Use of ecological momentary assessment in mood disorders research

Wenze, Susan J.; Miller, Ivan W.

doi:10.1016/j.cpr.2010.06.007

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Use of ecological momentary assessment in mood disorders research

Wenze, Susan J., Miller, Ivan W.·2010·Clinical Psychology Review

DOI 10.1016/j.cpr.2010.06.007

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Abstract

Ecological momentary assessment (EMA) entails repeated, intensive sampling of respondents' current experiences while they are engaged in their typical daily routines, in their natural environments. In this article we discuss benefits of using EMA techniques in mood disorders research, provide an overview of the various specific EMA techniques that have been used with mood-disordered populations to date, and summarize the diverse range of research questions that EMA has been used to explore in this field. In addition, we evaluate the feasibility and acceptability of using EMA techniques with this population and suggest additional areas that might be fruitful to investigate, with a focus on the extension of EMA techniques into treatment research. Overall, data suggest that using EMA techniques in mood disorders research is feasible, generally acceptable, and highly promising. We conclude with a discussion of caveats, limitations, and ethical considerations.

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Previous studies in patients with mood disorders have shown good overall feasibility and acceptability of high-frequency assessments, although there is likely to be an interaction between protocol burden and burden of illness.
“Previous studies in patients with mood disorders have shown good overall feasibility and acceptability of high-frequency assessments, although there is likely to be an interaction between protocol burden and burden of illness [46].”
From Wearable technology for high-frequency cognitive and mood assessment in major depressive disorder: longitudinal observational study (2019) · cites this paper as [46]
Adherence rates in this study are higher than in previous studies with a similar population, although those studies used different EMA methods (e.g., paper-and-pencil diaries, PDAs).
“Moreover, the adherence rates found in this study are even higher than in previous ones with a similar population, although these studies used different EMA methods (e.g., paper-and-pencil diaries, PDAs) [8,14,15].”
From Experienced burden of and adherence to smartphone-based ecological momentary assessment in persons with affective disorders (2020) · cites this paper as [8]
One limitation of the reviews by Ebner-Priemer and Trull (2009) and Wenze and Miller (2010) is that they mostly focus on the methods of the selected studies and are therefore more relevant to researchers than to clinicians.
“However, one limitation of these reviews is that they mostly focus on the methods of the selected studies and are therefore more relevant to researchers than to clinicians.”
From Mood Disorders in Everyday Life: A Systematic Review of Experience Sampling and Ecological Momentary Assessment Studies (2012) · cites this paper as Wenze & Miller (2010)
We only included studies in which participants met clinical criteria for MDD or BD, had a primary diagnosis of a mood disorder, and were assessed outside the laboratory more than once per day.
“Like Wenze and Miller (2010), we only included studies in which participants met clinical criteria for MDD or BD, had a primary diagnosis of a mood disorder, and were assessed outside the laboratory more than once per day.”
From Mood Disorders in Everyday Life: A Systematic Review of Experience Sampling and Ecological Momentary Assessment Studies (2012) · cites this paper as Wenze and Miller (2010)
More than half of the papers included in our review were published after the reviews by Ebner-Priemer and Trull (2009) and Wenze and Miller (2010).
“More than half of the papers included in our review were published after the reviews by Ebner-Priemer and Trull (2009) and Wenze and Miller (2010).”
