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The 52 symptoms of major depression: Lack of content overlap among seven common depression scales
Abstract
Background Depression severity is assessed in numerous research disciplines, ranging from the social sciences to genetics, and used as a dependent variable, predictor, covariate, or to enroll participants. The routine practice is to assess depression severity with one particular depression scale, and draw conclusions about depression in general, relying on the assumption that scales are interchangeable measures of depression. The present paper investigates to which degree 7 common depression scales differ in their item content and generalizability.Methods A content analysis is carried out to determine symptom overlap among the 7 scales via the Jaccard index (0=no overlap, 1=full overlap). Per scale, rates of idiosyncratic symptoms, and rates of specific vs. compound symptoms, are computed.Results The 7 instruments encompass 52 disparate symptoms. Mean overlap among all scales is low (0.36), mean overlap of each scale with all others ranges from 0.27 to 0.40, overlap among individual scales from 0.26 to 0.61. Symptoms feature across a mean of 3 scales, 40% of the symptoms appear in only a single scale, 12% across all instruments. Scales differ regarding their rates of idiosyncratic symptoms (0-33%) and compound symptoms (22-90%).Limitations Future studies analyzing more and different scales will be required to obtain a better estimate of the number of depression symptoms; the present content analysis was carried out conservatively and likely underestimates heterogeneity across the 7 scales.Conclusion The substantial heterogeneity of the depressive syndrome and low overlap among scales may lead to research results idiosyncratic to particular scales used, posing a threat to the replicability and generalizability of depression research. Implications and future research opportunities are discussed.
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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 [14]
Citations
Cites
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,845
The CES-D Scale: A Self-Report Depression Scale for Research in the General Population
Radloff, L. S. (1977) · Applied Psychological Measurement · doi:10.1177/014662167700100306 · Cited by 53,267
An inventory for measuring depression
BECK, A. T. (1961) · Archives of General Psychiatry · doi:10.1001/archpsyc.1961.01710120031004 · Cited by 38,032
Hamilton, M. (1960) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.23.1.56 · Cited by 32,817
Diagnostic and Statistical Manual of Mental Disorders
(2012) · Springer eBooks · doi:10.1007/springerreference_121117 · Cited by 20,772
A new depression scale designed to be sensitive to change
Montgomery, S. A., & Åsberg, M. (1979) · British Journal of Psychiatry · doi:10.1192/bjp.134.4.382 · Cited by 13,962
A self-rating depression scale
ZUNG, W. W. K. (1965) · Archives of General Psychiatry · doi:10.1001/archpsyc.1965.01720310065008 · Cited by 9,813
Cognitive Therapy for Depression
(2012) · PsycEXTRA Dataset · doi:10.1037/e675542012-001 · Cited by 9,678
Kessler, R. C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K. R., Rush, A. J., Walters, E. E., & Wang, P. S. (2003) · JAMA · doi:10.1001/jama.289.23.3095 · Cited by 7,988
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.09091379 · Cited by 7,067
Flagged first, then by citations
Research works printed but not linked: 1
- Santor, 2006, Eight Decades of Measurement in, Depress. Meas., 4, 135
Cited by
Sorted by citations
Bridge Centrality: A Network Approach to Understanding Comorbidity
Jones, P. J., Ma, R., & McNally, R. J. (2019) · Multivariate Behavioral Research · doi:10.1080/00273171.2019.1614898 · Cited by 1,895
Transdiagnostic approaches to mental health problems: Current status and future directions.
Dalgleish, T., Black, M., Johnston, D., & Bevan, A. (2020) · Journal of Consulting and Clinical Psychology · doi:10.1037/ccp0000482 · Cited by 883
Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them
Flake, J. K., & Fried, E. I. (2020) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245920952393 · Cited by 969
Self-citationRobinaugh, D. J., Hoekstra, R. H. A., Toner, E. R., & Borsboom, D. (2020) · Psychological Medicine · doi:10.1017/s0033291719003404 · Cited by 861
Using Network Analysis to Identify Central Symptoms of Adolescent Depression
Mullarkey, M. C., Marchetti, I., & Beevers, C. G. (2018) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2018.1437735 · Cited by 519
A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research
Conway, C. C., Forbes, M. K., Forbush, K. T., Fried, E. I., Hallquist, M. N., Kotov, R., Mullins-Sweatt, S. N., Shackman, A. J., Skodol, A. E., South, S. C., et al. (2019) · Perspectives on Psychological Science · doi:10.1177/1745691618810696 · Cited by 426
Maj, M., Stein, D. J., Parker, G., Zimmerman, M., Fava, G. A., De Hert, M., Demyttenaere, K., McIntyre, R. S., Widiger, T., & Wittchen, H. (2020) · World Psychiatry · doi:10.1002/wps.20771 · Cited by 435
Social media and depression symptoms: A network perspective.
