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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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“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]
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“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
Hamilton, M. (1960) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.23.1.56 · Cited by 32,817
A network theory of mental disorders
Borsboom, D. (2017) · World Psychiatry · doi:10.1002/wps.20375 · Cited by 3,482
Kirsch, I., Deacon, B. J., Huedo-Medina, T. B., Scoboria, A., Moore, T. J., & Johnson, B. T. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050045 · Cited by 2,442
Fried, E. I., & Nesse, R. M. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2014.10.010 · Cited by 1,043
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
Sparse whole-genome sequencing identifies two loci for major depressive disorder
CONVERGE consortium, Cai, N., Bigdeli, T. B., Kretzschmar, W., Li, Y., Liang, J., Song, L., Hu, J., Li, Q., Jin, W., et al. (2015) · Nature · doi:10.1038/nature14659 · Cited by 864
Cross-trial prediction of treatment outcome in depression: a machine learning approach
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
Research works printed but not linked: 6
- 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
- Chekroud AM, 2016, The Lancet Psychiatry, 366, 1
- National Institute of Mental Health, Breaking ground, breaking through: the strategic plan for mood disorders research (NIH Publication No. 03–5121)
Cited by
Sorted by citations
Items 101–200 of 220
Alsalloum, G. A., Dalibalta, S., & Hadijat, Y. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1654745 · Cited by 10
Shehu, A., Anyip, B., & Magaji, M. G. (2020) · Tropical Journal of Pharmaceutical Research · doi:10.4314/tjpr.v19i7.18 · Cited by 9
“Heterogeneity in depression hinders progress in treatment and research [4].”
BackgroundProlonged grief disorder symptomology in three African countries: A network analysis and comparison
Robinson, M., Armour, C., & Levin, Y. (2024) · Cambridge Prisms Global Mental Health · doi:10.1017/gmh.2024.54 · Cited by 13
“This is complemented by conceptual advances towards analysing individual symptoms and their interrelations rather than relying solely on aggregate scores or diagnostic checklists (Fried, 2017).”
BackgroundWatts, A. L., Boness, C. L., Loeffelman, J. E., Steinley, D., & Sher, K. J. (2020) · doi:10.31234/osf.io/paxd4 · Cited by 9
Panier, L. Y. X., Park, J., Kreitewolf, J., & Weinberg, A. (2024) · Biological Psychology · doi:10.1016/j.biopsycho.2024.108897 · Cited by 8
“That is, because depression is etiologically heterogeneous (Fried, 2017; Goldberg, 2011; Klein & Hajcak, 2015), the RewP may not show strong associations with symptoms of depression at any given time, but may rather reflect a trait-like vulnerability to some types of depression under certain…”
Winters, D. E., Pruitt, P. J., Gambin, M., Fukui, S., Cyders, M. A., Pierce, B. J., Lay, K., & Damoiseaux, J. S. (2021) · Child Psychiatry & Human Development · doi:10.1007/s10578-021-01242-2 · Cited by 8
Chiba, S., Numakawa, T., Murata, T., Kawaminami, M., & Himi, T. (2022) · Journal of Veterinary Medical Science · doi:10.1292/jvms.22-0103 · Cited by 8
“Although anhedonia, recognized in social and physical phenotypes, is one of the core symptoms of MDD, this symptom is difficult to treat using selective serotonin reuptake inhibitors, the first-line treatment for MDD [51].”
MethodInfluentialThe association between parental internalizing disorders and child school performance
Nordmo, M., Kleppestø, T. H., Sunde, H. F., Flatø, M., Demange, P., & Torvik, F. A. (2023) · npj Science of Learning · doi:10.1038/s41539-023-00182-x · Cited by 8
“Our fi ndings should be evaluated in light of the heterogeneity found in both anxiety and depression diagnoses 23,24 .”