From Mood Disorders in Everyday Life: A Systematic Review of Experience Sampling and Ecological Momentary Assessment Studies (2012) · cites this paper as Wenze and Miller (2010)

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Norton, M., Wonderlich, S. A., Myers, T. C., Mitchell, J. E., & Crosby, R. D. (2003) · European Eating Disorders Review · doi:10.1002/erv.518 · Cited by 48 · see citing works
Efficacy and utility of computer-assisted cognitive behavioural therapy for anxiety disorders
Przeworski, A., & Newman, M. G. (2006) · Clinical Psychologist · doi:10.1080/13284200500378779 · Cited by 43 · see citing works
Computer and manual self-help behavioral strategies for smoking reduction: Initial feasibility and one-year follow-up
Riley, W. T., Jerome, A., Behar, A., & Weil, J. (2002) · Nicotine & Tobacco Research · doi:10.1080/1462220021000032762 · Cited by 41 · see citing works
Circadian affective, cardiopulmonary, and cortisol variability in depressed and nondepressed individuals at risk for cardiovascular disease
Conrad, A., Wilhelm, F. H., Roth, W. T., Spiegel, D., & Taylor, C. B. (2008) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2007.08.003 · Cited by 41 · see citing works
Variability and severity of depression and anxiety in post traumatic stress disorder and major depressive disorder
Golier, J. A., Yehuda, R., Schmeidler, J., & Siever, L. J. (2001) · Depression and Anxiety · doi:10.1002/da.1022 · Cited by 32 · see citing works
Influence of dysphoria on positive and negative cognitive reactivity to daily mood fluctuations
Wenze, S. J., Gunthert, K. C., & Forand, N. R. (2006) · Behaviour Research and Therapy · doi:10.1016/j.brat.2006.08.010 · Cited by 32 · see citing works
Self-citation
Use of Palm computer as an adjunct to cognitive–behavioural therapy with an ultra‐high‐risk patient: a case report
Kimhy, D., & Corcoran, C. M. (2008) · Early Intervention in Psychiatry · doi:10.1111/j.1751-7893.2008.00083.x · Cited by 31 · see citing works
Diurnal Mood Variation in Melancholic Patients and Healthy Controls
Wefelmeyer, T., & Kuhs, H. (2010) · Psychopathology · doi:10.1159/000284990 · Cited by 24 · see citing works
Communication and psychiatric diagnosis: Tales of depressive moods from two contexts
Mokros, H. B. (1993) · Health Communication · doi:10.1207/s15327027hc0502_4 · Cited by 21 · see citing works
Differences between Depressed and Non-Depressed Residents of Nursing Homes on Measures of Daily Activity Involvement and Affect.
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FEASIBILITY OF COMPUTERIZED SCHEDULED GRADUAL REDUCTION FOR ADOLESCENT SMOKING CESSATION
Riley, W. T., Jerome, A., Behar, A., & Zack, S. (2002) · Substance Use & Misuse · doi:10.1081/ja-120001982 · Cited by 7 · see citing works

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Just-in-time adaptive interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support
Nahum-Shani, I., Smith, S. N., Spring, B. J., Collins, L. M., Witkiewitz, K., Tewari, A., & Murphy, S. A. (2018) · Annals of Behavioral Medicine · doi:10.1007/s12160-016-9830-8 · Cited by 2,171 · see citing works
Ambulatory Assessment
Trull, T. J., & Ebner-Priemer, U. (2013) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-050212-185510 · Cited by 761 · see citing works
Harnessing context sensing to develop a mobile intervention for depression
Burns, M. N., Begale, M., Duffecy, J., Gergle, D., Karr, C. J., Giangrande, E., & Mohr, D. C. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1838 · Cited by 646 · see citing works
The Lancet Psychiatry Commission on psychological treatments research in tomorrow's science
Holmes, E. A., Ghaderi, A., Harmer, C. J., Ramchandani, P. G., Cuijpers, P., Morrison, A. P., Roiser, J. P., Bockting, C. L. H., O'Connor, R. C., Shafran, R., et al. (2018) · The Lancet Psychiatry · doi:10.1016/s2215-0366(17)30513-8 · Cited by 624 · see citing works
Mood Disorders in Everyday Life: A Systematic Review of Experience Sampling and Ecological Momentary Assessment Studies
aan het Rot, M., Hogenelst, K., & Schoevers, R. A. (2012) · Clinical Psychology Review · doi:10.1016/j.cpr.2012.05.007 · Cited by 325 · see citing works
Passive and In-Situ assessment of mental and physical well-being using mobile sensors
Rabbi, M., Ali, S., Choudhury, T., & Berke, E. (2011) · Proceedings of the 13th international conference on Ubiquitous computing · doi:10.1145/2030112.2030164 · Cited by 243 · see citing works
Voice analysis as an objective state marker in bipolar disorder
Faurholt‐Jepsen, M., Busk, J., Frost, M. M., Vinberg, M., Christensen, E. M., Winther, O., Bardram, J. E., & Kessing, L. V. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.123 · Cited by 236 · see citing works
Rumination predicts heightened responding to stressful life events in major depressive disorder and generalized anxiety disorder.