Aalbers, G., McNally, R. J., Heeren, A., de Wit, S., & Fried, E. I. (2018) · Journal of Experimental Psychology General · doi:10.1037/xge0000528 · Cited by 330
Lu, B., Lin, L., & Su, X. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.03.074 · Cited by 357
Kaiser, T., Herzog, P., Voderholzer, U., & Brakemeier, E. (2021) · Depression and Anxiety · doi:10.1002/da.23136 · Cited by 296
Chase, H. W., Boudewyn, M. A., Carter, C. S., & Phillips, M. L. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0499-9 · Cited by 286
Revisiting the theoretical and methodological foundations of depression measurement
Fried, E. I., Flake, J. K., & Robinaugh, D. J. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-022-00050-2 · Cited by 314
Chekroud, A. M., Gueorguieva, R., Krumholz, H. M., Trivedi, M. H., Krystal, J. H., & McCarthy, G. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.0025 · Cited by 276
Fried, E. I., von Stockert, S., Haslbeck, J. M. B., Lamers, F., Schoevers, R. A., & Penninx, B. W. J. H. (2019) · Psychological Medicine · doi:10.1017/s0033291719002770 · Cited by 260
Kumar, P., Kumar, N., Aggarwal, P., & Yeap, J. A. L. (2021) · Current Psychology · doi:10.1007/s12144-021-01567-0 · Cited by 273
Moving forward: how depression heterogeneity hinders progress in treatment and research
Fried, E. (2017) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2017.1307737 · Cited by 220
Networks of major depressive disorder: A systematic review
Malgaroli, M., Calderon, A., & Bonanno, G. A. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2021.102000 · Cited by 211
Chevance, A., Ravaud, P., Tomlinson, A., Le Berre, C., Teufer, B., Touboul, S., Fried, E. I., Gartlehner, G., Cipriani, A., & Tran, V. T. (2020) · The Lancet Psychiatry · doi:10.1016/s2215-0366(20)30191-7 · Cited by 193
Strohmaier, S. (2020) · Mindfulness · doi:10.1007/s12671-020-01319-4 · Cited by 163
Almas, K. (1999) · PubMed · Cited by 169
John, A., Patel, U., Rusted, J. M., Richards, M., & Gaysina, D. (2018) · Psychological Medicine · doi:10.1017/s0033291718001137 · Cited by 184
The Heterogeneity of Mental Health Assessment
Newson, J. J., Hunter, D., & Thiagarajan, T. C. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00076 · Cited by 178
Cai, N., Choi, K. W., & Fried, E. I. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa115 · Cited by 160
Association between negative cognitive bias and depression: A symptom-level approach.