A complex systems model of temporal fluctuations in depressive symptomatologyPreprint
Jamalabadi, H., Hofmann, S. G., Teutenberg, L., Emden, D., Goltermann, J., Enneking, V., Meinert, S., Koch, K., Leehr, E. J., Stein, F., et al. (2022) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/fm76b · Cited by 10
Trajectories and Influences of Depression in Adolescents: A Latent Profile Transition Analysis Study
Dai, Y., Lin, S., Zhang, S., Wu, Z., Zhang, J., Li, Q., & Xiao, J. (2025) · Stress and Health · doi:10.1002/smi.3528 · Cited by 9
Saavedra, J. U., Deaso, E. A., Austin, M., Cadavid, L., Kraff, R., & Knowles, E. E. M. (2025) · JMIR Formative Research · doi:10.2196/66187 · Cited by 7
“These findings underscore EMA’s ability to capture dynamic mood changes [9,22-24 , 65 ] Activity data revealed that MDD cases spent less time asleep and in bed but took more naps than controls, suggesting that their sleep was more fragmented and variable than in controls.”
Rabinowitz, J. A., Ellis, J. D., Strickland, J. C., Hochheimer, M., Zhou, Y., Young, A. S., Curtis, B. L., & Huhn, A. S. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.05.029 · Cited by 7
Lee, J., Solomonov, N., Banerjee, S., Alexopoulos, G. S., & Sirey, J. A. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.732773 · Cited by 9
Gathier, A. W., Verhoeven, J. E., 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) · BMC Psychiatry · doi:10.1186/s12888-023-04518-0 · Cited by 6
Lunansky, G., Hoekstra, R. H. A., & Blanken, T. F. (2023) · Collabra Psychology · doi:10.1525/collabra.74841 · Cited by 6
Correlation between polygenic risk scores of depression and cortical morphology networks
Gong, Q., Wang, W., Nie, Z., Ma, S., Zhou, E., Deng, Z., Xie, X., Lyu, H., Chen, M., Kang, L., et al. (2025) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.240140 · Cited by 6
Depressive symptom heterogeneity among older adults after hip fracture
Kirk, J. M., Magaziner, J. S., Shardell, M. D., Ryan, A. S., Gruber‐Baldini, A. L., Orwig, D., Hochberg, M. C., & Rathbun, A. M. (2021) · Age and Ageing · doi:10.1093/ageing/afab168 · Cited by 6
Investigation of Psychoactive Medications: Challenges and a Practical and Scalable New Path
Taliaz, D., & Serretti, A. (2022) · CNS & Neurological Disorders - Drug Targets · doi:10.2174/1871527321666220628103843 · Cited by 6
Tang, X., Wong, D. F. K., Xu, H., & Hou, L. (2021) · Health & Social Care in the Community · doi:10.1111/hsc.13660 · Cited by 6
Nakamura, A., Yomogida, Y., Ota, M., Matsuo, J., Ishida, I., Hidese, S., & Kunugi, H. (2021) · Journal of Affective Disorders Reports · doi:10.1016/j.jadr.2021.100295 · Cited by 6
Ebrahimi, O. V., Borsboom, D., Hoekstra, R. H. A., Epskamp, S., Ostinelli, E. G., Bastiaansen, J. A., & Cipriani, A. (2023) · doi:10.31234/osf.io/wh6cf · Cited by 6
Bayer, J., van Velzen, L. S., Pozzi, E., Davey, C. G., Han, L. K. M., Bauduin, S., Bauer, J., Benedetti, F., Berger, K., Bonnekoh, L. M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.17.643677 · Cited by 5
A depression detection approach leveraging transfer learning with single-channel EEG
Sun, C., Guan, M., Duan, K., Gao, S., & Chen, Z. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/adcfc8 · Cited by 5
“In addition, MDD is a highly heterogeneous disorder and the EEG from the depressed may be diversified due to differences in individual, study designs, equipment settings (EEG amplifier, etc), and EEG acquisition settings (reference electrode, sampling rate, etc) [18, 19].”
Symptom networks in major depressive disorder and treatment response: special focus on TRD
Kautzky, A., Bartova, L., Dold, M., Souery, D., Montgomery, S., Zohar, J., Mendlewicz, J., Fabbri, C., Serretti, A., Tretiakov, E. O., et al. (2025) · European Psychiatry · doi:10.1192/j.eurpsy.2025.2454 · Cited by 6
“Targeting depression on the symptom level and finding patterns of co-expression has gained interest in recent years [16].”
