Cited by 157Anxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesPsychotherapy Techniques and ApplicationsPersonality Disorders and Psychopathology

The DOI matches its Crossref record; 62 of the 63 references it cites were found in a registry or an index.

Open trial of a personalized modular treatment for mood and anxiety

Open access

Fisher, Aaron J., Bosley, Hannah G., Fernandez, Katya C., Reeves, Jonathan W., Soyster, Peter D., Diamond, Allison E., Barkin, Jonathan·2019·Behaviour Research and Therapy

DOI 10.1016/j.brat.2019.01.010

Open this paper in CoChat — free account

Abstract

Psychosocial treatments for mood and anxiety disorders are generally effective, however, a number of treated individuals fail to demonstrate clinically-significant change. Consistent with the decades-old aim to identify 'what works for whom,' personalized and precision treatments have become a recent area of interest in medicine and psychology. The present study followed the recommendations of Fisher (2015) to employ a personalized modular model of cognitive-behavioral therapy. Employing the algorithms provided by Fernandez, Fisher, and Chi (2017), the present study collected intensive repeated measures data prior to therapy in order to perform person-specific factor analysis and dynamic factor modeling. The results of these analyses were then used to generated personalized modular treatment plans on a person-by-person basis. Thirty-two participants completed therapy. The average number of sessions was 10.38. Hedges g's for the Hamilton Rating Scale for Depression (HRSD) and Hamilton Anxiety Rating Scale (HARS) were 2.33 and 1.62, respectively. The change per unit time was g = .24/session for the HRSD and g = 0.17/session for the HARS. The current open trial provides promising data in support of personalization, modularization, and idiographic research paradigms.

Integrity signals

Registry

Crossref · 10.1016/j.brat.2019.01.010

Cites

62 of 62 references verified0 citation errors · 0 not checkable

Statistics

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

Claims the paper makes

We couldn’t retrieve this paper’s full text, 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?

Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
A rating scale for depression
Hamilton, M. (1960) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.23.1.56 · Cited by 32,817
Interrater reliability: The kappa statistic
McHugh, M. L. (2012) · Biochemia Medica · doi:10.11613/bm.2012.031 · Cited by 19,877
Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication
Kessler, R. C., Chiu, W. T., Demler, O., & Walters, E. E. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.6.617 · Cited by 12,052
The assessment of anxiety states by rating
HAMILTON, M. (1959) · British Journal of Medical Psychology · doi:10.1111/j.2044-8341.1959.tb00467.x · Cited by 11,455
Clinical significance: A statistical approach to defining meaningful change in psychotherapy research.
Jacobson, N. S., & Truax, P. (1991) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.59.1.12 · Cited by 7,770
Qgraph: Network visualizations of relationships in psychometric data
Epskamp, S., Cramer, A., Waldorp, L., Schmittmann, V., & Borsboom, D. (2012) · Journal of Statistical Software · doi:10.18637/jss.v048.i04 · Cited by 4,844
The 16-item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression
Rush, A. J., Trivedi, M. H., Ibrahim, H. M., Carmody, T. J., Arnow, B., Klein, D. N., Markowitz, J. C., Ninan, P. T., Kornstein, S., Manber, R., et al. (2003) · Biological Psychiatry · doi:10.1016/s0006-3223(02)01866-8 · Cited by 3,829
A network theory of mental disorders
Borsboom, D. (2017) · World Psychiatry · doi:10.1002/wps.20375 · Cited by 3,482
Toward a cognitive social learning reconceptualization of personality
Mischel, W. (1973) · Psychological Review · doi:10.1037/h0035002 · Cited by 3,181

