Dalkner, N., & Lehr, D. (2025) · doi:10.2196/preprints.78335
Multidimensional State Mindfulness Questionnaire (MSMQ)
Blanke, E. S., & Brose, A. (2025) · Springer eBooks · doi:10.1007/978-3-031-47219-0_24 · Cited by 1
Investigating factors on the intention to use mobile apps against food waste
Boecker, L., Hübner, D.-S., Radtke, U., Tóth, G., & Wohllebe, A. (2025) · International journal on food system dynamics · doi:10.1163/18696945-bja00009
Lane, C. R., Griffith, J. M., & Hankin, B. L. (2025) · The Journal of Early Adolescence · doi:10.1177/02724316251370618 · Cited by 1
“Experience sampling methods (ESM) address these shortcomings by collecting ecologically-valid data on a person ’ s experiences in real time (Shiffman et al., 2008; Trull & Ebner-Priemer, 2013).”
Engelskirchen, L., Asbrand, J., & Tuschen‐Caffier, B. (2025) · Cognitive Therapy and Research · doi:10.1007/s10608-025-10643-9
Schmitz, S. E., Hartnagel, L., & Ebner‐Priemer, U. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-14146-1.00014-0
Self-citationAmini-Nejad, R., Nater, U. M., & Mewes, R. (2025) · European Journal of Psychotraumatology · doi:10.1080/20008066.2025.2565058
Olfermann, R., & Reichert, M. (2025) · Springer eBooks · doi:10.1007/978-3-662-70475-2_29
Postelnicu, M. D., Istrate, O., Iliescu, D., & Ion, A. (2025) · Journal of Evidence-Based Psychotherapies · doi:10.24193/jebp.2025.2.10
徐, 浩. (2024) · Advances in Psychology · doi:10.12677/ap.2024.143184 · Cited by 1
Selvey-Bouyack, A. M., Nguyen‐Feng, V. N., Merians, A. N., & Frazier, P. A. (2025) · Journal of American College Health · doi:10.1080/07448481.2025.2597897
“Although daily measures reduce response bias and are more ecologically valid, 19 to better understand the relations between childhood emotional abuse and stressor exposure, it may be useful to have multiple time frames because some stressors may be best captured using daily measures (e.g., academic…”
Hong, D., Zhu, Y., Chen, R., Xiao, B., Huang, Y., & Yu, M. (2022) · Figshare · doi:10.6084/m9.figshare.19808945
Ebner-Priemer, U. W., Mühlbauer, E., Neubauer, A. B., Hill, H., Beier, F., Santangelo, P. S., Ritter, P. S., Kleindienst, N., Bauer, M., Schmiedek, F., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13265808
Self-citationZarate, D., Stavropoulos, V., Ball, M., de Sena Collier, G., & Jacobson, N. C. (2022) · Figshare · doi:10.6084/m9.figshare.20131117
Zarate, D., Stavropoulos, V., Ball, M., de Sena Collier, G., & Jacobson, N. C. (2022) · Figshare · doi:10.6084/m9.figshare.20131114
Kanning, M. K., Niermann, C. Y. N., Ebner-Primer, U., & Giurgiu, M. (2021) · Figshare · doi:10.6084/m9.figshare.15178787
Finkbeiner, M., Kühnhausen, J., Schmid, J., Conzelmann, A., Dürrwächter, U., Wahl, L.-M., Kelava, A., Gawrilow, C., & Renner, T. J. (2022) · Figshare · doi:10.6084/m9.figshare.20677865
Ebner-Priemer, U. W., Mühlbauer, E., Neubauer, A. B., Hill, H., Beier, F., Santangelo, P. S., Ritter, P. S., Kleindienst, N., Bauer, M., Schmiedek, F., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13265805
Self-citationZhang, X., Lewis, S., Chen, X., Zhou, J., Wang, X., & Bucci, S. (2024) · Figshare · doi:10.6084/m9.figshare.25572496
Finkbeiner, M., Wahl, L.-M., Kühnhausen, J., Schmid, J., Hellwig, L., Brenner, V., Dürrwächter, U., Conzelmann, A., Kelava, A., Renner, T. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26597837
Finkbeiner, M., Wahl, L.-M., Kühnhausen, J., Schmid, J., Hellwig, L., Brenner, V., Dürrwächter, U., Conzelmann, A., Kelava, A., Renner, T. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26597846
Ebner-Priemer, U. W., Mühlbauer, E., Neubauer, A. B., Hill, H., Beier, F., Santangelo, P. S., Ritter, P. S., Kleindienst, N., Bauer, M., Schmiedek, F., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13265802
Self-citationFinkbeiner, M., Wahl, L.-M., Kühnhausen, J., Schmid, J., Hellwig, L., Brenner, V., Dürrwächter, U., Conzelmann, A., Kelava, A., Renner, T. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26597843
Music Listening in Everyday Life
Feneberg, A. C., Hirsch, S., Mewes, R., & Nater, U. M. (2025) · Neurocultural health and wellbeing · doi:10.1007/978-3-662-72175-9_15 · Cited by 1
Petagna, K. D., Ecker, A., Reid, T. E., McMullen, K. M., Quigley, K. S., & Wormwood, J. B. (2026) · International Journal of Clinical and Health Psychology · doi:10.1016/j.ijchp.2025.100659 · Cited by 3
Ou, Y., de Bruijn, G., & Schulz, P. J. (2026) · doi:10.2196/preprints.88849
Detection of social connectedness in everyday life via multimodal lifelogging data
Dobbins, C., Fairclough, S. H., Haslam, C., Haslam, S. A., & Bentley, S. V. (2026) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2026.103749
Pryss, R., & Schlee, W. (2026) · Telematics and Informatics Reports · doi:10.1016/j.teler.2026.100355
Metadata
- 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
- 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
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