Heterogenous Subtypes of Late-Life Depression and Their Cognitive Patterns: A Latent Class Analysis
Wang, L., Zhang, T., Dang, W., Liu, S., Fan, Z., Tu, L., Zhang, M., Wang, H., Zhang, N., Ma, Q., et al. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.917111 · Cited by 5
Patra, S. (2017) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2017.11.039 · Cited by 5
Talwar, A., Huys, Q. J. M., Cormack, F. K., & Roiser, J. P. (2024) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-024-01223-7 · Cited by 6
“In recent years, the vast heterogeneity within psychiatric diagnoses has been highlighted (Fried, 2017; Fried & Nesse, 2015) and put forward as an explanation for inconsistent results in case–control studies.”
ResultVelázquez, R. G., Komulainen, K., Gluschkoff, K., Airaksinen, J., Määttänen, I., Rosenström, T. H., & Jokela, M. M. (2021) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2021.06.029 · Cited by 5
Association of stressful life events with depressive symptoms among adolescents: A network analysis
Luo, S., Feng, X., Li, L., Li, J., Chen, W., Xu, D., Xu, Z., & Guo, V. Y. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.120002 · Cited by 4
Min, S., Rhee, S. J., Song, Y., Ha, K., Ahn, Y. M., Kendler, K. S., Flint, J., & KOMOGEN‐D Group (2025) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.33056 · Cited by 4
Huong, C., & Brown, D. M. Y. (2024) · Mental health and physical activity · doi:10.1016/j.mhpa.2024.100586 · Cited by 4
Zhang, H., Wu, Z., Cao, L., Su, Y., Wang, F., Hong, W., Cai, Y., Peng, D., & Fang, Y. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.10.011 · Cited by 4
Osmanovic, S., Pajic, S., Petrović, I. B., & Portoghese, I. (2023) · Work · doi:10.3233/wor-230347 · Cited by 8
Pan, L., Huang, A., Chen, P., Sun, S., Zhang, H., & Li, R. (2024) · Current Psychology · doi:10.1007/s12144-024-06754-3 · Cited by 3
From dysphoria to anhedonia: age-related shift in the link between cognitive and affective symptoms
Harlev, D., Vituri, A., Shahar, M., & Wolpe, N. (2025) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbaf252 · Cited by 4
Chen, S.-Y., Chen, C., Lo, C., Lu, M., Hsu, C.-D., Chiu, Y.-H., Chen, C.-H., Lin, S., Huang, M., Chen, H., et al. (2021) · Nature and Science of Sleep · doi:10.2147/nss.s301357 · Cited by 4
“This phenotypic heterogeneity reflects the complex pathogenesis of depression, which hinders precise elucidation of the pathomechanisms of depression and development of precision medicine.(19) Consequently, when investigating the associations between depressive symptomatology and SWRDs, individual differences in depre…”
BackgroundDepressive Symptoms in Young and Middle-Aged Stroke Patients
Liu, Z., Zhang, Z., Wang, J., Song, G., Zhang, W., Xiang, D., Liu, Q., Budu, J. T., Lin, B., Chen, S., et al. (2023) · Nursing Research · doi:10.1097/nnr.0000000000000703 · Cited by 3
“Studies that group different depressive symptoms into a composite score and group participants with similar scores into one category can obscure important information (Fried, 2017).”
BackgroundLeveraging transparent ontology learning to refine constructs in neuroscience
Moreau, D., & Wiebels, K. (2025) · Neuroscience Informatics · doi:10.1016/j.neuri.2025.100199 · Cited by 3
Associations of uric acid and lipids with depression, dimensions of depression and anxiety symptoms
Kintzoglanakis, K., Kolias, P., Pavlou-Skantzis, L., Ntamka, P., Malles, A., Georgantzinos, I., Tzina, A. V., Themeli, T., & Karagiannakis, D. S. (2025) · Discover Mental Health · doi:10.1007/s44192-025-00313-3 · Cited by 3
“Thus, within the highly heterogeneous phenotype of depression, analyzing individual symptoms and their biological correlates -instead of adding symptoms to a sum-score-would facilitate progress on identifying biomarkers and more efficient antidepressants [18, 19].”
