One-year actigraphy study of sleep and rest-activity rhythms as markers of relapse in depression
Open accessAbstract
Importance: Given its recurrent nature and burden, major depressive disorder (MDD) warrants reliable methods of relapse prediction. Objective: To determine whether actigraphy-derived parameters, measured over 1 to 2 years, are associated with relapse. Design, Setting, and Participants: This was an observational cohort study with data collection from July 2016 to January 2019. The setting was multicentric. A referred sample of participants from outpatient psychiatric and primary care clinics across Canada were followed up for 1 to 2 years. Participants had a diagnosis of MDD and Montgomery-Åsberg Depression Rating Scale (MADRS) score less than or equal to 14 at baseline. Exposures: Actigraphy-derived parameters measured over 1 to 2 years. Main Outcome and Measures: The primary outcome was relapse, defined as any of the following: MADRS score greater than or equal to 22 for 2 consecutive weeks, psychiatric hospitalization, emergence of suicidal intent or behavior, or antidepressant treatment escalation—all adjudicated by an independent panel. Continuous actigraphy data were averaged every 2 weeks. Results: From a referred sample of 102 adults, 93 participants (mean [SD] age, 39.1 [12.7] years; 58 female [62%]) contributed approximately 32 000 complete actigraphy days (median, 46 weeks). In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (hazard ratio [HR], 0.46; 95% CI, 0.28-0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29-0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38-0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12-2.80; P = .01), and higher nighttime activity (HR, 1.86; 95% CI, 1.32-2.62; P < .001) were associated with relapse. In time-varying models, greater composite phase deviation (HR, 1.76; 95% CI, 1.04-2.98; P = .04) and lower RA (HR, 0.45; 95% CI, 0.21-0.97; P = .046) were associated with relapse, with RA remaining significant even after adjusting for concurrent MADRS scores (HR, 0.60; 95% CI, 0.36-0.98; P = .04). Actigraphy significantly differentiated individuals experiencing relapse from those with an ultrastable (MADRS score <14 throughout) and unstable (transient MADRS score, 14-22 without relapse) clinical course. Conclusions and Relevance: Actigraphy measures of sleep phase variability and daily activity amplitude were associated with depressive relapse, supporting actigraphy as a potential scalable biomarker to identify high-risk individuals and enable timely, personalized relapse prevention in MDD.
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TL;DR
In a multicentre observational cohort of adults with remitted major depressive disorder followed for 1–2 years, actigraphy-derived sleep and rest-activity rhythm parameters were associated with depressive relapse. Lower relative amplitude and greater sleep phase variability emerged as the most robust markers, with relative amplitude remaining significant after adjustment for concurrent depressive symptoms.
Key findings
- In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (HR, 0.46; 95% CI, 0.28–0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29–0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38–0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12–2.80; P = .01), and higher nighttime activity (HR, 1.86; 95% CI, 1.32–2.62; P < .001) were associated with relapse.
- In time-varying models, greater composite phase deviation (HR, 1.76; 95% CI, 1.04–2.98; P = .04) and lower RA (HR, 0.45; 95% CI, 0.21–0.97; P = .046) were associated with relapse; RA remained significant after adjusting for concurrent MADRS scores (HR, 0.60; 95% CI, 0.36–0.98; P = .04).
- Actigraphy significantly differentiated individuals who relapsed from those with an ultrastable clinical course (MADRS score <14 throughout) and an unstable course (transient MADRS score 14–22 without relapse).
Methods
- Design: observational, multicentre cohort study with data collection from July 2016 to January 2019; participants followed up for 1 to 2 years.
- Sample: referred sample from outpatient psychiatric and primary care clinics across Canada; 102 adults with MDD and baseline MADRS ≤14, of whom 93 (mean [SD] age, 39.1 [12.7] years; 58 female [62%]) contributed approximately 32,000 complete actigraphy days (median, 46 weeks).
- Analysis: actigraphy-derived parameters averaged every 2 weeks; relapse (MADRS ≥22 for 2 consecutive weeks, psychiatric hospitalization, emergence of suicidal intent or behavior, or antidepressant treatment escalation, adjudicated by an independent panel) modelled with Cox models adjusted for age, sex, season, and baseline MADRS, plus time-varying models.
Limitations
- Not stated in the paper (the available text is the abstract and record; no limitations section is included).