Beevers, C. G., Mullarkey, M. C., Dainer‐Best, J., Stewart, R. A., Labrada, J., Allen, J. J. B., McGeary, J. E., & Shumake, J. (2019) · Journal of Abnormal Psychology · doi:10.1037/abn0000405 · Cited by 158
Psychological measurement and the replication crisis: Four sacred cows
Lilienfeld, S. O., & Strother, A. N. (2020) · Canadian Psychology / Psychologie canadienne · doi:10.1037/cap0000236 · Cited by 144
The complex interplay between depression and multimorbidity in late life: risks and pathways
Triolo, F., Harber-Aschan, L., Murri, M. B., Calderón‐Larrañaga, A., Vetrano, D. L., Sjöberg, L., Marengoni, A., & Dekhtyar, S. (2020) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2020.111383 · Cited by 136
Theories and Models: What They Are, What They Are for, and What They Are About
Fried, E. I. (2020) · Psychological Inquiry · doi:10.1080/1047840x.2020.1854011 · Cited by 167
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
The Turker Blues: Hidden Factors Behind Increased Depression Rates Among Amazon’s Mechanical Turkers
Ophir, Y., Sisso, I., Asterhan, C. S. C., Tikochinski, R., & Reichart, R. (2019) · Clinical Psychological Science · doi:10.1177/2167702619865973 · Cited by 124
Yumeng, C. H. E. N., Zhang, Y., Guoliang, Y. U., & 俞, 国. (2022) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2022.00991 · Cited by 135
Everaert, J., & Joormann, J. (2019) · Clinical Psychological Science · doi:10.1177/2167702619859342 · Cited by 119
Djelantik, A. A. A. M. J., Robinaugh, D. J., Kleber, R. J., Smid, G. E., & Boelen, P. A. (2020) · Depression and Anxiety · doi:10.1002/da.22880 · Cited by 110
Let’s talk about pain catastrophizing measures: an item content analysis
Crombez, G., Paepe, A. L. D., Veirman, E., Eccleston, C., Verleysen, G., & Ryckeghem, D. M. L. V. (2020) · PeerJ · doi:10.7717/peerj.8643 · Cited by 113
Canalization and plasticity in psychopathology
Carhart-Harris, R. L., Chandaria, S., Erritzøe, D., Gazzaley, A. H., Girn, M., Kettner, H., Mediano, P. A. M., Nutt, D. J., Rosas, F. E., Roseman, L., et al. (2022) · Neuropharmacology · doi:10.1016/j.neuropharm.2022.109398 · Cited by 107
Longitudinal network structure of depression symptoms and self-efficacy in low-income mothers
Junior, H. P. D. O. S., Kossakowski, J. J., Schwartz, T. A., Beeber, L. S., & Fried, E. I. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191675 · Cited by 110
Blanken, T. F., Deserno, M. K., Dalege, J., Borsboom, D., Blanken, P., KERKHOF, G. A., & Cramer, A. O. J. (2018) · Scientific Reports · doi:10.1038/s41598-018-24224-2 · Cited by 103
Psychological Assessments in Legal Contexts: Are Courts Keeping “Junk Science” Out of the Courtroom?
Neal, T. M. S., Slobogin, C., Saks, M. J., Faigman, D. L., & Geisinger, K. F. (2019) · Gothic.net · doi:10.1177/1529100619888860 · Cited by 115
Instrumental assessment of balance and gait in depression: A systematic review
Murri, M. B., Triolo, F., Coni, A., Tacconi, C., Nerozzi, E., Escelsior, A., Respino, M., Neviani, F., Bertolotti, M., Bertakis, K. D., et al. (2019) · Psychiatry Research · doi:10.1016/j.psychres.2019.112687 · Cited by 95
Fried, E. I. (2017) · Health Psychology Review · doi:10.1080/17437199.2017.1306718 · Cited by 112
Forest therapy can prevent and treat depression: Evidence from meta-analyses
Rosa, C. D., Larson, L. R., Collado, S., & Profice, C. C. (2020) · Urban forestry & urban greening · doi:10.1016/j.ufug.2020.126943 · Cited by 106
Associations among diet, the gastrointestinal microbiota, and negative emotional states in adults
Taylor, A. M., Thompson, S. V., Edwards, C. G., Musaad, S. M. A., Khan, N. A., & Holscher, H. D. (2020) · Nutritional Neuroscience · doi:10.1080/1028415x.2019.1582578 · Cited by 92
Coping and resilience in adults: a cross-sectional network analysis
der Hallen, R. V., Jongerling, J., & Godor, B. P. (2020) · Anxiety Stress & Coping · doi:10.1080/10615806.2020.1772969 · Cited by 117
Integrating psychotherapy with the hierarchical taxonomy of psychopathology (HiTOP).