Ruscio, A. M., Gentes, E. L., Jones, J. D., Hallion, L. S., Coleman, E. S., & Swendsen, J. (2015) · Journal of Abnormal Psychology · doi:10.1037/abn0000025 · Cited by 228 · see citing works
“Ecological momentary assessment (EMA) has several unique advantages for addressing these gaps in the literature (Wenze & Miller, 2010).”
Background
Annual Research Review: Ecological momentary assessment studies in child psychology and psychiatry
Russell, M. A., & Gajos, J. M. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13204 · Cited by 236 · see citing works
A lifespan view of anxiety disorders
Lenze, E. J., & Wetherell, J. L. (2011) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2011.13.4/elenze · Cited by 227 · see citing works
The application of mHealth to mental health: opportunities and challenges
Marzano, L., Bardill, A., Fields, B., Herd, K., Veale, D., Grey, N., & Moran, P. (2015) · The Lancet Psychiatry · doi:10.1016/s2215-0366(15)00268-0 · Cited by 200 · see citing works
Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review
Dogan, E., Sander, C., Wagner, X., Hegerl, U., & Kohls, E. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7006 · Cited by 177 · see citing works
Using Ecological Momentary Assessment (EMA) to Assess Situation-Level Predictors of Alcohol Use and Alcohol-Related Consequences
Wray, T. B. (2014) · Alcohol research · doi:10.35946/arcr.v36.1.03 · Cited by 155 · see citing works
Spatio-temporal determinants of mental health and well-being: advances in geographically-explicit ecological momentary assessment (GEMA)
Kirchner, T., & Shiffman, S. S. (2016) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-016-1277-5 · Cited by 150 · see citing works
Factors contributing to depressive mood states in everyday life: A systematic review
Pemberton, R., & Fuller‐Tyszkiewicz, M. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.04.023 · Cited by 142 · see citing works
Temporal patterns of anxious and depressed mood in generalized anxiety disorder: a daily diary study
Starr, L. R., & Davila, J. (2012) · Behaviour Research and Therapy · doi:10.1016/j.brat.2011.11.005 · Cited by 134 · see citing works
Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone
Kim, H., Lee, S., Lee, S., Hong, S., Kang, H., & Kim, N. (2019) · JMIR mHealth and uHealth · doi:10.2196/14149 · Cited by 131 · see citing works
Real-Time Monitoring of Psychotherapeutic Processes: Concept and Compliance
Schiepek, G. K., Aichhorn, W., Gruber, M., Strunk, G., Bachler, E., & Aas, B. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00604 · Cited by 124 · see citing works
Assessing the availability of users to engage in just-in-time intervention in the natural environment
Sarker, H., Sharmin, M., Ali, A. A., Rahman, M. M., Bari, R., Hossain, S. M., & Kumar, S. (2014) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2632048.2636082 · Cited by 121 · see citing works
A systematic review of the psychometric properties, usability and clinical impacts of mobile mood-monitoring applications in young people
Dubad, M., Winsper, C., Meyer, C., Livanou, M., & Marwaha, S. (2017) · Psychological Medicine · doi:10.1017/s0033291717001659 · Cited by 120 · see citing works
Rumination interacts with life stress to predict depressive symptoms: An ecological momentary assessment study
Connolly, S. L., & Alloy, L. B. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2017.07.006 · Cited by 114 · see citing works
Ecological momentary assessment (EMA) of depression-related phenomena
Armey, M. F., Schatten, H. T., Bailen, N. H., & Miller, I. W. (2015) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2015.01.002 · Cited by 108 · see citing works
Self-citation
Ecological momentary assessment is a neglected methodology in suicidology
Davidson, C. L., Anestis, M. D., & Gutierrez, P. M. (2017) · Archives of Suicide Research · doi:10.1080/13811118.2015.1004482 · Cited by 108 · see citing works
Internet and mobile interventions for depression: Opportunities and challenges: <scp>Cuijpers et al</scp> .