Show all 63 references

Research works printed but not linked: 1

American Psychiatric Association, 2013, Vol. 5

Sorted by citations

The promise of machine learning in predicting treatment outcomes in psychiatry
Chekroud, A. M., Bondar, J., Delgadillo, J., Doherty, G., Wasil, A., Fokkema, M., Cohen, Z., Belgrave, D., DeRubeis, R., Iniesta, R., et al. (2021) · World Psychiatry · doi:10.1002/wps.20882 · Cited by 531
Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation
Stade, E. C., Stirman, S. W., Ungar, L. H., Boland, C. L., Schwartz, H. A., Yaden, D. B., Sedoc, J., DeRubeis, R. J., Willer, R., & Eichstaedt, J. C. (2024) · npj Mental Health Research · doi:10.1038/s44184-024-00056-z · Cited by 391
“…protocols, LLM applications for interventions that are highly structured, behavioral, and protocolized (e.g., CBT for insomnia [CBT-I] or exposure therapy for speci ﬁ c phobia) may be available sooner than applications delivering highly ﬂ exible or personalized interventions (for example 31 ).”
Background
Personalized Models of Psychopathology
Wright, A. G. C., & Woods, W. C. (2020) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-102419-125032 · Cited by 308
Illusory generalizability of clinical prediction models
Chekroud, A. M., Hawrilenko, M., Loho, H., Bondar, J., Gueorguieva, R., Hasan, A., Kambeitz, J., Corlett, P. R., Koutsouleris, N., Krumholz, H. M., et al. (2024) · Science · doi:10.1126/science.adg8538 · Cited by 251
Beyond linear mediation: Toward a dynamic network approach to study treatment processes
Hofmann, S. G., Curtiss, J. E., & Hayes, S. C. (2020) · Clinical Psychology Review · doi:10.1016/j.cpr.2020.101824 · Cited by 232
“72 the authors found after analyzing 31 clinical trials for depression (Fisher et al., 2019).”
Background
Improving mental health services: a 50-year journey from randomized experiments to artificial intelligence and precision mental health
Bickman, L. (2020) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-020-01065-8 · Cited by 184
Time to get personal? The impact of researchers’ choices on the selection of treatment targets using the experience sampling methodology
Bastiaansen, J. A., Kunkels, Y. K., Blaauw, F., Boker, S. M., Ceulemans, E., Chen, M., Chow, S.-M., de Jonge, P., Emerencia, A. C., Epskamp, S., et al. (2019) · doi:10.31234/osf.io/c8vp7 · Cited by 158
Self-citation
Examining the Concurrent and Predictive Validity of Single Items in Ecological Momentary Assessments
Song, J., Howe, E. S., Oltmanns, J. R., & Fisher, A. J. (2022) · Assessment · doi:10.1177/10731911221113563 · Cited by 173
Self-citation
CBT at the crossroads: the rise of transdiagnostic treatments.
Schaeuffele, C., Schulz, A., Knaevelsrud, C., Renneberg, B., & Boettcher, J. (2021) · International Journal of Cognitive Therapy · doi:10.1007/s41811-020-00095-2 · Cited by 150
Passive Sensing of Prediction of Moment-To-Moment Depressed Mood among Undergraduates with Clinical Levels of Depression Sample Using Smartphones
Jacobson, N. C., & Chung, Y. J. (2020) · Sensors · doi:10.3390/s20123572 · Cited by 139
Investigating the feasibility of idiographic network models.
Mansueto, A. C., Wiers, R. W., van Weert, J. C. M., Schouten, B. C., & Epskamp, S. (2023) · Psychological Methods · doi:10.1037/met0000466 · Cited by 147
The Differential Role of Central and Bridge Symptoms in Deactivating Psychopathological Networks
Castro, D., Ferreira, F., Castro, I., Rodrigues, A. R., Correia, M., Ribeiro, J., & Ferreira, T. B. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02448 · Cited by 150
Efficacy of Personalized Psychological Interventions: A Systematic Review and Meta-Analysis
Nye, A., Delgadillo, J., & Barkham, M. (2023) · Journal of Consulting and Clinical Psychology · doi:10.1037/ccp0000820 · Cited by 142
Measurement-Based and Data-Informed Psychological Therapy
Lutz, W., Schwartz, B., & Delgadillo, J. (2021) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-071720-014821 · Cited by 146
Implementing precision methods in personalizing psychological therapies: Barriers and possible ways forward
Deisenhofer, A., Barkham, M., Beierl, E. T., Schwartz, B., Doorn, K. A., Beevers, C. G., Berwian, I. M., Blackwell, S. E., Bockting, C., Brakemeier, E., et al. (2023) · Behaviour Research and Therapy · doi:10.1016/j.brat.2023.104443 · Cited by 123
Self-citation
Toward a Unified Framework for Positive Psychology Interventions: Evidence-Based Processes of Change in Coaching, Prevention, and Training
