Nocturnal motor activity and light exposure: objective actigraphy-based marks of melancholic and non-melancholic depressive disorder. Brief report
Open accessAbstract
Differentiation of melancholic (MEL) and non-melancholic (N-MEL) depression results from subjective assessment of psychomotor disturbance, which obscures their accurate diagnosis. CORE instrument assigned participants with severe or refractory depression to MEL or N-MEL group. Participants underwent 7 days of actigraphy. Data was fitted to a cosinusoidal curve corresponding to a 24-h rhythm. Nocturnal activity was significantly higher in N-MEL. ROC curve shows that average night activity discriminate participants with 71% sensitivity and 100% specificity (area under the curve = 0.84). Actigraphy contribute to the objective differentiation of depression subtypes, and have implications for research on their neurobiology and clinical management.
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Several digital biomarkers have been investigated for MDD characterization and diagnosis, including physical activity patterns, voice features, light exposure measurements, mobile phone GPS, and normal smartphone usage duration and frequency.
“In the recent years, several digital biomarkers have been investigated for MDD characterization and diagnosis such as measure patterns of physical activity (24, 25) features from voice samples (26, 27), light exposure measurements (25), mobile phone global positioning systems (GPS) and normal usage of smartphones such as usage duration and frequency (22).”
From A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms (2023) · cites this paper as [25]
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 109,841 · see citing works
Diagnostic and Statistical Manual of Mental Disorders
(2012) · Springer eBooks · doi:10.1007/springerreference_121117 · Cited by 20,769 · see citing works
The SBSM Guide to Actigraphy Monitoring: Clinical and Research Applications
Ancoli‐Israel, S., Martin, J. L., BLACKWELL, T. L., Buenaver, L. F., Liu, L., Meltzer, L. J., Sadeh, A., Spira, A. P., & Taylor, D. J. (2015) · Behavioral Sleep Medicine · doi:10.1080/15402002.2015.1046356 · Cited by 561 · see citing works
Methamphetamine dependence increases risk of neuropsychological impairment in HIV infected persons
Rippeth, J. D., Heaton, R. K., Carey, C. L., Marcotte, T. D., Moore, D. J., González, R., Wolfson, T. J., Grant, I., & the HNRC Group (2004) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617704101021 · Cited by 435 · see citing works
Missing the Dark: Health Effects of Light Pollution
Chepesiuk, R. (2009) · Environmental Health Perspectives · doi:10.1289/ehp.117-a20 · Cited by 372 · see citing works
Activity monitoring in patients with depression: A systematic review
Burton, C., McKinstry, B., Szentagotai Tătar, A., Serrano-Blanco, A., Pagliari, C., & Wolters, M. (2013) · Journal of Affective Disorders · doi:10.1016/j.jad.2012.07.001 · Cited by 249 · see citing works
Issues for DSM-5: Whither Melancholia? The Case for Its Classification as a Distinct Mood Disorder
Parker, G. B., Fink, M., Shorter, E., Taylor, M. A., Akiskal, H. S., Berríos, G. E., Bolwig, T. G., Brown, W. A., Carroll, B. J., Healy, D., et al. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.09101525 · Cited by 212 · see citing works
Defining melancholia: the primacy of psychomotor disturbance
Parker, G. B. (2007) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.2007.00959.x · Cited by 87 · see citing works
Gili, M., Roca, M., Armengol, S., Asensio, D., García‐Campayo, J., & Parker, G. B. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048200 · Cited by 84 · see citing works
24-h activity rhythm and sleep in depressed outpatients
Hori, H., Koga, N., Hidese, S., Nagashima, A., Kim, Y., Higuchi, T., & Kunugi, H. (2016) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2016.02.022 · Cited by 78 · see citing works
A meta-analysis of cognitive performance in melancholic versus non-melancholic unipolar depression
Zaninotto, L., Solmi, M., Veronese, N., Guglielmo, R., Ioime, L., Camardese, G., & Serretti, A. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.04.039 · Cited by 68 · see citing works
Smagula, S. F. (2016) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000283 · Cited by 47 · see citing works
Moraes, C. Á., Cambras, T., Dı́ez-Noguera, A., Schimitt, R. L., Dantas, G., Levandovski, R. M., & Hidalgo, M. P. L. (2013) · BMC Psychiatry · doi:10.1186/1471-244x-13-77 · Cited by 45 · see citing works
Is Internal Timing Key to Mental Health?