Cuijpers, P., Kleiboer, A., Karyotaki, E., & Riper, H. (2017) · Depression and Anxiety · doi:10.1002/da.22641 · Cited by 112 · see citing works
Everyday social interactions and intra-individual variability in affect: a systematic review and meta-analysis of ecological momentary assessment studies
Liu, H., Xie, Q. W., & Lou, V. W. Q. (2019) · Motivation and Emotion · doi:10.1007/s11031-018-9735-x · Cited by 104 · see citing works
Smartphone-based objective monitoring in bipolar disorder: status and considerations
Faurholt‐Jepsen, M., Bauer, M., & Kessing, L. V. (2018) · International Journal of Bipolar Disorders · doi:10.1186/s40345-017-0110-8 · Cited by 100 · see citing works
Daily mood monitoring of symptoms using smartphones in bipolar disorder: A pilot study assessing the feasibility of ecological momentary assessment
Schwartz, S., Schultz, S., Reider, A., & Saunders, E. F. H. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.11.013 · Cited by 90 · see citing works
Immediate Mood Scaler: Tracking Symptoms of Depression and Anxiety Using a Novel Mobile Mood Scale
Nahum, M., Vleet, T. V., Sohal, V. S., Mirzabekov, J. J., Rao, V. R., Wallace, D. L., Lee, M. B., Dawes, H. E., Stark‐Inbar, A., Jordan, J. T., et al. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.6544 · Cited by 92 · see citing works
Feasibility and Acceptability of Smartphone Assessment in Older Adults with Cognitive and Emotional Difficulties
Ramsey, A. T., Wetherell, J. L., Depp, C. A., Dixon, D. J., & Lenze, E. J. (2016) · Journal of Technology in Human Services · doi:10.1080/15228835.2016.1170649 · Cited by 91 · see citing works
Wearable technology for high-frequency cognitive and mood assessment in major depressive disorder: longitudinal observational study
Cormack, F., McCue, M., Taptiklis, N., Skirrow, C., Glazer, E., Panagopoulos, E., van Schaik, T. A., Fehnert, B., King, J., & Barnett, J. H. (2019) · JMIR Mental Health · doi:10.2196/12814 · Cited by 79 · see citing works
Technology-based parenting interventions for children's physical and psychological health: a systematic review and meta-analysis
Flujas-Contreras, J. M., García‐Palacios, A., & Becerra, I. G. (2019) · Psychological Medicine · doi:10.1017/s0033291719000692 · Cited by 78 · see citing works
Pain, hedonic regulation, and opioid misuse: Modulation of momentary experience by Mindfulness-Oriented Recovery Enhancement in opioid-treated chronic pain patients
Garland, E. L., Bryan, C. J., Finan, P. H., Thomas, E. A., Priddy, S. E., Riquino, M. R., & Howard, M. O. (2017) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2016.07.033 · Cited by 71 · see citing works
Movement patterns in women at risk for perinatal depression: use of a mood-monitoring mobile application in pregnancy
Faherty, L. J., Hantsoo, L., Appleby, D., Sammel, M. D., Bennett, I. M., & Wiebe, D. J. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx005 · Cited by 62 · see citing works
Ambulatory Assessment
Carpenter, R. W., Wycoff, A. M., & Trull, T. J. (2016) · Assessment · doi:10.1177/1073191116632341 · Cited by 72 · see citing works
Experienced burden of and adherence to smartphone-based ecological momentary assessment in persons with affective disorders
van Genugten, C. R., Schuurmans, J., Lamers, F., Riese, H., Penninx, B. W. J. H., Schoevers, R. A., Riper, H. M., & Smit, J. H. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9020322 · Cited by 71 · see citing works
“Nevertheless, systematic reviews showed encouraging results regarding the burden experienced and adherence rates by persons with affective disorders [8,14,15].”