Ciarrochi, J., Hayes, S. C., Oades, L. G., & Hofmann, S. G. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.809362 · Cited by 104
Feasibility and utility of idiographic models in the clinic: A pilot study
Frumkin, M. R., Piccirillo, M. L., Beck, E. D., Grossman, J. T., & Rodebaugh, T. L. (2020) · Psychotherapy Research · doi:10.1080/10503307.2020.1805133 · Cited by 100
A process-based approach to cognitive behavioral therapy: A theory-based case illustration
Ong, C. W., Hayes, S. C., & Hofmann, S. G. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1002849 · Cited by 91
Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data
Lorenzo‐Luaces, L., Peipert, A., Jesús-Romero, R. D., Rutter, L. A., & Rodríguez‐Quintana, N. (2020) · International Journal of Cognitive Therapy · doi:10.1007/s41811-020-00094-3 · Cited by 62
A Web-Based Application for Personalized Ecological Momentary Assessment in Psychiatric Care: User-Centered Development of the PETRA Application
Bos, F. M., von Klipstein, L., Emerencia, A. C., Veermans, E., Verhage, T., Snippe, E., Doornbos, B., Hadders-Prins, G., Wichers, M., & Riese, H. (2022) · JMIR Mental Health · doi:10.2196/36430 · Cited by 70
Specifying the mechanisms and targets of emotion regulation: A translational framework from affective science to psychological treatment.
Southward, M. W., Sauer-Zavala, S. E., & Cheavens, J. S. (2021) · Clinical Psychology Science and Practice · doi:10.1037/cps0000003 · Cited by 69
Measuring the active elements of cognitive-behavioral therapies
Cohen, Z. D., Barnes-Horowitz, N. M., Forbes, C. N., & Craske, M. G. (2023) · Behaviour Research and Therapy · doi:10.1016/j.brat.2023.104364 · Cited by 58
Is it worth it to personalize the treatment of PTSD? – A variance-ratio meta-analysis and estimation of treatment effect heterogeneity in RCTs of PTSD
Herzog, P., & Kaiser, T. (2022) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2022.102611 · Cited by 64
Single-subject research in psychiatry: facts and fictions
Zuidersma, M., Riese, H., Snippe, E., Booij, S. H., Wichers, M., & Bos, E. H. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.539777 · Cited by 54
Affect Dynamics as Predictors of Symptom Severity and Treatment Response in Mood and Anxiety Disorders: Evidence for Specificity
Bosley, H. G., Soyster, P. D., & Fisher, A. J. (2019) · Journal for Person-Oriented Research · doi:10.17505/jpor.2019.09 · Cited by 50
Self-citation
Core eating disorder fears: Prevalence and differences in eating disorder fears across eating disorder diagnoses
Brown, M. L., & Levinson, C. A. (2022) · International Journal of Eating Disorders · doi:10.1002/eat.23728 · Cited by 47
Embracing the Complexity of our Inner Worlds: Understanding the Dynamics of Self-Compassion and Self-Criticism
Ferrari, M., Ciarrochi, J., Yap, K., Sahdra, B. K., & Hayes, S. C. (2022) · Mindfulness · doi:10.1007/s12671-022-01897-5 · Cited by 55
Personalized models of psychopathology as contextualized dynamic processes: An example from individuals with borderline personality disorder.
Woods, W. C., Arizmendi, C., Gates, K. M., Stepp, S. D., Pilkonis, P. A., & Wright, A. G. C. (2020) · Journal of Consulting and Clinical Psychology · doi:10.1037/ccp0000472 · Cited by 48
Perceived Causal Problem Networks: Reliability, Central Problems, and Clinical Utility for Depression
Klintwall, L., Bellander, M., & Cervin, M. (2021) · Assessment · doi:10.1177/10731911211039281 · Cited by 57
Process-based therapy: A personalized approach to treatment
Moskow, D. M., Ong, C. W., Hayes, S. C., & Hofmann, S. G. (2023) · Journal of Experimental Psychopathology · doi:10.1177/20438087231152848 · Cited by 45
Insights from Personalized Models of Brain and Behavior for Identifying Biomarkers in PsychiatryPreprint
Kraus, B. T., Zinbarg, R. E., Braga, R. M., Nusslock, R., Mittal, V. A., & Gratton, C. (2023) · PsyArXiv (OSF Preprints) · doi:10.1016/j.neubiorev.2023.105259 · Cited by 48
Identifying the presence and timing of discrete mood states prior to therapy
Fisher, A. J., & Bosley, H. G. (2020) · Behaviour Research and Therapy · doi:10.1016/j.brat.2020.103596 · Cited by 44
Self-citation
Integrating theory-based and data-driven methods to case conceptualization: A functional analysis approach with ecological momentary assessment
Scholten, S., Lischetzke, T., & Glombiewski, J. A. (2021) · Psychotherapy Research · doi:10.1080/10503307.2021.1916639 · Cited by 50
A Personalised Approach to Identifying Important Determinants of Well-being
