The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Moving forward: how depression heterogeneity hinders progress in treatment and research
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Few would argue that depression research in the last two decades has led to major improvements of clinical care for patients. The tools and insights we have at our disposal today have not changed m...
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In the citing paper
“At the extreme, two individuals can meet criteria for a diagnosis of major depressive disorder without sharing any single symptom. 7”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [7]
In the citing paper
“Revisiting the hypothesis of Taylor and colleagues (46), one potential reason why model personalisation may provide benefits over “traditional” machine learning methods is because this allows to deal with heterogeneity, a feature that is characteristic both of depression and the way patients respond to treatment (83, 84).”
From Personalised depression forecasting using mobile sensor data and ecological momentary assessment (2022) · cites this paper as [83]
In the citing paper
“Despite its medical importance MDD is poorly defined and diagnosed since its diagnosis is mostly based on data subjectively reported by the patients themselves (13–15) and lack of objective, clinically relevant outcome measure.”
From A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms (2023) · cites this paper as [13]
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Cites
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Self-citationDepression sum-scores don’t add up: why analyzing specific depression symptoms is essential
Fried, E. I., & Nesse, R. M. (2015) · BMC Medicine · doi:10.1186/s12916-015-0325-4 · Cited by 981
Self-citationAssociation of Symptom Network Structure With the Course of Depression
van Borkulo, C. D., Boschloo, L., Borsboom, D., Penninx, B. W. J. H., Waldorp, L., & Schoevers, R. A. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.2079 · Cited by 883
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Chekroud, A. M., Zotti, R. J., Shehzad, Z., Gueorguieva, R., Johnson, M. K., Trivedi, M. H., Cannon, T. D., Krystal, J. H., & Corlett, P. R. (2016) · The Lancet Psychiatry · doi:10.1016/s2215-0366(15)00471-x · Cited by 676
The 52 symptoms of major depression: lack of content overlap among seven common depression scales
Fried, E. I. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.10.019 · Cited by 649
Critical Slowing Down as a Personalized Early Warning Signal for Depression
Wichers, M., Groot, P. C., & Psychosystems, E. G. (2016) · Psychotherapy and Psychosomatics · doi:10.1159/000441458 · Cited by 399
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- Santor DA, 2006, Measurement, 4, 135
- Chekroud AM, 2017, JAMA Psychiatry, 6511
- Le Noury J, 2015, The BMJ, 101006
- Fried EI, 2016, Soc Psychiatry Psychiatr Epidemiol, 1, 1
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Cited by
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Items 201–220 of 220
A network analysis of psychosocial risk factors and depression in adolescence
Buzinel, J., Norman, J., Hughes-Nind, J., & Carlisi, C. O. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.122080
White Matter Stratification in Depression Predicts Multidimensional Antidepressant ResponsesPreprint
Qin, J., Wang, X., Ni, H., Wu, Y., Liu, H., Hua, L., Yan, R., Tang, H., Zhao, P., Yao, Z., et al. (2025) · medRxiv · doi:10.64898/2025.12.08.25341854
O’Driscoll, C., Buckman, J. E. J., Fried, E. I., Saunders, R., Cohen, Z. D., Ambler, G., DeRubeis, R. J., Gilbody, S., Hollon, S. D., Kendrick, T., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14545012
Self-citationGathier, A. W., Verhoeven, J., van Oppen, P., Penninx, B. W. J. H., Merkx, M. J. M., Dingemanse, P., Stehouwer, K. M. K. S., van den Bulck, C. M. M., & Vinkers, C. H. (2023) · Figshare · doi:10.6084/m9.figshare.22599298
O’Shields, J., Soni, H., & Mowbray, O. P. (2025) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2025.106243
“Expanding symptom measurement to the 52 different symptoms covered by the 7 most common depressive symptom scales may be one avenue for improving diagnostic subtyping (Fried, 2017b).”