- Evident from the text: the sample was a referred clinical sample, which may limit generalizability; the abstract does not report model discrimination, calibration, or a validation sample, so the predictive performance of actigraphy as a scalable biomarker is not quantified here.
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Claims the paper makes
- Findingown data§ Abstract
Baseline higher nighttime activity is associated with relapse in Cox models adjusted for age, sex, season, and baseline MADRS score (HR, 1.86; 95% CI, 1.32-2.62; P < .001).
“In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (hazard ratio [HR], 0.46; 95% CI, 0.28-0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29-0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38-0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12-2.80; P = .01), and higher nighttime activity (HR, 1.”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Baseline lower relative amplitude (RA) is associated with relapse in Cox models adjusted for age, sex, season, and baseline MADRS score (HR, 0.45; 95% CI, 0.29-0.70; P < .001).
“In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (hazard ratio [HR], 0.46; 95% CI, 0.28-0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29-0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38-0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12-2.80; P = .01), and higher nighttime activity (HR, 1.”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Greater composite phase deviation is associated with relapse in time-varying models (HR, 1.76; 95% CI, 1.04-2.98; P = .04).
“In time-varying models, greater composite phase deviation (HR, 1.76; 95% CI, 1.04-2.98; P = .04) and lower RA (HR, 0.45; 95% CI, 0.21-0.97; P = .046) were associated with relapse, with RA remaining significant even after adjusting for concurrent MADRS scores (HR, 0.60; 95% CI, 0.36-0.98; P = .04).”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Lower relative amplitude (RA) remains significantly associated with relapse after adjusting for concurrent MADRS scores (HR, 0.60; 95% CI, 0.36-0.98; P = .04).
“In time-varying models, greater composite phase deviation (HR, 1.76; 95% CI, 1.04-2.98; P = .04) and lower RA (HR, 0.45; 95% CI, 0.21-0.97; P = .046) were associated with relapse, with RA remaining significant even after adjusting for concurrent MADRS scores (HR, 0.60; 95% CI, 0.36-0.98; P = .04).”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Baseline higher wake after sleep onset is associated with relapse in Cox models adjusted for age, sex, season, and baseline MADRS score (HR, 1.77; 95% CI, 1.12-2.80; P = .01).
“In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (hazard ratio [HR], 0.46; 95% CI, 0.28-0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29-0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38-0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12-2.80; P = .01), and higher nighttime activity (HR, 1.”
Quote in the paperSubstantial claim
- Findingown data§ Abstract
Baseline lower sleep regularity is associated with relapse in Cox models adjusted for age, sex, season, and baseline MADRS score (HR, 0.46; 95% CI, 0.28-0.74; P = .002).
“In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (hazard ratio [HR], 0.46; 95% CI, 0.28-0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29-0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38-0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12-2.80; P = .01), and higher nighttime activity (HR, 1.”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Baseline lower sleep efficiency is associated with relapse in Cox models adjusted for age, sex, season, and baseline MADRS score (HR, 0.57; 95% CI, 0.38-0.85; P = .005).
“In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (hazard ratio [HR], 0.46; 95% CI, 0.28-0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29-0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38-0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12-2.80; P = .01), and higher nighttime activity (HR, 1.”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Lower relative amplitude (RA) is associated with relapse in time-varying models (HR, 0.45; 95% CI, 0.21-0.97; P = .046).
“In time-varying models, greater composite phase deviation (HR, 1.76; 95% CI, 1.04-2.98; P = .04) and lower RA (HR, 0.45; 95% CI, 0.21-0.97; P = .046) were associated with relapse, with RA remaining significant even after adjusting for concurrent MADRS scores (HR, 0.60; 95% CI, 0.36-0.98; P = .04).”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Actigraphy significantly differentiated individuals experiencing relapse from those with an ultrastable clinical course (MADRS score <14 throughout) and an unstable clinical course (transient MADRS score, 14-22 without relapse).
“Actigraphy significantly differentiated individuals experiencing relapse from those with an ultrastable (MADRS score <14 throughout) and unstable (transient MADRS score, 14-22 without relapse) clinical course.”
Quote in the paperSubstantial claim - Interpretationown data§ Abstract
Actigraphy measures of sleep phase variability and daily activity amplitude are associated with depressive relapse.