Hopwood, C. J., Bagby, R. M., Gralnick, T. M., Ro, E., Ruggero, C. J., Mullins‐Sweatt, S. N., Kotov, R., Bach, B., Cicero, D. C., Krueger, R. F., et al. (2019) · Journal of Psychotherapy Integration · doi:10.1037/int0000156 · Cited by 101
The registration continuum in clinical science: A guide toward transparent practices
Benning, S. D., Bachrach, R. L., Smith, E. A., Freeman, A. J., & Wright, A. G. C. (2019) · Journal of Abnormal Psychology · doi:10.1037/abn0000451 · Cited by 77
Gosmann, N. P., Costa, M. D. A., Jaeger, M. D. B., Motta, L. S., Frozi, J., Spanemberg, L., Manfro, G. G., Cuijpers, P. J., Pine, D. S., & Salum, G. A. (2021) · PLoS Medicine · doi:10.1371/journal.pmed.1003664 · Cited by 98
Measuring Depression in Autistic Adults: Psychometric Validation of the Beck Depression Inventory–II
Williams, Z. J., Everaert, J., & Gotham, K. O. (2020) · Assessment · doi:10.1177/1073191120952889 · Cited by 84
Ogunmoroti, O., Osibogun, O. I., Spatz, E. S., Okunrintemi, V., Mathews, L. M., Ndumele, C. E., & Michos, E. D. (2021) · Preventive Medicine · doi:10.1016/j.ypmed.2021.106891 · Cited by 84
Effect of Forest Therapy on Depression and Anxiety: A Systematic Review and Meta-Analysis
Yeon, P., Jeon, J. Y., Jung, M.-S., Min, G.-M., Kim, G.-Y., Han, K.-M., Shin, M., Jo, S.-H., Kim, J.-G., & Shin, W.-S. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182312685 · Cited by 95
Sex differences in the inflammation-depression link: A systematic review and meta-analysis
Jarkas, D., Villeneuve, A. H., Daneshmend, A., Villeneuve, P. J., & McQuaid, R. J. (2024) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2024.07.037 · Cited by 84
Patalay, P., & Fried, E. I. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13333 · Cited by 79
Everaert, J., Vrijsen, J. N., Martin‐Willett, R., van de Kraats, L., & Joormann, J. (2022) · Psychological Bulletin · doi:10.1037/bul0000367 · Cited by 91
Ramadianto, A. S., Kusumadewi, I., Agiananda, F., & Raharjanti, N. W. (2022) · BMC Psychiatry · doi:10.1186/s12888-022-03745-1 · Cited by 107
Kraus, J., Scholz, D. D., Meßner, E.-M., Messner, M., & Baumann, M. R. K. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02917 · Cited by 74
Heinrich, M., Zagorscak, P., Eid, M., & Knaevelsrud, C. (2018) · Assessment · doi:10.1177/1073191118803738 · Cited by 81
Depressive and anxiety symptoms in patients with COPD: A network analysis
Yohannes, A. M., Murri, M. B., Hanania, N. A., Regan, E. A., Iyer, A. S., Bhatt, S. P., Kim, V., Kinney, G. L., Wise, R. A., Eakin, M. N., et al. (2022) · Respiratory Medicine · doi:10.1016/j.rmed.2022.106865 · Cited by 81
Zhang, Y., Juanjuan, J. I. N., & Guoliang, Y. U. (2022) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2022.00965 · Cited by 70
Dharmayani, P. N. A., Juergens, M., Allman-Farinelli, M. A., & Mihrshahi, S. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18020780 · Cited by 74
Zhou, J. L., Zhou, J., Feng, L., Feng, Y., Xiao, L., Xu, C., Yang, J., & Wang, G. (2022) · Psychological Medicine · doi:10.1017/s0033291722003385 · Cited by 67
Poor Separation of Clinical Symptom Profiles by DSM-5 Disorder Criteria
Newson, J. J., Pastukh, V., & Thiagarajan, T. C. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.775762 · Cited by 72
DSM disorders and their criteria: how should they inter-relate?
