Co-Variation of Depressive Mood and Locomotor Dynamics Evaluated by Ecological Momentary Assessment in Healthy Humans
Open accessAbstract
Computerized ecological momentary assessment (EMA) is widely accepted as a "gold standard" method for capturing momentary symptoms repeatedly experienced in daily life. Although many studies have addressed the within-individual temporal variations in momentary symptoms compared with simultaneously measured external criteria, their concurrent associations, specifically with continuous physiological measures, have not been rigorously examined. Therefore, in the present study, we first examined the variations in momentary symptoms by validating the associations among self-reported symptoms measured simultaneously (depressive mood, anxious mood, and fatigue) and then investigated covariant properties between the symptoms (especially, depressive mood) and local statistics of locomotor activity as the external objective criteria obtained continuously. Healthy subjects (N = 85) from three different populations (adolescents, undergraduates, and office workers) wore a watch-type computer device equipped with EMA software for recording the momentary symptoms experienced by the subjects. Locomotor activity data were also continuously obtained by using an actigraph built into the device. Multilevel modeling analysis confirmed convergent associations by showing positive correlations among momentary symptoms. The increased intermittency of locomotor activity, characterized by a combination of reduced activity with occasional bursts, appeared concurrently with the worsening of depressive mood. Further, this association remained statistically unchanged across groups regardless of group differences in age, lifestyle, and occupation. These results indicate that the temporal variations in the momentary symptoms are not random but reflect the underlying changes in psychophysiological variables in daily life. In addition, our findings on the concurrent changes in depressive mood and locomotor activity may contribute to the continuous estimation of changes in depressive mood and early detection of depressive disorders.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A study on the relationship between mood and physical activity using wearable actigraphs (n = 85) showed that distinct activity patterns correspond with worsening depressive symptoms.
“A study on the relationship between mood and physical activity using wearable actigraphs (n = 85) showed that distinct activity patterns correspond with worsening depressive symptoms [96].”
From Wearables and the Medical Revolution (2018) · cites this paper as [96]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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
Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence
Singer, J. D., & Willett, J. B. (2003) · doi:10.1093/acprof:oso/9780195152968.001.0001 · Cited by 10,647 · see citing works
The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490 · cited 1× · see citing works
“For the univariate multilevel modeling, a false discovery rate (FDR) procedure [50] was performed at a q value of 0.”
MethodDiagnostic and Statistical Manual of Mental Disorders
Siegel, L. J., & Fletcher‐Janzen, E. (2008) · Wiley eBooks · doi:10.1002/9780470373699.speced0655 · Cited by 8,468 · see citing works
Ecological momentary assessment
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.3.022806.091415 · Cited by 6,454 · see citing works
A Survey Method for Characterizing Daily Life Experience: The Day Reconstruction Method
Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004) · Science · doi:10.1126/science.1103572 · Cited by 3,422 · cited 1× · see citing works
“Showing such associations is considered to be important because locomotor activity can be measured in a truly continuous manner, and finding objective correlates of momentary mood scores can compensate for a known drawback of EMA that the data based on sparse sampling may not provide contiguous data despite high level…”
BackgroundLooking for Spinoza: Joy, Sorrow, and the Feeling Brain
Gross, H. S. (2004) · The Journal of Nervous and Mental Disease · doi:10.1097/01.nmd.0000130139.70393.da · Cited by 2,053 · see citing works
Ecological Momentary Assessment (Ema) in Behavioral Medicine
Stone, A. A., & Shiffman, S. (1994) · Annals of Behavioral Medicine · doi:10.1093/abm/16.3.199 · Cited by 1,931 · cited 4× · see citing works
“Collecting data in natural settings can enhance the validity of measurements, thus avoiding the pitfalls of retrospective recall, which highly distort self-report data collection [1].”
BackgroundInfluentialLooking for Spinoza : Joy, Sorrow, and the Feeling Brain
Damásio, A. R. (2003) · Dominican Scholar (Dominican University of California) · Cited by 1,879 · see citing works
Suls, J., & Bunde, J. (2005) · Psychological Bulletin · doi:10.1037/0033-2909.131.2.260 · Cited by 878 · cited 1× · see citing works
“Various studies demonstrate the covariation between depressive and anxious moods, suggesting the possibility to categorize them into the same class of a broader negative affect dimension [51,52,53].”
BackgroundPhysical Activity Reduces the Risk of Subsequent Depression for Older Adults
Strawbridge, W. J. (2002) · American Journal of Epidemiology · doi:10.1093/aje/kwf047 · Cited by 818 · cited 1× · see citing works
“The associations between depressive mood and alterations in the levels and patterns of locomotor activity have been shown in epidemiological samples [39,40,41,42,43] and clinical depression [31,32], but the underlying mechanism is unknown.”
BackgroundPatient non-compliance with paper diaries
Stone, A. A., Shiffman, S., Schwartz, J. E., Broderick, J. E., & Hufford, M. R. (2002) · BMJ · doi:10.1136/bmj.324.7347.1193 · Cited by 810 · cited 1× · see citing works
“, “faked compliance”) [3].”
Physical Activity and Depression: Evidence from the Alameda County Study
Camacho, T. C., ROBERTS, R. E., LAZARUS, N. B., Kaplan, G. A., & Cohen, R. D. (1991) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116074 · Cited by 654 · cited 1× · see citing works
“The associations between depressive mood and alterations in the levels and patterns of locomotor activity have been shown in epidemiological samples [39,40,41,42,43] and clinical depression [31,32], but the underlying mechanism is unknown.”