BackgroundInfluential
Objective Measurement of Sociability and Activity: Mobile Sensing in the Community
Berke, E. M., Choudhury, T., Ali, S., & Rabbi, M. (2011) · The Annals of Family Medicine · doi:10.1370/afm.1266 · Cited by 66 · see citing works
The evidence-based practice of psychotherapy: Facing the challenges that lie ahead
Gaudiano, B. A., & Miller, I. W. (2013) · Clinical Psychology Review · doi:10.1016/j.cpr.2013.04.004 · Cited by 67 · see citing works
Self-citation
Ecological Momentary Assessment of Adolescent Problems, Coping Efficacy, and Mood States Using a Mobile Phone App: An Exploratory Study
Kenny, R., Dooley, B. A., & Fitzgerald, A. (2016) · JMIR Mental Health · doi:10.2196/mental.6361 · Cited by 63 · see citing works
Ecological momentary assessment as a measurement tool in depression trials
Targum, S. D., Sauder, C. L., Evans, M., Saber, J. N., & Harvey, P. D. (2021) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2021.02.012 · Cited by 63 · see citing works
The promise of digital mood tracking technologies: are we heading on the right track?
Malhi, G. S., Hamilton, A., Morris, G., Mannie, Z., Das, P., & Outhred, T. (2017) · Evidence Based Mental Health · doi:10.1136/eb-2017-102757 · Cited by 62 · see citing works
Just-in-time adaptive ecological momentary assessment (JITA-EMA)
Schneider, S., Junghaenel, D. U., Smyth, J. M., Wen, C. K. F., & Stone, A. A. (2023) · Behavior Research Methods · doi:10.3758/s13428-023-02083-8 · Cited by 54 · see citing works
Dynamic patterns in psychotherapy--discontinuous changes and critical instabilities during the treatment of obsessive compulsive disorder.
Heinzel, S., Tominschek, I., & Schiepek, G. K. (2014) · PubMed · Cited by 54 · see citing works
Internet-based treatment of depression
Cuijpers, P. J., Riper, H. M., & Andersson, G. (2015) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2014.12.026 · Cited by 53 · see citing works
Prospective crowdsensing versus retrospective ratings of tinnitus variability and tinnitus–stress associations based on the TrackYourTinnitus mobile platform
Pryss, R. C., Probst, T., Schlee, W., Schobel, J., Langguth, B., Neff, P. K. A., Spiliopoulou, M., & Reichert, M. (2018) · International Journal of Data Science and Analytics · doi:10.1007/s41060-018-0111-4 · Cited by 53 · see citing works
Smartphone-based self-monitoring in bipolar disorder: evaluation of usability and feasibility of two systems
Faurholt‐Jepsen, M., Torri, E., Cobo, J., Yazdanyar, D., Palao, D. J., Cardoner, N., Andreatta, O., Mayora, O., & Kessing, L. V. (2019) · International Journal of Bipolar Disorders · doi:10.1186/s40345-018-0134-8 · Cited by 51 · see citing works
Real-Time Monitoring of Non-linear Suicidal Dynamics: Methodology and a Demonstrative Case Report
Fartacek, C., Schiepek, G. K., Kunrath, S., Fartacek, R. R., & Plöderl, M. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00130 · Cited by 50 · see citing works
Nonlinear Dynamics: Theoretical Perspectives and Application to Suicidology
Schiepek, G. K., Fartacek, C., Sturm, J., Kralovec, K., Fartacek, R. R., & Plöderl, M. (2011) · Suicide and Life-Threatening Behavior · doi:10.1111/j.1943-278x.2011.00062.x · Cited by 45 · see citing works
Daily variation in post traumatic stress symptoms in individuals with and without probable post traumatic stress disorder