Kendler, K. S. (2017) · Psychological Medicine · doi:10.1017/s0033291717000678 · Cited by 66
The relationship between text message sentiment and self-reported depression
Liu, T., Meyerhoff, J., Eichstaedt, J. C., Karr, C. J., Kaiser, S. M., Kording, K. P., Mohr, D. C., & Ungar, L. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.12.048 · Cited by 72
Bean, C. A. L., Summers, C. B., & Ciesla, J. A. (2022) · Behaviour Research and Therapy · doi:10.1016/j.brat.2022.104153 · Cited by 70
Murri, M. B., Caruso, R., Ounalli, H., Zerbinati, L., Berretti, E., Costa, S., Recla, E., Folesani, F., Kissane, D. W., Nanni, M. G., et al. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.06.074 · Cited by 68
Roberts, C., Sahakian, B. J., & Robbins, T. W. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.09.001 · Cited by 63
Primbs, M. A., Pennington, C. R., Lakens, D., Silan, M. A. A., Lieck, D., Forscher, P. S., Buchanan, E. M., & Westwood, S. J. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916221100420 · Cited by 72
Phua, D. Y., Kee, M. Z. L., Koh, D. X. P., Rifkin‐Graboi, A., Daniels, M., Chen, H., Chong, Y. S., Broekman, B. F. P., Magiati, I., Karnani, N., et al. (2017) · Development and Psychopathology · doi:10.1017/s0954579417001249 · Cited by 68
Mental health and working conditions among French medical students: A nationwide study
Rolland, F., Hadouiri, N., Haas-Jordache, A., Gouy, E., Mathieu, L., Goulard, A., Morvan, Y., & Frajerman, A. (2022) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.03.001 · Cited by 61
Bard, H. A., O’Driscoll, C., Miller, C. B., Henry, A. L., Cape, J. D., & Espie, C. A. (2022) · Sleep Medicine · doi:10.1016/j.sleep.2022.12.005 · Cited by 63
The centrality of DSM and non-DSM depressive symptoms in Han Chinese women with major depression
Kendler, K. S., Aggen, S. H., Flint, J., Borsboom, D., & Fried, E. I. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.11.032 · Cited by 65
Panayiotou, M., Black, L., Carmichael-Murphy, P., Qualter, P., & Humphrey, N. (2023) · Nature Mental Health · doi:10.1038/s44220-023-00063-7 · Cited by 62
Bondar, J., Caye, A., Chekroud, A. M., & Kieling, C. (2020) · The Lancet Psychiatry · doi:10.1016/s2215-0366(20)30060-2 · Cited by 60
Criteria for assessing grant applications: a systematic review
Hug, S. E., & Aeschbach, M. (2020) · Humanities and Social Sciences Communications · doi:10.1057/s41599-020-0412-9 · Cited by 60
Predicting the future of neuroimaging predictive models in mental health
Tejavibulya, L., Rolison, M. J., Gao, S., Liang, Q., Peterson, H., Dadashkarimi, J., Farruggia, M. C., Hahn, C. A., Noble, S., Lichenstein, S. D., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01635-2 · Cited by 58
Maglanoc, L. A., Landrø, N. I., Jonassen, R., Kaufmann, T., Córdova‐Palomera, A., Hilland, E., & Westlye, L. T. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.05.005 · Cited by 59
Fuzzy constructs in technology usage scales
Davidson, B. I., Shaw, H., & Ellis, D. A. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107206 · Cited by 63
Djelantik, A. A. A. M. J., Robinaugh, D. J., & Boelen, P. A. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114472 · Cited by 57
Edwards, C. J., Garety, P., & Hardy, A. (2019) · Psychological Medicine · doi:10.1017/s0033291719002381 · Cited by 54
Wang, Y., Wang, J., Liu, X., & Zhu, T. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.661213 · Cited by 61
Predicting treatment outcome in depression: an introduction into current concepts and challenges
Rost, N., Binder, E. B., & Brückl, T. M. (2022) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-022-01418-4 · Cited by 66
Mofsen, A. M., Rodebaugh, T. L., Nicol, G. E., Depp, C. A., Miller, J. P., & Lenze, E. J. (2019) · JMIR Mental Health · doi:10.2196/11845 · Cited by 51
The future of psychological treatments: The Marburg Declaration