Singh, S., Cunningham, J. E. A., Uher, R., Becker, S., & Nunes, A. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106652 · Cited by 3
Wang, J., Wu, D., DeLorenzo, C., & Yang, J. (2024) · PLoS ONE · doi:10.1371/journal.pone.0299625 · Cited by 3
Ho, C.-C., Peng, S., Yu, Y.-H., Chu, Y.-R., Huang, S., & Kuo, P. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.08.139 · Cited by 3
Clinical depression and the chemical imbalance theory: social work practice dilemmas
Murphy, M. G., Schelbe, L. A., & Lacasse, J. R. (2021) · Social Work in Mental Health · doi:10.1080/15332985.2021.2017387 · Cited by 3
“…about the use of CONTACT Melissa G. Murphy mgm07f@fsu.edu Florida State University, 296 Champions Way, Tallahassee, FL 32306 © 2021 Taylor & Francis the depression label, as well as the attendant use of psychiatric drugs (e.g., Fried, 2017; Horwitz & Wakefield, 2007; Wakefield & Schmitz, 2013).”
BackgroundIdentification of structural brain alterations in adolescents with depressive symptomatology
Bashford‐Largo, J., Blair, J., Blair, K. S., Dobbertin, M. D., Dominguez, A. J., Hatch, M., & Bajaj, S. (2023) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2023.110723 · Cited by 3
“Depression is an extremely heterogeneous diagnosis which makes classification difficult in therapeutic settings (Fried, 2017).”
BackgroundZheng, Z., An, Y., Lu, Y., Cheng, X., & Yuan, G. F. (2024) · Current Psychology · doi:10.1007/s12144-024-06324-7 · Cited by 3
“Network analysis models conceptualize psychological disorders (e.g., depression) as interactions between symptoms and refine the study of psychological disorders to the level of symptoms (Borsboom & Cramer, 2013 ; Fried, 2017a, 2017b ).”
Clarke, J. C. (2021) · Psychoanalytic Psychotherapy · doi:10.1080/02668734.2021.1953117 · Cited by 3
“Empirically, symptoms matter too (Chevance et al., 2020; Fried, 2017).”
BackgroundDepression and depressive disorders
Griffith, J. M., McCormick, K. C., & Hankin, B. L. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-96023-6.00037-3 · Cited by 4
Mindlis, I., Rodebaugh, T. L., Kiosses, D. N., & Reid, M. C. (2025) · Journal of Applied Gerontology · doi:10.1177/07334648251362020 · Cited by 2
“Symptom heterogeneity of both depression and MM has been suggested to hinder the effectiveness of existing interventions (Fried, 2017; Fried & Nesse, 2015b; Suls et al., 2022).”
Network analysis and comparison of psychological distress among women with miscarriage experience
Robinson, M., Galeotti, M., Mitchell, G., Tomlinson, M., & Aventin, Á. (2025) · Psychology Health & Medicine · doi:10.1080/13548506.2025.2587261 · Cited by 2
“Previous evidence has shown that the degree of centrality or importance may vary greatly between individuals and groups (Fried, 2017).”
InfluentialLi, M., Li, J.-X., Han, J.-M., Liu, X., Gao, X.-Z., Chen, L.-M., Zhou, Z., & Zhou, H. (2025) · BMC Psychiatry · doi:10.1186/s12888-025-07684-5 · Cited by 3
“The reason for this discrepancy may be related to the high heterogeneity of MDD, including differences in pathology, clinical symptoms, as well as treat-ment and post-intervention methods [59, 60].”
Forster, A., Rodrigues, J., Sperlich, B., & Hewig, J. S. (2026) · Psychophysiology · doi:10.1111/psyp.70217 · Cited by 3
“Along this line, differences in the etiology or phenomenology of symptoms across patients may introduce even greater difficulties in terms of replicable results (e.g., Fried 2017).”