Ciarrochi, J., Sahdra, B. K., Hayes, S. C., Hofmann, S. G., Sanford, B., Stanton, C. E., Yap, K., Fraser, M. I., Gates, K. M., & Gloster, A. T. (2024) · Cognitive Therapy and Research · doi:10.1007/s10608-024-10486-w · Cited by 45
Process-based functional analysis can help behavioral science step up to novel challenges: COVID - 19 as an example
Hayes, S. C., Hofmann, S. G., & Stanton, C. E. (2020) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2020.08.009 · Cited by 39
Using ambulatory assessment to measure dynamic risk processes in affective disorders
Stange, J. P., Kleiman, E. M., Mermelstein, R. J., & Trull, T. J. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.08.060 · Cited by 42
An Examination of Idiographic Networks of Posttraumatic Stress Disorder Symptoms
Reeves, J. W., & Fisher, A. J. (2020) · Journal of Traumatic Stress · doi:10.1002/jts.22491 · Cited by 44
Self-citation
Examining the associations between PTSD symptoms and aspects of emotion dysregulation through network analysis
Haws, J. K., Brockdorf, A. N., Gratz, K. L., Messman, T. L., Tull, M. T., & DiLillo, D. (2022) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2022.102536 · Cited by 38
Innovative Psychotherapieforschung: auf dem Weg zu einer evidenz- und prozessbasierten individualisierten und modularen Psychotherapie
Brakemeier, E., & Herpertz, S. C. (2019) · Der Nervenarzt · doi:10.1007/s00115-019-00808-9 · Cited by 36
The unified protocol as an internet-based intervention for emotional disorders: Randomized controlled trial
Schaeuffele, C., Homeyer, S. L., Perea, L., Scharf, L., Schulz, A., Knaevelsrud, C., Renneberg, B., & Boettcher, J. (2022) · PLoS ONE · doi:10.1371/journal.pone.0270178 · Cited by 39
Machine learning to predict sports-related concussion recovery using clinical data
Chu, Y., Knell, G., Brayton, R. P., Burkhart, S. O., Jiang, X., & Shams, S. (2022) · Annals of Physical and Rehabilitation Medicine · doi:10.1016/j.rehab.2021.101626 · Cited by 39
Evidence for the Feasibility of Person-Specific Ecological Momentary Assessment Across Diverse Populations and Study Designs
Soyster, P. D., Bosley, H. G., Reeves, J. W., Altman, A. D., & Fisher, A. J. (2019) · Journal for Person-Oriented Research · doi:10.17505/jpor.2019.06 · Cited by 33
Self-citation
Idiographic network analysis of discrete mood states prior to treatment
Howe, E. S., Bosley, H. G., & Fisher, A. J. (2020) · Counselling and Psychotherapy Research · doi:10.1002/capr.12295 · Cited by 35
Self-citation
A SMART approach to personalized care: preliminary data on how to select and sequence skills in transdiagnostic CBT
Sauer-Zavala, S. E., Southward, M. W., Stumpp, N. E., Semcho, S., Hood, C. O., Garlock, A., & Urs, A. (2022) · Cognitive Behaviour Therapy · doi:10.1080/16506073.2022.2053571 · Cited by 35
Evidence-Based Strategies for Treatment Personalization: A Review
Stumpp, N. E., & Sauer-Zavala, S. (2022) · Cognitive and Behavioral Practice · doi:10.1016/j.cbpra.2021.10.004 · Cited by 29
Innovations to improve outcomes and uptake of psychotherapies for mental disorders: a state‐of‐the‐art review
Cuijpers, P. J., Harrer, M., & Furukawa, T. A. (2026) · World Psychiatry · doi:10.1002/wps.70002 · Cited by 31
Transdiagnostic Processes as Mediators of Change in an Internet-Delivered Intervention Based on the Unified Protocol
Schaeuffele, C., Bär, J., Buengener, I., Grafiadeli, R., Heuthaler, E., Strieder, J., Ziehn, P., Knaevelsrud, C., Renneberg, B., & Boettcher, J. (2022) · Cognitive Therapy and Research · doi:10.1007/s10608-021-10272-y · Cited by 24
Precision medicine in alcohol use disorder: Mapping etiologic and maintenance mechanisms to mechanisms of behavior change to improve patient outcomes.
Boness, C. L., & Witkiewitz, K. A. (2022) · Experimental and Clinical Psychopharmacology · doi:10.1037/pha0000613 · Cited by 29
An Answer to “So What?” Implications of Network Theory for Research and Practice
Jones, P. J., & Robinaugh, D. J. (2021) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.20200050 · Cited by 27
A Review of Explicit and Implicit Assumptions When Providing Personalized Feedback Based on Self-Report EMA Data
Leertouwer, I., Cramer, A. O. J., Vermunt, J. K., & Schuurman, N. K. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.764526 · Cited by 27
Online Acceptance and Commitment Therapy for People with Painful Diabetic Neuropathy in the United Kingdom: A Single-Arm Feasibility Trial