Silman, D., Middag, M. E., Cleare, A. J., Young, A. H., & Strawbridge, R. (2025) · BJPsych Open · doi:10.1192/bjo.2025.10932
“6 Standard, full-length outcome measures with conventional sum-scoring could place undue emphasis on symptoms that are less universally clinically relevant – the Hamilton Depression Rating Scale (HAM-D), 7 for example, includes symptoms not featured in modern diagnostic criteria for MDD (e.g.…”
Bellaert, N., Cassioli, F., Crowley, M. J., Lim, Y. W., Rossignol, M., Deveney, C. M., & Tseng, W. (2026) · Psychophysiology · doi:10.1111/psyp.70260
“A symptom-based approach may improve our understanding of depression (Fried 2017; Insel et al. 2010), as individual MDD symptoms are linked to distinct risk factors (Fried et al. 2014), inflammatory markers (Frank et al. 2021; Fried, Von Stockert, et al. 2020; van Eeden et al. 2020), and brain…”
White Matter Stratification in Depression Predicts Multidimensional Antidepressant ResponsesPreprint
Qin, J., Wang, X., Ni, H., Wu, Y., Liu, H., Hua, L., Yan, R., Tang, H., Zhao, P., Yao, Z., et al. (2026) · eLife · doi:10.7554/elife.110078
White Matter Stratification in Depression Predicts Multidimensional Antidepressant ResponsesPreprint
Qin, J., Wang, X., Ni, H., Wu, Y., Liu, H., Hua, L., Yan, R., Tang, H., Zhao, P., Yao, Z., et al. (2026) · eLife · doi:10.7554/elife.110078.1
Multidimensional characterization of structure aberrations for biotypes of major depressive disorder
Zhang, J., Zhang, H., Sun, H., Qin, T., Pan, J., Chen, J., Li, W., Chen, M., Cheng, B., & Wang, J. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.121876
Karnick, A. T., Brick, L. A. D., Rice, T. B., Williams, K., Robison, M., Edelman, S. M., Schatten, H. T., Joiner, T. E., & Capron, D. W. (2026) · Behaviour Research and Therapy · doi:10.1016/j.brat.2026.105052
Rethinking apathy assessment in neurological disorders: conceptual and clinical challenges
Noreña, D. D., Lago, M. R., Adrover‐Roig, D., & Cubillo, I. S. (2026) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/acag030
Heterogeneity in perinatal depression: A systematic review of network analyses
Schwabe, I., Sibbald, L., van den Heuvel, M. I., Boekhorst, M. G. B. M., & Loter, K. (2026) · Journal of Affective Disorders Reports · doi:10.1016/j.jadr.2026.101084
Hinnen, C., Mols, F., & Schoormans, D. (2026) · Psycho-Oncology · doi:10.1002/pon.70555
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“5 – 7 ) .”
Apostol, M., Valles, T. E., Corlier, J., Leuchter, M. K., Young, A. I., Artin, H., Koek, R. J., Einstein, E. H., Wilke, S. A., Oughli, H. A., et al. (2026) · medRxiv · doi:10.64898/2026.08.03.26359627
Kim, S., Bein, O., Carter, E. J., Zhang, H., Lee, J., Yu, Z., Marino, P., Sirey, J. A., Kiosses, D. N., Alexopoulos, G. S., et al. (2026) · Journal of Medical Internet Research · doi:10.2196/92348
“Self-reports are typically collected only at periodic intervals, missing the daily dynamics and even moment-to-moment fluctuations in behavioral patterns [4,5].”
A process model of stress generation in internalizing disorders
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“This aggregation may obscure neural correlates specific to individual symptoms rather than overall severity (32) and masks the substantial heterogeneity in symptom profiles and their dynamics, which can differ substantially even at equivalent levels of severity (33,34).”
Pareek, T., Hung, I., Hoadley, A., Hobelmann, J. G., Parnham, T., Rabinowitz, J. A., & Huhn, A. S. (2026) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2026.113364
Metadata
- Authors
- Fried, E.
- Affiliations
- Departmenf of Psychology, University of Amsterdam, Amsterdam, Netherlands
- Venue
- Expert Review of Neurotherapeutics
- Publisher
- Informa UK Limited
- Published
- 2017-03-22
- Volume
- 17
- Issue
- 5
- Pages
- 423-425
- ISSN
- 1473-7175 (ISSN-L)
- 1744-8360
- OpenAlex
- W2601225127
- Cited by
- 220
- References
- 23
- Citations by year
- 2026: 22 · 2025: 34 · 2024: 31 · 2023: 31 · 2022: 22 · 2021: 40 · 2020: 13 · 2019: 15 · 2018: 7 · 2017: 5
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Expert Review of Neurotherapeutics (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- European Research Council Consolidator (647209)
- Topics
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Clinical Psychology › Psychological Treatments and Disorders
- Keywords
- depression heterogeneity, depression treatment, depression research, clinical care, endophenotypes
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