Bhattacharjee, Y. (2007) · Science · doi:10.1126/science.317.5844.1488 · Cited by 41 · see citing works
Clinical differences between melancholic and nonmelancholic depression as defined by the CORE system
Caldieraro, M. A., Baeza, F. L. C., Pinheiro, D. O., Ribeiro, M. R., Parker, G. B., & Fleck, M. P. D. A. (2012) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2012.05.012 · Cited by 39 · see citing works
Fasmer, O. B., Hauge, E. R., Berle, J. Ø., Dilsaver, S. C., & Oedegaard, K. J. (2016) · Psychiatry Investigation · doi:10.4306/pi.2016.13.1.112 · Cited by 38 · see citing works
Quinn, C. R., Harris, A. W. F., & Kemp, A. H. (2012) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617711001858 · Cited by 30 · see citing works
Lin, C., Huang, C., & Liu, S.-K. (2015) · Psychiatry Research · doi:10.1016/j.psychres.2015.11.009 · Cited by 15 · see citing works
Flagged first, then by citations
Cited by
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Circadian depression: A mood disorder phenotype
Carpenter, J. S., Crouse, J. J., Scott, E. M., Naismith, S. L., Wilson, C., Scott, J., Merikangas, K. R., & Hickie, I. B. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.02.045 · Cited by 114 · see citing works
Using digital phenotyping to accurately detect depression severity
Jacobson, N. C., Weingarden, H., & Wilhelm, S. (2019) · Journal of Nervous & Mental Disease · doi:10.1097/nmd.0000000000001042 · Cited by 94 · see citing works
Digital phenotype of mood disorders: A conceptual and critical review
Maatoug, R., Oudin, A., Adrien, V., Saudreau, B., Bonnot, O., Millet, B., Ferreri, F., Mouchabac, S., & Bourla, A. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.895860 · Cited by 43 · see citing works
Depression Level Classification Using Machine Learning Classifiers Based on Actigraphy Data
Choi, J., Ko, I., & Han, S. (2021) · IEEE Access · doi:10.1109/access.2021.3105393 · Cited by 31 · see citing works
Minaeva, O., Riese, H., Lamers, F., Antypa, N., Wichers, M., & Booij, S. H. (2020) · Journal of Medical Internet Research · doi:10.2196/22634 · Cited by 28 · see citing works
Vignapiano, A., Monaco, F., Pagano, C., Piacente, M., Farina, F., Petrillo, G., Sica, R., Marenna, A., Shin, J. I., Solmi, M., et al. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1321345 · Cited by 14 · see citing works
Taliaz, D., & Souery, D. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10143109 · Cited by 14 · see citing works
Piccin, J., Viduani, A. C., Buchweitz, C., Pereira, R. B., Zimerman, A., Amando, G. R., Cosenza, V., Ferreira, L. Z., McMahon, N. A. G., de Melo, R. F., et al. (2023) · JAACAP Open · doi:10.1016/j.jaacop.2023.11.002 · Cited by 14 · see citing works
Peis, I., López-Moríñigo, J.-D., Pérez-Rodríguez, M. M., Barrigón, M. L., Ruiz-Gómez, M., Artés-Rodrı́guez, A., & Baca‐García, E. (2020) · Scientific Reports · doi:10.1038/s41598-020-74425-x · Cited by 11 · see citing works
Validation of the English version of the Mood Rhythm Instrument
de Oliveira, M. A. B., Epifano, K., Mathur, S., Carvalho, F. G., Medeiros, M. S., Carissimi, A., Francisco, A. P., Garay, L. L. D. S., Adán, A., Hidalgo, M. P. L., et al. (2020) · BMC Psychology · doi:10.1186/s40359-020-00397-2 · Cited by 9 · see citing works
The Revised Mood Rhythm Instrument: A Large Multicultural Psychometric Study