Kioskli, K., Scott, W., Winkley, K., Godfrey, E., & McCracken, L. M. (2020) · Pain Medicine · doi:10.1093/pm/pnaa110 · Cited by 24
Ecological Momentary Assessment in psychotherapy research: A systematic review
Mink, F., Lutz, W., & Hehlmann, M. I. (2025) · Clinical Psychology Review · doi:10.1016/j.cpr.2025.102565 · Cited by 34
Generating Accurate Personalized Predictions of Future Behavior: A Smoking ExemplarPreprint
Fisher, A. J., & Soyster, P. D. (2019) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/e24v6 · Cited by 21
Self-citation
Temporal dynamics of depression, cognitive performance and sleep in older persons with depressive symptoms and cognitive impairments: a series of eight single-subject studies
Zuidersma, M., Lugtenburg, A., van Zelst, W., Reesink, F. E., Deyn, P. P. D., Strijkert, F., Zuidema, S. U., & Voshaar, R. C. O. (2021) · International Psychogeriatrics · doi:10.1017/s1041610221000065 · Cited by 18
An Initial Study of Practicing Psychologists’ Views of the Utility of Ecological Momentary Assessment for Difficult Psychotherapy Cases
Ellison, W. D. (2020) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-020-01093-4 · Cited by 23
Heterogeneity in affective complexity among men and women.
Foster, K. T., & Beltz, A. M. (2021) · Emotion · doi:10.1037/emo0000956 · Cited by 20
Subjectifying the Personality State: Theoretical Underpinnings and an Empirical Example
Lazarus, G., Sened, H., & Rafaeli, E. (2020) · European Journal of Personality · doi:10.1002/per.2278 · Cited by 23
Negative Emotion Differentiation Predicts Psychotherapy Outcome: Preliminary Findings
Lazarus, G., & Fisher, A. J. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.689407 · Cited by 21
Self-citation
Imagery Rescripting Versus Extinction: Distinct and Combined Effects on Expectancy and Revaluation Learning
Woelk, M., Krans, J., Raes, F., Vervliet, B., & Hagenaars, M. A. (2021) · Clinical Psychological Science · doi:10.1177/21677026211055169 · Cited by 15
Precision Mental Health and Data-Informed Decision Support in Psychological Therapy: An Example
Lutz, W., Schaffrath, J., Eberhardt, S. T., Hehlmann, M. I., Schwartz, B., Deisenhofer, A., Vehlen, A., Schürmann, S., Uhl, J., & Moggia, D. (2023) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-023-01330-6 · Cited by 24
Defining and operationalizing personalized psychological treatment – a systematic literature review
Harnas, S. J., Knoop, H., Sprangers, M. A. G., & Braamse, A. M. J. (2024) · Cognitive Behaviour Therapy · doi:10.1080/16506073.2024.2333345 · Cited by 20
Why Does Therapy Work? An Idiographic Approach to Explore Mechanisms of Change Over the Course of Psychotherapy Using Digital Assessments
Altman, A. D., Shapiro, L. A., & Fisher, A. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00782 · Cited by 14
Self-citation
The future of the eating disorder field: Inclusive, aware of systems, and personalized
Levinson, C. A., Cusack, C. E., Hunt, R. A., Fitterman-Harris, H. F., Ralph‐Nearman, C., & Hooper, S. C. (2024) · Behaviour Research and Therapy · doi:10.1016/j.brat.2024.104648 · Cited by 15
Personalized networks of eating disorder symptoms predicting eating disorder outcomes and remission
Levinson, C. A., Cash, E. D., Welch, K. C., Epskamp, S., Hunt, R. A., Williams, B. M., Keshishian, A. C., & Spoor, S. P. (2020) · International Journal of Eating Disorders · doi:10.1002/eat.23398 · Cited by 15
Examining the Concurrent and Predictive Validity of Single Items in Ecological Momentary AssessmentsPreprint
Song, J., Howe, E. S., Oltmanns, J. R., & Fisher, A. J. (2022) · doi:10.31234/osf.io/p2fqu · Cited by 15
Self-citation
Person-specific dynamics between negative emotions and suicidal thoughts
Kuehn, K. S., Piccirillo, M. L., Kuczynski, A. M., King, K. M., Depp, C. A., & Foster, K. T. (2024) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2024.152495 · Cited by 15
Improving the Science of Adolescent Social Media and Mental Health: Challenges and Opportunities of Smartphone-Based Mobile Sensing and Digital Phenotyping
Hamilton, J. L., Dreier, M. J., Caproni, B., Fedor, J., Durica, K. C., & Low, C. A. (2024) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-024-00443-5 · Cited by 19
Using the experience sampling methodology to measure anhedonia and its correlates in mental health research: A systematic review
Beames, J. R., Uyttebroek, L., Edwards, C., Eisele, G. V., Kemme, N. D. F., Collier, O., van Roekel, E., Kwapil, T. R., Kirtley, O. J., & Myin‐Germeys, I. (2025) · Clinical Psychology Review · doi:10.1016/j.cpr.2025.102590 · Cited by 15