Rief, W., Asmundson, G. J. G., Bryant, R. A., Clark, D. M., Ehlers, A., Holmes, E. A., McNally, R. J., Neufeld, C. B., Wilhelm, S., Jaroszewski, A. C., et al. (2024) · Clinical Psychology Review · doi:10.1016/j.cpr.2024.102417 · Cited by 54
A generalizable speech emotion recognition model reveals depression and remission
Hansen, L., Zhang, Y., Wolf, D., Sechidis, K., Ladegaard, N., & Fusaroli, R. (2021) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13388 · Cited by 58
Miloyan, B. H., & Fried, E. I. (2017) · World Psychiatry · doi:10.1002/wps.20439 · Cited by 53
Kim, D., Kwon, H., Ha, M., Lim, M. H., & Kim, K. M. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.12.002 · Cited by 56
Karstoft, K., & Armour, C. (2022) · Journal of Traumatic Stress · doi:10.1002/jts.22880 · Cited by 52
Bereavement or breakup: Differences in networks of depression
Burger, J., Stroebe, M., Perrig‐Chiello, P., Schut, H. A. W., Spahni, S., Eisma, M. C., & Fried, E. I. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.01.157 · Cited by 56
Bunaciu, A., Bliuc, A., Best, D. W., Hennessy, E. A., Belanger, M. J., & Benwell, C. (2023) · Addiction Research & Theory · doi:10.1080/16066359.2023.2245323 · Cited by 60
Knowing What We're Talking About
Peters, G.-J., & Crutzen, R. (2024) · Meta-Psychology · doi:10.15626/mp.2022.3638 · Cited by 56
van Loo, H. M., van Borkulo, C. D., Peterson, R. E., Fried, E. I., Aggen, S. H., Borsboom, D., & Kendler, K. S. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.10.038 · Cited by 53
Veal, C., Tomlinson, A., Cipriani, A., Bulteau, S., Henry, C., Müh, C., Touboul, S., Waal, N. D., Lévy-Soussan, H., Furukawa, T. A., et al. (2024) · The Lancet Psychiatry · doi:10.1016/s2215-0366(23)00438-8 · Cited by 52
Savelieva, K., Komulainen, K., Elovainio, M. J., & Jokela, M. M. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.09.024 · Cited by 53
Burnout, resilience, and coping among esports players: A network analysis approach
Poulus, D., Sargeant, J. A., Zarate, D., Griffiths, M. D., & Stavropoulos, V. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108139 · Cited by 47
Dejonckheere, E., Kalokerinos, E. K., Bastian, B. B., & Kuppens, P. (2018) · Cognition & Emotion · doi:10.1080/02699931.2018.1524747 · Cited by 52
Lunansky, G., van Borkulo, C. D., & Borsboom, D. (2020) · European Journal of Personality · doi:10.1002/per.2263 · Cited by 58
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Exploring the links between specific depression symptoms and brain structure: A network study
Hilland, E., Landrø, N. I., Kraft, B., Tamnes, C. K., Fried, E. I., Maglanoc, L. A., & Jonassen, R. (2019) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12969 · Cited by 46
O’Driscoll, C., Buckman, J. E. J., Fried, E. I., Saunders, R., Cohen, Z. D., Ambler, G., DeRubeis, R. J., Gilbody, S. M., Hollon, S. D., Kendrick, T., et al. (2021) · BMC Medicine · doi:10.1186/s12916-021-01971-0 · Cited by 55
Metadata
- Authors
- Fried, E. I.
- Affiliations
- University of Amsterdam (NL)
- Corresponding author
- Fried, Eiko I.
- ORCID
- Fried, Eiko I.
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 208
- Pages
- 191-197
- ISSN
- 0165-0327 (ISSN-L)
- OpenAlex
- W2537247270
- Cited by
- 649
- References
- 42
- Citations by year
- 2026: 73 · 2025: 77 · 2024: 93 · 2023: 75 · 2022: 87 · 2021: 84 · 2020: 78 · 2019: 46 · 2018: 22 · 2017: 12
- FWCI
- 37.96
- Type
- journal article
- Language
- en
- Update notices
- erratum (2020-01-01)
- Open access
- closed
- Locations
- Journal of Affective Disorders (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- major depressive disorder, depressive symptoms, depression rating scales, symptom overlap, scale heterogeneity, measurement invariance, replicability, generalizability, Jaccard similarity
- MeSH terms
- Depressive Disorder, Major, Major Depressive Disorder, Humans, Psychiatric Status Rating Scales, Reproducibility of Results
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