de Oliveira, M. A. B., Filho, E. J. D. M., Carissimi, A., Garay, L. L. D. S., Medeiros, M. S., Bandeira, D. R., Carvalho, F. G., Mathur, S., Epifano, K., Adán, A., et al. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10030388 · Cited by 7 · see citing works
Circadian Strain, Light Exposure, and Depressive Symptoms in Rural Communities of Southern Brazil
Pilz, L. K., Xavier, N. B., Levandovski, R. M., de Oliveira, M. A. B., Tonon, A. C., Constantino, D. B., Machado, V., Roenneberg, T., & Hidalgo, M. P. L. (2022) · Frontiers in Network Physiology · doi:10.3389/fnetp.2021.779136 · Cited by 7 · see citing works
Minaeva, O., Riese, H., Booij, S. H., Lamers, F., Giltay, E., Scheer, F., & Hu, K. (2024) · Psychological Medicine · doi:10.1017/s0033291724002769 · Cited by 6 · see citing works
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 · see citing works
Prospects of machine learning applications in affective disorders
Mosolova, E., Alfimov, A. Е., Kostyukova, E. G., & Mosolov, S. N. (2025) · Digital Diagnostics · doi:10.17816/dd634885 · Cited by 4 · see citing works
Digital Phenotype of Mood Disorders: a conceptual and critical review (Preprint)Preprint
Maatoug, R., Oudin, A., Adrien, V., Saudreau, B., Bonnot, O., Millet, B., Ferreri, F., Mouchabac, S., & Bourla, A. (2021) · doi:10.2196/preprints.36054
Amando, G. R., Xavier, N. B., Borges, R. B., da Mota, M. S. S., Pereira, R. B., Manfro, P. H., Rohrsetzer, F., Piccin, J., Souza, L., Nexha, A., et al. (2025) · Chronobiology International · doi:10.1080/07420528.2025.2496345
Additional file 1 of Validation of the English version of the Mood Rhythm Instrument
Oliveira, M. A. B., Epifano, K., Mathur, S., Carvalho, F. G., Scop, M., Carissimi, A., Francisco, A. P., Garay, L. L. D. S., Adán, A., Hidalgo, M. P. L., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12150993
Orzechowski, R., Amando, G. R., França, B. R., Tocchetto, B. F., Pilz, L. K., de Souza, A. F., Hirakata, V. N., Fregni, F., Hidalgo, M. P., & Caumo, W. (2026) · Behavioral Sleep Medicine · doi:10.1080/15402002.2026.2648511
Biological heterogeneity of melancholic, atypical, anxious, and psychotic depression
Nadei, O. V., & Ternovaya, E. V. (2026) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2026.111923
- Authors
- Tonon, A. C., Fuchs, D. F. P., Barbosa Gomes, W., Levandovski, R., Pio de Almeida Fleck, M., Hidalgo, M. P. L., & da Silva Alencastro, L.
- Affiliations
- Universidade Federal do Rio Grande do Sul (BR)
- Corresponding author
- Tonon, André Comiran
- Venue
- Psychiatry Research
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 258
- Pages
- 587-590
- ISSN
- 0165-1781 (ISSN-L)
- OpenAlex
- W2748311435
- Cited by
- 20
- References
- 18
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 1 · 2023: 2 · 2022: 3 · 2021: 5 · 2020: 4 · 2019: 1
- FWCI
- 1.77
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-sa
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Psychiatry Research (publishedVersion)
- PubMed (publishedVersion)
- Lume (Universidade Federal do Rio Grande do Sul) (submittedVersion, cc-by-nc-sa)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- endogenous depression, non-melancholic depression, depression subtypes, actigraphy, light exposure, circadian rhythm, psychomotor disorders
- MeSH terms
- Adult, Circadian Rhythm, Darkness, Depressive Disorder, Female, Humans, Male, Middle Aged, Motor Activity, Psychomotor Disorders, ROC Curve, Sensitivity and Specificity, Area Under Curve, Actigraphy, Depressive Disorder, Treatment-Resistant
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