Montet, J., Montalban, E., Dexpert, S., Magne, E., Beau, C., Forestier, D., Ledaguenel, P., Gostner, J. M., Fuchs, D., Aouizerate, B., et al. (2026) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2026.106547 · Cited by 2
A genome-wide investigation of depression among individuals with and without irritability
St‐Pierre, J., Jang, J., Nagy, C., Fiori, L. M., Turecki, G., Dupuis, J., Bhatnagar, S., & Orri, M. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03548-w · Cited by 2
“This phenotypic heterogeneity has raised important concerns among clinicians and researchers about the reliability, validity, and utility of depression as a homogeneous clinical phenotype [10].”
Feedback-related negativity: A biomarker for depression
Haofang, Q. I. N., HUANG, R., & Jia, S. (2021) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2021.00404 · Cited by 2
“…es in P sy ch ol og ic al S ci en ce 感性在抑郁代际传递之间的调节作用, 并提示了 在母亲有抑郁史的儿童中, 奖赏敏感性降低的亚 群患抑郁症的风险可能最大, 因此增强奖赏敏感 性或许是对未来抑郁发作的一种潜在预防手段。 值得注意的是, 虽然该研究中部分被试 3 年之后 抑郁程度增加, 但符合临床抑郁症标准的被试非 常少; 因此, 需要进一步的工作来评估奖赏敏感 性的减弱对临床抑郁发作的预测作用。 3 FRN 对抑郁症的预测作用 青春期是抑郁症的高发期之一。有证据表明, 从童年期到青春期 , 抑郁症的发病率显著上升 (Costello et…”
Lipid parameters and depression in patients with chronic tinnitus: A cross-sectional observation
Boecking, B., Klasing, S., Brüeggemann, P., Rose, M., & Mazurek, B. (2024) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2024.111613 · Cited by 3
Misiak, B., Rejek, M., Bielawski, T., Błoch, M., Samochowiec, J., Bąba-Kubiś, A., Gawęda, Ł., & Maciaszek, J. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.09.002 · Cited by 2
Seizer, L., Renner, T. J., & Löchner, J. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119800 · Cited by 2
Park, S., Kim, J., & Kim, D. (2019) · Nordic Journal of Psychiatry · doi:10.1080/08039488.2019.1692234 · Cited by 2
“approach for diagnosis-based analysis in the field of psychiatric disorders [12,13].”
MethodUnderstanding in vivo modelling of depression
Bannach‐Brown, A. (2019) · ERA · Cited by 1
Hartung, T. J., Fried, E. I., Mehnert-Theuerkauf, A., Hinz, A., & Vehling, S. (2019) · doi:10.31234/osf.io/8r569 · Cited by 4
Self-citationDelineating the Shared Genetics Across the Mood Disorders Spectrum
Warrier, V. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.04.017 · Cited by 1
Kaiser, A. J. E., Shippen, N. A., Tufty, L. M., Lejeune, J., Zolli, N., & Meinzer, M. C. (2023) · Autism and child psychopathology series · doi:10.1007/978-3-031-41709-2_14 · Cited by 2
Tao, Y., Yan, Y., Wang, M., Fan, H., Dou, Y., Zhao, L., Ni, R., Wei, J., Yang, X., & Ma, X. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.120068 · Cited by 2
Peripheral immune system activity in young psychiatry patients
Seizer, L., Löchner, J., & Renner, T. J. (2025) · Brain Behavior & Immunity - Health · doi:10.1016/j.bbih.2025.101143 · Cited by 1
“Thus, the relation between depression and inflammation may be more pronounced when examined in relation to symptom severity scores rather than a diagnosis-based approach, given the many heterogeneous clinical presentations of depression (Goldberg, 2011; Fried, 2017).”
Norbury, A., Fairs, G., Georgescu, A. L., Nour, M. M., Molimpakis, E., & Goria, S. (2026) · Scientific Reports · doi:10.1038/s41598-025-33331-w · Cited by 1
Viduani, A. C., Ferreira, L. Z., Buchweitz, C., Piccin, J., Fisher, H. L., van Heerden, A. C., Kohrt, B. A., Mondelli, V., Kieling, C., & Araujo, R. M. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.121956 · Cited by 1
Counts, N. Z., Gionfriddo, P., & Chapman, R. H. (2020) · Applied Health Economics and Health Policy · doi:10.1007/s40258-020-00568-7 · Cited by 1
Stańczykiewicz, B., Bogudzińska, B., Kowalski, K., & Misiak, B. (2023) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2023.106924 · Cited by 1
“In this regard, clear and valid diagnostic boundaries of major depression are difficult to be established.”