Biggs, Q. M., Ursano, R. J., Wang, J., Krantz, D. S., Carr, R. B., Wynn, G. H., Probe, D. M., Dacuyan‐Faucher, N., & Fullerton, C. S. (2019) · BMC Psychiatry · doi:10.1186/s12888-019-2041-7 · Cited by 42 · see citing works
Ecological momentary assessment (EMA) of mental health outcomes in veterans and servicemembers: A scoping review
Gromatsky, M. A., Sullivan, S. R., Spears, A. P., Mitchell, E. L., Walsh, S., Kimbrel, N. A., & Goodman, M. S. (2020) · Psychiatry Research · doi:10.1016/j.psychres.2020.113359 · Cited by 37 · see citing works
The relationship between value-based actions, psychological distress and well-being: A multilevel diary study
Grégoire, S., Doucerain, M., Morin, L., & Finkelstein-Fox, L. (2021) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2021.03.006 · Cited by 38 · see citing works
Using ecological momentary assessment to determine media use by individuals with and without major depressive disorder
Primack, B. A., Silk, J. S., DeLozier, C. R., Shadel, W. G., Dillman Carpentier, F. R., Dahl, R. E., & Switzer, G. E. (2011) · Archives of Pediatrics & Adolescent Medicine · doi:10.1001/archpediatrics.2011.27 · Cited by 37 · see citing works
The promise of mobile technologies and single case designs for the study of individuals in their natural environment
Vilardaga, R., Bricker, J. B., & McDonell, M. G. (2014) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2014.03.003 · Cited by 37 · see citing works
Nature at work: The effects of day-to-day nature contact on workers’ stress and psychological well-being
Perrins, S. P., Varanasi, U., Seto, E., & Bratman, G. N. (2021) · Urban forestry & urban greening · doi:10.1016/j.ufug.2021.127404 · Cited by 34 · see citing works
Characterizing eating behavioral phenotypes in mood disorders: a narrative review
Koning, E., Vorstman, J. A. S., McIntyre, R. S., & Brietzke, E. M. (2022) · Psychological Medicine · doi:10.1017/s0033291722002446 · Cited by 35 · see citing works
Requirements for a Flexible and Generic API Enabling Mobile Crowdsensing mHealth Applications
Pryss, R. C., Schobel, J., & Reichert, M. (2018) · doi:10.1109/resacs.2018.00010 · Cited by 35 · see citing works
SPECIFIC MOOD SYMPTOMS CONFER RISK FOR SUBSEQUENT SUICIDAL IDEATION IN BIPOLAR DISORDER WITH AND WITHOUT SUICIDE ATTEMPT HISTORY: MULTI-WAVE DATA FROM STEP-BD
Stange, J. P., Kleiman, E. M., Sylvia, L. G., Magalhães, P. V. D. S., Berk, M., Nierenberg, A. A., & Deckersbach, T. (2016) · Depression and Anxiety · doi:10.1002/da.22464 · Cited by 33 · see citing works
Caregiver Daily Reporting of Symptoms in Autism Spectrum Disorder: Observational Study Using Web and Mobile Apps
Bangerter, A., Manyakov, N. V., Lewin, D., Boice, M., Skalkin, A., Jagannatha, S., Chatterjee, M., Dawson, G., Goodwin, M. S., Hendren, R. L., et al. (2019) · JMIR Mental Health · doi:10.2196/11365 · Cited by 33 · see citing works
Forecasting the Future, Remembering the Past: Misrepresentations of Daily Emotional Experience in Generalized Anxiety Disorder and Major Depressive Disorder
Mathersul, D. C., & Ruscio, A. M. (2019) · Cognitive Therapy and Research · doi:10.1007/s10608-019-10048-5 · Cited by 33 · see citing works
Harnessing Mental Imagery and Enhancing Memory Specificity: Developing a Brief Early Intervention for Depressive Symptoms in Adolescence