“Actigraphy measures of sleep phase variability and daily activity amplitude were associated with depressive relapse, supporting actigraphy as a potential scalable biomarker to identify high-risk individuals and enable timely, personalized relapse prevention in MDD.”
Quote in the paperSubstantial claim - Interpretationown data§ Abstract
Actigraphy is a potential scalable biomarker to identify high-risk individuals with MDD.
“Actigraphy measures of sleep phase variability and daily activity amplitude were associated with depressive relapse, supporting actigraphy as a potential scalable biomarker to identify high-risk individuals and enable timely, personalized relapse prevention in MDD.”
Quote in the paperSubstantial claim- Rests on an assumption: Major depressive disorder is recurrent and burdensome.
- Study design and conductown data§ Abstract
The time-varying analysis of relative amplitude adjusted for concurrent MADRS scores.
“with RA remaining significant even after adjusting for concurrent MADRS scores”
Quote in the paperSubstantial claim - Interpretationreasoning§ Abstract
Actigraphy could enable timely, personalized relapse prevention in MDD.
“Actigraphy measures of sleep phase variability and daily activity amplitude were associated with depressive relapse, supporting actigraphy as a potential scalable biomarker to identify high-risk individuals and enable timely, personalized relapse prevention in MDD.”
Quote in the paperSubstantial claim- Rests on an assumption: Major depressive disorder is recurrent and burdensome.
- Classified as probably not a substantial claim. 2
Classified as probably not a substantial claim.
Study design and conductnone given§ AbstractRelapse was adjudicated by an independent panel.
“all adjudicated by an independent panel”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductown data§ AbstractCox models were adjusted for age, sex, season, and baseline MADRS score.
“In Cox models adjusted for age, sex, season, and baseline MADRS score”
Quote in the paperSubstantial claim
The paper relies on this without support.
Major depressive disorder is recurrent and burdensome.
“Given its recurrent nature and burden, major depressive disorder (MDD) warrants reliable methods of relapse prediction.”
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The extracted medians showed substantial heterogeneity, ranging from very early relapse in severe or treatment-resistant samples with medians between 53 and 90 days to substantially longer intervals in maintenance-treated populations (218-294 days).
“The extracted medians showed substantial heterogeneity, ranging from very early relapse in severe or treatment−resistant samples with medians between 53 and 90 days (14, 21, 23, 38) to substantially longer intervals in maintenance−treated populations (218–294 days) (33, 40, 45).”
From Administrative criteria in the relapse of depressive disorder: a critical appraisal (2026) · cites this paper as [45]
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Self-citationEdinger, J. D., Eldridge-Smith, E. D., Buysse, D. J., Thase, M. E., Krystal, A. D., Wiskniewski, S., & Manber, R. (2023) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.10514 · Cited by 13 · see citing works
Handling missing data in rest-activity time series measured by actimetry
Tonon, A. C., Pilz, L. K., Amando, G. R., Constantino, D. B., Borges, R. B., Caye, A., Rohrsetzer, F., Souza, L., Fisher, H. L., Kohrt, B. A., et al. (2022) · Chronobiology International · doi:10.1080/07420528.2022.2051714 · Cited by 12 · see citing works
Self-citationBurghoorn, D. G., Booij, S. H., Schoevers, R. A., & Riese, H. (2024) · BJPsych Open · doi:10.1192/bjo.2024.789 · Cited by 7 · see citing works
Lam, R. W., Rnic, K., Nunez, J.-J., Ho, K., LeMoult, J., Nunes, A., Chakrabarty, T., Foster, J. A., Frey, B. N., Harkness, K. L., et al. (2025) · The Canadian Journal of Psychiatry · doi:10.1177/07067437251337603 · Cited by 6 · see citing works
Self-citationPrognostic models for predicting relapse or recurrence of depression
Moriarty, A. S., Meader, N., Gilbody, S. M., Chew-Graham, C. A., Churchill, R. C., Ali, S., Phillips, R. S., Riley, R. D., & McMillan, D. (2019) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd013491 · Cited by 5 · see citing works
Yang, H.-J., Cheng, W., Hsiao, M.-C., Huang, S.-C., Kubo, T., Hang, L., & Lee, C. W. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1214143 · Cited by 5 · see citing works
Nunes, A., Pavlova, B., Cunningham, J. E. A., Nuñez, J.-J., Quilty, L. C., Foster, J. A., Harkness, K. L., Ho, K., Lam, R. W., Li, Q. S., et al. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.06.023 · Cited by 5 · see citing works
Self-citationSymptom network connectivity indices as predictors of relapse in major depressive disorder
Nunes, A., Pavlová, B., Nuñez, J.-J., Quilty, L. C., Foster, J. A., Harkness, K. L., Ho, K. T., Lam, R. W. M., Li, Q. S., Milev, R. V., et al. (2025) · Psychiatry Research · doi:10.1016/j.psychres.2025.116562 · Cited by 5 · see citing works
Self-citation
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Administrative criteria in the relapse of depressive disorder: a critical appraisal
Bernal-Cueto, S., Cegla-Schvartzman, F., & Baca-García, E. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1796386
“%) articles included in the review (1, 2, 4 – 7, 9 – 17, 19 – 21, 23 – 31, 34, 35, 41 – 45, 47 – 52, 54, 55).”