BackgroundReproductive toxicity of JJH201501 in rats: Perinatal study
Sun, M., Peng, Y., & Qiao, H. (2024) · Birth Defects Research · doi:10.1002/bdr2.2303 · Cited by 1
“Moreover, it has a complex origin involving genetic, environmental, and neurobiological factors that affect brain function, including altered neuro-transmitter systems, contributing to the heterogeneity of MDD presentation (Athira et al., 2019; Fried, 2017; Leff-Gelman et al., 2016).”
BackgroundByrne, B., McInerney, A. M., & Deschênes, S. S. (2024) · Irish Journal of Psychological Medicine · doi:10.1017/ipm.2024.10 · Cited by 1
“…interest or pleasure, and suicidal ideation (APA 2013), there is considerable heterogeneity in the depressive symptoms experienced by individuals (Fried 2017, Wakefield & Schmitz 2013) as well as evidence that individual depressive symptoms differ in their risk factors, associations with…”
BackgroundHorne, S. J., & Quigley, L. (2024) · Cognitive Therapy and Research · doi:10.1007/s10608-024-10503-y · Cited by 1
“…sum-score measures for depression, as these measures may obfuscate the underlying relationships between individual symptoms and important depression-related findings, including risk of depression onset, risk of depression relapse, and treatment responsiveness (Fried, 2017; Fried & Nesse, 2015).”
Yao, B., Long, Z., Lin, X., Chen, G., Li, X., Ye, Z., & Liu, J. (2025) · Frontiers in Pharmacology · doi:10.3389/fphar.2025.1664784 · Cited by 2
Neuropsychology of depression in people with epilepsy
Freitag, H. (2019) · Swiss Archives of Neurology Psychiatry and Psychotherapy · doi:10.4414/sanp.2019.03072 · Cited by 1
Personal Devices and Smartphone Applications for Detection of Depression
Basco, M. R., Kyrarini, M., & Makedon, F. S. (2020) · Psychiatric Annals · doi:10.3928/00485713-20200505-01 · Cited by 1
Prospective Mental Imagery in Depression: Impact on Reward Processing and Reward-Motivated Behaviour
Renner, F., Werthmann, J., Paetsch, A., Bär, H. E., Heise, M., & Bruijniks, S. J. E. (2021) · doi:10.23668/psycharchives.4769 · Cited by 1
Kraft, B., Bø, R., Hoorelbeke, K., Koster, E. H. W., Jonassen, R., Harmer, C. J., & Landrø, N. I. (2023) · Psychiatry Research Communications · doi:10.1016/j.psycom.2023.100137 · Cited by 1
Taliaz, D., Lilian, R. R., Schurr, R., & Levin, L. (2023) · Medical Research Archives · doi:10.18103/mra.v11i10.4658
The Killing of a Sacred Veneer: Depressive Symptoms in Athletes
Tahtinen, R. E. (2021) · Liverpool John Moores University · doi:10.24377/ljmu.t.00014387 · Cited by 1
Ballou, N., & Zendle, D. I. (2021) · doi:10.31234/osf.io/9ejhk · Cited by 1
Helmich, M. A. (2022) · University of Groningen research database (University of Groningen / Centre for Information Technology) · doi:10.33612/diss.200101721 · Cited by 2
Mills, H. (2023) · Open Access Victoria University of Wellington | Te Herenga Waka (Figshare) · doi:10.26686/wgtn.24190137 · Cited by 1
The current state and future prospects of depression research (clinical and classification problems)
Ivanets, N. N., Kinkulkina, M. A., Tikhonova, Y. G., & Avdeeva, T. I. (2018) · S S Korsakov Journal of Neurology and Psychiatry · doi:10.17116/jnevro201811810176
Stress as a model for neurobiology of depression
Juruena, M. F. (2018) · Journal of Systems and Integrative Neuroscience · doi:10.15761/jsin.1000197