Pile, V., Smith, P. A., Leamy, M. C., Oliver, A., Blackwell, S. E., Meiser‐Stedman, R., Dunn, B. D., Holmes, E. A., & Lau, J. Y. F. (2020) · Cognitive Therapy and Research · doi:10.1007/s10608-020-10130-3 · Cited by 32 · see citing works
Evaluation of Ecological Momentary Assessment for Tinnitus Severity
Goldberg, R. L., Piccirillo, M. L., Nicklaus, J. E., Skillington, S. A., Lenze, E. J., Rodebaugh, T. L., Kallogjeri, D., & Piccirillo, J. F. (2017) · JAMA Otolaryngology–Head & Neck Surgery · doi:10.1001/jamaoto.2017.0020 · Cited by 32 · see citing works
La dimension interpersonnelle de la pleine conscience
Khoury, B., Grégoire, S., & Dionne, F. (2020) · Annales Médico-psychologiques revue psychiatrique · doi:10.1016/j.amp.2018.10.018 · Cited by 22 · see citing works
Ecological momentary assessment of mood and physical activity in people with depression.
Hollands, L., Lambert, J., Price, L., Powell, D., & Greaves, C. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.03.085 · Cited by 26 · see citing works
Ecological Momentary Assessment and Intervention in Nonsuicidal Self-Injury: A Novel Approach to Treatment
Armey, M. (2012) · Journal of Cognitive Psychotherapy · doi:10.1891/0889-8391.26.4.299 · Cited by 28 · see citing works
Telemonitoring with respect to Mood Disorders and Information and Communication Technologies: Overview and Presentation of the PSYCHE Project
Javelot, H., Spadazzi, A., Weiner, L., Garcia, S., Gentili, C., Kosel, M., & Bertschy, G. (2014) · BioMed Research International · doi:10.1155/2014/104658 · Cited by 34 · see citing works
Differences between Android and iOS Users of the TrackYourTinnitus Mobile Crowdsensing mHealth Platform
Pryss, R. C., Reichert, M., Schlee, W., Spiliopoulou, M., Langguth, B., & Probst, T. (2018) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2018.00078 · Cited by 29 · see citing works
Screening for Depression in Daily Life: Development and External Validation of a Prediction Model Based on Actigraphy and Experience Sampling Method
Minaeva, O., Riese, H., Lamers, F., Antypa, N., Wichers, M., & Booij, S. H. (2020) · Journal of Medical Internet Research · doi:10.2196/22634 · Cited by 28 · see citing works
The impact and measurement of social dysfunction in late‐life depression: an evaluation of current methods with a focus on wearable technology
Hodgetts, S., Gallagher, P., Stow, D., Ferrier, I. N., & O'Brien, J. T. (2016) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4632 · Cited by 30 · see citing works
Real-time emotion detection by quantitative facial motion analysis
Saadon, J. R., Yang, F., Burgert, R., Mohammad, S., Gammel, T., Sepe, M., Rafailovich, M. H., Mikell, C. B., Polak, P., & Mofakham, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282730 · Cited by 29 · see citing works
Contemporary Approaches to Frequent Mood Monitoring in Bipolar Disorder
Malik, A., Goodwin, G. M., & Holmes, E. A. (2011) · Journal of Experimental Psychopathology · doi:10.5127/jep.014311 · Cited by 28 · see citing works
Repeated self-evaluations may involve familiarization: An exploratory study related to Ecological Momentary Assessment designs in patients with major depressive disorder
Vachon, H., Fortes-Bourbousson, M., Deschamps, T., Doron, J., Bulteau, S., Sauvaget, A., & Thomas-Ollivier, V. (2016) · Psychiatry Research · doi:10.1016/j.psychres.2016.08.034 · Cited by 27 · see citing works