Confounding and Circularity in Actigraphy Prediction
Xiao, Y. (2026) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2026.1290
Confounding and Circularity in Actigraphy Prediction—Reply
Tonon, A. C., & Frey, B. N. (2026) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2026.1293
Self-citationDigital conversation companions
Helmchen, L. A., George, A. S., Ghiassi, A., & Bam, D. (2026) · The Gerontologist · doi:10.1093/geront/gnag151
Thelagathoti, R. K., Vijaya Saraswathi, R., Dinkel, D. M., Ali, H., & Fernando, R. M. (2026) · Sensors · doi:10.3390/s26134168
Longitudinal course is an essential dimension in psychiatric classification
Khayachi, A., Ortiz, A., & Alda, M. (2026) · Journal of Psychiatry and Neuroscience · doi:10.1139/jpn-2026-0070
Takano, Y., Okajima, I., Sumi, Y., & Kadotani, H. (2026) · Sleep Medicine · doi:10.1016/j.sleep.2026.109227
Wearable sensors offer opportunities for phenotyping perinatal mood disorders: a narrative review
Carrioli, O., Bruce, L. K., Kriplani, S. M., Schaap, T., Stewart, C., & Smarr, B. L. (2026) · Reproduction · doi:10.1093/reprod/xaag115
Wu, Q., Fan, X., & Qi, X. (2026) · Health Nexus Digital Health and Medical AI · doi:10.63802/hndh.v1.i1.358
- Authors
- Tonon, A. C., Nexha, A., Cunningham, J. E. A., d’Eon, J., Chakrabarty, T., Farzan, F., Foster, J. A., Harkness, K. L., Hassel, S., Ho, K., Lam, R. W., Milev, R., Minuzzi, L., Müller, D. J., Nunes, A., Parikh, S. V., Quilty, L. C., Rotzinger, S., Soares, C. N., Taylor, V. H., Turecki, G., Uher, R., Kennedy, S. H., & Frey, B. N.
- Affiliations
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
- McMaster University (CA)
- Dalhousie University (CA)
- University of British Columbia (CA)
- Simon Fraser University (CA)
- The University of Texas Southwestern Medical Center (US)
- Queen's University (CA)
- University of Calgary (CA)
- St. Joseph’s Healthcare Hamilton (CA)
- University of Toronto (CA)
- University of Michigan (US)
- Centre for Addiction and Mental Health (CA)
- McGill University (CA)
- ORCID
- Venue
- JAMA Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 2026-04-01
- Volume
- 83
- Issue
- 4
- Pages
- 379
- ISSN
- 2168-622X (ISSN-L)
- OpenAlex
- W7128591209
- Semantic Scholar
- 24c8bf47bd26ad70550fbb0df57e8d87e3030877
- Cited by
- 9
- References
- 58
- Citations by year
- 2026: 9
- FWCI
- 69.01
- Type
- journal article
- Language
- en
- Open access
- Locations
- JAMA Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- 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
- actigraphy, sleep-wake cycle, rest-activity rhythm, depression relapse, major depressive disorder, recurrence prediction, sleep regularity, relative amplitude, sleep efficiency, wake after sleep onset, nighttime activity, seasonal variation, seasonal affective disorder
- MeSH terms
- Adult, Major Depressive Disorder, Female, Humans, Male, Middle Aged, Recurrence, Rest, Sleep, Cohort Studies, Actigraphy
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.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
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 ›
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