A Close Look at the Role of Time in Affect Dynamics Research
Lazarus, G., Song, J., Crawford, C. M., & Fisher, A. J. (2021) · Springer eBooks · doi:10.1007/978-3-030-82965-0_5 · Cited by 15
Self-citation
Self-Efficacy Effects on Symptom Experiences in Daily Life and Early Treatment Success in Anxiety Patients
Paersch, C., Recher, D., Schulz, A., Henninger, M., Schlup, B., Künzler, F., Homan, S., Kowatsch, T., Fisher, A. J., Horn, A. B., et al. (2024) · Clinical Psychological Science · doi:10.1177/21677026231205262 · Cited by 14
Self-citation
Personalised app-based relapse prevention of depressive and anxiety disorders in remitted adolescents and young adults: a protocol of the StayFine RCT
Robberegt, S. J., Kooiman, B., Albers, C. J., Nauta, M. H., Bockting, C., & Stikkelbroek, Y. A. J. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-058560 · Cited by 13
Accurate Machine Learning Prediction in Psychiatry Needs the Right Kind of Information
Kraus, B. T., Sampathgiri, K., & Mittal, V. A. (2023) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2023.4302 · Cited by 12
Personality psychology is getting personal: Advancing the field through personalization
Modersitzki, N., Phan, L. V., McDonald, S., Wright, A. G. C., & Renner, K. (2025) · European Journal of Personality · doi:10.1177/08902070251316915 · Cited by 13
Idiographic bidirectional associations of stressfulness of events and negative affect in daily life as indicators for mental health: An experience sampling study
Kraiss, J. T., Vaessen, T., & ten Klooster, P. M. (2024) · Stress and Health · doi:10.1002/smi.3433 · Cited by 11
Network analyses of ecological momentary emotion and avoidance assessments before and after cognitive behavioral therapy for anxiety disorders
Meine, L. E., Müller-Bardorff, M., Recher, D., Paersch, C., Schulz, A., Spiller, T. R., Galatzer‐Levy, I. R., Kowatsch, T., Fisher, A. J., & Kleim, B. (2024) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2024.102914 · Cited by 14
Self-citation
Praxisorientierte Forschung in der Psychotherapie
Herzog, P., Kaiser, T., & Brakemeier, E. (2022) · Zeitschrift für Klinische Psychologie und Psychotherapie · doi:10.1026/1616-3443/a000665 · Cited by 10
Technology-Based Ecological Momentary Assessment in Clinical Psychology
Colombo, D., Suso‐Ribera, C., Fernández‐Álvarez, J., Cipresso, P., García‐Palacios, A., Riva, G., & Botella, C. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818697-8.00003-0 · Cited by 9
Clinician Opinions: Perceived Utility of and Barriers to Incorporating Pretreatment Ecological Momentary Assessment Into Clinical Care
Soyster, P. D., Song, F., & Fisher, A. J. (2022) · Behavior Therapy · doi:10.1016/j.beth.2022.08.005 · Cited by 11
Self-citation
Separation Anxiety Symptom Profiles and Parental Accommodation Across Pediatric Anxiety Disorders
Phillips, K. E., Norris, L. A., & Kendall, P. C. (2020) · Child Psychiatry & Human Development · doi:10.1007/s10578-019-00949-7 · Cited by 8
Artificial Intelligence in Clinical Psychology
Tuena, C., Chiappini, M., Repetto, C., & Riva, G. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818697-8.00001-7 · Cited by 9
The next generation of developmental psychopathology research: Including broader perspectives and becoming more precise
Valentino, K., & Edler, K. (2024) · Development and Psychopathology · doi:10.1017/s0954579424000142 · Cited by 10
Machine learning models for temporally precise lapse prediction in alcohol use disorder.
Wyant, K., Sant'Ana, S. J. K., Fronk, G. E., & Curtin, J. J. (2024) · Journal of Psychopathology and Clinical Science · doi:10.1037/abn0000901 · Cited by 8
Cognitive behavioral therapies are evidence-based – based on what? A systematic review and meta-analysis of recent randomized controlled trials of cognitive behavioral therapies for depression
O’Toole, M. S., Ramsdal, N. B., Nørskov, C. S., Roepstorff, I. G., Buskbjerg, C. R., Mads, B., Christiansen, & Elkjær, E. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119791 · Cited by 7
Are central eating disorder network symptoms sensitive to item selection and sample? Implications for conceptualization of eating disorder psychopathology from a network perspective.
Cusack, C. E., Vanzhula, I. A., Sandoval-Araujo, L. E., Pennesi, J., Kelley, S. W., & Levinson, C. A. (2023) · Journal of Psychopathology and Clinical Science · doi:10.1037/abn0000865 · Cited by 9
Technological Interventions for Emotion Regulation