Using Smartphone Survey Data and Machine Learning to Identify Situational and Contextual Risk Factors for HIV Risk Behavior Among Men Who Have Sex with Men Who Are Not on PrEP
Wray, T. B., Luo, X., Ke, J., Pérez, A. E., Carr, D. J., & Monti, P. M. (2019) · Prevention Science · doi:10.1007/s11121-019-01019-z · Cited by 28 · see citing works
Behavior change through automated e-mails: Mediation analysis of self-help strategy use for depressive symptoms
Morgan, A. J., Mackinnon, A. J., & Jorm, A. F. (2012) · Behaviour Research and Therapy · doi:10.1016/j.brat.2012.11.002 · Cited by 28 · see citing works
The Emotion Regulation Strategies of Adolescents and their Parents: An Experience Sampling Study
Silva, E., Freire, T., & Faria, S. (2018) · Journal of Child and Family Studies · doi:10.1007/s10826-018-1015-6 · Cited by 27 · see citing works
ULTEMAT: A mobile framework for smart ecological momentary assessments and interventions
van de Ven, P., O’Brien, H., Henriques, R., Klein, M., Msetfi, R., Nelson, J., Rocha, A., Ruwaard, J., O’Sullivan, D., & Riper, H. (2017) · Internet Interventions · doi:10.1016/j.invent.2017.07.001 · Cited by 26 · see citing works
Assessment of Psychological Distress in Adults With Type 2 Diabetes Mellitus Through Technologies: Literature Review
Bassi, G., Gabrielli, S., Donisi, V., Carbone, S., Forti, S., & Salcuni, S. (2020) · Journal of Medical Internet Research · doi:10.2196/17740 · Cited by 27 · see citing works
L atina Adolescent Sleep and Mood: An Ecological Momentary Assessment Pilot Study
Garcia, C. M., Zhang, L., Holt, K., Hardeman, R. R., & Peterson, B. L. (2014) · Journal of Child and Adolescent Psychiatric Nursing · doi:10.1111/jcap.12082 · Cited by 28 · see citing works
Advances in Scientific Possibilities Offered by Real-Time Monitoring Technology
Kleiman, E. M., & Nock, M. K. (2017) · Psychiatry · doi:10.1080/00332747.2017.1325661 · Cited by 26 · see citing works
A perspective on the use of ecological momentary assessment and intervention to promote stroke recovery and rehabilitation
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Authors: Wenze, S. J., & Miller, I. W.
Affiliations: Brown University (US)
Corresponding author: Wenze, Susan J.
ORCID: Wenze, Susan J.
Miller, Ivan W.
Venue: Clinical Psychology Review
Publisher: Elsevier BV
Published: 2010-08
Volume: 30
Issue: 6
Pages: 794-804
ISSN: 0272-7358 (ISSN-L)
DOI: 10.1016/j.cpr.2010.06.007
OpenAlex: W2087767034
Cited by: 205
References: 95
Citations by year: 2026: 18 · 2025: 26 · 2024: 13 · 2023: 9 · 2022: 7 · 2021: 14 · 2020: 21 · 2019: 14 · 2018: 13 · 2017: 21 · 2016: 14 · 2015: 8 · 2014: 6 · 2013: 5 · 2012: 7
FWCI: 0.84
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Clinical Psychology Review (publishedVersion)
PubMed (publishedVersion)
Topics: Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Social Sciences › Psychology › Social Psychology › Mental Health via Writing
Keywords: ecological momentary assessment, mood disorders, feasibility and acceptability, treatment research, research ethics, naturalistic data collection
MeSH terms: Humans, Research Design, Self-Assessment, Severity of Illness Index, Mood Disorders

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