BackgroundStrategies for analyzing ecological momentary assessment data.
Schwartz, J. E., & Stone, A. A. (1998) · Health Psychology · doi:10.1037//0278-6133.17.1.6 · Cited by 631 · see citing works
van Eck, M., Berkhof, H., Nicolson, N., & Sulon, J. (1996) · Psychosomatic Medicine · doi:10.1097/00006842-199609000-00007 · Cited by 617 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundStrategies for analyzing ecological momentary assessment data.
Schwartz, J. E., & Stone, A. A. (1998) · Health Psychology · doi:10.1037/0278-6133.17.1.6 · Cited by 484 · cited 1× · see citing works
“, individual differences such as age, gender and occupation) [49], using SAS Proc Mixed (SAS 9.”
MethodSTRESSORS AND MOOD MEASURED ON A MOMENTARY BASIS ARE ASSOCIATED WITH SALIVARY CORTISOL SECRETION
Smyth, J. M., Ockenfels, M. C., Porter, L. S., Kirschbaum, C., Hellhammer, D. H., & Stone, A. A. (1998) · Psychoneuroendocrinology · doi:10.1016/s0306-4530(98)00008-0 · Cited by 468 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundThieme, K., Turk, D. C., & Flor, H. (2004) · Psychosomatic Medicine · doi:10.1097/01.psy.0000146329.63158.40 · Cited by 465 · cited 1× · see citing works
“Various studies demonstrate the covariation between depressive and anxious moods, suggesting the possibility to categorize them into the same class of a broader negative affect dimension [51,52,53].”
BackgroundTrends in Ambulatory Self-Report
Conner, T. S., & Barrett, L. F. (2012) · Psychosomatic Medicine · doi:10.1097/psy.0b013e3182546f18 · Cited by 365 · cited 1× · see citing works
“communication technology (ICT) [4,5].”
Core symptoms of major depressive disorder: relevance to diagnosis and treatment
Kennedy, S. H. (2008) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2008.10.3/shkennedy · Cited by 353 · cited 1× · see citing works
“For example, fatigue is a common complaint in depressive patients [54,55,56,57].”
BackgroundThe Science of Real-Time Data Capture: Self-Reports in Health Research
Atienza, A. A. (2007) · Cited by 289 · see citing works
The many faces of fatigue in major depressive disorder
Demyttenaere, K., De Fruyt, J., & Stahl, S. M. (2005) · The International Journal of Neuropsychopharmacology · doi:10.1017/s1461145704004729 · Cited by 288 · cited 1× · see citing works
“For example, fatigue is a common complaint in depressive patients [54,55,56,57].”
BackgroundEcological Momentary Assessment
Kirchner, T., & Shiffman, S. S. (2013) · Wiley eBooks · doi:10.1002/9781118384404.ch20 · Cited by 286 · see citing works
Physical activity, exercise coping, and depression in a 10-year cohort study of depressed patients
Harris, A. H. S., Cronkite, R. C., & Moos, R. H. (2006) · Journal of Affective Disorders · doi:10.1016/j.jad.2006.02.013 · Cited by 258 · cited 1× · see citing works
“The associations between depressive mood and alterations in the levels and patterns of locomotor activity have been shown in epidemiological samples [39,40,41,42,43] and clinical depression [31,32], but the underlying mechanism is unknown.”
BackgroundFluctuations in self-esteem and paranoia in the context of daily life.
Thewissen, V., Bentall, R. P., Lecomte, T., van Os, J., & Myin‐Germeys, I. (2008) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.117.1.143 · Cited by 254 · cited 1× · see citing works
“self-reported symptoms [7,8,9].”
Stone, A. A., Broderick, J. E., Shiffman, S. S., & Schwartz, J. E. (2003) · Pain · doi:10.1016/j.pain.2003.09.020 · Cited by 252 · cited 1× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundActivity 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 · cited 3× · see citing works
“Lower or higher mean activity levels could quantify the states related to psychomotor retardation or agitation, respectively [24,26].”
BackgroundMobile Health: Revolutionizing Healthcare Through Transdisciplinary Research
Kumar, S., Nilsen, W., Misha Pavel, C., & Srivastava, M. B. (2013) · Computer · doi:10.1109/mc.2012.392 · Cited by 243 · see citing works
Stone, A. A., Broderick, J. E., Porter, L. S., & Kaell, A. T. (1997) · Arthritis & Rheumatism · doi:10.1002/art.1790100306 · Cited by 240 · cited 1× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundActigraphy and Motion Analysis: New Tools for Psychiatry
Teicher, M. H. (1995) · Harvard Review of Psychiatry · doi:10.3109/10673229509017161 · Cited by 231 · cited 4× · see citing works
“Lower or higher mean activity levels could quantify the states related to psychomotor retardation or agitation, respectively [24,26].”