Fernández‐Álvarez, J., Díaz‐García, A., Colombo, D., Botella, C., Cipresso, P., & Riva, G. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818697-8.00033-9 · Cited by 8
A randomised controlled feasibility trial (the HARMONIC Trial) of a novel modular transdiagnostic intervention—Shaping Healthy Minds—versus psychological treatment-as-usual, for clinic-attending adults with comorbid mood, stressor-related and anxiety disordersPreprint
Black, M., Johnston, D. E., Elliott, R., O'Leary, C., Patel, S., Smith, A., Parker, J., Griffiths, K., Klaus, K., Clarke, J., et al. (2023) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/7muz5 · Cited by 7
Generalized Anxiety Disorder
Llera, S. J., Shin, K. E., Erickson, T. M., Przeworski, A., & Newman, M. G. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-818697-8.00213-2 · Cited by 6
Sleep Quality Moderates the Relationship Between Daily Mean Levels and Variability of Positive Affect
Song, J., Crawford, C. M., & Fisher, A. J. (2023) · Affective Science · doi:10.1007/s42761-022-00177-8 · Cited by 6
Self-citation
Emotion differentiation among individuals in a randomized clinical trial for alcohol use disorder: Within- and between-person associations with affect, craving, and alcohol use in daily life
Knapp, K. S., Bradizza, C. M., Zhao, J., Linn, B. K., Wilding, G. E., LaBarre, C., & Stasiewicz, P. R. (2024) · Behaviour Research and Therapy · doi:10.1016/j.brat.2024.104474 · Cited by 8
Beyond one-size-fits-all suicide prediction: Studying idiographic associations of risk factors for suicide in a psychiatric sample using ecological momentary assessment
Kraiss, J. T., Glaesmer, H., Forkmann, T., Spangenberg, L., Hallensleben, N., Schreiber, D., & Höller, I. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.07.050 · Cited by 7
An Idiographic Network Approach to Posttraumatic Stress Disorder: Symptom Heterogeneity and Implications for Treatment
Bridges‐Curry, Z. (2025) · Cognitive Therapy and Research · doi:10.1007/s10608-025-10575-4 · Cited by 7
Using Personalized Assessment and Network Model Feedback in Psychotherapy: Proof of Principle for the TheraNet ProjectPreprint
Hall, M., Wagner, A. A., Scherner, P. V., Michael, K. L., Lawyer, G., Lutz, W., & Rubel, J. A. (2022) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/8deyj · Cited by 8
Delineating Discrete Generalizable States from Intraindividual Time Series: Towards a Science of MomentsPreprint
Lazarus, G., Song, J., Jeronimus, B. F., & Fisher, A. J. (2023) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/4nxqh · Cited by 5
Self-citation
The Unified Protocol as an Internet-based Intervention for Emotional Disorders: Randomized Controlled Trial
Schaeuffele, C., Homeyer, S. L., Perea, L., Scharf, L., Schulz, A., Knaevelsrud, C., Renneberg, B., & Boettcher, J. (2020) · doi:10.31234/osf.io/528tw · Cited by 9
Increasing Completion of Daily Patient-Reported Outcomes in Psychotherapies for Late-Life Depression through User-Centered Design
Carter, E., Benda, N. C., Kim, S., Qiu, Y., Yu, Z., Gunning, F. M., Kiosses, D. N., Sirey, J. A., Alexopoulos, G. S., & Banerjee, S. (2024) · Applied Clinical Informatics · doi:10.1055/s-0044-1790545 · Cited by 6
Relations among coping style, and depression and anxiety symptoms in medical graduate students: a transdiagnostic network analysis
Guo, Z., Zhang, Y., Pi, P., Zhu, X., Cui, Y., Miao, D., & Lü, H. (2024) · Current Psychology · doi:10.1007/s12144-024-05912-x · Cited by 5
Exploring Opportunities to Augment Psychotherapy with Language Models
Yang, Y., Viranda, T., Meter, A. V., Choudhury, T., & Adler, D. A. (2024) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3613905.3650990 · Cited by 5
Identifying Person-Specific Drivers of Depression in Adolescents: Protocol for a Smartphone-Based Ecological Momentary Assessment and Passive Sensing Study
Ng, M. Y., Frederick, J., Fisher, A. J., Allen, N. B., Pettit, J. W., & McMakin, D. L. (2024) · JMIR Research Protocols · doi:10.2196/43931 · Cited by 8
Self-citation
Temporal Directionality Between Symptoms During Treatment of Depressed Inpatients: A Dynamic Time Warp Network Analysis
Cocx‐Swiebel, D. A., van Son, G. E., Scheper, A., Stuivenga, M., Sabbe, B., Hebbrecht, K., & Giltay, E. J. (2024) · Clinical Psychology & Psychotherapy · doi:10.1002/cpp.3062 · Cited by 5
Data-Informed Advances and Technology Augmentation
Lutz, W. (2022) · Cognitive and Behavioral Practice · doi:10.1016/j.cbpra.2022.02.008 · Cited by 5