“Moreover, in addition to accounting for other psychological, social and economic risk factors [10]; although it should be stressed that not all individuals whom experience ELS will go on to develop Depression in adulthood, and therefore we need also to identify bio-psycho-social protective factors that could lead to r…”
BackgroundExpressive writing in patients with depressive disorder: Narrative analysis
zdraví, N. Ú. D., Říha, D., Ševčíková, M., Kvapilová, J., & Preiss, M. (2021) · Ceskoslovenska psychologie · doi:10.51561/cspsych.65.2.289
Biomarkers of Anhedonia and Mood Disorders in Depressed Individuals
张, 欣. (2021) · Advances in Psychology · doi:10.12677/ap.2021.116158
Uma análise teórica da depressão sob a visão dos modelos psicométricos hegemônicos
Baptista, M. N., & Franco, V. R. (2024) · Estudos e Pesquisas em Psicologia · doi:10.12957/epp.2024.67278
Saavedra, J. U., Knowles, E. E. M., Deaso, E. A., Cadavid, L., & Austin, M. (2024) · doi:10.2196/preprints.66187
Paz, V., Williams, D. M., Richards, M., Tassino, B., da Silva, A. C. R., & Garfield, V. (2024) · medRxiv · doi:10.1101/2024.12.08.24318680
Hagen, H., Røssberg, J. I., Harmer, C. J., Jonassen, R., Landrø, N., & Bø, R. (2024) · Neuroscience Applied · doi:10.1016/j.nsa.2024.104185
Paladino, D. A., Gonzalez, L. M., & Watson, J. C. (2025) · Wiley eBooks · doi:10.1002/9781394347292.ch19
Zilcha‐Mano, S. (2025) · Clinical Psychological Science · doi:10.1177/21677026241301056
“Findings suggest that emotions (Jacobson et al., 2023), including depression (Fisher et al., 2017; Fried, 2017; van Eeden et al., 2019), vary within persons over time.”
Dogan, A. E., Genç, H. A., Balaç, S., Şenol, Ş. H., Ayas, G., Dogan, Z., Bora, E., Ceylan, D., & Şar, V. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1516920 · Cited by 1
Chronischer Tinnitus aus psychologischer Sicht
Boecking, B., & Mazurek, B. (2025) · HNO · doi:10.1007/s00106-025-01586-4 · Cited by 2
Generalizability of Risk Models for Treatment-Resistant Depression Across Three Health SystemsPreprint
Walsh, C. G., Ripperger, M. A., McCoy, T. H., Castro, V. M., Hu, Y., Kirchner, H. L., Ruderfer, D. M., & Perlis, R. H. (2025) · medRxiv · doi:10.1101/2025.05.21.25328089
Jassim, N., Hagan, C. C., Holt, R., Goodyer, I. M., & Suckling, J. (2025) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2025.112019
Associations between depression severity and immune activity in children and adolescents
Seizer, L., Renner, T. J., & Löchner, J. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.120190 · Cited by 1
Predictive Modelling of Depression Treatment Response using Individual Symptoms and Latent FactorsPreprint
Buehler, S. K., Heinzle, J., Eladawi, M. A., Lee, C. T., Hanlon, A. K., O’Keane, V., Harty, S., Lynch, K., Stephan, K. E., & Gillan, C. M. (2025) · medRxiv · doi:10.1101/2025.09.17.25335980
Douglas, C., Congdon, E. L., Huang, C., Seok, D., Cohen, Z. D., Akre, S., Tozzo, V., Huang, F., Ramo-Larios, D., Bernier, R. A., et al. (2025) · medRxiv · doi:10.1101/2025.10.01.25337105
“3,4,5,6 Current classification frameworks for depression and anxiety largely ignore their heterogeneity, grouping individuals experiencing symptoms into discrete diagnostic categories.”
Hagen, H. S., Røssberg, J. I., Harmer, C. J., Jonassen, R., Landrø, N. I., & Bø, R. (2025) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/j.jbtep.2025.102073
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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