BackgroundInfluentialStone, A. A., Schwartz, J. E., Schkade, D. A., Schwarz, N., Krueger, A. B., & Kahneman, D. J. (2006) · Emotion · doi:10.1037/1528-3542.6.1.139 · Cited by 227 · cited 1× · see citing works
“Showing such associations is considered to be important because locomotor activity can be measured in a truly continuous manner, and finding objective correlates of momentary mood scores can compensate for a known drawback of EMA that the data based on sparse sampling may not provide contiguous data despite high level…”
BackgroundTylee, A. T., Gastpar, M., Lépine, J., & MENDLEWICZ, J. (1999) · International Clinical Psychopharmacology · doi:10.1097/00004850-199905002-00001 · Cited by 221 · see citing works
Shiffman, S., Balabanis, M. H., Gwaltney, C., Paty, J., Gnys, M., Kassel, J. D., Hickcox, M., & Paton, S. M. (2007) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2007.05.017 · Cited by 219 · cited 1× · see citing works
“In addition, some studies demonstrated that addictive behaviors such as smoking [18,19] and alcohol consumption [20,21] are related to the fluctuations in psychological states, e.”
BackgroundDaily Fluctuations in Self-Control Demands and Alcohol Intake.
Muraven, M., Collins, R. L., Shiffman, S., & Paty, J. A. (2005) · Psychology of Addictive Behaviors · doi:10.1037/0893-164x.19.2.140 · Cited by 211 · cited 1× · see citing works
“In addition, some studies demonstrated that addictive behaviors such as smoking [18,19] and alcohol consumption [20,21] are related to the fluctuations in psychological states, e.”
BackgroundSteptoe, A., Gibson, E. L., Hamer, M., & Wardle, J. (2006) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2006.10.001 · Cited by 210 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundA time-lagged momentary assessment study on daily life physical activity and affect.
Wichers, M., Peeters, F., Rutten, B. P. F., Jacobs, N., Derom, C., Thiery, E., Delespaul, P., & van Os, J. (2012) · Health Psychology · doi:10.1037/a0025688 · Cited by 199 · cited 1× · see citing works
“Furthermore, the associations of momentary psychological states with self-reported physical activity were demonstrated [22,23].”
BackgroundKamarck, T. W., Shiffman, S. M., Smithline, L., Goodie, J. L., Paty, J. A., Gnys, M., & Jong, J. Y.-K. (1998) · Health Psychology · doi:10.1037/0278-6133.17.1.17 · Cited by 195 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundLindwall, M., Larsman, P., & Hagger, M. S. (2011) · Health Psychology · doi:10.1037/a0023268 · Cited by 193 · cited 1× · see citing works
“The associations between depressive mood and alterations in the levels and patterns of locomotor activity have been shown in epidemiological samples [39,40,41,42,43] and clinical depression [31,32], but the underlying mechanism is unknown.”
BackgroundUniversal Scaling Law in Human Behavioral Organization
Nakamura, T., Kiyono, K., Yoshiuchi, K., Nakahara, R., Struzik, Z. R., & Yamamoto, Y. (2007) · Physical Review Letters · doi:10.1103/physrevlett.99.138103 · Cited by 157 · cited 5× · see citing works
“Higher skewness could characterize the intermittent bursts of locomotor activity [31,32,48].”
BackgroundResultInfluentialSelf-citationKimhy, D., Delespaul, P., Corcoran, C. M., Ahn, H., Yale, S. A., & Malaspina, D. (2005) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2005.09.007 · Cited by 148 · cited 1× · see citing works
“self-reported symptoms [7,8,9].”
Berle, J. Ø., Hauge, E. R., Oedegaard, K. J., Holsten, F., & Fasmer, O. B. (2010) · BMC Research Notes · doi:10.1186/1756-0500-3-149 · Cited by 140 · cited 1× · see citing works
“It is considered that momentary micro-fluctuations in behavioral data, specifically those in locomotor activity capturing bodily acceleration counts in a continuous fashion, reflect the dynamics of systems organizing human behavior and can be used to probe behavioral disorders, including mental illnesses [24,25,26,27,…”
BackgroundBleil, M. E., Gianaros, P. J., Jennings, J. R., Flory, J. D., & Manuck, S. B. (2008) · Psychosomatic Medicine · doi:10.1097/psy.0b013e31816baefa · Cited by 128 · cited 1× · see citing works
“Various studies demonstrate the covariation between depressive and anxious moods, suggesting the possibility to categorize them into the same class of a broader negative affect dimension [51,52,53].”
BackgroundSymptoms of fatigue and sleepiness in major depressive disorder.
Baldwin, D. S., & Papakostas, G. I. (2006) · PubMed · Cited by 125 · see citing works
Dunton, G. F., Atienza, A. A., Castro, C. M., & King, A. C. (2009) · Annals of Behavioral Medicine · doi:10.1007/s12160-009-9141-4 · Cited by 122 · cited 1× · see citing works
“Furthermore, the associations of momentary psychological states with self-reported physical activity were demonstrated [22,23].”
BackgroundPsychosocial Stress and Cardiovascular Risk: What is the Role of Daily Experience?
Kamarck, T. W., Schwartz, J. E., Shiffman, S. S., Muldoon, M. F., Sutton‐Tyrrell, K., & Janicki, D. L. (2005) · Journal of Personality · doi:10.1111/j.0022-3506.2005.00365.x · Cited by 117 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundMotor activity and autonomic cardiac functioning in major depressive disorder
Volkers, A. C. W. (2002) · Journal of Affective Disorders · doi:10.1016/s0165-0327(02)00066-6 · Cited by 116 · cited 1× · see citing works
“It is considered that momentary micro-fluctuations in behavioral data, specifically those in locomotor activity capturing bodily acceleration counts in a continuous fashion, reflect the dynamics of systems organizing human behavior and can be used to probe behavioral disorders, including mental illnesses [24,25,26,27,…”
BackgroundJahng, S., Solhan, M. B., Tomko, R. L., Wood, P. K., Piasecki, T. M., & Trull, T. J. (2011) · Journal of Abnormal Psychology · doi:10.1037/a0024686 · Cited by 104 · cited 1× · see citing works
“In addition, some studies demonstrated that addictive behaviors such as smoking [18,19] and alcohol consumption [20,21] are related to the fluctuations in psychological states, e.”
BackgroundOf Mice and Men — Universality and Breakdown of Behavioral Organization
Nakamura, T., Takumi, T., Takano, A., Aoyagi, N., Yoshiuchi, K., Struzik, Z. R., & Yamamoto, Y. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002050 · Cited by 101 · cited 5× · see citing works
“Higher skewness could characterize the intermittent bursts of locomotor activity [31,32,48].”
BackgroundResultInfluentialSelf-citationStavrakakis, N., de Jonge, P., Ormel, J., & Oldehinkel, A. J. (2011) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2011.09.004 · Cited by 100 · cited 1× · see citing works
“The associations between depressive mood and alterations in the levels and patterns of locomotor activity have been shown in epidemiological samples [39,40,41,42,43] and clinical depression [31,32], but the underlying mechanism is unknown.”
BackgroundFrontal white matter integrity is related to psychomotor retardation in major depression
Walther, S., Hügli, S., Höfle, O., Federspiel, A., Horn, H., Bracht, T., Wiest, R., Strik, W. K., & Müller, T. (2012) · Neurobiology of Disease · doi:10.1016/j.nbd.2012.03.019 · Cited by 100 · cited 1× · see citing works
“It is considered that momentary micro-fluctuations in behavioral data, specifically those in locomotor activity capturing bodily acceleration counts in a continuous fashion, reflect the dynamics of systems organizing human behavior and can be used to probe behavioral disorders, including mental illnesses [24,25,26,27,…”
BackgroundCircadian Rest-Activity Disturbances in Seasonal Affective Disorder
Teicher, M. H. (1997) · Archives of General Psychiatry · doi:10.1001/archpsyc.1997.01830140034007 · Cited by 96 · cited 2× · see citing works
“In order to quantitatively evaluate such alterations, several actigraphic studies have been conducted in depression patients by showing the significant decrease in activity levels during daytime and disruption of the circadian rhythm [24,25,26].”
BackgroundBest practice in symptom assessment: a review
McColl, E. (2004) · Gut · doi:10.1136/gut.2003.034355 · Cited by 89 · cited 1× · see citing works
“Showing such associations is considered to be important because locomotor activity can be measured in a truly continuous manner, and finding objective correlates of momentary mood scores can compensate for a known drawback of EMA that the data based on sparse sampling may not provide contiguous data despite high level…”
BackgroundNeuroprotection in Schizophrenia
Jarskog, L. F., & Lieberman, J. A. (2006) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.0906e09 · Cited by 89 · see citing works
The relationship between psychologic distress and cancer‐related fatigue
Tchekmedyian, N. S., Kallich, J. D., McDermott, A. M., Fayers, P. M., & Erder, M. H. (2003) · Cancer · doi:10.1002/cncr.11463 · Cited by 84 · cited 1× · see citing works
“with these moods have also been reported in patients with cancer [59].”
BackgroundWithin-day temporal patterns of smoking, withdrawal symptoms, and craving
Chandra, S., Scharf, D., & Shiffman, S. (2011) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2010.12.027 · Cited by 84 · cited 1× · see citing works
“In addition, some studies demonstrated that addictive behaviors such as smoking [18,19] and alcohol consumption [20,21] are related to the fluctuations in psychological states, e.”
BackgroundSkapinakis, P., Lewis, G., & Mavreas, V. G. (2003) · American Journal of Psychiatry · doi:10.1176/appi.ajp.160.4.785 · Cited by 66 · cited 1× · see citing works
“In chronic fatigue syndrome, the high rate of its comorbidity with both moods has been reported [58].”
BackgroundEnhanced Persistency of Resting and Active Periods of Locomotor Activity in Schizophrenia
Sano, W., Nakamura, T., Yoshiuchi, K., Kitajima, T., Tsuchiya, A., Esaki, Y., Yamamoto, Y., & Iwata, N. (2012) · PLoS ONE · doi:10.1371/journal.pone.0043539 · Cited by 62 · cited 1× · see citing works
“Higher skewness could characterize the intermittent bursts of locomotor activity [31,32,48].”
BackgroundSelf-citationA test whether two AIC'S differ significantly
Linhart, H. (1988) · South African Statistical Journal · Cited by 62 · see citing works
Positive affect and distressed affect over the day in older people.
Steptoe, A., Leigh, E. S., & Meena Kumari, B. (2011) · Psychology and Aging · doi:10.1037/a0023303 · Cited by 61 · cited 1× · see citing works
“self-reported symptoms [7,8,9].”
Smith, T. W., Birmingham, W. C., & Uchino, B. N. (2012) · Health Psychology · doi:10.1037/a0026947 · Cited by 54 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundKim, J., Kikuchi, H., & Yamamoto, Y. (2012) · British Journal of Health Psychology · doi:10.1111/bjhp.12000 · Cited by 43 · cited 2× · see citing works
“A watch-type computer (Ruputer, ECOLOG, 42 g; Seiko Instruments Inc., Tokyo, Japan) [45] was used as the ED to record momentary symptoms.”
MethodSelf-citationRobles, T. F., Shetty, V., Zigler, C. M., Glover, D. A., Elashoff, D. A., Murphy, D. A., & Yamaguchi, M. (2010) · Biological Psychology · doi:10.1016/j.biopsycho.2010.10.006 · Cited by 41 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundTension-Type Headache and Physical Activity: An Actigraphic Study
Kikuchi, H., Yoshiuchi, K., Ohashi, K., Yamamoto, Y., & Akabayashi, A. (2007) · Cephalalgia · doi:10.1111/j.1468-2982.2007.01436.x · Cited by 35 · cited 1× · see citing works
“, Ardsley, NY, USA), widely used in clinical fields [24,31,32,47].”
BackgroundSelf-citationMulti-Scale Motility Amplitude Associated with Suicidal Thoughts in Major Depression
Indic, P., Murray, G., Maggini, C., Amore, M., Meschi, T., Borghi, L., Baldessarini, R. J., & Salvatore, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0038761 · Cited by 35 · see citing works
Friedberg, F., & Sohl, S. J. (2008) · International Journal of Behavioral Medicine · doi:10.1007/bf03003071 · Cited by 28 · see citing works
Ritz, T., Rosenfield, D., DeWilde, S., & Steptoe, A. (2010) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2010.05.004 · Cited by 15 · cited 2× · see citing works
“Many studies have demonstrated the strength of EMA in terms of the minimization of recall biases [36,37,38] and the correlation with other objective measures [10,11,12,13,14,15,16,17].”
BackgroundAutonomic neurocardiac regulation in major depressive disorder
Volkers, A. C. W., Tulen, J. H. M., van den Broek, W. W., Bruijn, J. A., Passchier, J., & Pepplinkhuizen, L. (2000) · European Neuropsychopharmacology · doi:10.1016/s0924-977x(00)80173-x · Cited by 4 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Wearables and the Medical Revolution
Dunn, J., Runge, R., & Snyder, M. (2018) · Personalized Medicine · doi:10.2217/pme-2018-0044 · Cited by 654 · see citing works
“A study on the relationship between mood and physical activity using wearable actigraphs (n = 85) showed that distinct activity patterns correspond with worsening depressive symptoms [96].”
Wen, C. K. F., Schneider, S., Stone, A. A., & Spruijt-Metz, D. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6641 · Cited by 350 · see citing works
Merikangas, K. R., Swendsen, J., Hickie, I. B., Cui, L., Shou, H., Merikangas, A. K., Zhang, J., Lamers, F., Crainiceanu, C., Volkow, N. D., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.3546 · Cited by 231 · see citing works
Windows into human health through wearables data analytics
Witt, D. R., Kellogg, R., Snyder, M. P., & Dunn, J. (2019) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2019.01.001 · Cited by 160 · see citing works
A smartwatch-based framework for real-time and online assessment and mobility monitoring
Kheirkhahan, M., Nair, S., Davoudi, A., Rashidi, P., Wanigatunga, A. A., Corbett, D. B., Mendoza, T., Manini, T. M., & Ranka, S. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.11.003 · Cited by 138 · see citing works
“These results are consistent with other reports on pain [10, 11], fatigue [12, 13, 14] and depressive mood [15, 16, 17].”
ResultμEMA: Microinteraction-based ecological momentary assessment (EMA) using a smartwatch
Intille, S., Haynes, C., Maniar, D., Ponnada, A., & Manjourides, J. (2016) · Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing · doi:10.1145/2971648.2971717 · Cited by 130 · see citing works
“…the potential of watch-type devices to quantify behavior using EMA e.g., perceived exertion [48], cardiovascular activity [16], depressive mood [24], here we focus on the use of µ EMA to make temporally-dense self-report sustainable, so that each interruption contains only a single, simple…”
BackgroundStamford, J. A., Schmidt, P. N., & Friedl, K. E. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2464354 · Cited by 86 · see citing works
“Depressive mood is associated with lowered activity levels [50] and disordered sleep [42], [29], and there is some evidence that aspects of mood (depression, anxiety, mania) and psychotic features (confusion, hallucination, delusion) affect motor presentation in PD.”
BackgroundJuengst, S. B., Graham, K. M., Pulantara, I. W., McCue, M. P., Whyte, E. M., Dicianno, B. E., Parmanto, B., Arenth, P. M., Skidmore, E. R., & Wagner, A. K. (2015) · Brain Injury · doi:10.3109/02699052.2015.1045031 · Cited by 86 · see citing works
“medicine, given its greater efficiency and accuracy than more traditional methods, such as journaling [21, 22].”
BackgroundO'Brien, J. T., Gallagher, P., Stow, D., Hammerla, N., Ploetz, T., Firbank, M., Ladha, C., Ladha, K., Jackson, D., McNaney, R., et al. (2017) · Psychological Medicine · doi:10.1017/s0033291716002166 · Cited by 76 · see citing works
“…there are important limitations to the interpretability of the data they produce due to a lack of agreement as what constitutes light/moderate/intense activity in older adults and the likelihood that these arbitrary categorizations reduce data fi delity (van Hees, 2012; Kim et al. 2013 a ).”
Zarate, D., Stavropoulos, V., Ball, M., Collier, G. D. S., & Jacobson, N. C. (2022) · BMC Psychiatry · doi:10.1186/s12888-022-04013-y · Cited by 79 · see citing works
Faherty, L. J., Hantsoo, L., Appleby, D., Sammel, M. D., Bennett, I. M., & Wiebe, D. J. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx005 · Cited by 62 · see citing works
Potential benefits of integrating ecological momentary assessment data into mHealth care systems
Kim, J., Marcusson‐Clavertz, D., Yoshiuchi, K., & Smyth, J. M. (2019) · BioPsychoSocial Medicine · doi:10.1186/s13030-019-0160-5 · Cited by 66 · see citing works
“…the associations between depressive mood (EMA) and physical activity (passive sensor) using a variety of aggregation time frames for physical activity; in brief, their findings suggested that one-hour physical activity epochs are appropriate to investigate the association with depressive mood [25].”
BackgroundSelf-citationTamási, V., Petschner, P., Ádori, C., Kirilly, E., Andó, R. D., Tóthfalusi, L., Juhász, G., & Bagdy, G. (2014) · PLoS ONE · doi:10.1371/journal.pone.0113662 · Cited by 60 · see citing works
“A recent study found a strong association between depressed mood and altered locomotor patterns (decreased locomotor activity and intermittent periods of low activity) [12].”
BackgroundMicrointeraction Ecological Momentary Assessment Response Rates
Ponnada, A., Haynes, C., Maniar, D., Manjourides, J., & Intille, S. S. (2017) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3130957 · Cited by 59 · see citing works
“captured depressive mood and locomotor dynamics using a watch-computer with physical joystick input (reported 94% response rate for 7 days) [26] and compared responses from EMA and the Day Reconstruction Method for fatigue assessment (reported 90.”
MethodDai, R., Lu, C., Yun, L., Lenze, E. J., Avidan, M. S., & Kannampallil, T. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106207 · Cited by 47 · see citing works
Kim, J., Nakamura, T., Kikuchi, H., Yoshiuchi, K., Sasaki, T., & Yamamoto, Y. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2440764 · Cited by 45 · see citing works
Self-citationTimm, I., Giurgiu, M., Ebner‐Priemer, U., & Reichert, M. (2024) · Sports Medicine · doi:10.1007/s40279-024-02016-1 · Cited by 45 · see citing works
“However, some results indicated an inverse relationship between PA and depressive states [125–127].”
BackgroundKim, J., Conroy, D. E., & Smyth, J. M. (2019) · Annals of Behavioral Medicine · doi:10.1093/abm/kaz045 · Cited by 42 · see citing works
Self-citationTeicher, M. H., Ohashi, K., Lowen, S. B., Polcari, A. M., & Fitzmaurice, G. M. (2015) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2015.08.012 · Cited by 36 · see citing works
“…collected using a watch-type computer (Ruputer, ECOLOG, 42 g; Seiko Instruments Inc., Tokyo, Japan), with 20 mm × 30 mm LCD screen and joystick and buttons as input devices, plus a built in actigraph, that was a forerunner to current sport fitness watches (Kim et al. , 2013a, Kim et al. , 2013b).”
Murray, A. L., Brown, R., Zhu, X., Speyer, L. G., Yang, Y., Xiao, Z., Ribeaud, D., & Eisner, M. (2022) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.11.014 · Cited by 32 · see citing works
Sulis, W. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0168 · Cited by 25 · see citing works
Digital Phenotyping in Child and Adolescent Psychiatry: A Perspective
Nisenson, M., Lin, V., & Gansner, M. (2021) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000310 · Cited by 21 · see citing works
“Many of the included studies noted this problem as major limitations.(36,38,41,50,52,57,58) Furthermore, the lack of standardization of protocols or established best practices renders comparisons across studies difficult.”
BackgroundMcCarthy, B., O’Neill, G. J., & Abu‐Ghannam, N. (2022) · Marine Drugs · doi:10.3390/md20080493 · Cited by 19 · see citing works
“Low locomotor activity, low energy and fatigue are associated with depressed mood and other psychiatric disorders [101].”
BackgroundKim, J., Marcusson‐Clavertz, D., Togo, F., & Park, H. (2018) · Computational and Mathematical Methods in Medicine · doi:10.1155/2018/8652034 · Cited by 18 · see citing works
“Depressive mood scoretj = γ00 + γ10 (local statistics of physical activitytj) + ζ0j + εtj [see [85] for details].”
BackgroundMethodInfluentialSelf-citationStochastic Differential Equation Models with Time-Varying Parameters
Chen, M., Chow, S., & Hunter, M. D. (2018) · Springer eBooks · doi:10.1007/978-3-319-77219-6_9 · Cited by 17 · see citing works
Drinking Levels and Profiles of Alcohol Addicted Rats Predict Response to Nalmefene
Foo, J. C., Vengeliene, V., Noori, H. R., Yamaguchi, I., Morita, K., Nakamura, T., Yamamoto, Y., & Spanagel, R. (2019) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.00471 · Cited by 17 · see citing works
“Differences in mean activity could indicate psychomotor agitation/retardation, while variance characterizes variability of activity and skewness represents intermittency of activity; shown to be biomarkers able to characterize disease states (Kim et al., 2013; Nakamura et al., 2016).”
BackgroundSelf-citationQuantitative Evaluation of the Use of Actigraphy for Neurological and Psychiatric Disorders
Pan, W., Song, Y., Kwak, S., Yoshida, S., & Yamamoto, Y. (2014) · Behavioural Neurology · doi:10.1155/2014/897282 · Cited by 16 · see citing works
“[39] examined the variations in momentary symptoms of depressive mood, anxious mood, and fatigue and investigated covariant properties between the symptoms, and local statistics of locomotor activity were also detected by using an actigraphy.”
MethodSelf-citationDynamical state transitions into addictive behaviour and their early-warning signals
Foo, J. C., Noori, H. R., Yamaguchi, I., Vengeliene, V., Cosa‐Linan, A., Nakamura, T., Morita, K., Spanagel, R., & Yamamoto, Y. (2017) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2017.0882 · Cited by 16 · see citing works
Self-citationKim, J., Foo, J. C., Murata, T., & Togo, F. (2024) · Stress and Health · doi:10.1002/smi.3447 · Cited by 13 · see citing works
Self-citationChikhaoui, B., Ye, B., & Mihailidis, A. (2017) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-017-0537-x · Cited by 13 · see citing works
“Kim et al. (2013) investigated covariant properties between the symptoms of depressive mood, anxious mood, and fatigue and locomotor activity using an actigraphy.”
MethodTakahashi, H., Nakamura, T., Kim, J., Kikuchi, H., Nakahachi, T., Ishitobi, M., Ebishima, K., Yoshiuchi, K., Ando, T., Stickley, A., et al. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00355 · Cited by 12 · see citing works
“Further, this pattern of locomotor activity has been significantly associated with the worsening of depressive mood in healthy adults and depressive patients (10, 19).”
BackgroundMethodSelf-citationAlcohol solution strength preference predicts compulsive‐like drinking behavior in rats
Foo, J. C., Meinhardt, M. W., Skorodumov, I., & Spanagel, R. (2022) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.14910 · Cited by 12 · see citing works
Kim, J., Nakamura, T., Kikuchi, H., Yoshiuchi, K., & Yamamoto, Y. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6945149 · Cited by 12 · see citing works
Self-citationDrexl, K., Ralisa, V., Amoussou, J. R., Wen, C. K. F., Urben, S., Plessen, K. J., & Glaus, J. (2025) · Journal of Medical Internet Research · doi:10.2196/65710 · Cited by 10 · see citing works
Seeking a fingerprint: analysis of point processes in actigraphy recording
Gudowska-Nowak, E., Ochab, J. K., Oleś, K., Beldzik, E., Chialvo, D. R., Domagalik, A., Fąfrowicz, M., Marek, T., Nowak, M. A., Ogińska, H., et al. (2016) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/2016/05/054034 · Cited by 9 · see citing works
“…summary measures allow for hypothesis testing using classic statistical methods [ 14, 21 – 23 ] , large amounts of relevant information are disclosed in those complex data when more advanced tools of quantification ( see section 3 ) , like fractal analysis, are applied [ 11, 13, 15, 17, 24, 25 ] .”
BackgroundMethodApplication of Empirical Mode Decomposition to Mother and Infant Physical Activity
Shimizu, E., Kim, J., Yoshiuchi, K., Yamamoto, Y., & Nakamura, T. (2018) · Methods of Information in Medicine · doi:10.3414/me18-02-0001 · Cited by 8 · see citing works
“Mood states, specifically depressive mood and anxiety (total depression and total anxiety, respectively), were scored using the depression and anxiety mood scale (DAMS) [11, 12, 13] (▶ Figure 1c).”
MethodSelf-citationGait disorders in unipolar and bipolar depression
Bogdanova, D. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e15864 · Cited by 7 · see citing works
Seeking a fingerprint: analysis of point processes in actigraphy recording
Gudowska Nowak, E., Ochab, J. K., Oleś, K., Beldzik, E., Chialvo, D. R., Domagalik, A., Fąfrowicz, M., Marek, T., Nowak, M. A., Ogińska, H., et al. (2016) · Americanae (AECID Library) · Cited by 7 · see citing works
Murayama, Y., Inoue, K., Yamazaki, C., Kameo, S., Nakazawa, M., & Koyama, H. (2019) · The Tohoku Journal of Experimental Medicine · doi:10.1620/tjem.249.101 · Cited by 7 · see citing works
Longitudinal User Engagement with Microinteraction Ecological Momentary Assessment (μEMA)
Ponnada, A., Wang, S. D., Li, J., Wang, W., Dunton, G. F., Hedeker, D., & Intille, S. S. (2025) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3749541 · Cited by 6 · see citing works
“For instance, Kikuchi et al. used watches to prompt participants several times a day with questions on tension-type headaches, depressive mood, and fatigue [42, 43].”
Takeishi, K.-I., Kawaguchi, H., Akioka, K., Noguchi, M., Arimura, E., Abe, M., Ushikai, M., Okita, S., Tanimoto, A., & Horiuchi, M. (2018) · In Vivo · doi:10.21873/invivo.11204 · Cited by 6 · see citing works
Dewa, L. H., Pappa, S., Greene, T., Cooke, J., Mitchell, L., Hadley, M., Simplicio, M. C. D., Woodcock, T. M., & Aylin, P. P. (2022) · JMIR Research Protocols · doi:10.2196/33817 · Cited by 5 · see citing works
A momentary biomarker for depressive mood
Kim, J., Nakamura, T., & Yamamoto, Y. (2016) · In Silico Pharmacology · doi:10.1186/s40203-016-0017-6 · Cited by 6 · see citing works
“Keywords: Physical activity, Depressive mood, Major depressive disorders, Ecological momentary assessment, Psychobehavioral biomarker”
BackgroundMethodInfluentialSelf-citationPsychobehavioral validity of self-reported symptoms based on spontaneous physical activity
Kim, J., Nakamura, T., Kikuchi, H., & Yamamoto, Y. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319276 · Cited by 4 · see citing works
Self-citationNiculescu, I., Arora, T., & Iaboni, A. (2020) · Aging & Mental Health · doi:10.1080/13607863.2020.1793899 · Cited by 3 · see citing works
Association of Locomotor Activity During Sleep Deprivation Treatment With Response
Foo, J. C., Sirignano, L., Trautmann, N., Kim, J., Witt, S. H., Streit, F., Frank, J., Zillich, L., Meyer‐Lindenberg, A., Ebner‐Priemer, U., et al. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00688 · Cited by 3 · see citing works
“+/−30 min) VAS mood assessments, as in (31), hereafter referred to as “locomotor activity.”
BackgroundSelf-citationSystematik E-Mental-Health-Interventionen
Meisenzahl, E. M., & Sprick, U. (2023) · Springer eBooks · doi:10.1007/978-3-662-64457-7_3 · Cited by 1 · see citing works
Vuuregge, A. H., Zhang, Y., Meulmeester, W. M., Bockting, C., Lucassen, P. J., Heininga, V. E., Schrantee, A., & Mul, J. D. (2025) · Applied Psychology Health and Well-Being · doi:10.1111/aphw.70086 · Cited by 1 · see citing works
“…mood as a within-person measure and related this to physical activity (Cushing et al., 2018; Fuller-Tyszkiewicz et al., 2017; Haas et al., 2017; Kim et al., 2013; Langguth et al., 2016); (2) including a between-person variable of baseline depressive symptomatology based on validated…”
InfluentialHaralanov, S., Haralanova, E., Bogdanova, D., Dimitrov, R., Milushev, E., & Shkodrova, D. (2021) · Springer eBooks · doi:10.1007/978-3-030-61721-9_39 · Cited by 1 · see citing works
Haralanov, S., Haralanova, E., Milushev, E., & Shkodrova, D. (2018) · Springer eBooks · doi:10.1007/978-3-319-95360-1_32 · Cited by 1 · see citing works
Assessment of Variability in Irregularly Sampled Time Series: Applications to Mental Healthcare
Bonilla-Escribano, P., Ramírez, D., Porras‐Segovia, A., & Artés-Rodrı́guez, A. (2020) · Mathematics · doi:10.3390/math9010071 · Cited by 1 · see citing works
“Missing data represent a particularly common issue in EMA studies and it is usually dealt with discarding data points that do not meet certain criteria, such as removing responses provided over 30 min after being prompted [22].”
BackgroundInfluentialHagaman, A. K., Mercado, D. L., Poudyal, A., Bemme, D., Boone, C., van Heerden, A. C., Byanjankar, P., Maharjan, S. M., Thapa, A., & Kohrt, B. A. (2020) · Research Square · doi:10.21203/rs.3.rs-82137/v1 · Cited by 1 · see citing works
“For example, features of movement extracted from passive sensing data have been associated with loneliness [30], worsening of depressive mood [32], and changes in state of patients with bipolar disorder [26].”
BackgroundKeith, N. R., Xu, H., de Groot, M., Hemmerlein, K., & Clark, D. O. (2016) · Clinical Medicine Insights Women s Health · doi:10.4137/cmwh.s34687
勤労者の日常生活下における行動、心理、生理、環境情報の統合連続モニタリングと大規模データベースの利活用
志村, 広., 中村, 亨., 金鎭赫, 菊地, 裕., 吉内, 一., & 山本, 義. (2017) · ヒューマンインタフェース学会論文誌 · doi:10.11184/his.19.2_163
Health and biosensor technology—A revolution underway for the well-being of the population
Bastidas, G. A., & Iglesias, R. (2024) · Wearable Technology · doi:10.54517/wt.v4i1.2618 · Cited by 1 · see citing works
Mastronardi, C., Powers, J., Menna, R., & Rappaport, L. M. (2026) · JMIR Research Protocols · doi:10.2196/76333
“We also note that naturalistic assessments of adolescents may often occur less frequently than assessments of adults or young adults (undergraduate students [155]).”
- Authors
- Kim, J., Nakamura, T., Kikuchi, H., Sasaki, T., & Yamamoto, Y.
- Affiliations
- The University of Tokyo (JP)
- National Center of Neurology and Psychiatry (JP)
- Corresponding author
- Yamamoto, Yoshiharu
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-09-13
- Volume
- 8
- Issue
- 9
- Pages
- e74979
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3773004
- OpenAlex
- W2023143019
- Cited by
- 58
- References
- 66
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 5 · 2021: 4 · 2020: 4 · 2019: 5 · 2018: 10 · 2017: 6 · 2016: 6 · 2015: 5 · 2014: 3
- FWCI
- 6.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Ministry of Education, Culture, Sports, Science and Technology
- Japan Society for the Promotion of Science (22650157, 25870183, 23700795, 23240094)
- Japan Science and Technology Agency
- Core Research for Evolutional Science and Technology
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- depressive mood, locomotor activity, ecological momentary assessment, actigraphy, anxious mood, fatigue, early detection of depression, healthy adults
- MeSH terms
- Adolescent, Adult, Age Factors, Depression, Female, Humans, Life Style, Male, Models, Biological, Motor Activity, Self-Assessment, Software
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.
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 ›
Are you an author, or do you see a problem with this page? Request a review