Authors: Fisher, A. J., Bosley, H. G., Fernandez, K. C., Reeves, J. W., Soyster, P. D., Diamond, A. E., & Barkin, J.
Affiliations: University of California, Berkeley (US)
Center for Creative Leadership (US)
Corresponding author: Fisher, Aaron J.
ORCID: Fisher, Aaron J.
Bosley, Hannah G.
Reeves, Jonathan W.
Soyster, Peter D.
Venue: Behaviour Research and Therapy
Publisher: Elsevier BV
Published: 2019-05
Volume: 116
Pages: 69-79
ISSN: 0005-7967 (ISSN-L)
DOI: 10.1016/j.brat.2019.01.010
OpenAlex: W2915885068
Cited by: 156
References: 63
Citations by year: 2026: 12 · 2025: 16 · 2024: 30 · 2023: 17 · 2022: 22 · 2021: 23 · 2020: 27 · 2019: 9
FWCI: 23.78
Type: journal article
Language: en
Open access: green
doi.org
Licence: public-domain
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Behaviour Research and Therapy (publishedVersion)
PubMed (publishedVersion)
PsyArXiv (OSF Preprints) (submittedVersion, public-domain)
PsyArXiv (OSF Preprints) (submittedVersion)
OSF Preprints (OSF Preprints) (submittedVersion)
Topics: Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
Social Sciences › Psychology › Clinical Psychology › Personality Disorders and Psychopathology
Keywords: personalized treatment, mood disorders, anxiety disorders, depression, anxiety, treatment response prediction, idiographic research
MeSH terms: Adolescent, Adult, Algorithms, Anxiety Disorders, Major Depressive Disorder, Female, Humans, Male, Middle Aged, Cognitive Behavioral Therapy, Young Adult, Precision Medicine

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

Open trial of a personalized modular treatment for mood and anxiety

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks